Illuminating the Mental Memoriam by Steve Ramirez Submitted to The

Illuminating the Mental Memoriam by Steve Ramirez Submitted to the Department of Brain and Cognitive Sciences in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY IN NEUROSCIENCE at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY June 2015 © Massachusetts Institute of Technology 2015. All rights reserved.

Author ...... Department of Brain and Cognitive Sciences June 24, 2015

Certified by ...... Susumu Tonegawa Professor of Neuroscience Thesis Supervisor

Accepted by ...... Matthew A. Wilson Professor of Neuroscience Director of Graduate Education for BCS

Illuminating the Mental Memoriam by Steve Ramirez Submitted to the Department of Brain and Cognitive Sciences on June, 2015, in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY IN NEUROSCIENCE

Abstract Memories thread and unify our overall sense of being. With the accumulation of our knowledge about how memories are formed, consolidated, retrieved, and updated, neuroscience has reached a point where brain cells active during these discrete mnemonic processes can be identified and manipulated at rapid timescales. Here, I begin with historical studies that lead to the modern memory engram theory. Then, I present our recent advances in memory research that combine transgenic and optogenetic approaches to reveal underlying neuronal substrates sufficient for activating mnemonic processes. Our studies’ conclusions are threefold: (1) we provide proof of principle evidence demonstrating that learning-related neural changes can be isolated at the level of single cells, and that these cells can then be tagged for subsequent manipulation; (2) a defined subset of hippocampus cells are sufficient to elicit the neuronal and behavioral expression of memory recall, as well as sufficient to modify existing positive and negative memories; (3) and finally, artificially activated memories can be leveraged to acutely and chronically suppress psychiatric disease-related states. We propose that hippocampus cells that show activity-dependent changes during learning construct a cellular basis for contextual memory engrams and that directly activating these endogenous neuronal processes may be an effective means to correct maladaptive behaviors. Thesis Supervisor: Susumu Tonegawa Title: Picower Professor of Neuroscience

This thesis is dedicated to my mentor and friend, Xu Liu— a knight of science, shining, forever; And to Pedro Ramirez and Delmy Moreno— unconditionally loving parents, clothed in the American Dream, together.

“This is no time for caution”

Contents

1 Background: A neural basis for memory engrams 7

1.1.1 Introduction: A 2000-year-old idea; a 100-year-old hypothesis

1.1.2 A seahorse in an ocean of activity

2 Activity-dependent and inducible systems for neuronal tagging 17

2.1.1 Introduction: Crystalizing an engram in motion

2.1.2 Combining optogenetic and transgenic technologies

3 Illuminating a memory 27

3.1.1 Introduction: loss-of-function approaches to dissecting memory

3.1.2 Results: Hippocampus cells are sufficient for memory expression

3.1.3 Discussion

3.1.4 Methods

4 Updating the contents of a memory 67

4.1.1 Introduction: The ebb and flow of the mnemonic river

4.1.2 Results: Hippocampus cells are sufficient to act as a functional CS

4.1.3 Discussion

4.1.4 Methods

5 Switching the valence associated with a memory 105

5.1.1 Introduction: Coloring in memories with emotions

5.1.2 Results: Hippocampus cells are functionally plastic

5.1.3 Discussion

5.1.4 Methods

6 Activating memories to rescue maladaptive states 139

6.1.1 Introduction: Broken thoughts are broken brains

6.1.2 Results: Positive memories suppress depression-like states

6.1.3 Discussion

6.1.4 Methods

7 Conclusion: Engram cells have come of age 197

8 References 210

9 Appendix I: Liu and Ramirez et al. Nature, 2012

10 Appendix II: Ramirez and Liu et al. Science, 2013

11 Appendix III: Ramirez et al. Frontiers in Behavioral Neuroscience, 2013

12 Appendix IV: Liu and Ramirez et al. Phil. Trans. of the Royal Society, 2014

13 Appendix V: Redondo and Kim et al. Nature, 2014

14 Appendix VI: Liu et al. Cold Spring Harbor Press, 2015

15 Appendix VII: Ramirez et al. Nature, 2015

This thesis is written as a composite of Appendices I-VII.

Chapter 1: A neural basis for memory engrams

How does the brain—a condensed lump of universe consisting of billions and billions of cells—produce the seemingly ephemeral process of mental time travel, of memory? A tantalizing hint comes from the observation that learning leaves enduring changes in the brain. These changes come in various forms and occur at various timescales: gene regulation, protein production, receptor trafficking, morphological and physiological modifications, circuit-level changes in synaptic efficacy, all working in parallel to provide a physical substrate for our mental time machine. Here, I propose that memory is possible because the brain is mutable. This chapter is about the physical processes enabling that mutability and the corresponding enduring changes that occur as a result of learning. It is about the mutable mental memoriam—the flexible biological architecture that enables memory.

1.1.1 Introduction: A 2000-year-old idea; a 100-year-old hypothesis

The idea of a mutable brain (termed “neural plasticity” in modern neuroscience) dates back to Plato, who originally proposed that memories leave a stamp or trace in the mind, much akin to the impression on a wax tablet left by a signet ring (Campbell, 1883).

In modern terms, this physical trace exists as an enduring, experience-dependent change in neural activity in response to learning. After Plato, it took nearly two millennia to translate learning and memory in neural terms and to hypothesize their biological underpinnings. In short, the consequence that learning has on the brain is the formation of an “engram”, or the sum total biophysical and electrophysiological enduring changes that comprise a discrete memory distributed throughout the brain.

In the early 1900s, Richard Semon—a German zoologist—coined the term

“engram” and put forth its first rigorous definition (Schacter, 1978; Schacter et al. 1982).

Semon defined engrams as “…the enduring though primarily latent modification in the irritable substance produced by a stimulus (from an experience)…” This irritable substance, of course, was the mutable brain; the stimuli involved include exogenous and endogenous cues that trigger the learning process. Semon’s engram theory centered on two laws: the “Law of Engraphy” and the “Law of Ecphory,” which he proposed as explanations for memory storage and memory retrieval, respectively. The Law of

Engraphy for memory storage states, “All simultaneous excitations (derived from experience)…form a connected simultaneous complex of excitations which, as such acts engraphically, that is to say leaves behind it a connected and to that extent, separate unified engram-complex” (Semon, 1923). The Law of Ecphory for memory retrieval states that, “The partial return of an energetic situation which has fixed itself engraphically acts in an ecphoric sense upon a simultaneous engram complex” (Semon,

1923). Semon’s accurate intuitions were twofold: memories leave behind an observable trace in the brain; and, memories are often triggered by partial cues that were present at the time of encoding, which subsequently reactivate the entirety of the engram-complex

(Semon, 1904 and 1909). In modern terms, he intuited that the hippocampus can keep similar episodes separate (i.e. pattern separation) and can facilitate the recall of entire episodes from environmental cues (i.e. pattern completion) (Nakazawa, 2004).

Despite Semon’s prescient hypotheses, a fundamental question remained: what specific mental machinery could achieve the remarkable cognitive feat of constructing memories? Three seminal findings in neuroscience — one systematic, one accidental, and one tragic — paved the way for subsequent memory research. The underlying candidate in all three discoveries was a seahorse-shaped structure tucked just behind the ears functioning in a sea of additional brain cells.

Starting in the early 1920’s, the neuropsychologist Karl Lashley became one of the first researchers to systematically resect parts of the rodent brain in an attempt to relate the size of the damage to memory performance, to search for the engram (Lashley,

1950). He was openly enchanted by the idea of isolating the trace. Frustrated after a decade’s worth of experiments, Lashley concluded that no matter how much damage he inflicted on the brain’s overlaying mantle, the cortex, he could never fully make his rats perform at chance levels on a maze. He simply could not erase the memory. Of course, memories are now thought to be distributed across the brain; Lashley’s error was to assume that memories (of which there are numerous types to begin with) were localized to single brain regions.

And then, in the same decade, the Canadian neurosurgeon Wilder

Penfield accidentally discovered a remarkable node sufficient to reinstate the recollective

9 process (Penfield, 1950). A Princeton graduate and first-string football tackle, Penfield would treat several patients with epilepsy by carefully resecting the problematic neural tissue that gave rise to seizures. However, in order to distinguish between healthy and problematic tissue, Penfield applied jolts of electricity to the brain and reported his patients’ responses — some were innocuous, others were signatures of seizure onset, or auras. After applying electrical stimulation to areas of cortex near the hippocampus, about 8% of Penfield’s patients reported that they were unwillingly recalling vivid memories of past experiences. As one patient reported, “I am seeing a picture of a dog and a cat…the dog is chasing the cat.” Or, “It sounded like a voice saying words, but it was so faint that I couldn’t get it” (Penfield, 1950). This study gave neuroscientists a first glance at what geneticists call “gain-of-function” or “sufficiency” evidence for the notion that the medial temporal lobe (MTL) harbors a biological locus for activating memory.

Electrically activating this lump of brain tissue was sufficient to induce the conscious recollection of a specific memory in humans. Fittingly, Penfield’s work would then set the stage for a surgery that would become a cornerstone of memory research—a surgery to which every subsequent experiment in the field is indebted.

William Beecher Scoville was the neurosurgeon whose scalpel would carefully expose one of the most elegant, philosophically-charged principles of neurobiology: broken brains give rise to broken thoughts; moreover, specific broken brain pieces give rise to specific impairments in cogntion. His patient’s name was Henry Molaison—the mighty H.M. A Connecticut native, H.M. had two sizable portions near and within the medial temporal lobe removed to treat the epileptic convulsions that had so devastated his youth. Scoville carefully maneuvered into an area right above H.M.’s ears to surgically remove part of the hippocampus and surrounding cortical areas. After the surgery on

September 1st, 1953, H.M., a 27 year old, became suspended in time; he lived in a

“permanent present tense” (Corkin, 2013). Without a hippocampus, he developed anterograde amnesia, the inability to form new memories, as well as graded retrograde amnesia, the inability to recall memories of past experiences that occurred close in time to the surgery. Forever stuck in the present, H.M. taught us that certain parts of the brain were crucial for processing and storing memories of these experienced events. Without a hippocampus, he lost his ability to bridge personal events across large spans of space and time and, in turn, gave us an unforgettable neuronal roadmap for navigating the brain’s memory systems.

As a result of H.M., neuroscientists now had a general brain region—namely, the medial temporal lobe—as a candidate that could potentially be a locus for memory; the search for a neural correlate of memory intensified. However, the brain speaks on the staggeringly fast timescale of milliseconds. Traditionally, researchers have been able to eavesdrop on neural activity with hair-thin electrodes placed into the brain that pick up physiological signals. In addition, manipulating neural activity has usually relied on lesions or cocktails of drugs to modulate activity. However, lesions indiscriminately and irreversibly destroy neural tissue; drugs take minutes or even hours to have a full effect.

Both are difficult to restrict spatially in terms of the amount of brain they influence.

But on August 14th, 2005, everything changed. As Yogi Berra once said, “The future ain’t what it used to be.” This day will be revisited in section 2.1.2.

1.1.2 A seahorse in an ocean of activity

Structures within the medial temporal lobe (MTL), especially the hippocampus, have been shown to be crucial sites involved in memory formation, consolidation, retrieval, and updating. Our ability to consciously recollect events and factual knowledge of the past is an aspect of cognition is termed episodic memory—a subtype of declarative memory which functions to represent personally experienced events (Tulving, 1983). To do so, the hippocampus is thought to rapidly form representations using highly processed and multimodal sensory inputs that synapse onto adjacent cortical areas. The mneuominc information conveyed across these neurons in turn feeds into the hippocampus itself to be coalesced into a stable representation and fed forward to downstream networks for further processing.

Since episodic memory is essential to a normal life, an understanding of the normal circuitry underlying hippocampal function is crucial if we are to understand the diseased state in disorders that give rise to episodic memory impairments. However, the process by which episodic memory emerges through the interaction of millions of neurons distributed across various brain regions is a poorly understood, albeit energetically debated and studied phenomenon (Eichenbaum, 2003, 2004; Squire et al.

2004, 2007).

Since H.M., a large number of subsequent studies in humans (Rempel-Clower et al. 1996; Schmolck et al. 2002), as well as in non-human primates and rodents (Jarrard,

1993; Zola and Squire, 2001), have established that the hippocampus is crucial for the formation of memories that include “what-where-when” components, or context- temporal-informational domains, or episodic memories (Eichenbaum, 2004).

Additionally, the hippocampus’ structure and function has been extraordinarily conserved

12 across mammalian clades, permitting a thorough experimental interrogation and deconstruction of its functions in animal models (Eichenbaum, 2003).

In terms of structure, the canonical trisynaptic pathway of the hippocampus consists of the dentate gyrus (DG), CA3, and CA1, with a newly appreciated anatomical and behaviorally relevant role for CA2 (Kohara et al. 2013; Denny et al. 2014; Tanaka et al. 2014; Hitti and Siegelbaum, 2014). A plethora of lesion, electrophyiological, and optogenetic studies have implicated each hippocampal subregion in differentially processing spatial and non-spatial components of learning and memory (Nakazawa et al.

2003; Eichenbaum, 2004; Goshen, 2014).

As a candidate mechanism supporting many of these mnemonic processes, the strengths of synapses throughout the hippocampus are altered in an experience-dependent manner. In the 21st century, Canadian psychologist Donald Hebb put a modern spin on

Plato’s wax tablet and hypothesized that neurons that “fire together” also “wire together”

(Hebb, 1949)—a conceptual antecedent of long-term potentiation (LTP). Tim Bliss and

Terje Lømo’s experimental demonstration of long-term potentiation (LTP) (Bliss and

Lomo, 1973), followed by the essential role of NMDA receptors in LTP induction

(Collingridge et al. 1983), provided a molecular framework under which to investigate potentiation as a putative synaptic mechanism underlying certain forms of learning and memory.

Not surprisingly, partly due to technological and conceptual limitations, Semon did not elaborate on his engram theory of memory, especially with regards to the biological nature of “…the enduring though primarily latent modification in the irritable substance produced by a stimulus…” (Semon, 1921). Since his time, a large amount of studies have been directed to the characterization of LTP and other facets of synaptic

13 plasticity, and their potential role in learning and memory. Activity-dependent increases of the size and density of dendritic spines, for instance, have also been proposed as contributing to memory encoding (Bailey and Kandel, 1993). There have also been studies suggesting that a cell-wide alteration, such as an augmented intrinsic excitability, may contribute to memory (Daoudal and Debanne, 2003). The contributions of both types of structural and physiological plasticity to engrams are discussed in the concluding chapter.

The initial pharmacological blockade experiments utilized the NMDA receptor

(NMDAR) antagonist, AP5, and these studies were consistent with the notion that LTP is essential for learning, especially memories that involved spatial navigation (Morris et al.

1986). The validity of this hypothesis was demonstrated with the targeted genetic ablation of NMDARs in the CA1 region of the hippocampus (Tsien et al. 1996) with impairments in spatial memory reported. A subsequent report concluded that CA1

NMDAR were in fact dispensable for spatial learning per se, but the same report showed an robustly detectable level of NMDAR RNA in CA1 and hence the possibility that the remaining CA1 NMDAR supported spatial learning can not be excluded (Bannerman et al. 2012). These authors nonetheless reactivated a provocative hypothesis (Vinogradova,

1975) that ascribes CA1/DG NMDAR differential roles in learning and memory processes. Indeed, mice with NMDAR ablation in DG and CA3 show robust impairments in pattern separation and pattern completion, respectively (McHugh et al. 2007;

Nakazawa et al. 2003). Another study did not detect the effect of NMDAR deletion in the

DG cells on pattern separation (Niewoehner et al. 2007), but this may be due to the fact that different behavioral paradigms were used. Regardless, these observations generally

14 support the role of NMDAR-dependent synaptic plasticity, including LTP, in subtypes of hippocampal-dependent memory.

Furthermore, consistent with its role in processing various aspects of spatial and temporal information, the hippocampus in general is thought to be critical for the formation of the contextual component of fear memories (Phillips and LeDoux, 1992;

Kim and Fanselow, 1992). More specifically, computational models predict that DG in particular orthogonalizes inputs from entorhinal cortex into separate spatial representations (Treves and Rolls, 1994), while CA1 integrates input from both entorhinal cortex and CA3 to act as the hippocampus’s main output of highly processed spatial information. Behavioral experiments support DG’s essential role for discriminating between similar contexts, and in vivo recordings in freely moving animals show that DG granule cells are exquisitely sensitive to subtle changes in contextual information (Leutgeb et al. 2007). Blocking CA1’s activity through lesions, pharmacology, or genetic manipulations has also revealed its obligatory role in spatial and contextual memory (Lee and Kesner, 2004; Tsien et al. 1997).

Cellular studies of immediately early gene (IEG) expression show that sparse populations of DG granule cells (2–4%) are activated in a given context (Schmidt et al.

2011; Chawla et al. 2005), whereas a high proportion (40-70%) of CA1 cells are recruited for the same context (Guzowski, 2002). Moreover, whereas the same population of DG granule cells is activated repeatedly in the same environment, different environments or even different tasks activate different populations of DG and, to a lesser degree, CA1 cells (Satvat et al. 2011; Kubik et al. 2007). This change in proportion of active cells in a given environment, termed “global remapping,” is also observed using electrophysiological single-unit recordings (Leutgeb et al. 2004 and 2007). These lines of

15 evidence point to the DG as an ideal target for the formation of contextual memory engrams that represent discrete environments, which lead our group to hypothesize that the DG in particular is both necessary and sufficient for memory expression—topics which are taken up in Chapter 3.

Chapter 2: Activity-dependent and inducible systems for neuronal tagging By combining our current knowledge about neurons, synaptic connections, and neuronal circuits, Semon’s Engram Theory of Memory can now be rephrased as follows:

“When a subject undergoes an experience, or episode, a set of selected stimuli from the experience, or episode, activate populations of neurons to induce enduring biochemical and electrophysiological changes in these cells and their connections, each contributing to the storage of the memory. Subsequently, when a part of the original stimuli returns, these cells are reactivated to evoke the recall of the specific memory.” As such, the term

“engram” refers to the enduring cellular and synaptic changes accompanying learning that underlie the formation and recall of a definined memory. It is distributed throughout the brain; a variety of brain areas differentially and synchronously contribute mneuomnic information; it is the collective neuronal architecture subserving a specific memory in all its richness and detail; it is mutable. Further, the phrase “engram cells” refers to a speficic population of neurons that have been activated by learning, in which these enduring cellular and synaptic changes have occurred as a consequence of learning, and whose subsequent reactivation by stimuli that compose part of the original stimuli delivered during learning results in recall of the original memory. The information contained by engram cells will depend on the brain area in which they are identified and on how these cells communicate to the memory-related circuit of which they are a component.

This chapter provides a genetic basis for the identification of engram cells in the brain as well as their putative physiological properties.

2.1.1 Introduction: Crystalizing an engram in motion

The search for the engram is not a new endeavor. Pioneering studies abound in multiple animal models: baby chicks and the phenomenon of imprinting, rabbits and eyeblink conditioning, rodents and modality-specific activity in sensory cortices—all of these have greatly advanced our understanding of how a memory trace is biologically realized (Olds et al. 1972; Christian and Thompson, 2003; Horn et al. 2001). These pioneering studies led to a notion that different types of memory may be differentially processed across multiple brain regions (Squire, 2004). Indeed, numerous efforts have been made during the past 30 years to identify the sites where each of these types of memory are located by using lesion, physiological, or functional magnetic resonance imaging methods combined with behavioral paradigms. These efforts led to the identification of brain regions or brain systems that are crucial for their respective type of memory, but also fell short of identifying a specific subpopulation(s) of neurons in these brain regions or systems as truly memory engram cells, for reasons discussed below.

Readers are referred to extensive reviews for the discussion of earlier efforts to identify brain regions or systems that play important roles in various forms of engram processing

(Horn et al. 2001; Martin and Morris, 2002; Christian and Thompson, 2003; Weinberger,

2004).

Because of the methodological limitations employed in these studies, it was not possible to demonstrate that a specific subpopulation of cells in the respective brain region, as opposed to neighboring cells in the same brain region, qualified as engram- bearing cells. Meeting this challenge has required a combinatorial use of new technologies, including immediate early genes (IEG)-based labeling systems, transgenics, optogenetics, pharmacogenetics, in vitro and in vivo physiology of single cells and

18 behavioral paradigms. To demonstrate that a specific population of neurons qualifies as cells containing a component of the engram, at least three conditions must be satisfied

(Tonegawa et al. 2015). First, it is crucial demonstrate that learning induces enduring biochemical/electrophysiological changes in these cells (e.g. changes in AMPA/NMDA ratios, cellular excitability, spine growth); next, it is crucial demonstrate that direct reactivation of these cells results in the cellular and behavioral expression of the discrete memory; finally, (and exceptions abound given parallel pathways and compensatory mechanisms, which are discussed in the concluding chapter), it is useful to demonstrate that the real-time activity of these cells are necessary for the expression of the discrete memory. In other words, once must observe cellular changes, show the sufficiency in inducing recall, and show necessity for memory expression. Individually, these criteria can expose putative nodes for memory storage, as many studies have done beforehand.

The pioneering studies cited above, for instance, were mostly correlative in nature and provided tantalizing hints that the cells studies were involved in processing a component of an engram, but they did not demonstrate it. Collectively, these criteria, while not all- encompassing, provide a modern framework for causally testing an ensemble’s contribution to memory (Martin and Morris, 2002).

Accordingly, an abundance of observational studies across the evolutionary ladder have pinpointed general areas of the nervous system where engrams may be processed and/or ultimately stored. For instance, in flies, when a particular odor was paired with foot shock, defined neurons within the olfactory learning pathway, such as those in the antennal lobes and mushroom bodies, changed their responses selectively towards the odor used in the training, suggesting that cue-specific memory traces were formed within these cell populations as a result of learning (Liu and Davis, 2009; Yu et al. 2006).

Similar neuronal activity changes induced by olfactory associative learning have also been reported in mice (Kass et al. 2013).

Moreover, to identify which cells are active during the formation of a memory, it is possible to utilize the activity-dependent nature of immediate early genes (IEGs).

Neurons communicate effectively by means of electrical and chemical signals – both processes induce cascades of intracellular events that can affect the up- and down- regulation of precise genetic programs. It is believed that long-term memory (LTM) formation induces gene transcription and protein translation at the time of training to alter neural morphology, receptor densities, and overall excitability (Flavell and Greenberg,

2008). Multiple rounds of transcription have been identified with much emphasis placed on IEGs, which are transcribed within minutes in an experience-dependent manner by transcription factor proteins already present in a neuron’s cytoplasm (Guzowski, 2002).

Indeed, learning elicits an elegant coordination of neural activity distributed throughout the brain. This activity can be partly, albeit indirectly, reflected by the expression IEGs such as c-Fos, Arc, and Zif268. More specifically, when a neuron spikes past a sufficient threshold, the accompanying influx of calcium activates various kinases, such as the protein kinase families, effector molecules, such as the cAMP response element binding protein (CREB), and ultimately signals a cascade of molecular events that eventually make their way to the genome (Flavell and Greenburg, 2008). One robustly characterized pathway involves the calcium-mediated induction of CREB activity, which binds to genes with consensus cAMP-response elements (CRE) and modulates their transcription within minutes in vitro (Greenberg, 1998) as well as in vivo

(Guzowski et al. 1999). The functionality of the correspondingly activated genes is

20 varied: they can encode for transcription factors, structural proteins, receptors, and growth factors, among many other cellular functions.

One of these genes includes the IEG c-Fos, a regulatory transcription factor with a

CRE sequence, whose mRNA levels peak within ~30-45 minutes and whose protein form peaks between ~60-90 minutes (Guzowski et al. 2002). As such, the expression of c-Fos can be leveraged to reflect a histological “snapshot” of recent neural activity within the aforementioned timeframes. Of course, while the temporal resolution of IEGs is limited to the time it takes for transcription and translation to occur, the spatial pattern of activity provided is beneficial for mapping out the many interacting neural regions involved in processing memories. For instance, by examining the expression of IEGs such as c-Fos, several groups have found that selected cell populations active during the acquisition of a fear memory were preferentially reactivated during the recall of that memory in different areas of the mouse brain, such as the amygdala (Reijmers et al. 2007), the hippocampus

(Deng et al. 2013; Tayler et al. 2013), multiple layer II cortical areas including the sensory cortex (Xie et al. 2014) and the prefrontal cortex (Zelikowsky et al. 2014). In humans, IEG studies are by necessity sparse, although single unit recordings can still detect individual neuronal activity and have indeed identified cells in the hippocampus and surrounding areas that were reactivated only during the free memory recall of a particular individual, landmark (Quiroga et al. 2005), or episode (Gelbard-Sagiv et al.

2008). These observational experiments showed that the activities of defined neurons are closely tied to selected memories, hinting at the possibility that engram-processing cells are contained in the populations of the neurons studied. The topics of sufficiency and necessity are covered in the subsequent chapters.

The most well characterized IEGs are zif268, c-fos, and Arc/Arg3.1, and all have been implicated in supporting memory formation. Mice with a deletion of zif268 show deficits in contextual fear conditioning (CFC) and the hidden platform variant of the

Morris Water Maze (MWM) (Jones et al. 2001). A similar result was obtained in mice lacking the c-fos gene in the central nervous system (Fleischmann et al. 2003). These mice also had impaired long-term potentiation (LTP), but developmental effects of c-fos gene deletion could not be excluded from contributing to the observed phenotypes.

Antisense oligodeoxynucleotide (As-ODN)-mediated blockade of c-fos translation in the hippocampus caused impaired consolidation of inhibitory avoidance, MWM, and socially transmitted food preference behaviors (Guzowski and McGaugh, 1997; Guzowski, 2002;

Countryman et al. 2005), all of which are tasks thought to depend on the integrity of the hippocampus. As-ODN mediated translational inhibition of Arc, and mice with global genetic deletion of Arc, have demonstrated an obligatory role for this IEG in consolidation of MWM, fear conditioning, conditioned taste aversion, and novel object recognition as well (Guzowski et al. 2000; Plath et al. 2006).

In addition, studies of Arc and c-fos expression after behavioral training have shown that the proportion of cells expressing these IEGs in DG (2-6%), CA3 (20-40%), and CA1 (40-70%) after exposure to a novel environment resembles the proportion of hippocampal excitatory cells physiologically active in a given environment, which further validates their use as an indicator of recent neural activity (Vazdarjanova and Guzowski,

2004). The pattern of c-fos and Arc expression is selective for specific spatial contexts, and it is stable upon re-exposure to the same environment—the IEG-mediated neuronal

“snapshot” of an engram that we observe seems to be highly conjunctive in nature but with remarkably labile synaptic properties that allow flexible memory updating, which is

22 discussed in subsequent chapters (Guzowski et al. 2006; Richards and Frankland, 2013).

It is in light of these studies that our primary hypothesis for memory engrams emerges – namely, that hippocampus cells expressing c-fos during learning are participating in the encoding of specific experience and that, therefore, the reactivation of these cells may be capable of driving a component of the memory trace itself.

2.1.2 Combining optogenetic and transgenic technologies

August 14th, 2005, gave the world a paper that would instantly launch a thousand projects—a true scientific revolution had started; a seismic paradigm shit of Kuhnian magnitude. Ed Boyden, Feng Zhang, Ernst Bamberg, Georg Nagel, and Karl Deisseroth at Stanford pioneered a technique that would permit neuroscientists to probe the brain at the level on which it communicates—namely, milliseconds (Boyden et al. 2005). The principle behind optogenetics is astonishingly simple: genetically trick brain cells to respond to light, and thus confer millisecond control over defined sets of cells in the brain. When combined with transgenic technologies, it becomes possible to genetically target cell bodies, dendrites, and terminals, within virtually any cell type in the brain (e.g. dopaminergic, serotonergic). The single component system utilizes the algae-derived channelrhodopsin-2 for excitation or the archaea-derived halorhopsin, engineered in viruses of various serotypes (e.g. adeno associated virus, lentivirus, herpes-simple virus) to rapid delivery into brain tissue. For a comprehensive overview on the variety of opsins available and their caveats, see Yizhar et al. 2011 and Hausser, 2014.

It now became possible to rigorously test some of the more technically challenging hypotheses about memory engrams, namely, those centering on activating brain cells to test their sufficiency in driving behavior. Was it possible to artificially reactivate a specific population of neurons activated by learning to mimic behavioral recall elicited by natural cues? Such studies have been difficult due to the lack of proper tools that allow precise temporal and spatial control over the activity of defined neuronal populations. With the advent of optogenetics, such manipulations indeed have become possible. For instance, by combining the activity-dependent, doxycycline-regulatable c- fos-tTA system (Reijmers et al. 2007) and ChR2-mediated optogenetics, we were able to

24 label with ChR2 a sparse population of DG neurons in the mice that were activated by contextual fear memory conditioning. Subsequently, when these cells were reactivated by blue light in a context different from the original one used for the conditioning, these animals displayed freezing behavior as evidence of fear memory recall (Figure 2A) (Liu et al. 2012). Importantly, this type of DG-mediated light-induced fear memory recall was also recently shown to require CA1 neuronal activity during encoding in order for the labeled DG engram cells to be able to subsequently drive freezing behavior (Ryan et al.

2015). This finding is consistent with the notion that labeled DG engram cells are not hard-wired to a fear motor output the way areas such as the periaqueductal gray are presumably. These studies are discussed in detail in chapter 3.

Additionally, a slew of newly genetically engineered mice also permit activity- dependent and inducible control of genes of interest. For example, a recent study demonstrated the powerful use of a tamoxifen-dependent recombinase CreERT2 mouse in which the immediately early genes Arc and Fos drive the expression of genes of interest within a 12 hour window (Guenthner et al. 2013) in all hippocampal subregions and cortex. Another study engineered ArcCreERT2 bacterial artificial chromosome (BAC) transgenic mice for indelible labeling of cells in an activity-dependent and inducible manner as well (Denny et al. 2014).

Gain-of-function studies also identified putative engram cell populations outside of the hippocampus. Two groups of researchers were able to over-express CREB in a small population of LA cells, which made them preferentially recruited into the memory trace of the subsequent fear conditioning. They labeled these cells with exogenous receptors, TRPV1 or DREADD (designer receptors exclusively activated by designer drug) receptor hM3Dq. When they artificially activated these labeled neurons by

25 administrating the receptor ligands capsaicin (for TRPV1) or CNO (for hM3Dq) in a novel environment, the animals showed modest fear memory recall (Kim et al. 2014; Yiu et al. 2014). More recently, retrosplenial cortex (RSC) neurons activated during the formation of a fear memory were also shown to be able to elicit fear memory recall when re-activated through optogenetics in a novel context (Cowansage et al. 2014). This RSC- driven memory also preferentially reactivated activity in several cortical and subcortical areas known to process various components of memories, including the BLA, CeA, entorhinal cortex, and trends in the auditory and piriform cortex. Together, these experiments demonstrate that selected neuronal ensembles that are activated by learning are capable of eliciting memory recall once they are reactivated, thus providing compelling evidence for the existence of memory engram cells. Given such evidence, the remaining task is to identify the nature of the enduring changes that elicited in these cells by learning, which is further discussed in chapter 7.

Chapter 3: Illuminating a memory

A defined memory is thought to be encoded by a distinct set of cells—cells that are distributed throughout various cortical and subcortical areas, each differentially contributing to an overall engram. A simplified proposition of how components of episodic-like memory can be systematically teased apart is that each brain region differentially contributes to behaviors depending on task demands and the kinds of memories processed. Presumably, episodic-like memories with salient visual and auditory information contain traces in their corresponding cortical areas (e.g. A1, V1, respectively) (Weinberger, 2004); contextual information may leave a trace in entorhinal- hippocampal regions (Eichenbaum, 2000); the emotional tone involved in the memory can be partially realized via amygdala activity (LeDoux, 2000); and translating motivational states into motor output can be processed in ventral striatal circuits, particularly the nucleus accumbens, as well as its striatal targets (Ambroggi et al. 2008).

The coordinated activity among these and many other brain regions perhaps produces the richness of an episodic memory in real-time. I posit that such a manner of systematically assessing and ascribing functions to defined sets of cells produces powerful hypotheses concerning how components of an engram can be isolated, activated, or inactivated, as well as equally powerful predictions on their causal contributions to behavior and cognition. It is feasible, for instance, that a “tone engram” can be isolated in auditory cortical areas and inhibited during tone memory recall, perhaps even leaving the contextual components of the memory intact. Or, one can test if hippocampal activity is necessary for the cortical reinstatement of modality-specific responses originally active during learning (see Tanaka et al. 2014). Indeed, these tantalizing hypotheses are now

27 tractable in light of the technologies and conceptual advances described in the preceding chapters.

Neurons in areas such as the hippocampus, amygdala, and cortex can be tagged during learning for subsequent identification and manipulation. Moreover, their ablation or inactivation results in reduced memory expression, suggesting their necessity in mnemonic processes. However, up until 2012, a critical question of sufficiency remained: could one elicit the behavioral output of a specific memory by directly activating a population of neurons that was active during learning? In this chapter, we show that optogenetic reactivation of hippocampal neurons activated during fear conditioning is sufficient to induce freezing behavior. We labeled a population of hippocampal dentate gyrus neurons activated during fear learning with channelrhodopsin-2 (ChR2) and later optically reactivated these neurons in a different context. The mice showed increased freezing only upon light stimulation, indicating light-induced fear memory recall. This freezing was not detected in non-fear conditioned mice expressing ChR2 in a similar proportion of cells, nor in fear conditioned mice with cells labeled by EYFP instead of

ChR2. Finally, activation of cells labeled in a context not associated with fear did not evoke freezing in mice that were previously fear conditioned in a different context, suggesting that light-induced fear memory recall is context-specific. Together, our findings suggest that activating a sparse but specific ensemble of hippocampal neurons previously active dearing learning is sufficient for memory recall. Moreover, our experimental approach offers a general method of mapping cellular populations potentially bearing memory engrams.

3.1.1 Introduction: loss-of-function approaches to dissecting memory

How is a distinct memory formed and stored in the brain? Recent studies indicate that defined populations of neurons correspond to a specific memory trace, suggesting a cellular correlate of a memory engram (Reijmers et al. 2007; Han et al. 2007). Selective ablation or inhibition of such neuronal populations erased the fear memory response indicating that these cells are necessary for fear memory expression (Han et al. 2009).

However, to demonstrate that a cell population is a cellular basis of a specific fear memory engram, one has to conduct a mimicry experiment to show that direct activation of such a population is sufficient for inducing the associated behavioral output (Martin and Morris 2002). Sufficiency experiments have been technically challenging before the combination of transgenic and optogenetic technologies, partly due to the limitations of pharmacological agonists and indiscriminate electrical stimulation—the main limitation being specificity. How can we specifically target and manipulate only the brain cells active during memory-related processes?

A rich body of literature has informed the field on which brain areas and which cells are necessary for memory storage and expression. Loss-of-function studies manipulate the system by either eliminating or inhibiting memory-related neuronal populations to see if such manipulations cause the impairment of a memory. By randomly over-expressing the transcription activator cAMP response element-binding protein

(CREB) in a small population of neurons in the lateral amygdala (LA), a group of researchers could make these cells more likely to be recruited to become a part of engram cells during a subsequent fear conditioning training (Han et al. 2007). By selectively ablating these cells using a diphtheria toxin-based method (Han et al. 2009) or inhibiting these cells with allatostatin (Zhou et al. 2009), two groups of researchers were able to

29 interfere with the recall of the associated fear memory in mice. Using an activity- dependent and inducible system based on the promoter of IEG Arc and a Cre recombinase activated by Tamoxifen, Denny et al. (2014) labeled neuronal populations that were activated in either the dentate gyrus (DG) or CA3 of the hippocampus during the acquisition of a contextual fear memory, and subsequently inactivated these cells using optogenetics. This resulted in impairment of the fear memory recall (Denny et al.

2014). Given that ~80% of Arc+ cells are also c-Fos+, this finding on the necessity of DG cells compliments our findings on the sufficiency of DG cells (Liu et al. 2012, discussed below) in modulating context-specific memories. Another study used a c-Fos-based targeting strategy and found similar memory impairments when previously active CA1 neurons were optogenetically inhibited during fear memory recall (Tanaka et al. 2014).

The latter study also found that when context-specific CA1 cells were inhibited, cortical reinstatement failed to occur in the subiculum, lateral entorhinal cortex, amygdala and retrosplenial cortex. Importantly, this study also showed that if CA1 cells that would normally be active to encode an overlapping contextual representation were inhibited, the new representation was simply stored in another population of CA1 cells instead and would still lead to unimpaired fear memory recall. This demonstrates that hippocampus engrams can be stored in varying hippocampal cell populations; in other words, inhibiting hippocampus engram cells inhibits the recall of the labeled memory but does not inhibit the learning of new memories of similar contextual content. Therefore, hippocampal engram cells are not hard-wired to a given perceptual input the way areas such as the retina are presumably—a conjecture that was only recently tested by leveraging the aforementioned loss-of-function strategies.

Other studies have shown that contextual memory associated with a positive reinforcer such as cocaine could be blocked by either inactivating a minority of nucleus accumbens neurons that were active in the drug-associated environment in rats by the

Daun02 method (Koya et al. 2009), or by suppression of a small population of LA neurons over-expressing CREB (thus were also more active in the environment previously associated with drug administration) using pharmacogenetics method in mice

(Hsiang et al. 2014). Collectively, these experiments demonstrated that the disrupted cell populations impair the memory, supporting the notion that they contain an obligatory part of the engram complex.

In the next section, I describe our experimental approach to tackle the sufficiency issue in attempting to activate context-specific memories. As reviewed earlier, we began by targeting the hippocampus in light of its critical role in the formation of the contextual component of fear memories. More specifically, modeling and experimental studies have demonstrated an essential role of the dentate gyrus (DG) of the hippocampus in discriminating between similar contexts. Cellular studies of immediately early gene

(IEG) expression showed that sparse populations of DG granule cells (2–4%) are activated in a given context. Moreover, although the same population of DG granule cells is activated repeatedly in the same environment, different environments or different tasks activate different populations of DG granule cells. These lines of evidence point to the

DG as an ideal target for the formation of contextual memory engrams that represent discrete environments. We tested whether or not a set of DG cells active during fear conditioning were sufficient for the behavioral expression of a fear memory on May 26,

2011. What follows are the results of our experiments, which demonstrate that DG cells

31 active during fear conditioning define an active neural population sufficient for the behavioral expression of fear upon subsequent optogenetic reactivation.

3.1.2 Results: Hippocampus cells are sufficient for memory expression

To label and reactivate a subpopulation of DG cells active during the encoding of a memory, we targeted the DG of c-fos-tTA transgenic mice with the AAV9-TRE-ChR2-

EYFP virus and an optical fiber implant (Fig. 1a). This approach directly couples the promoter of c-fos, an IEG often used as a marker of recent neuronal activity, to the tetracycline transactivator (tTA), a key component of the doxycycline (Dox) system for inducible expression of a gene of interest. In our system, the presence of Dox inhibits c- fos-promoter-driven-tTA from binding to its target tetracycline-responsive element (TRE) site, which in turn prevents it from driving ChR2-EYFP expression. In the absence of

Dox, training-induced neuronal activity selectively labels active c-fos–expressing DG neurons with ChR2-EYFP, which can then be reactivated by light stimulation during testing (Fig. 1b, c). We confirmed that our manipulation restricts the expression of ChR2-

EYFP largely to the DG area of the hippocampus (Fig. 1d–g).

First, to characterize the inducible and activity-dependent expression of ChR2-

EYFP, we examined its expression timeline under various treatments (Fig. 2a–h). We observed a complete absence of ChR2-EYFP expression in DG neurons while mice were on Dox (Fig. 2a). Two days off Dox was sufficient to induce ChR2-EYFP expression in home-caged mice (Fig. 2b). The number of ChR2-EYFP–positive cells increased significantly in response to two days off Dox followed by fear conditioning (FC; Fig. 2c).

We found that the vast majority of c-fos–positive cells was also ChR2-EYFP–positive

(Supplementary Fig. 1), confirming that activity-dependent labeling with ChR2-EYFP recapitulated the induction of endogenous c-fos. A similar increase in ChR2-EYFP expression was seen in a group of mice that was exposed to the same context and tone as the FC group but had no shocks delivered (NS; Fig. 2d). ChR2-EYFP expression lasted at

33 least five days (Fig. 2e) and was gone by 30 days (Fig. 2f). Kainic-acid–induced seizures resulted in complete labeling of DG cells with ChR2-EYFP (Fig. 2g), indicating that the relatively sparse labeling in the FC or NS groups was not due to the low infection rate of the virus, but reflected the natural low activity of DG neurons during the training sessions.

Notably, NS and FC treatments resulted in similar proportions of ChR2-EYFP–positive cells (Fig. 2h). ChR2-EYFP expression following FC seemed to be restricted to the excitatory neurons, as no overlap was detected between ChR2-EYFP–positive neurons and GABA-positive inhibitory neurons (Supplementary Fig. 2).

We injected c-fos-tTA mice with either AAV9-TRE-ChR2-EYFP or AAV9-TRE-

EYFP, subjected them to fear conditioning while off Dox, and then put them back on

Dox to test for light-evoked responses from DG cells the following day. The mice were anesthetized for in vivo recordings and blue light pulses (473 nm, 0.1 Hz, 15 ms pulse duration) were delivered to the DG. Consistent with the sparse labeling of DG neurons

(Fig. 2h), we identified only 10 DG neurons that responded to light stimulation from nine c-fos-tTA mice injected with AAV9-TRE-ChR2-EYFP (the ChR2 group). In these neurons, we detected a reliable increase of spike probability precisely time-locked to the onset of light pulses (Fig. 2l, m). These cells also showed robust responses to trains of 20

Hz light stimulation with a slight decrease in spike probability over time that remained significantly higher above baseline (Fig. 2n). We did not find any light-responsive cells in the 10 c-fos-tTA mice injected with AAV9-TRE-EYFP (the EYFP group; data not shown). Most of the ChR2-EYFP–positive cells in the ChR2 group of mice were also positive for endogenous c-fos after optical stimulation, although not all c-fos–positive cells expressed ChR2-EYFP. Very few neurons expressing EYFP in the EYFP group of mice were c-fos–positive (Fig. 2i–k and Supplementary Fig. 3). The proportion of c-fos–

34 positive cells in the downstream CA3 region was greater in the ChR2 group compared with the EYFP group after optical stimulation of DG neurons, and this number was comparable to the proportion of CA3 c-fos–positive cells obtained by exposing a separate group of fear conditioned mice to the conditioned context (Supplementary Fig. 4).

Next, we tested whether activating a population of DG neurons labeled by ChR2-

EYFP during the encoding of a fear memory was sufficient for memory recall. The experimental group (Exp) consisted of c-fos-tTA mice unilaterally injected with AAV9-

TRE-ChR2-EYFP and implanted with an optical fiber targeting the DG (Fig. 1a). Mice were kept on Dox and underwent five days of habituation to record their basal level of freezing in one context (context A) during both light-off and light-on epochs. Next, they were taken off Dox and underwent fear conditioning in a distinct chamber (context B) in which a tone was paired with shock. The mice were then subjected to five days of testing with light-off and light-on epochs in context A while on Dox (Fig. 1c). During the habituation sessions, the Exp mice showed very little freezing during either light-off or light-on epochs. In contrast, after fear conditioning, freezing levels during light-on epochs were significantly higher compared with light-off epochs, which indicated light- induced fear memory recall (Fig. 3a). Increased freezing during light-on epochs was observed across all five days of test sessions with no discernible day-dependent difference (Supplementary Fig. 5g). These data suggest that DG cells that express endogenous c-fos during training, and therefore become labeled by ChR2-EYFP, define an active neural population that is sufficient for memory recall upon subsequent reactivation.

To rule out the possibility that post-training freezing by optical stimulation was due to the activation of DG cells unrelated to fear learning, we injected another group of

35 mice (NS) with AAV9-TRE-ChR2-EYFP and administered the same habituation, training, and test sessions as the Exp group, except that no shock was delivered during the training session. Despite the fact that a similar level of ChR2-EYFP expression was detected in the NS group compared with the Exp group, both in terms of proportion of cells labeled

(Fig. 2h) and ChR2-EYFP fluorescence intensity per cell (Supplementary Fig. 6), light did not induce post-training freezing in the NS group (Fig. 3b). This indicates that the freezing observed in the Exp group requires optical activation of a specific subset of

ChR2-EYFP–positive DG cells that are associated with FC and that activating a population of DG cells not associated with FC does not induce freezing. Yet another group of mice (EYFP) were injected with AAV9-TRE-EYFP and underwent identical habituation, training, and testing sessions as the Exp group. The proportion of cells expressing EYFP was comparable to that seen in the Exp group expressing ChR2-EYFP

(Supplementary Fig. 7). However, the EYFP group did not show increased post-training freezing (Fig. 3c). This result rules out the possibility that increased freezing in the Exp group was due to any non-specific effects of post-training optical stimulation.

The light-induced freezing levels of the Exp group were relatively low (~15%) compared with those typically reported from exposure to a conditioned context (~60%).

One possibility is that light activation of background-activity–induced ChR2-EYFP (Fig.

2b) interfered with the expression of the specific fear memory. We confirmed that limiting the off Dox period from two days to one day reduced the background expression of ChR2-EYFP by at least twofold (compare Supplementary Fig. 8a Home cage with Fig.

2h Home cage). A group of mice (Exp-1day) that went through the same design outlined in Figure 1c but with this modification showed greater freezing levels (~25%) during the light-on epoch of test sessions compared to the Exp group (Fig. 3d, f). Another possible

36 factor contributing to the modest light-induced freezing in the Exp group may be the limited number of cells optically stimulated. To test this possibility, we bilaterally injected a group of mice (Exp-Bi) with AAV9-TRE-ChR2-EYFP and bilaterally implanted optical fibers targeting the DG, and then subjected these mice to the same scheme as that shown in Figure 1c. During the light-on epochs of the test sessions, the

Exp-Bi group exhibited levels of freezing (~35%) that were almost as high as those induced by the conditioned context (Fig. 3e, f, Supplementary Fig. 9).

We next examined whether the light-induced fear memory recall was context- specific. First, to test whether two different contexts activate similar or distinct populations of DG cells, we took the mice off Dox for two days and then exposed them to a novel context (context C, an open field) to label the active DG cells with ChR2-EYFP.

After being put back on Dox, the mice were fear conditioned in a different context

(context B) and sacrificed 1.5 hours later (Fig. 4a). The expression of ChR2-EYFP was used to identify cells previously activated in context C whereas endogenous c-fos was used to identify cells recently activated in context B. Immunohistochemical analyses revealed a chance level of overlap between ChR2-EYFP–positive and c-fos–positive cells, suggesting that two independent DG cell populations were recruited for the representation of the two distinct contexts (Fig. 4b–g). To test the context-specificity of light-induced recall of a fear memory, we subjected a new group of mice (an open field- fear conditioned group, OF-FC) to habituation sessions in context A, followed by two days off Dox and context C exposure to label neurons active in context C with ChR2-

EYFP. Next, we put the mice back on Dox and performed fear conditioning in context B

(Fig. 4h). These mice were then placed back in context A and tested for light-induced freezing. Light failed to evoke a significant increase in freezing responses (Fig. 4i).

Similarly low levels of freezing were observed in another group of mice (FC-OF) in which fear conditioning in context B while on Dox preceded exposure to context C while off Dox (Supplementary Fig. 10). Together, these results indicate that light reactivation of cells labeled in context C did not induce fear memory recall associated with context B.

3.1.3 Discussion

Here we have shown that optical activation of hippocampal cells that were active during fear conditioning elicits freezing behavior. To our knowledge, this is the first demonstration that directly activating a subset of cells involved in the formation of a memory is sufficient to induce the behavioral expression of that memory. Our results and previous studies that addressed the necessity of similarly sparse cell populations in the amygdala argue that defined cell populations can form a cellular basis for fear memory engrams (Reijmers et al. 2007; Han et al. 2007 and 2009). The memory engram that we selectively labeled and manipulated is likely contextual in nature, as previous studies have demonstrated that hippocampal interventions affect conditioned freezing responses to a context but not a tone (Phillips and LeDoux, 1992). Indeed, recent findings show that optogenetic inhibition of the hippocampal CA1 region during training or testing both inhibited the recall of contextual fear memory, while leaving auditory-cued fear memory recall intact (Goshen et al. 2011). However, we cannot completely rule out the possibility that the fear memory recalled in our experiments may have some tone memory component.

Our observation that freezing responses were elicited by optical stimulation in the experimental groups (Exp, Exp-1day, and Exp-Bi), but not in the OF-FC or FC-OF group, strongly supports a dual memory engram hypothesis of contextual fear conditioning. In this hypothesis, hippocampal cells are recruited to form contextual memory engrams, but these contextual engrams alone do not represent a complete fear memory. For a fear memory to be formed, the information from the contextual memory engram must be transferred to the basolateral amygdala (BLA) coincidentally with the information representing a foot shock. In the OF-FC or FC-OF scheme, two distinct contextual

39 memory engrams were formed in the DG, which were represented by two distinct sets of

DG cells. One of these two contextual engrams (the one for context B) was associated with the representation of the shock, but not the other engram (the one for context C).

Since ChR2 labeled the latter, but not the former, optical stimulation could not elicit fear memory expression.

Although we have demonstrated the “sufficiency” of a DG memory engram for the behavioral expression of fear memory, it does not necessarily mean that this engram is “necessary” for behavioral recall. During contextual fear conditioning, it is likely that multiple contextual memory engrams are formed in a series of hippocampal regions.

Each of these engrams may contribute to the formation of the complete fear memory in the BLA and may also be capable of reactivating it independently as we observed in the case of the DG engrams. Since the hippocampus is not a linear feed-forward network but contains several parallel circuits, inhibiting the formation or activation of contextual engrams in one region may not necessarily block the expression of the fear memory. For instance, disruption of contextual memory engrams in the DG could be circumvented by

CA1 engrams, which could be generated through the direct input from the entorhinal cortex and may be sufficient to activate the fear memory engram in the BLA. Indeed, we recently generated a mouse mutant, which permitted us to demonstrate that the DG input to the CA3 is dispensable in the formation and retrieval of contextual fear memory

(Nakashiba et al. 2012).

Notably, a more recent optogenetic study (Khierbek et al. 2013) supported the findings of Nakashiba et al. (2012) by demonstrating that real-time inhibition of POMC- defined DG cells affected fear memory encoding, but not retrieval. However, Denny et al.

(2014) found that optical inhibition of a defined set of previously active DG cells indeed

40 was necessary for fear memory retrieval. Such findings are not inconsistent; rather, they highlight the caution needed when interpreting multiple sets of data generated by disparate sets of techniques and their associated levels of specificity. For example, it is feasible that optical inhibition of the majority of DG cells leads to rapid compensation by other cortical areas (e.g. entorhinal cortex layer III) while optical inhibition of a sparse population of previously active DG cells unmasks their necessary contribution to behavior, in a sense “short-circuiting” memory recall in real-time. This speculation remains to be determined. However, the same applies for sufficiency studies: for instance, it is feasible that activation of the majority of DG cells may mask the behavioral contributions that the sparse population of cells embedded in the network perform, while activation of the sparse population itself can reliably recapitulate the associated behavior

(Liu et al. 2012). Indeed, a previous study utilized a c-Fos-based tagging strategy and found that pharmacogenetic activation of cells previously active during fear learning failed to recapitulation memory recall (Garner et al. 2012), while optogenetic activation of a sparse set of DG cells indeed reinstated the behavioral expression of fear memory.

Collectively, the approach and methods described in this work provide a powerful tool for mapping and manipulating the various components comprising an engram. A multifaceted analysis of these components and their interplay will reveal the nature of the overall memory engram. Indeed, these experiments directly test the hypothesis that hippocampal learning-activated c-fos-expressing cells are sufficient to activate a hippocampus-dependent memory. In summary, optogenetic reactivation of cells active during fear learning was sufficient to drive the associated fear response (Liu et al. 2012), thus demonstrating their causal contributions to activating the behavioral expression of a memory.

3.1.4 Methods

Subjects

The c-fos-tTA mice were generated from TetTag mice (Reijmers et al. 2007) by breeding them with C57BL/6J mice and selecting those carrying only the c-fos-tTA transgene and not the bi-cistronic tetO promoter driving tau-LacZ and tTAH100Y transgenes. These mice also contained a separate transgene consisting of a c-fos promoter driving the expression of nuclear-localized 2-hr half-life EGFP (shEGFP), which is distinct from the whole-cell- localized ChR2-EYFP. Mice had food and water ad libitum and were socially housed until the beginning of the surgery. The mice were 8–12 weeks old at the time of surgery and had been raised on food containing 40 mg/kg Dox for four weeks prior to surgery.

Mice were single housed post-surgery and throughout the rest of the experiments. All procedures relating to mouse care and treatment conformed to the institutional and NIH guidelines.

Virus construct and packaging

The pAAV-TRE-ChR2-EYFP plasmid was constructed by cloning TRE-ChR2-EYFP into an AAV backbone using SpeI restriction site at the 5’ terminus and blunt end at the 3’ terminus of the insert. The pAAV-TRE-EYFP plasmid was constructed by removing the

ChR2 fragment from the pAAV-TRE-ChR2-EYFP plasmid using NheI and AgeI restriction sites, blunting with T4 DNA polymerase, and self-ligation of the vector, which retained the ATG start codon of the EYFP gene from the ChR2-EYFP fusion gene. The recombinant AAV vectors were serotyped with AAV9 coat proteins and packaged by the

Gene Therapy Center and Vector Core at the University of Massachusetts Medical

13 13 School. Viral titers were 1 × 10 GC/ml for AAV9-TRE-ChR2-EYFP and 1.5 × 10

GC/ml for AAV9-TRE-EYFP.

Stereotactic injection and optical fiber implant

All surgeries were performed under stereotaxic guidance. Mice were anesthetized using

500 mg/kg Avertin. The virus was injected using a glass micropipette attached to a 10 µl

Hamilton microsyringe (701LT; Hamilton, Reno, NV) through a microelectrode holder

(MPH6S; WPI, Sarasota, FL) filled with mineral oil. A microsyringe pump (UMP3; WPI,

Sarasota, FL) and its controller (Micro4; WPI, Sarasota, FL) were used to control the speed of the injection. The needle was slowly lowered to the target site and remained for

10 min before the beginning of the injection. Mice for timeline studies and head-fixed electrophysiology recordings were injected bilaterally (–2.2 mm AP; ±1.3 mm ML; –2.0 mm DV) with 0.15 µl AAV9 virus at a rate of 0.1 µl/min. After the injection the needle stayed for five additional minutes before it was slowly withdrawn. The mice used for behavior tests were unilaterally or bilaterally injected with the virus same as described above. After withdrawing of the needle, a Doric patchcord optical fiber (200 µm core diameter; Doric lenses, Quebec, Canada) precisely cut to the optimal length was lowered above the injection site (–2.2 mm AP; ±1.3mm ML; –1.6 mm DV). Three jewelry screws were screwed into the skull surrounding the implant site of each hemisphere to provide extra anchor points. A layer of adhesive cement (C&B Metabond; Parkell, Edgewood,

NY) was applied followed with dental cement (Teets cold cure; A-M Systems, Sequim,

WA) to secure the optical fiber implant. A cap made from the bottom part of a 15 ml

Falcon tube (for unilateral implant) or the top part of an Eppendorf tube (for bilateral

43 implant) was inserted to protect the implant and the incision was closed with sutures. The mouse was given 1.5 mg/kg Metacam as analgesics and remained on a heating pad until fully recovered from anesthesia. Mice were allowed to recover for two weeks before all subsequent experiments. All fiber placements (Supplementary Fig. 11) and viral injection sites were verified histologically. As criteria we only included mice with ChR2-EYFP expression limited to the dentate gyrus, which lead to the exclusion of two mice throughout the study.

ChR2-EYFP and EYFP expression timeline

Fourteen days post-surgery, subjects were either kept on Dox and immediately sacrificed or taken off Dox for one or two days. The mice from the latter two groups were either sacrificed with no further treatments (home cage), or underwent fear conditioning or no shock protocols as described in the behavior section below. After each treatment, mice were sacrificed 1.5 hours, 24 hours, five days, or 30 days later as described in the main text and underwent immunohistochemistry procedures. For seizure experiments, mice were taken off Dox for two days and injected i.p. with 20 mg/kg kainic acid. The mice were sacrificed six hours after the first behavioral onset of seizure.

In vivo recording

Mice were anesthetized by isoflurane inhalation and placed in the stereotactic system with anesthesia maintained with 0.5–1% isoflurane throughout the recording. An optrode consisting of a tungsten electrode (1 MΩ) glued to an optical fiber (200 µm core diameter,

Doric Lenses, Inc.), with the tip of the electrode extending beyond the tip of the fiber by

500 µm was used for simultaneous optical stimulation and extracellular recordings. The optrode was lowered to the dentate gyrus (–2.2 mm AP; 1.3 mm ML; –2.0 mm DV) using a hydraulic micromanipulator (Model 640; David Kopf Instruments, Tujunga, CA). The optical fiber was connected to a 200 mW 473 nm laser (MBL F473; Opto Engine,

Midvale, UT) and controlled by a function generator (33220A; Agilent Technologies,

Santa Clara, CA). The power intensity of light emitted from the optrode was calibrated to about 9 mW, which was consistent with the power intensity used in the behavioral assays.

To identify ChR2-labeled cells, light pulses of 15 ms were delivered at 0.1 Hz at the recording sites approximately every 5–10 µm throughout the dentate gyrus. After light responsive cells were detected, two types of light stimuli were tested: 15 ms light pulse every 10 s and a train of ten 15 ms light pulses at 20 Hz every 10 s. Unit activity was band-pass filtered (500 Hz–5 KHz) and acquired with an Axon Digidata 1440A acquisition system running Clampex 10.2 software. Data was analyzed with custom software written in Matlab. Following the recording, endogenous c-fos expression was induced by delivering two epochs of 3-min light stimulation (9 mW, 20 Hz, 15 ms) separated by three min to dentate gyrus, same as in behavioral experiments (see below).

Mice were sacrificed and perfused 90 min later.

Immunohistochemistry

Mice were overdosed with Avertin and perfused transcardially with cold phosphate buffer saline (PBS), followed by 4% paraformaldehyde (PFA) in PBS. Brains were extracted from the skulls and kept in 4% PFA at 4 °C overnight. Fifty µm coronal slices

45 were taken using a vibrotome and collected in cold PBS. For immunostaining, each slice was placed in PBST (PBS + 0.2% Triton X-100) with 5% normal goat serum for one hour and then incubated with primary antibody at 4 °C for 24 hours (rabbit anti-c-fos

1:5000, Calbiochem, La Jolla, CA; rabbit anti-GABA 1:5000, Abcam, Cambridge, MA; chicken anti-GFP 1:500, Invitrogen, Carlsbad, CA). Slices then underwent three wash steps for 10 minutes each in PBST, followed by one hour incubation with secondary antibody (1:200 AlexaFlour488 anti-chicken, Invitrogen; 1:200 AlexFlour568 anti-rabbit,

Invitrogen). Slices were then incubated for 15 minutes with 4’, 6-diamidino-2- phenylindole (DAPI; 1:10,000) and underwent three more wash steps of 10 min each in

PBST, followed by mounting and coverslipping on microscope slides.

Cell counting

To characterize the expression timeline of ChR2-EYFP and EYFP, the number of EYFP immunoreactive neurons in dentate gyrus were counted from six coronal slices (spaced

120 µm from each other) per mouse (n = 5 for ChR2 group, n = 3 for EYFP group).

Coronal slices were taken from dorsal hippocampus centered on coordinates covered by our optical fiber implants (–1.94 mm to –2.46 mm AP; Supplementary Fig. 11). Confocal fluorescence images were acquired on a Leica TCS SP2 AOBS scanning laser microscope using a 20×/0.70 NA oil immersion objective. The image analysis module

Visiomorph DP within VIS (Visiopharm, Copenhagen, Denmark) calculated the number of ChR2-EYFP–positive or EYFP-positive cells per section by thresholding EYFP immunoreactivity above background levels and using DAPI staining to distinguish between nuclei. The analysis module also permitted isolation of only ChR2-EYFP–

46 positive and EYFP-positive neurons by setting size and fluorescence thresholds to filter out nuclear-localized c-fos-shEGFP–positive cells. The cell body layer of DG granule cells was outlined as a region of interest (ROI) according to the DAPI signal in each slice.

A similar protocol was followed for c-fos–positive cell counts in DG and CA3, except a

Cy3 filter was applied for the latter. For quantification comparisons, we used a one-way

ANOVA followed by Tukey’s multiple comparisons using an α = 0.05. Data was analyzed using Microsoft Excel with the Statplus plug-in and Prism (GraphPad Software).

To analyze the overlap between c-fos and ChR2-EYFP–expressing or EYFP-expressing cells, a z-stack method was used in conjunction with ImageJ to montage 10 optical stacks

(1 µm each, step size 10 µm) taken under a 20×/0.70 NA oil immersive objective.

Separate GFP and Cy3 filtered images were digitally combined to produce composite images. Equal cutoff thresholds were applied to all captures to remove background autoflouresence. All imaging and analyses were performed blind to the experimental conditions. To quantify the expression levels of ChR2-EYFP per cell, an experimenter blind to each condition used ImageJ to calculate the fluorescence intensity signal as integrated density for 10 randomly chosen DG cells per hippocampal slice (n = 3 slices per mouse, 5 mice per condition; Supplementary Fig. 6).

Behavior assays

All the behavior tests were conducted during the light cycle of the day. Four different contexts were used in the behavior assays. Context A was a 30 × 25 × 33 cm conditioning chamber within a room with black walls, black curtains, and dim lighting. The chamber

47 had a white plastic floor and was scented with 0.25% benzaldehyde. Context B was a 29

× 25 × 22 cm conditioning chamber within a second room with white walls and bright lighting. The chamber had a gridded floor and a triangular roof, and was scented with 1% acetic acid. Context C was a 41 × 41 × 31 cm unscented open field arena within a third room with white walls and intermediate lighting. Context D was a 29 × 25 × 22 cm conditioning chamber in the same room as context C. It had a white acrylic glass floor and was unscented. The experimental groups (Exp, Exp-1day, and Exp-Bi) and EYFP control (EYFP) groups underwent exactly the same training protocol. During the habituation session, each mouse was introduced to context A daily for five days while on

40 mg/kg Dox food. Each day the mouse was loaded into the chamber and the optical fiber implant was connected to a 473 nm laser (MBL F473; Opto Engine, Midvale, UT) controlled by a function generator (33220A; Agilent Technologies, Santa Clara, CA). The mouse was then allowed to explore the chamber for 12 min. The 12 min session was divided into four 3-min epochs, with the first and third epoch as the light-off epochs, and the second and fourth epochs as the light-on epochs. During the light-on epochs, the mouse received light stimulation (9 mW, 20 Hz, 15 ms) for the entire three min duration.

At the end of the 12 min, the mouse was immediately detached from the laser and returned to its home cage. Following the fifth habituation session, the mouse was kept on regular food without Dox for one (Exp-1day) or two (Exp, Exp-Bi, and EYFP) days until the training session. On the training day the mouse received three training trials separated by three hours in home cage. For each training trial, the mouse was kept in the conditioning chamber in context B for 500 s. A tone (20 s, 75 dB, 2000 Hz) was turned on at 180 s, 260 s, 340 s, and 420 s, each of which co-terminated with a foot shock (2 s,

0.75 mA). After the third training trial, the mouse was returned to its home cage and placed on food containing 1 g/kg Dox over night to rapidly turn off any additional ChR2-

EYFP or EYFP expression. The test session started the next day and the mouse was switched back to food containing 40 mg/kg Dox. The procedure for the 5-day test session was exactly the same as the habituation session in context A. The day after the last test session, the mouse was returned to the original context B and exposed to the chamber for

300 s for a retrieval session to assay contextual fear memory. The next day, the mouse was introduced to context D for cued fear memory retrieval. This session lasted for 780 s, with a tone (60 s, 75 dB, 2000 Hz) turned on at 180 s, 420 s and 660 s. The no shock

(NS) group went through the same habituation, training, and test sessions as the Exp group, except that no foot shock was given during the training session. The open field- fear conditioned (OF-FC) group went through the same habituation sessions. After the fifth habituation session, Dox was removed from the mouse’s diet for two days, followed by exposure to the open field arena in context C to allow for 10 minutes of active exploration. The mouse was subsequently returned to its home cage and placed on 1 g/kg

Dox food over night. The following day, the mouse was fear conditioned in context B in the same manner as described above. Test sessions were administered across five days in context A on 40 mg/kg Dox food, and the OF-FC group also underwent context and tone probe trials after the five days of testing. The fear conditioned-open field (FC-OF) group went through the same habituation sessions. The day after the fifth habituation, the mouse was kept on 40 mg/kg Dox food and went through the fear conditioning procedure in context B as described above. The mouse was placed off Dox for two days after fear conditioning. Then the mouse was exposed to the open field arena in context C and allowed to freely explore for 10 min, after which the mouse was returned to home cage with 1 g/kg Dox food over night, followed by test sessions across five days in context A on 40 mg/kg Dox food. Freezing behavior for training, context, and tone probe trials was recorded with a digital camera and measured with FreezeFrame software (ActiMetrics,

Wilmette, IL). Light stimulation during the habituation and test sessions interfered with the motion detection of the program, and thus the freezing of these sessions was manually scored. Two experimenters scored each video independently in a double-blinded manner.

The over-all scores showed a < 3% difference between the two experimenters and for simplicity only one set of score from one experimenter was reported. The manual scoring and computer scoring of the same training videos gave similar freezing scores. For each group, within each session (habituation and test) and within each epoch (light-on and light-off), a one-way ANOVA with repeated measures followed by Tukey’s multiple comparisons (α = 0.05) revealed no difference across five days (Supplementary Fig. 5).

We therefore averaged the freezing level across five days for each mouse. A Two-way

ANOVA with repeated measures followed by Tukey’s multiple comparisons (α = 0.05) revealed that only the experimental groups (Exp, Exp-1day, and Exp-Bi) showed an increase in averaged freezing levels for light-on epochs of test sessions compared to light-off epochs of test sessions and light-on epochs of habituation sessions (Fig. 3a, d, and e).

Figure 1. Basic experimental protocols and selective labeling of the DG cells by

ChR2-EYFP. a, The c-fos-tTA mouse was injected with AAV9-TRE-ChR2-EYFP and implanted with an optical fiber targeting DG. b, When off Dox, training induces the expression of c-fos-tTA, which binds to TRE and drives the expression of ChR2-EYFP, labeling a subpopulation of activated cells (yellow) in DG. c, Basic experimental scheme. Mice were habituated in context A with light stimulation while on Dox for five days, then taken off Dox for two days and fear conditioned (FC) in context B. Mice were put back on Dox and tested for five days in context A with light stimulation. d, Representative image showing the expression of ChR2-EYFP in a mouse that was taken off Dox for two days and underwent FC training. An image of each rectangular area in (d) is magnified showing DG (e), CA1 (f), and CA3 (g). The green signal from ChR2-EYFP in the DG spreads throughout entire granule cells, including dendrites (e), while the green signal confined to the nuclei in CA1 and CA3 is due to shEGFP expression from the c-fos- shEGFP construct of the transgenic mouse (f, g). Blue is nuclear marker DAPI.

Figure 2. Activity dependent expression and stimulation of ChR2-EYFP. a–f,

Representative images of DG from c-fos-tTA mice injected with AAV9-TRE-ChR2- EYFP and sacrificed after the following treatments: a, On Dox. b, Off Dox for two days in home cage. c, Same as (b) followed by fear conditioning (FC). d, Same as (c) except no shock was delivered (NS). e, Same as (c), five days post-training. f, Same as (c), 30 days post-training. g, Same as (b) followed by kainic acid injection to induce seizure. Residual green signal in (a) and (f) are from nuclear-localized c-fos-shEGFP (see Fig. 1 legend). h, Percentage of ChR2-EYFP–positive cells after various treatments represented by (a) to (g) (n = 5 subjects each; F6,28 = 94.43, *P < 0.05; ***P < 0.001). i, j,

Representative DG cells after light stimulation in c-fos-tTA mice injected with AAV9-

TRE-ChR2-EYFP (i) or AAV9-TRE-EYFP (j). k, Percentage of c-fos–positive cells among ChR2-EYFP–positive cells or EYFP-positive cells after light stimulation (n = 3

52 subjects each; ***P < 0.001). l, Light-evoked single unit activity of a DG neuron from a c-fos-tTA mouse injected with AAV9-TRE-ChR2-EYFP. Peri-event histogram (top) and raster plot (bottom) show reliable and precisely time-locked spiking relative to the onset of 15 ms light pulses (blue bar). Inset shows an overlay of waveforms for all the spikes during light stimulation. m, Spike probability and peak latency for all the light-responsive cells (n = 10) recorded as in (l). n, Multi-unit activity in the DG from a c-fos-tTA mouse injected with AAV9-TRE-ChR2-EYFP in response to trains of 10 light pulses (15 ms; blue bars) at 20 Hz. Scale bar in (a) 250 µm.

Figure 3. Optical stimulation of engram-bearing cells induces post-training freezing. a, c-fos-tTA mice injected with AAV9-TRE-ChR2-EYFP and trained with FC (Exp group) show elevated freezing during three min light-on epochs. Freezing for each epoch represents 5-day average (Supplementary Fig. 5a, g). Freezing levels for the two light-off and light-on epochs are further averaged in the inset. (n = 12, F1,22 = 37.98, ***P < 0.001). b, Mice trained similar to (a) but without foot shock (NS group) do not show increased light-induced freezing (n = 12). c, Mice injected with AAV9-TRE-EYFP and trained with FC (EYFP group) do not show increased light-induced freezing (n = 12). d, Mice trained similar to (a) but kept off Dox for one day before FC training (Exp-1day group) showed greater freezing during test light-on epochs compared to Exp group (n = 5,

F1,8 = 38.26, ***P <0.001). e, Mice trained similar to (a) but bilaterally injected with

AAV9-TRE-ChR2-EYFP and implanted with optical fibers (Exp-Bi group) showed even higher levels of freezing during test light-on epochs (n = 6, F1,10 = 85.14, ***P < 0.001). f,

Summary of freezing levels of the five groups during test light-on epochs (F4,42 = 37.62, *P < 0.05; ***P < 0.001).

Figure 4. Labeling and stimulation of independent DG cell populations. a, c-fos-tTA mice injected with AAV9-TRE-ChR2-EYFP were taken off Dox and exposed to context C to label activated cells with ChR2-EYFP (yellow), then put back on Dox and trained with FC in context B to activate endogenous c-fos (red). Representative images of DG from these mice are shown in (b) to (e). b, ChR2-EYFP–labeled cells activated in context C. c, c-fos–labeled cells activated in context B. d, Nuclear marker DAPI. e, Merge. The white and red circles show examples of ChR2-EYFP–positive and c-fos–positive cells, respectively. The c-fos–positive cells in (e) appear yellow because they express both endogenous c-fos (red) and the nuclear-localized c-fos-shEGFP (green) (see Figure 1 legend). f, Percentage of ChR2-EYFP–positive, endogenous c-fos–positive, and double- positive cells among total cells (DAPI+) (n = 5). g, Observed percentage of double- positive cells is the same as what would be expected if the two cell populations were independent (i.e. a product of the observed percentage of ChR2-EYFP–single-positive and c-fos–single-positive cells.) h, Behavior setup for mice exposed to an open field in context C while off Dox and subsequently fear conditioned in context B while on Dox (OF-FC). i, OF-FC mice (n = 5) do not show increased light-induced freezing. Scale bar in (b) 10 µm.

Supplementary Fig. 1. ChR2-EYFP expression after fear conditioning recapitulates endogenous c-fos expression. The c-fos-tTA mice were injected with AAV9-TRE- ChR2-EYFP targeting the DG and kept on Dox for a month prior to training. Then, they were taken off Dox for two days to open a window of activity-dependent labeling by ChR2-EYFP. The mice were next fear conditioned and sacrificed 1.5 hours after training to measure ChR2-EYFP and c-fos expression. (a) ChR2-EYFP, (b) c-fos, (c) DAPI, and (d) merged images. Each white rectangle is magnified to the right of the image. (e) Quantifications revealed > 93% overlap between ChR2-EYFP and c-fos–positive cells after training (n = 4–6 slices of dorsal DG/subject).

Supplementary Fig. 2. GABA and ChR2-EYFP–positive cells do not overlap.

(a) Dentate gyrus from experimental mice kept off Dox for two days and then subjected to fear conditioning express ChR2-EYFP in excitatory cells. (b) Anti-GABA. (c) DAPI. (d) Merged image. Scale bar in (a) 250 µm.

Supplementary Fig. 3. Light stimulation induces c-fos expression in cells expressing ChR2-EYFP but not EYFP.

(a)–(d) Representative DG cells after light stimulation in c-fos-tTA mice injected with

AAV9-TRE-ChR2-EYFP. (e)–(h) Representative DG cells after light stimulation in c-fos- tTA mice injected with AAV9-TRE-EYFP. (a) ChR2-EYFP. (e) EYFP. (b), (f) c-fos. (c), (g) DAPI. (d), (h) Merged images.

Supplementary Fig. 4. In vivo optical stimulation of DG cells increases c-fos expression in CA3. (a) Quantifications of c-fos expression in the CA3 of mice expressing ChR2-EYFP or EYFP after light stimulation, or a control group of mice after physiological contextual fear memory recall in the original trained context (n = 3/group,

F2,6 = 4.898, *P < 0.05). Representative c-fos positive CA3 cells in the EYFP-only group (b), ChR2-EYFP group (c), or physiological contextual fear memory recall group (d).

Supplementary Fig. 5. Habituation and testing sessions across five days.

(a)–(f) Habituation sessions produced < 5% freezing in the Exp (a), EYFP (b), no shock (NS) (c), OF-FC (d), Exp-1day (e), and Exp-Bi (f) groups. (g)–(i) Testing sessions produced significant increases in freezing during light-on epochs only in the Exp (g), Exp-1day (k), and Exp-Bi (l) groups, but not in the EYFP (h), NS (i), or OF-FC (j) groups throughout the five days. n = 12 for Exp, NS, and EYFP groups, n = 5 for Exp- 1day and OF-FC, and n = 6 for Exp-Bi.

Supplementary Fig. 6. Similar ChR2-EYFP expression levels within cells after fear conditioning and no shock exposure.

(a) ChR2-EYFP in no shock (NS) and fear conditioned (FC) groups show similar levels of fluorescence signal (n = 5 subjects each). Representative images of DG from the NS group (b) or the FC group (c). Each white rectangle is magnified to the right of the image.

Supplementary Fig. 7. Inducible and activity-dependent EYFP expression.

(a) Quantifications of EYFP expression levels in c-fos-tTA mice injected with AAV9-

TRE-EYFP and underwent different treatments (n = 3 per group, F2,6 =, 32.52, *** P < 0.001). (b) Minimal expression of EYFP in the presence of Dox. When subjects were taken off Dox for two days and fear conditioned, EYFP expression was robust throughout the dentate gyrus (c) and this expression was still present five days post-training (d). DAPI (blue), EYFP (green). Scale bar in (b) 250 µm.

Supplementary Fig. 8. Dox removal for one day is sufficient to induce ChR2-EYFP expression. (a) Quantifications revealed that mice kept off Dox for one day in home cage showed low basal levels of ChR2-EYFP and significantly higher amounts of ChR2-EYFP after fear conditioning (n = 3 per condition, *P = 0.0343). Representative DG section from a mouse kept off Dox for one day in home cage (b) or after fear conditioning (c).

Supplementary Fig. 9. Freezing time course during light stimulation and context probe trials.

Freezing time course for Exp-Bi group during light stimulation on day one (a), day three (b), and day five (c) of test session, and during context probe trial (d). For light stimulation, time 0 indicates the beginning of light onset. For the context probe trial, time 0 indicates when the mouse entered the chamber (n = 6).

Supplementary Fig. 10. Labeling and stimulation of independent DG cell populations. (a) Basic behavior setup for the Fear Conditioned-Open Field (FC-OF) group. The cfos-tTA mice were injected with AAV9-TRE-ChR2-EYFP and implanted with an optical fiber targeting the DG and kept on Dox food for two weeks. Then they were habituated to context A with light-on and light-off epochs for five days, and fear conditioned in context B while still on Dox. The next day the mice were taken off Dox for two days to open a window for activity-dependent labeling during which they were exposed to context C to label cells activated in this environment with ChR2-EYFP. Once placed back on Dox, the mice were tested in context A with light-on and light-off epochs for five days. (b) Averaged data reveal < 5% freezing across all light-off and light-on epochs throughout habituation and test sessions. Mice trained with FC-OF (n = 10) do not show increased light-induced freezing during five days of habituation sessions (c) or test sessions (d).

Supplementary Fig. 11. Optical fiber placements among different mice used in behavior tests.

The histologically verified optical fiber tip locations are marked by ×. Each mouse was implanted unilaterally, except the Exp-Bi group, which received bilateral implants.

Different colors represent different groups. Numbers indicate the anteroposterior coordinates from bregma.

Chapter 4: Updating the contents of a memory

Memories are reconstructions of the past and, as such, can be unreliable. The hippocampus has been shown to mediate both the recall of veridical episodic memories as well as that recall of false memories. However, the underlying neuronal processes sufficient to render a memory labile, followed by subsequent updating of the memory with the new information, remain poorly understood. Here, we created a false memory in mice by optogenetically manipulating memory engram-bearing cells in the hippocampus.

Dentate gyrus (DG) or CA1 neurons activated by exposure to a particular context were labeled with channelrhodopsin-2 (ChR2). These neurons were later optically reactivated during fear conditioning in a different context. The DG experimental group showed increased freezing in the original context in which a foot shock was never delivered. The recall of this false memory was context-specific, activated similar downstream regions engaged during natural fear memory recall, and was also capable of driving an active fear response. Our data demonstrate that it is possible to generate an internally represented and behaviorally expressed fear memory by manipulating DG engram cells. These DG cells, in turn, are sufficient to act as a conditioned stimulus (e.g. contextual representation) that can be artificially associated with an external event of high valence

(e.g. foot shocks).

This chapter focuses on the labile nature of episodic memory, the neuronal processes that render memories susceptible to updating, and the cognitive hiccups that occur when false memories are formed.

4.1.1 Introduction: The ebb and flow of the mnemonic river

As mentioned in Chapter 2, change over time is as natural a process in the universe as it is in the brain. Again, the idea of a mutable brain (i.e. “neural plasticity” in modern neuroscience) dates back to Plato, who originally proposed that the brain is a wax tablet and that memories leave behing a physical imprint or trace when formed (Campbell,

1883). Summarizing the philosophy of Heraclitus in a single aphorism, Plato wrote in one of his dialogues, “No man steps in the same river twice.” Likewise, no person experiences the same memory twice. Memories are not immutable video records of the experienced past that are projected onto a mental theater; rather, they are mnemonic rivers that ebb, flow, and thereby reconstruct the neuronal riverbeds that structurally support various streams of information.

The idea that memory is a reconstruction of the past was championed two millennia after Plato in the early 1930s by the British psychologist Frederic Bartlett.

Bartlett began by reciting slightly inconsistent fables to people from several cultural backgrounds, most famously The War of the Ghosts, (Bartlett, 1932). While recalling the fable, many subjects unintentionally modified the contents of the story into a logical narrative that contained new elements that fit within their cultural milieu. Bartlett discovered that streams of recalled contextual information could act as a modifiable scaffold onto which information is added or distorted. He had unearthed the labile nature of the mnemonic river.

Since Bartlett, the process of memory “updating” has been experimentally realized in both humans and rodents. Rats given electroconvulsive shocks shortly after recalling an aversive memory subsequently display profound amnesia for the original event (Misanin et al. 1968). This process of memory updating, later termed

“reconsolidation,” was rediscovered in 2000 and shown to be dependent on protein synthesis in the lateral amygdala (Nader et al. 2000) or hippocampus depending on the type of memory recalled (Debiec et al. 2002). In the intervening years, it has become clear that memory is reconstructive in nature: the act of recalling a memory renders it labile and susceptible to modification (Nader et al. 2000; Debiec et al. 2002; Tse et al.

2007).

Moreover, memory’s imperfections are not limited to pathological cases, as they are also present in healthy humans, in whom distortions and illusions of memories occur frequently. Such modifications can occur through the incorporation of misinformation into memory from external sources, such as leading questions, deception, and other causes—the phenomenon of suggestibility. They can also occur through the phenomenon of misattribution, when retrieved information is assigned to the wrong source. Striking examples abound demonstrating the dramatic instances in which suggestibility and misattribution errors distort memories of crime scenes, childhood events, and traumatic experiences, which were often recalled under interrogation in the court of law or during psychotherapy sessions (Loftus et al. 2003; Schacter and Loftus, 2013). Suffice it to say, the “mischievous mnemonic device” that is the brain seems to enable both veridical and false memories (Dudai and Morris, 2013).

More specifically, the activity of the anterior MTL in general and the hippocampus in particular have been positively correlated with the strength of both veridical and false memory recall (Cabeza et al. 2001), thus making the hippocampus an ideal candidate for interrogating the neuronal conditions that support false memory formation. Amnesic patients with MTL atrophy, likewise, are sometimes less susceptible to false recognition than matched controls (Schacter et al. 1996). Taken together, these

69 results suggest that MTL networks participating in generating episodic imagery are also involved in misremembering imagined events as experienced episodes.

Human studies utilizing behavioral and fMRI techniques, however, have not been able to delineate which hippocampal subregions are sufficient for false memory formation, thus necessitating animal models for a more spatially and temporally precise analysis of these neural circuits. Thus, while cognitive psychology has greatly enhanced our understanding of false memories through behavioral and functional neuroimaging studies, the underlying neuronal and circuit level processes that enable these cognitive quirks remain vastly unexplored. In light of the results observed in Liu et al. (2012), we reasoned that c-Fos expressing DG cells active during learn define an active neural population that is sufficient to act as a conditioned stimulus (CS) when optically reactivated. To test this hypothesis, it is necessary to artificially reactivate this CS while simultaneously delivering an unconditioned stimulus (US), thus opening the possibility of linking the two events. We hypothesized that such a manipulation would create an artificial CS-US association and would therefore reveal a putative neuronal substrate supporting the formation of a type of false memory.

4.1.2 Results: Hippocampus cells are sufficient to act as a functional CS

We investigated whether a light-activated contextual memory in the DG or CA1 can serve as a functional conditioned stimulus (CS) in fear conditioning. Our system utilizes c-fos-tTA transgenic mice in which the promoter of the c-fos gene drives the expression of the tetracycline transactivator (tTA) to induce expression of a gene of interest downstream of the tetracycline-responsive element (TRE). We injected an AAV virus encoding TRE-ChR2-mCherry into the DG or CA1 of c-fos-tTA animals (Fig. 1a).

ChR2-mCherry expression was completely absent in the DG of animals that had been raised with doxycycline (Dox) in the diet (on Dox) (Fig. 1b). Exploration of a novel context under the condition of Dox withdrawal (off Dox) elicited an increase in ChR2- mCherry expression (Fig. 1c). We confirmed the functionality of the expressed ChR2- mCherry by recording light-induced spikes in cells expressing ChR2-mCherry from both acute hippocampal slices and in anaesthetized animals (Fig. 1d-f). Furthermore, optical stimulation of ChR2-mCherry-expressing DG cells induced cFos expression throughout the anterior-posterior axis of the DG (Supplementary Fig. 1a-i).

We first took virus-infected and fiber-implanted animals off Dox to open a time window for labeling cells activated by the exploration of a novel context (context A) with

ChR2-mCherry. The animals were then put back on Dox to prevent any further labeling.

The next day, we fear-conditioned this group in a distinct context (context B) while optically reactivating the cells labeled in context A. On the following two days, we tested the animals’ fear memory in either the original context A or a novel context C (Fig. 1g).

If the light-reactivated cells labeled in context A can produce a functional conditioned stimulus (CS) during fear conditioning in context B, then the animals should express a false fear memory by freezing in context A, but not in context C.

First we examined the degree of overlap of the cell populations activated in contexts A and C. We injected a group of c-fos-tTA mice with an AAV virus encoding

TRE-ChR2-mCherry and exposed them to context A while off Dox to label activated DG cells with ChR2-mCherry. These animals were then immediately placed back on Dox to prevent further labeling. The next day, half of the animals were exposed to context C and the other half were re-exposed to context A as a control. Both groups were sacrificed 1.5 hours later. DG cells activated by the first exposure to context A were identified by

ChR2-mCherry expression and cells activated by the exposure to context C or the re- exposure to context A were identified by the expression of endogenous c-Fos. The c-Fos generated by the first exposure to context A had been degraded by the time the animals underwent their second context exposure. Contexts A and C recruited statistically independent populations of DG cells. In contrast, two exposures to context A recruited substantially overlapping cell populations in the dorsal DG (Fig. 2a–e).

When DG cells activated by the exposure to context A were reactivated with light during fear conditioning in a distinct context B, the animals subsequently froze in context

A at levels significantly higher than the background levels, while freezing in context C did not differ from background levels (Fig. 2f). This increased freezing in context A was not due to generalization because a control group expressing only mCherry that underwent the exact same training protocol did not show the same effect (Fig. 2f). A separate group of animals expressing ChR2-EYFP instead of ChR2-mCherry in the DG that underwent the same behavioral schedule also showed increased freezing in context A

(Supplementary Fig. 2a).

New experimental and control groups of mice were taken off Dox in context A to label activated cells, and then placed in context C on the following day while back on

Dox. In this experiment, although conditioning took place after the formation of both context A and context C memories, only those cells encoding context A were reactivated by light during fear conditioning. Subsequently, all groups of mice displayed background levels of freezing in context C. In contrast, in the context A test the next day, the experimental group showed increased freezing levels compared to the mCherry-only group, confirming that the recall of the false memory is specific to context A (Fig. 2g).

This freezing was not observed in another ChR2-mCherry group that underwent the same behavioral protocol but without light stimulation during fear conditioning in context B, or in a group in which an immediate shock protocol was administered in context B with light stimulation of context A cells (Fig. 2g, Supplementary Fig. 3). In a separate group of animals, we labeled cells active in context C rather than context A and repeated similar experiments as above. These animals showed freezing in context C but not context A

(Supplementary Fig. 2b).

The hippocampus processes mnemonic information by altering the combined activity of subsets of cells within defined subregions in response to discrete episodes

(Kubik et al. 2007; Guzowski et al. 1999; Leutgeb et al. 2007). Therefore, we investigated whether applying the same parameters and manipulations to CA1 as we did to the DG could form a false memory. We first confirmed that light could activate cells expressing ChR2-mCherry along the anterior-posterior axis of the CA1 similar to the DG

(Supplementary Fig. 1j–r). Also similar to the DG (Fig. 2a–e), the overlap of active CA1 cells was significantly lower across contexts (A and C) compared to a re-exposure to the same context (A and A). However, the degree of overlap for the two contexts was much greater in CA1 (30%) than in the DG (~1%). When we labeled CA1 cells activated in context A and reactivated these cells with light during fear conditioning in context B, no

73 increase in freezing was observed in the experimental group expressing ChR2-mCherry compared to the mCherry-only control group in either context A or context C, regardless of whether the animals were exposed to context C or not prior to fear conditioning in context B (Fig. 2m, n).

The simultaneous availability of two CS’s can sometimes result in competitive conditioning; the memory for each individual CS is acquired less strongly compared to when it is presented alone, and the presentation of two simultaneous CS’s to animals trained with a single CS can also lead to decrement in recall (Brandon et al. 2000). In our experiments, it is possible that the light-activated DG cells encoding context A interfered with the acquisition or expression of the genuine fear memory for context B. Indeed, upon re-exposure to context B, the experimental group froze significantly less than the group that did not receive light during fear conditioning or the group expressing mCherry alone (Fig. 3a and Supplementary Fig. 4). During light-on epochs in the context B test, freezing increased in the experimental group and decreased in the group that did not receive light during fear conditioning (Fig. 3a and Supplementary Fig. 2c). We conducted similar experiments with mice in which the manipulation was targeted to the CA1 region and found no differences in the experimental or control groups during either light-off or light-on epochs of the context B test (Supplementary Fig. 5).

Memory recall can be induced for a genuine fear memory by light reactivation of the corresponding engram in the DG (Liu et al. 2012). To investigate if this applies to a false fear memory, we examined fear-memory recall of experimental and control groups of mice in a distinct context (context D) with light-off and light-on epochs (Fig. 3b). All groups exhibited background levels of freezing during light-off epochs. The experimental group, however, froze at significantly higher levels (~25%) during light-on epochs. This

74 light-induced freezing in context D was not observed in control animals that underwent the same behavioral schedule but did not receive light during fear conditioning in context

B, in animals expressing mCherry alone, in animals receiving immediate shock, or in animals in which CA1 was manipulated instead (Fig. 3B, Supplementary Figs. 2d, 3c, 4 and 5).

Moreover, we quantified the levels of c-Fos expression in the basolateral amygdala

(BLA) and the central amygdala (CeA) during the recall of a false and genuine fear memory (Han et al. 2009; Rogan et al. 1999; Johansen et al. 2010; Maren and Quirk

2004; Li et al. 2013; Ciocchi et al. 2010). Both sessions elicited a significant increase in c-Fos-positive cells in the BLA and CeA compared to a control group exploring a neutral context (Fig. 3c–f).

Finally, a new cohort of mice was trained in a conditioned place avoidance (CPA) paradigm (Lammel et al. 2012). Naïve animals did not show an innate preference for either chamber across multiple days (Supplementary Fig. 6). An experimental group injected with the ChR2-mCherry virus and a control group injected with the mCherry- only virus were taken off Dox and exposed to one chamber of the CPA apparatus to label the DG cells activated in this chamber. These animals were then placed back on Dox and on the following day were exposed to the opposite chamber. Next, the mice were fear conditioned in a different context with light stimulation. The following day, they were placed back into the CPA apparatus and their preference between the chambers was measured (Fig. 4a). After conditioning, the experimental group showed a strong preference for the unlabeled chamber over the labeled chamber, whereas the mCherry- only group spent an equal amount of time exploring both chambers (Fig. 4b–d and

Supplementary Fig. 6). Notably, exposure to the two chambers activated statistically

75 independent population of DG cells (Fig. 4e–k). We conducted similar behavioral tests targeting the CA1 subregion of the hippocampus and the experimental group did not show any chamber preference (Fig. 4l, m).

4.1.3 Discussion

Our results show that cells activated previously in the hippocampal DG region can subsequently serve as a functional CS in a fear conditioning paradigm when artificially reactivated during the delivery of a US. The consequence is the formation of a false associative fear memory to the CS that was not naturally available at the time of the US delivery. This is consistent with previous findings that high frequency stimulation of the perforant path, an input to DG, can serve as a CS in a conditioned suppression paradigm

(Doyere et al. 1992).

Memory is constructive in nature; the act of recalling a memory renders it labile and highly susceptible to modification (Nader et al. 2000; Loftus, 2003). In humans, memory distortions and illusions occur frequently. These phenomena often result from the incorporation of misinformation into memory from external sources (Schacter and

Loftus 2012; Roediger and McDermott, 1992). Cognitive studies in humans have reported robust activity in the hippocampus during the recall of both false and genuine memories (Cabeza et al. 2001). However, human studies utilizing behavioral and fMRI techniques have not been able to delineate the hippocampal subregions and circuits that are responsible for the generated false memories. Our experiments provide an animal model in which false and genuine memories can be investigated at the memory engram level (McTighe et al. 2010). We propose that optical reactivation of cells that were naturally activated during the formation of a contextual memory induced the retrieval of that memory and the retrieved memory became associated with an event of high valence

(i.e. a foot shock) to form a new but false memory. Thus, the experimental group of animals showed increased freezing in a context in which they were never shocked

(context A). Although our design for the formation and expression of a false memory was

77 for a laboratory setting, and the retrieval of the contextual memory during conditioning occurred by artificial means (i.e. light), we speculate that the formation of at least some false memories in humans may occur in natural settings by internally driven retrieval of a previously formed memory and its association with concurrent external stimuli of high valence.

Our experiments also allowed us to examine the dynamic interaction between the false and genuine memories at different stages of the memory process. During the acquisition phase, the artificial contextual information (context A by light activation) either competed with the genuine contextual cues (context B by natural exposure) for the valence of the US (foot shock), or may have interfered with the perception of the genuine contextual cues. This resulted in reduced expression of both false and genuine fear memories compared to the strength of recall attainable after normal fear conditioning (Fig.

3a, compare the two groups during the light-off epoch). This could also be related to the overshadowing effects for multiple CS’s (Pavlov, 1927). During the recall phase in context B, the false memory and the genuine memory were either additive (Fig. 3a, compare the with-light group during light-off and light-on epochs) or competitive (Fig.

3a, compare the no light group during light-off and light-on epochs). All these observations are consistent with the predictions of an updated Rescorla-Wagner componential model for two independent CS’s and suggest that the light-activated artificial CS is qualitatively similar to the genuine CS.

In rodents, two lesion studies (McTighe et al. 2010; Romberg et al. 2012) investigated object recognition memory in rats with surgical or pathological perirhinal cortex lesions and found that experimental rats tended to treat novel experiences as familiar, thus leading to the false recognition of objects. While the rich repertoire of

78 human false memories is difficult to fully model in animals, a starting point is to take a

Pavlovian approach and deconstruct the learning process into conditioned and unconditioned stimuli associations. A series of recent studies have successfully demonstrated the proof of principle of artificially linking CS’s and US’s to form novel associative memories. To circumvent the lack of spatial and temporal specificity that lesion studies often confer, Johannsen et al. (2010) demonstrated that optically activated lateral amygdala (LA) cells were sufficient to substitute as a US during tone (CS) presentations and, upon subsequent tone presentations, animals displayed fear behavior despite the CS and US having never been naturally, or exogenously, presented.

Another study demonstrated that an activated population of piriform cortex neurons, when paired with rewards or shocks, could drive the associated appetitive or aversive behavioral output upon stimulation of the same neurons (Choi et al. 2011).

Moreover, pairing footshocks with optogenetically reactivated secondary auditory cortex and MGN inputs to the LA was also sufficient to form an associative fear memory to the optically activated terminals (Kwon et al 2014). A more recent study elegantly demonstrated that optically inducing LTP or LTD from MGN terminals into the LA was sufficient to promote or inhibit a previously formed memory, thus engineering the inactivation and reactivation of a specific memory and causally linking its expression to these types of synaptic plasticity (Nabavi et al. 2014).

In summary, as reviewed in this chapter, optical reactivation of hippocampal dentate gyrus cells that were previously active during context exploration was shown to be sufficient to act as an artificial, context-specific CS during fear conditioning, which thereby formed an artificial CS-US association, or a putative false memory, because the artificially constructed memory never had its contiguous experiences naturally linked

(Ramirez et al. 2014). This finding is discussed in detail in the next section. These results are consistent with the Temporal Context Model (TCM) in humans, which posits that contextual memory reactivation can be linked to novel information that is presented at the time of reactivation (Jacques et al. 2014; Gershman et al. 2013). While the relationship between animal models and human false memories remains unclear presently, it does enable future study of memory-updating processes at the level of discrete brain regions and defined populations of cells. A point that is often overlooked when generating artificial associative memories in animal models is that the formation of false memories in humans often occurs as a result of recombining mnemonic elements of discrete experiences into a new, reconstructed memory that is not a veridical representation of the past. These memories in humans are not de novo and require pre-existing memories as a scaffold onto which distinct experiences can be incorporated to update the memory itself

(Tse et al. 2007; Gershman et al. 2013). Similarly, in the aforementioned studies, the artificial memories generated are not de novo constructions; rather, they are results of artificially linking either a pre-existing memory or concurrent learning processes with events of high valence.

In a parallel study with Ramirez et al. 2013, a pharmacogenetic study constructed a synthetic fear memory that can be recalled only with the concurrent reactivation of cells encoding for both a previously learned context and natural re-exposure to an aversive context (Garner et al. 2012). Compared to the viral-based optogenetic manipulations in

Ramirez et al. 2013, a key difference in the system utilized in Garner et al. 2012 is that all c-fos-expressing cells in the forebrain and midbrain were labeled and activated over the span of several minutes. The differences observed here have two implications: region- specific optogenetic manipulations, when compared to forebrain-wide pharmacogenetic

80 perturbations, perhaps more reliably recapitulate the endogenous neural activity required for direct reactivation of context-specific fear behavior; however, the spatial structure of activity recruited with forebrain-wide manipulations perhaps recapitulate the global internal dynamics necessary to merge, or hybridize, two memories. We propose that activating neurons in much wider spatial and temporal domains may favor the formation of a synthetic memory, which may not be easily retrievable by the cues associated with each individual memory. In contrast, activating neurons in a more spatially (only small populations of DG cells) and temporally restricted manner (only a few minutes during light stimulation) may favor the formation of two distinct (false and genuine) memories as observed in our case. In line with this hypothesis, when we manipulated CA1 cells by the same procedures as the ones used for DG cells, we could not create a false memory

(i.e. freezing in context A). In CA1, the overlap of the cell populations activated by consecutive exposures to a pair of contexts is much greater than in the DG. While additional work is needed to reveal the nature of CA1 engrams, we hypothesize that our negative CA1 behavioral data could be a result of contextual engrams relying less on a population code and increasingly on a temporal code as they travel through the trisynaptic circuit.

Moreover, using the same cFos-driven ChR2 labeling strategy, a recent study demonstrated that, in addition to optogenetically driving a hippocampal contextual engram, BLA cells responding to a stimulus of high valence can be simultaneously activated to form an association with the hippocampal-driven contextual memory

(Ohkawa et al. 2015). The synchronous activation of the hippocampus cells representing a conditioned stimulus (e.g. context) and the BLA cells representing an unconditioned stimulus (e.g. foot shocks) thus led to the creation of a new associative fear memory and shared similar molecular mechanisms as the formation of a genuine fear memory (e.g.

81 protein-synthesis-dependence and glutamate activity dependence). Together, these studies provide several lines of convincing evidence that CS and US information can be artificially driven and linked together in defined populations of neurons and give us mechanistic insight into the formation of false memories.

Indeed, both Plato’s wax tablet and Heraclitus’s ever-changing river require the pre-existence of physical substrates onto which the signets or waters of experience can leave their transitory mark. Whether or not the engineered memories in the aforementioned studies are purely Pavlovian in nature or contains episodic components is a topic ripe for future investigation. For example, while activation of the periaqueductal gray or central amygdala regions (Ciocchi et al. 2010), or hippocampus (Liu et al. 2012), retrosplenial (Cowansage et al. 2014), and BLA cells (Kim et al. 2014) associated with an aversive experience, can all produce fear behavior, the qualitative nature and internal representations of these behaviors can either be akin to an uncontrollable knee-jerk reflex, an overall “feeling” of fear, or an episodic recollection. It is likely that the regions targeted, the manner in which they are targeted, and the technique utilized to perturb cellular activity may constrain the kinds of mnemonic content (or lack thereof) conjured up during stimulation. This concept is further elaborated upon in the conclusion.

4.1.4 Methods

Subjects

The c-fos-tTA mice were generated by crossing TetTag mice with C57BL/6J mice and selecting those carrying the c-fos-tTA transgene. Mice were group-housed with littermates until the beginning of the surgery and given food and water ad libitum. The mice were 8–14 weeks old at the time of surgery and had been raised on a diet containing

40 mg kg–1 doxycycline for a minimum of 1 week before surgery. Mice were housed individually post-surgery and throughout the duration of the experiments. All procedures relating to mouse care and treatment conformed to the institutional and National Institutes of Health guidelines.

Virus constructs

The pAAV-TRE-ChR2-mCherry plasmid was constructed by replacing the EYFP sequence in the pAAV-TRE-ChR2-EYFP plasmid with the sequence for mCherry using

AgeI and BsrGI restriction sites. The pAAV-TRE-mCherry plasmid was constructed by removing the ChR2 fragment from the pAAV-TRE-ChR2-mCherry plasmid using NheI and AgeI restriction sites, blunting with T4 DNA polymerase, and self-ligating the vector, which retained the ATG start codon of the mCherry gene from the ChR2-mCherry fusion gene. These plasmids were used to generate AAV9 viruses by the Gene Therapy Center and Vector Core at the University of Massachusetts Medical School. Viral titers were 8 ×

12 13 10 GC/ml for AAV9-TRE-ChR2-mCherry and 1.4 × 10 GC/ml for AAV9-TRE-

13 13 mCherry. Viral titers were 1 × 10 GC/ml for AAV9-TRE-ChR2-EYFP and 1.5 × 10

GC/ml for AAV9-TRE-EYFP as previously reported.

Stereotactic injection and optical fiber implant

All surgeries were performed under stereotaxic guidance. Mice were anaesthetized using 500 mg kg–1 Avertin. Each animal underwent bilateral craniotomies using a 0.5 mm diameter drill bit at –2.2 mm anterioposterior (AP), ±1.3 mm mediolateral (ML) for DG injections; –2.0 mm AP, ±1.5 mm ML for CA1 injections. The virus was injected using a mineral oil-filled glass micropipette joined by a microelectrode holder to a 10 µl Hamilton microsyringe. A microsyringe pump and its controller were used to control the speed of the injection. The needle was slowly lowered to the target site (–2.0 mm dorsoventral (DV) for DG injections; –1.2 mm DV for CA1 injections) and remained for five min before the beginning of the injection. All mice were injected

–1 bilaterally with 0.15 µl AAV9 virus at a rate of 0.6 µl min . The micropipette was kept at the target site for another five minutes post-injection before being slowly withdrawn.

After withdrawing of the needle, a bilateral patch cord optical fiber implant (200 µm core diameter) was lowered above the injection site (–1.6 mm DV for DG; –1.0 mm DV for

CA1). A miniature screw was screwed securely into the skull at the anterior and posterior edges of the surgical site to provide two extra anchor points for the implant. A layer of adhesive cement was applied to secure the optical fiber implant to the skull. A protective cap made from the top portion of a black polypropylene microcentrifuge tube was used to encircle the surgical site, and dental cement was applied to secure the cap to the implant and close up the surgical site. Each animal was given 1.5 mg kg–1 analgesics via intraperitoneal injection and remained on a heating pad until fully recovered from anesthesia. All mice were allowed to recover for two weeks before all subsequent experiments. All fiber placements and viral injection sites were verified histologically.

We only included mice in this study that had opsin or fluorophore expression limited to either DG or to CA1.

Slice recordings

Mice (P30–P35) were anesthetized by isoflurane, decapitated and brains were quickly removed. Sagittal slices (300 µm thick) were prepared by using a vibratome in an oxygenated cutting solution at ~4 °C. Slices were then incubated at room temperature

(~23 °C) in oxygenated ACSF until the recordings. The cutting solution contained (in mM): 3 KCl, 0.5 CaCl2, 10 MgCl2, 25 NaHCO3, 1.2 NaH2PO4, 10 D-glucose, 230 sucrose, saturated with 95% O2 – 5% CO2 (pH 7.3, osmolarity 300 mOsm). The ACSF contained (in mM): 124 NaCl, 3 KCl, 2 CaCl2, 1.3 MgSO4, 25 NaHCO3, 1.2 NaH2PO4,

10 D-glucose, saturated with 95% O2 – 5% CO2 (pH 7.3, osmolarity 300 mOsm).

Individual slices were transferred into a submerged experimental chamber and perfused with oxygenated ACSF warmed at 36 °C (±0.5 °C) at a rate of 3 ml/min during recordings. Whole cell recordings in current clamp or voltage clamp mode were performed by using an IR-DIC microscope mounting a water immersion 40× objective

(NA 0.8), equipped with four automatic manipulators and a CCD camera. For all the recordings borosilicate glass pipettes were fabricated with resistances of 8 to 10 MΩ, and filled with the following intracellular solution (in mM): 110 K-gluconate, 10 KCl, 10

HEPES, 4 ATP, 0.3 GTP, 10 phosphocreatine and 0.5% biocytin. The osmolarity of this intracellular solution was 290 mOsm and the pH was 7.25. Access resistance (Ra) was monitored throughout the duration of the experiment and data acquisition was suspended whenever the resting membrane potential was depolarized above –50 mV or the Ra was beyond 20 MΩ. Recordings were amplified using up to two dual channel amplifiers,

85 filtered at 2 kHz, digitized (20 kHz), and acquired using custom made software running on Igor Pro. Optogenetic stimulation was achieved through a 460 nm LED light source driven by TTL input with a delay onset of 25 µs (subtracted off-line for the estimation of the latencies). Light power on the sample was 33 mW/mm2. Slices were stimulated by a train of twenty 15 ms light pulses at 20 Hz every 5 s. In voltage clamp mode cells were held at –70 mV for EPSC measurements while in current clamp mode, EPSP and Aps were measured at resting potentials.

Head-fixed recording

Mice were anaesthetized by injection (100 ml kg–1) of a mixture of ketamine (100 mg ml–1) / xylazine (20 mg ml–1) and placed in the stereotactic instrument with anaesthesia maintained with a series of ketamine boost (100 mg ml–1) throughout the recording. Body temperature was maintained by a pack of Hand Warmers. An optrode consisting of a tungsten electrode (0.5 MΩ) attached to an optical fiber (200 µm core diameter), with the tip of the electrode extending beyond the tip of the fiber by 300 µm, was used for simultaneous optical stimulation and extracellular recordings. The optrode was slowly lowered to the DG (AP −2.2 mm; ML +1.3 mm; DV −2.0 mm) using a hydraulic micropositioner at a speed of 50 µm per 5−10 min. The optical fiber was connected to a 200 mW 473 nm blue laser and controlled by a waveform generator. The power intensity of light emitted from the optrode was calibrated to about 7 mW, which was consistent with the power intensity used in the behavioral assays. To identify ChR2- labelled cells, light pulses of 15 ms were delivered at 0.2 Hz at the recording sites approximately every 50 µm throughout the DG. After light responsive cells were detected, two types of light stimuli were tested: 15 ms light pulse every 5 s and a train of ten 15 ms

86 light pulses at 20 Hz every 5 s. Unit activity was band-pass filtered (500 Hz–5 kHz) and acquired with an Axon Digidata 1440A acquisition system running Clampex 10.2 software. Data were analyzed with custom software written in Matlab. After the recording, endogenous c-Fos expression was induced by delivering two epochs of 3-min light stimulation (7 mW, 20 Hz, 15 ms), separated by 3 min, to the DG, the same as in behavioral experiments (see below). Mice were sacrificed and perfused 90 min later.

Immunohistochemistry

Mice were overdosed with 750–1000 mg kg–1 Avertin and perfused transcardially with cold PBS, followed by 4% paraformaldehyde (PFA) in PBS. Brains were extracted from the skulls and kept in 4% PFA at 4 °C overnight, then transferred to PBS. Fifty µm coronal slices were taken using a vibratome and collected in cold PBS. For immunostaining, each slice was placed in PBS-T (PBS + 0.2% Triton X-100) with 5% normal goat serum for 1 h and then incubated with one or more primary antibodies

(1:1000 dilution) at 4°C for 24 h (600-401-379 Rockland; A10262, Invitrogen; SC-52,

Santa Cruz). Slices then underwent three wash steps for 10 min each in PBS-T, followed by 1 h incubation with secondary antibody at 1:200 dilution (A11039, Invitrogen;

A21429, Invitrogen). Slices then underwent three more wash steps of 10 min each in

PBS-T, including DAPI (1:10000 dilution) in the first wash step, followed by mounting with Vectashield H-1200 and coverslipping on microscope slides.

Behavior assays

All behavior tests were administered during the light cycle (7 am –7 pm) of the day. Contextual fear conditioning assays were conducted in one of the four distinct contexts (A, B, C, and D). Context A was a 29 × 25 × 22 cm chamber with removable black cardboard floor and scented with 1% acetic acid from a tray underneath. Within each chamber was a black plastic triangular roof. Context A was located underneath two lamps emitting red light in a room with dim lighting. Context B was a 30 × 25 × 33 cm chamber with metal gridded floor and scented with 0.25% benzaldehyde. It is located in a second room with black walls, black curtains, and intermediate lighting. Context C was a

29 × 25 × 22 cm chamber with glossy white plastic floor and scented with 1 ml of citral in a tray underneath the floor. It is in a third room with bright light distinct from context

A and B. Context D was a 32 × 25 × 27 cm unscented chamber with matte white plastic floor within a 64 × 73 × 40 sound attenuating cubicle with internal lightings. It is located in a fourth room distinct from contexts A, B, and C.

Prior to the behavioral experiments, all mice were handled for five days. They were taken off Dox for 42 hours to open a window of activity-dependent labeling. They were then placed in context A and allowed to explore for ten minutes, after which they were immediately removed from the chamber and placed on 40 mg kg–1 Dox diet to shut off further labeling. Twenty-four hours later, mice were individually placed into context

B and plugged to a complimentary optical fiber patch cord, which was connected to a 473 nm laser under the control of a function generator. Mice were trained in context B for a total of 420 s. They were first allowed to explore context B for 120 s, after which blue light was administered (20 Hz, 15 ms pulse width, ~7–15 mW output from fiber tip) for the remaining 300 seconds. At 240 s into training, three mild foot shocks (0.75 mA)

88 lasting 2 seconds each were administered with a sixty-second inter-shock interval. At the

420 s mark, mice were immediately removed from context B and placed back into their home cages. All post-training tests in contexts A (A’) and C (C’) consisted of three- minute exposure to the contexts. Test trials during re-exposure to context B (B’) or exposure to context D each lasted six minutes, beginning with a three-minute light-off epoch followed by a three-minute light-on epoch, with the same light stimulation parameters as the training session. Separate cohorts of mice underwent a similar behavioral schedule but were pre-exposed to context C for 10 min while on Dox a day after the first exposure to context A (Fig. 2g, n). The immediate shock group underwent the same behavioral protocol described for the group in which context A was labeled, except that training in context B lasted for 10 s with light stimulation, at the end of which a single 0.75 mA shock was administered for 2 s. While mice were in contexts A and C, freezing behavior was continuously recorded with a digital camera and measured with

FreezeFrame software. Light stimulation during training on context B, re-exposure to context B (B’), or exposure to context D interfered with the motion detection of the program. To circumvent this issue, freezing during these sessions was manually scored by two experimenters in a double-blind fashion. The manual scoring and automated scoring yielded freezing scores with a difference of less than 5%.

For the conditioned place avoidance (CPA) experiments, the CPA apparatus consisted of two 15 × 15 × 20 cm chambers (A and B) connected by a triangular neutral zone (15 cm for each side). Chamber A consisted of black and white striped walls and contained a transparent floor with small irregular indentations. Chamber B consisted of black and white alternating polka dotted walls and contained a smooth plastic floor. The mice did not have an innate preference for either portion of the apparatus (fig. S6a).

Experimental mice were first taken off Dox for 42 hours to open a window of activity- dependent labeling. They were then exposed in a counterbalanced manner to either chamber A or B (labeled chamber) for ten minutes to label the cells active in the respective chamber. Then they were placed back on Dox diet and exposed to the other chamber (unlabeled chamber) 24 h later. These mice then underwent the same fear conditioning protocol with light stimulation in context B as described above. Twenty-four hours later, all groups were placed in the neutral zone of the CPA apparatus and preference scores were measured continuously across a twelve-minute session by automated scoring software. To calculate preference scores, we divided the total amount of time that each animal spent in the unlabeled chamber by the total amount of time it spent in the labeled chamber. Thus a value above 1 indicates a preference for the unlabeled chamber; and a value below 1 indicates a preference for the labeled chamber.

Moreover, to calculate difference scores, we subtracted the total amount of time each animal spent in the unlabeled chamber by the total amount of time the animal spent in the labeled chamber.

Cell counting

To measure the extent to which populations of active cells overlap between the exposure to the same or different contexts, we counted the number of mCherry and c-Fos immunoreactive neurons in DG and CA1 from five coronal slices (spaced 160 µm from each other) per mouse (n = 4 for all groups). These slices were taken from dorsal hippocampus and focused on the coordinates that our injection and optical fiber implants targeted (–1.94 mm to –2.74 mm AP). Fluorescence images were acquired using a

90 microscope with a ×20/0.50 NA objective. Mice injected with AAV-TRE-ChR2-mCherry in DG and CA1 were first taken off Dox for 42 hours to open a period of activity- dependent labeling. They were then placed in context A for ten minutes to label the cells active in this environment and placed on Dox immediately following the session. The next day, half of the mice were placed back in context A (the A-A group) and half were placed in a distinct context C (the A-C group). Both groups were sacrificed 1.5 h later for immunohistochemistry analyses. The overlap between mCherry and c-Fos in these experiments was quantified with ImageJ. Background autoflourescence was removed by applying an equal cutoff threshold to all images by an experimenter blind to experimental conditions. Statistical chance was calculated by multiplying the observed percentage of mCherry-single-positive cells by the observed percentage of c-Fos-single-positive-cells.

To measure the extent to which false and genuine memories engage similar brain regions, mice were taken off Dox for 42 hours and then exposed to context A for ten minutes to label DG cells with ChR2-mCherry. The following day, they were exposed to context C while on Dox for ten minutes. These mice were then divided into three groups: two groups underwent fear conditioning in context B with light stimulation as described above, and one group with no light stimulation during fear conditioning. For the first two groups, one group was then re-exposed to context C (C’) and sacrificed 1.5 h later. The other group was re-exposed to context A (A’) for a false memory test and sacrificed 1.5 h later. The third group, which did not receive light during fear conditioning, was re- exposed to context B (B’) for natural fear memory recall, and sacrificed 1.5 h later.

Automated cell counting of c-Fos–positive cells was performed in the amygdala by utilizing image analysis software. This module quantified the number of c-Fos– positive cells per section (5 coronal slices per mouse; n = 6 mice per condition) by

91 thresholding c-Fos immunoreactivity above background levels and by using DAPI staining to differentiate between nuclei. Our regions of interest (ROI) included the basolateral amygdala and central amygdala. Our sampled amygdala slices were spaced at least 40 µm from each other and we focused on slices between –1.30 mm to –1.70 mm from Bregma. Each ROI was manually outlined for quantification. For statistical analysis, we used a one-way ANOVA followed by Tukey’s multiple comparisons (α = 0.05). All data were analyzed and graphed using Microsoft Excel with the Statplus plug-in and

Prism.

In a separate group of c-fos-tTA animals injected with AAV9-TRE-ChR2-mCherry targeted to either the DG or CA1, we determined the extent to which light activates cells along the anterior-posterior axis of these subregions. These groups were taken off Dox and exposed to context A for 10 min to induce ChR2-mCherry in DG or CA1. While back on Dox, light stimulation was administered (300 sec, ~9 mW, 20 Hz, 15 ms pulse width) the following day in context D and animals were sacrificed 1.5 hours later for histological analyses and quantification of cFos-positive cells using the immunohistochemistry protocol described above. The intermediate slices were defined as slices directly underneath the center of our optic fiber implant (-2.2 mm AP for DG and -

2.0 mm AP for CA1) whereas anterior or posterior slices were selected 500 µm away from the intermediate slices.

Figure 1. Activity-dependent labeling and light-activation of hippocampal neurons, and the basic experimental scheme. (A) The c-fos-tTA mice were bilaterally injected with

AAV9-TRE-ChR2-mCherry and implanted with optical fibers targeting DG. (B) While on Dox, exploration of a novel context did not induce expression of ChR2-mCherry. (C) While off Dox, exploration of a novel context induced expression of ChR2-mCherry in DG. (D) Light pulses induced spikes in a CA1 neuron expressing ChR2-mCherry. The recorded neuron is shown labeled with biocytin in (E). (F) Light pulses induced spikes in DG neurons recorded from a head-fixed anesthetized c-fos-tTA animal expressing ChR2- mCherry. (G) Basic experimental scheme. Post-surgery mice were taken off Dox and allowed to explore context A to let DG or CA1 cells become labeled with ChR2-mCherry. Mice were put back on Dox and fear conditioned in context B with simultaneous delivery of light pulses. Freezing levels were then measured in both the original context A and a

93 novel context C. The light green shading indicates the presence of Dox in the diet during corresponding stages of the scheme. Prime (’) indicates the second exposure to a given context. The yellow lightning symbol and blue shower symbol indicate foot shocks and blue light delivery, respectively. Red circles represent neurons encoding context A that are thus labeled with ChR2-mCherry. Gray and white circles represent neurons encoding context B and C, respectively. Asterisks (*) indicate neurons activated either by exposure to context or light stimulation.

Figure 2. Creation of a false contextual fear memory. (A–E) c-fos-tTA mice injected with AAV9-TRE-ChR2-mCherry in the DG were taken off Dox and exposed to context A to label the activated cells with mCherry (red), then put back on Dox and exposed to the same context A (A and E) or a novel context C (B and D) 24 h later to let activated cells

95 express c-Fos (green). Images of the DG from these animals are shown in (A) to (D), and the quantifications are shown in (E) (n = 4 subjects each; ***P < 0.001, unpaired Student’s t-test). Blue and red dashed lines indicate the chance level of overlap for A-A and A-C groups, respectively. (F) Top: Training and testing scheme of animals injected with AAV9-TRE-ChR2-mCherry or AAV9-TRE-mCherry. Various symbols are as explained in Fig. 1. Bottom: Animals’ freezing levels in context A before fear conditioning and in context A and C after fear conditioning (n = 8 for ChR2-mCherry group and n = 6 for mCherry group; ***P < 0.001, two-way analysis of variance (ANOVA) with repeated measures followed by Bonferroni post-hoc test). (G) Top:

Training and testing scheme of animals injected with AAV9-TRE-ChR2-mCherry or

AAV9-TRE-mCherry. One control group injected with AAV9-TRE-ChR2-mCherry did not receive light stimulation during fear conditioning (ChR2-mCherry, No light). Bottom: Animals’ freezing levels in context A and C before and after fear conditioning (n = 11 for ChR2-mCherry group and n = 12 for mCherry, and n = 9 for ChR2-mCherry, No light groups; ***P < 0.001, two-way ANOVA with repeated measures followed by Bonferroni post-hoc test). (H–L) Animals underwent the same protocol as in (A) to (E), except the virus injection was targeted to CA1. Representative images of CA1 from these animals are shown in (H) to (K), and the quantifications are shown in (L) (n = 4 subjects each; *P = 0.009, unpaired Student’s t-test). (M) Same as (F), except the viral injection and implants were targeted to CA1 (n = 8 for ChR2-mCherry and mCherry groups; n.s., not significant, two-way ANOVA with repeated measures followed by Bonferroni post-hoc test). (N) Same as (G), except the viral injection and implants were targeted to CA1 (n = 6 for ChR2-mCherry group and n = 5 for mCherry group). Scale bar in (A) and (H) is 250 µm.

Figure 3. The false and genuine fear memories interact with each other and both recruit the amygdala. (A) Animals that underwent the behavioral protocol shown in Fig. 2G were re-exposed to context B and the freezing levels were examined both in the absence and presence of light stimulation (n = 11 for ChR2-mCherry group and n = 9 for ChR2- mCherry, No light group; *P = 0.027; ***P < 0.001; #P = 0.034, two-way analysis of variance (ANOVA) with repeated measures followed by Bonferroni post-hoc test). (B) Animals that underwent the behavioral protocol shown in (A) were placed in a novel context D and the freezing levels were examined both in the absence and presence of light stimulation (n = 11 for ChR2-mCherry group and n = 9 for ChR2-mCherry, No light group; **P = 0.007, two-way analysis of variance (ANOVA) with repeated measures followed by Bonferroni post-hoc test). (C) Three groups of mice underwent the training shown in (A) and were sacrificed after testing in either context B (natural recall), A (false recall), or C (neutral context). The percentage of c-Fos-positive cells was calculated for each group in basolateral amygdala (BLA) and central amygdala (CeA) (n = 6 subjects each; ***P < 0.001). Images for natural recall, false recall, or neutral context are shown in (D), (E), and (F).

Figure 4. The false memory supports active fear behavior. (A) The scheme for conditioned place avoidance paradigm. Various symbols are as explained in Fig. 1. (B)

Locomotion traces during testing from animals injected with AAV9-TRE-mCherry (top), or animals injected with AAV9-TRE-ChR2-mCherry and DG cells subsequently labeled, corresponding to either the left (middle) or right (bottom) chamber. (C and D) ChR2- mCherry and mCherry group preferences for the labeled vs. unlabeled chambers as shown by the ratio (C) or the difference in duration of the time spent in each chamber (D).

(n = 8; *P = 0.013; **P = 0.008, unpaired Student’s t-test). The red dashed line indicates no preference. (E–K), c-fos-tTA mice injected with AAV9-TRE-EYFP in the DG were taken off Dox and exposed to one chamber to label the activated cells with EYFP (green), then put back on Dox and exposed to the opposite chamber 24 h later to let activated cells express c-Fos (red). Expression of EYFP (E and H), expression of c-Fos (F and I), and a

98 merged view (G and J) are shown. Filled arrows indicate cells expressing EYFP. Hollow arrows indicate cells expressing c-Fos. These cells appear yellow because they express both endogenous c-Fos (red) and the nuclear-localized c-fos-shEGFP (green) from the mouse line (10). Quantifications from the dorsal blades of the DG are shown in (K) (n =

4). Red dashed lines indicate the chance level of overlap. (L and M) Same as (C and D), except the viral injection and implants were targeted to CA1 (n = 6 each group)

Supplementary Fig. 1. Light stimulation induced cFos expression in ChR2+ cells throughout DG or CA1. (A–I) Animals expressing ChR2-mCherry (red) in the DG were treated with or without light stimulation and the expression of cFos (green) was examined. Representative anterior, intermediate, posterior, and higher magnification images of DG for the light stimulated group (A, B, C, and G) and no light group (D, E, F, and H) are shown. Quantification of cFos positive cells among ChR2 positive cells is shown in (I). A: anterior, I: intermediate, P: posterior. (n = 3/group; ***P < 0.001). (J–R) The same as A-I, except the ChR2-mCherry is expressed in CA1.

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Supplementary Fig. 2. Formation of false memory is reproducible under various conditions. (A) Top: c-fos-tTA animals injected with AAV9-TRE-ChR2-EYFP or AAV9- TRE-EYFP in DG underwent training and testing shown. Bottom: animals’ freezing levels in context A before fear conditioning and in context A and C after fear conditioning (n = 8 for each group; ***P < 0.001). (B) The c-fos-tTA animals injected with AAV9-TRE-ChR2-mCherry or AAV9-TRE-mCherry in DG that underwent the behavioral protocol shown above. The freezing levels for each session are shown (n = 8 for ChR2-mCherry group and n = 7 for mCherry group; ***P < 0.001). (C and D) The same animals from B were re-exposed to context B (C) and context D (D). The freezing levels were examined both in the absence and presence of light stimulation. (*P < 0.05; **P < 0.01).

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Supplementary Fig. 3. Animals undergoing an immediate shock protocol with light stimulation do not form a false fear memory.

(A) The c-fos-tTA animals injected with AAV9-TRE-ChR2-mCherry in the DG underwent the behavioral protocol shown above and their freezing levels for each session are shown below (n = 8 for ChR2-mCherry). (B and C) The same animals were re- exposed to context B and context D. Freezing levels were examined both in the absence and presence of light stimulation. (n.s.: not significant).

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Supplementary Fig. 4. False memory formation interfered with genuine memory recall.

(A) The c-fos-tTA animals injected with AAV9-TRE-ChR2-mCherry or AAV9-TRE- mCherry in DG that underwent the behavioral protocol shown above were re-exposed to context B and the freezing levels were measured. (n = 8 for ChR2-mCherry group and n = 6 for mCherry group; ***P < 0.001). (B and C) The c-fos-tTA animals injected with

AAV9-TRE-mCherry in DG that underwent the behavioral protocol shown above were re-exposed to context B (B) and context D (C). The freezing levels were examined both in the absence and presence of light stimulation. (n = 6; n.s.: not significant).

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Supplementary Fig. 5. Fear memory tests for CA1 animals in context B and context D.

The c-fos-tTA animals injected with AAV9-TRE-ChR2-mCherry or AAV9-TRE- mCherry in CA1 that underwent the behavioral protocol shown above were re-exposed to context B (A) and context D (B). The freezing levels were examined both in the absence and presence of light stimulation. (n = 6 for ChR2-mCherry group and n = 5 for mCherry group).

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Supplementary Fig. 6. Control data for the CPA experiments. (A) A group of wild-type mice were exposed to the CPA apparatus and allowed to explore both chambers freely for 3 consecutive days. Their preferences for the chambers were measured as a ratio of time spent in each chamber during each day (n = 6). (B) The c-fos-tTA animals injected with either AAV9-TRE-ChR2-mCherry or AAV9-TRE- mCherry in DG were taken off Dox and exposed to one chamber (Labeled) of the CPA apparatus, then put back on Dox and exposed to the other chamber (Unlabeled) the next day. Total distances traveled for each exposure were shown for each chamber for both groups (n = 8 for each group).

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Chapter 5: Switching the valence associated with a memory

In the mid 1900s, researchers discovered that damage to certain areas of the temporal lobe produced profound impairments in episodic memory, while damage to other areas of the temporal lobe dramatically attenuated various components of emotional memories, including fear and sexual behaviour (for a comprehensive review, see LeDoux

2000). Decades of subsequent research revealed that the hippocampus was crucially involved in the former; and, perhaps the most crucial structure involved in the latter was a bilateral, almond-shaped series of nuclei, which collectively are referred to as the basolateral amygadala (BLA).

As discussed in the previous chapter, nearly a century later, it was discovered that memories—episodic and emotional—are both malleable because of their intrinsic reconstructive property (Nader et al. 2000). This labile property of memory has been used clinically to treat maladaptive behaviours by attempting to update and suppress fear memories, for instance, with mnemonic information carrying neutral or positive valence

(Monfils et al. 2009; Schiller et al. 2010; Agren et al. 2012; Johnson and Casey, 2014).

However, the neuronal mechanisms and circuits that enable the switching of the valence of memories remain largely unknown. In addition, despite recent promising advances, it is also unclear if the same population of defined brain cells within the hippocampus and amygdala has the capacity to drive both appetitive and aversive behaviours, or if their behavioural output is more rigid and thus fixed into driving one particular behaviour

(Paton et al. 2006; Shabel et al. 2009; Namburi et al. 2015)

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In this chapter, we probe the hippocampal-amygdala machinery potentially underlying the reversal of the valence associated with a memory, as well as the capacity of the underlying circuitry to support multiple behavioural outputs, by utilizing our previously developed c-Fos-labelling strategy in combination with optogenetics. We began by targeting a specific set of DG or BLA cells that were active during fear or reward conditioning in mice. As expected, both groups showed fear or reward-related responses to optical stimulation that occurred in a place preference/aversion assay. Next, both groups once again had the same set of cells optically reactivated but while being simultaneously conditioned with a stimulus of the opposite valence. For example, the

DG/BLA groups that had cells labelled during reward conditioning subsequently had these cells optically reactivated but during fear conditioning; on the other hand, the

DG/BLA groups that had cells labelled during fear conditioning subsequently had these cells optically reactivated but during reward conditioning. A final behavioural test revealed that the DG groups showed light-induced behaviours consistent with a “switch” of the valence associated with each memory, while the BLA group did not show such a

“switch” and only showed light-induced behaviours consistent with the valence associated with the originally labelled set of cells. Thus, DG neurons activated during the encoding of an emotional memory have a type of functional plasticity that permits the expression of a memory of an oppositely associated valence, while a defined set of BLA cells are fixed in their capacity to drive reward or fear-associated behaviours. Our findings provide mechanistic insight into the circuitry enabling the malleability of memory, as well as reveal a potential strategy for targeting circuit-specific elements to control a memory’s emotional tone in a therapeutic setting.

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5.1.1 Introduction: Coloring in memories with emotions

Decades of work has implicated the hippocampus in processing the contextual components associated with a memory, while downstream areas such as the amygdala have been heavily implicated in emotional processing (Eichenbaum, 2000; LeDoux,

2000). At the neurophysiological level, for instance, entorhinal grid cells and hippocampal place cells process various types of spatial information (e.g. landmarks, environments, changes in environmental structure), while amygdala cells respond robustly to emotionally salient stimuli, such as positive and negative cues (e.g. cocaine, footshocks) (Leutgeb et al. 2004; Leutgeb et al. 2007; Haftin et al. 2005; Fyhn et al. 2004 and 2007; Paton et al. 2006). Accordingly, damage to the hippocampus gives rise to spatial memory deficits in several behavioral assays including contextual fear conditioning, context-specific reconsolidation, and watermaze navigation (Debiec et al.

2002; Kandel et al. 2014). On the other hand, damage to the amygdala prevents contextual and tone fear memory recall (Phillips and LeDoux, 1992; Goshen et al. 2011), reconsolidation (Nader et al. 2000), and the association between neutral stimuli and high valence events both in an anterograde and retrograde manner (Miserendino et al. 1990;

Han et al. 2009).

Reconsolidation permits memories to be rapidly updated and also permits new information, including information associated with distinct valences (e.g. aversive or rewarding) potentially to be integrated into a previously acquired memory. These phenomena are protein synthesis-dependant (Nader et al. 2000; Lee, 2009) and have been shown to occur in rodents and humans (Parsons and Ressler, 2013). As a testament to the power of updating memories of a particular valence with stimuli associated with an opposite valence, Olshavsky et al. 2013 successfully updated an appetitive memory with

108 aversive stimuli, thereby weakening the behavioural contributions of the former.

Conversely, Haubrich et al. (2015) modified an aversive memory by “updating its emotional valence to a less aversive level.” They achieved this by naturally reactivating an aversive memory but in the presence of an appetitive stimulus (e.g. food rewards), which ultimately led to an enduring attenuation of fear expression. Importantly, such a manipulation prevented reinstatement and spontaneous recovery, which lends credence to its longterm potential therapeutic value. Successful emotional memory updating did not occur if memory destabilization was pharmacologically prevented with calcium or

NMDA blockers, providing tantalizing mechanistic insights to the underlying molecular substrates supporting such updating.

While the valence of memories is malleable because of their intrinsic reconstructive property, the neuronal circuits flexible enough to support such “emotional updating” are unclear. If the hippocampus processes context independent of valence, and the amygdala assigns valence to an associated context, a prediction of this model is that hippocampal cells processing contextual information can be rapidly updated while amygdala cells are fixed at the neuronal level in their ability to assign emotional relevance to an event. Such a notion also predicts that the same contextual engram in the hippocampus has the capacity to drive appetitive and aversive behaviors because the emotional tone associated with such memories is realized in downstream areas, while distinct populations of amygdala cells are perhaps hardwired in their ability to drive opposing behaviors. Moreover, it is unknown whether the DG drives the expression of memories irrespective of the nature of the US (i.e. threatening or rewarding) and the properties of the conditioned response (i.e. aversive or appetitive). On the other hand, the amygdala has been shown to encode both negative and positive valence, but the outputs

109 of specific BLA cells and their capacity to drive such associated behaviours reminds controversial (Paton et al. 2006; Tye et al. 2007; Shabel et al. 2009). The subsequent section describes our attempt to determine whether or not DG and BLA cells indeed show such flexibility or rigidity in their capacity to drive opposing behaviors.

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5.1.2 Results: Hippocampus, and not BLA, cells are functionally plastic

To target engram-bearing cells we infected DG and BLA neurons of c-fos-tTA male mice with AAV9 virus expressing, under the TRE promoter, ChR2 and mCherry fusion protein (DG-ChR2 and BLA-ChR2 mice) or mCherry-only (DG-mCherry and

BLA-mCherry mice) (Fig. 1a, b, Supplementary Methods). This method restricts the expression of ChR2 to neurons in which the immediate early gene (IEG) c-fos is expressed during the encoding of a memory and only in the absence of the antibiotic

Doxycycline (Dox) in the diet. A similar proportion of neurons express ChR2 after encoding a fear memory (foot shock) or a reward memory (interaction with female mice in the home cage) (Fig. 1c). To test the capability of the ChR2-labelled neurons to drive two different responses we developed two optogenetic place memory tests: the

Optogenetic Place Avoidance (OptoPA) test for assessing avoidance behaviour and

Optogenetic Place Preference (OptoPP) test for assessing appetitive behaviour (see

Methods Summary and Supplementary Fig. 1).

On day 1 of the protocol, the mice underwent a habituation session while on Dox in the OptoPA or OptoPP test (Fig. 1d,g). During habituation, there was no effect of the laser during the ON phase (Fig. 1e,h). As previously described, the biased nature of both conditioned place memory tests produced non-significant trends towards avoidance for

OptoPA and preference for OptoPP. On day 3, off Dox, animals habituated to the

OptoPA test were fear conditioned to Context A (fear memory group) while the mice habituated to the OptoPP test spent 2 hours in their home cage with one female mouse

(reward memory group, Context B). During both procedures, active cells were labelled with ChR2-mCherry or mCherry-only. At the end of day 3 all animals were put back on

Dox, closing the labelling time-window for the remainder of the experiment. On day 5

111 the fear memory group underwent OptoPA testing while the reward memory group was subjected to the OptoPP test. Both DG- and BLA-ChR2 mice in the fear memory group exhibited greater avoidance behaviour in the OptoPA test compared to mCherry mice

(Fig. 1f). In the reward memory group, both DG- and BLA-ChR2 mice showed greater appetitive response than mCherry mice (Fig. 1i). Mice labelled with neutral engrams showed responses similar to mCherry controls (Supplementary Fig. 2).

To investigate whether the valence of the information contained by DG or BLA engram cells can be reversed, we conducted within-subject experiments involving the reactivation of engram cells while mice experienced unconditioned stimuli of opposite valence to the one labelled (hereafter we refer to this process as ‘induction’). A new control group of mice was also introduced where the laser was active but no US was delivered (DG-ChR2-no-US). In a ‘Fear-to-Reward’ experiment (Fig. 2ab), an OptoPA test on day 5 produced avoidance responses in the DG-ChR2, BLA-ChR2 and DG-ChR2- no-US mice similar to those described in figure 1 (Fig. 2b). On day 7, mice received blue light while alone in their home cage for 12 minutes (DG-ChR2-No-US) or while interacting with 2 female mice (DG-ChR2 and BLA-ChR2). On day 9, the OptoPP test was used in the Fear-to-Reward experiment to test whether the neurons activated by the blue light could now drive an appetitive response. Only the DG-ChR2 mice showed an increase in the time spent in the target zone compared to DG-mCherry controls (Fig. 2b).

Reactivation of the DG engram in the absence of females during the memory modification protocol was insufficient to switch the response in DG-ChR2-no-US mice.

Stimulation of the memory engram cells labelled in the BLA also failed to switch the response elicited during the OptoPP test (BLA-ChR2 mice). Thus, only in the DG-ChR2

112 mice, the same neuronal ensemble whose reactivation led to avoidance during the

OptoPA test on day 5 produced an appetitive response on day 9.

For the Reward-to-Fear experiment (Fig. 2c, d), an OptoPP test on day 5 revealed appetitive responses in the DG-ChR2, BLA-ChR2 and DG-ChR2-no-US mice (Fig. 2d).

On day 7, mice received blue light while exploring a fear-conditioning box (Context A) for 8 minutes (Dg-ChR2-no-US) or while receiving mild-foot shocks (DG-ChR2, BLA-

ChR2). DG-ChR2 mice, but not DG-ChR2-no-US, significantly decreased their preference for the target zone compared to DG-mCherry (Fig. 2d). In the case of BLA-

ChR2 mice, optogenetic stimulation significantly compensated for the natural bias correction displayed by BLA-mCherry animals.

When data from the two protocols (i.e. Fear-to-Reward and Reward-to-Fear) was analysed together, scatter plot analysis of the individual performance in the first test against the second test revealed a significant correlation only for the DG-ChR2 mice (Fig.

2e) but not for the BLA-ChR2 group (Fig. 2f) or any other control group (Supplementary

Fig. 3). Changes in preference from data normalized to baseline scores also revealed the bidirectional reversal of the responses driven by engram reactivation only on the DG-

ChR2 mice (Supplementary Fig. 4).

We next investigated the effect of our manipulations at the cellular level. Animals were injected with TRE-ChR2-mCherry in both the BLA and the DG but implanted with optic fibres only on the DG (Fig. 3a). While off Dox on day 1, mice experienced foot shock or female exposure, labelling the engram in both the DG and the BLA (Fig. 3b).

On day 3, back on Dox, the mice experienced either an event with the opposite valence without engram reactivation (–Light+US), with optogenetic stimulation (+Light+US), or received optogenetic stimulation but without US delivery (+Light–US). On day 5, all the

113 mice were placed in neutral context C and laser stimulation was delivered for 12 minutes.

One hour later, the mice were perfused and brain sections were stained against mCherry to visualize the engram cells labelled on day 1 and against GFP from a c-fos-shGFP transgene, as a surrogate for endogenous c-fos to reveal which cells had been active recently. Blue light stimulation of the DG on day 5 reactivated a similar proportion of engram-bearing cells in the DG in all groups (Fig. 3d). In all groups, the BLA cells upregulating c-fos after the artificial reactivation of DG neurons significantly overlapped with those cells labelled during the original experience (Fig. 3e). To our knowledge, this is the first time that engram reactivation (in DG) has been shown to recapitulate the neuronal activity experienced during learning in another brain region (BLA) downstream in the processing of memories. However, in the +Light+US group, the overlap between labelled and reactivated cells in the BLA was significantly reduced compared to the other two conditions (Fig. 3f). Moreover, the degree of DG engram cell reactivation plotted against the degree of BLA engram reactivation revealed a significant correlation in the –

Light+US and the +Light–US groups but not in the +Light+US group (Fig. 3g).

We next studied the effect of the induction protocol on fear memories. First, in the

Reward-to-Fear group, we looked at the reactivation of the reward engram during the encoding of a fear memory and its effect on subsequent recall (Fig. 4a). On day 7, during induction, DG-ChR2 and BLA-ChR2 displayed less freezing than mCherry controls and wild type animals (Fig. 4b). This decreased fear was also present during the long-term memory recall test on day 11 revealing a persistent effect of reactivating a reward engram during fear-memory encoding.

Finally, to test the effect of the induction procedure on the original memory, animals in the Fear-to-Reward group were tested on day 11 for freezing in the original

114 context (i.e. context A) (Fig. 4c). The DG-ChR2 mice showed a significant reduction in their freezing response similar to that seen in wild-type mice after an extinction protocol even though DG-ChR2 were never re-exposed to context A between encoding and testing

(Fig. 4d). DG-mCherry mice and DG-ChR2-No-US mice displayed levels of freezing similar to those recorded during the encoding session. Interestingly, compared to encoding, BLA-ChR2, but not BLA-mCherry mice, showed elevated freezing during the test session.

To assess whether, in addition to reducing the freezing levels, our induction procedure had increased the positive valence associated with the test context, we measured the time mice spent sniffing, an indication of reward expectation and presence of female cues. Indeed, during context A test on day 11, only DG-ChR2 mice spent more time sniffing than any other group, both as percentage of total time and also after correcting for differences in freezing levels (Fig. 4e, f).

Using recently developed context-specific optogenetic engram labelling and activation methods we have shown that engram-labelled neurons in the DG and BLA are capable of driving both avoidance and appetitive responses (Fig. 1). Next, re-activating fear labelled neurons in the DG, but not the BLA, during a rewarding experience rewrote the valence of such neuronal ensemble so as to drive an appetitive response. Likewise, reactivating the reward labelled neurons in the DG, but not BLA, during a fearful experience rewrote the valence of such population so as to drive avoidance behaviour

(Fig. 2). We conclude that the valence of the response to the DG engram activation, but not the BLA engram, can be bi-directionally reversed.

This switch in valence was also evidenced at the cellular level by the functional rewiring observed between the DG-engram and the BLA-engram after the memory

115 induction protocol (Fig. 3). As predicted by memory models and correlation studies

(Maren and Fanselow, 1995), driving the DG engram results in the firing of BLA neurons active during encoding. Then, following predictions of synaptic plasticity theory (Hebb,

1949), we hypothesized that the reactivation of the DG engram neurons during the presentation of a US that has a value opposite to the one originally encoded would bind the DG engram to a new subset of neurons in the BLA, which is likely responsible for the expression of the new unconditioned response. Indeed, after induction, the functional connectivity between the original DG and the BLA engram decreased, and DG-engram reactivation became less effective in activating the original BLA-engram (Fig. 3).

By applying genetic manipulations to two interacting brain areas, our study features a new type of neural circuit analysis that pinpoints the downstream basolateral amygdala to the application of emotional valence. Thus, context encoding in the hippocampus is plastic with respect to emotion while the amygdala has hard-wired emotion engrams: the amygdala assigns an emotional valence to neutral hippocampal contextual engrams.

Previously, others have shown that randomly labelled populations of neurons can be artificially associated with fear (Han et al. 2009) and drive opposing behaviours (Choi et al. 2011). However, these neurons originally encoded unspecified information. Here, because our engram labelling technology allows for the targeting of neurons that were activated during natural memory encoding to express ChR2 we were able to label a specific memory trace and ultimately affect the behaviour elicited by natural cue recall

(Fig. 4). Specifically, fear engram reactivation by optogenetics during a reward experience decreased the subsequent fear response and increased exploratory and reward- seeking behaviour. While extinction (Monfils et al. 2009), counter-conditioning (Nasser

116 et al. 2012) and reconsolidation (Schiller et al. 2010) protocols rely on the presentation of the original stimulus in order to alter its valence, our present study achieved mnemonic valence alteration without mice being presented with the original stimulus.

Our results show that BLA engrams drive aversive and appetitive responses but lack the functional plasticity necessary to reverse their valence after the induction protocol (Fig. 2). This supports the hypothesis that downstream of the DG (Pape and Pare,

2010), valence-specific populations of neurons exist in the BLA—fear neurons and reward neurons (Muramoto et al. 2010; Herry et al. 2008)— whose output is downstream of the network where the valence is assigned to a context. Consequently, not only does the BLA engram fail to reverse its valence but reactivating the BLA engram to modify the emotions associated with memories strengthens the original CR as seen here (Fig. 4b) and by others (Huff et al. 2013; Kim et al. 2013).

Thus, we have found that at the level of the DG, the circuit encoding a context-US association shows the plasticity sufficient to rewrite the value of the context and reverse the valence of its associated response. These results underscore the importance of targeting the DG neurons in modifying the emotional response to particular memories and may contribute to novel therapies by bringing the reversal of neural connectivity through targeted plasticity into the realm of memories.

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5.1.3 Discussion

We previously demonstrated that it was possible to artificially update a neutral memory with negative valence (Ramirez et al. 2013). Accordingly, we next set out to identify key neural nodes that originally were capable of driving appetitive or fear responses but that could subsequently be associated with an event of the opposite valence to drive the newly linked response. Based on the data of Redondo et al. (2014), our conclusions are threefold: DG cells can be artificially switched from driving fear to reward responses and vice versa while BLA cells do not show such functional plasticity given our experimental parameters; the DG induction protocol effectively attenuated the valence associated with the originally labeled memory; and DG cells are capable of reactivating the set of originally active/labeled BLA cells, demonstrating a stable circuit- level correlate of a memory trace.

Using recently developed techniques to label and activate memory engram- bearing cells, we have shown that both the DG and BLA neurons activated during context-specific fear or reward conditioning can drive aversive and appetitive responses, respectively, upon optogenetic reactivation of these cells. We have also shown that artificially reactivating fear-labelled neurons in the DG, but not in the BLA, during a subsequent reward conditioning was sufficient to reverse the dominant valence associated with the memory. Reciprocally, artificially reactivating reward-labelled neurons in the

DG, but not in the BLA, during a subsequent fear condition was sufficient to reverse the dominant valence associated with the original memory-bearing cells (Fig. 2). We conclude that the valence associated with the hippocampal memory engram is bidirectionally reversible. In contrast, the inability of the BLA engram to reverse the valence of the memory suggests that at least two functionally distinct neuronal

118 populations exist in the BLA—neurons that drive aversive responses and neurons that drive appetitive responses.

The synaptic dialogue between the hippocampus and the amygdala has a rich history (Seidenbecher et al. 2003; McGaugh 2000; Maren and Quirk 2004; Roozendaal et al. 2009; Bienvenu et al. 2012). For example, hippocampal output has been shown to be sufficient to induce synaptic plasticity in the amygdala and post-training inactivation of the dorsal hippocampus prevents context-dependent neuronal activity in the amygdala

(reviewed in LeDoux 2014; see also Peck et al. 2013). In addition, as mentioned in the introduction, studies have shown that BLA cells respond to both aversive and appetitive responses (Paton et al. 2006; Tye et al. 2007; Shabel et al. 2009). We thus predicted that driving the DG engram associated with a particular valence would result in firing of the corresponding BLA engram-bearing cells active during encoding—a hypothesis that was supported by the data in Fig. 3 (Light-,US+). In accordance with the synaptic plasticity theory, we hypothesized that optogenetic reactivation of the DG engram-bearing cells during the presentation of a US with a valence opposite the original one would strengthen the connectivity, perhaps indirectly, of these DG cells with a new subset of BLA neurons while weakening the connections established during the original learning. This hypothesis is supported by the finding that the overlap of BLA neurons activated by stimulation of the DG engram-bearing cells was reduced after induction than the overlap observed in no induction controls (Fig. 3f, j). The observation that the levels of c-fos activation were similar across groups suggests that a new population of BLA neurons was recruited in the Light+US+ group.

Memory modifications and alterations have previously been studied in various forms such as extinction (Monfils et al. 2009), counter-conditioning (Nasser et al. 2012)

119 and reconsolidation (Schiller et al. 2010). However, as previously mentioned, these phenomena all relied on the re-presentation of naturally occurring CS. Thus it is difficult to assess the degree of the identity of cell activated by the original and repeated CS deliveries. In our study, cells activated during the encoding of memory of a valence were reactivated with light to serve as the CS for the formation of memory of the opposite valence, allowing our experiments to pinpoint the critical nodes for the reversal of the behavioural response.

By applying optogenetic manipulations to two interacting brain areas, our study provides a new type of neural circuit analysis that reveals functional relationships between brain areas with respect to the expression of memories. Previously, others have shown that neurons that artificially upregulate CREB and express ChR2 in the BLA can be artificially activated to drive fear (Yiu et al. 2014). Also, randomly labelled populations of neurons in the piriform cortex can drive opposing behaviours after their stimulation is paired with a US of positive or negative valence (Choi et al. 2011). Here, because our engram labelling technology allows for the targeting of neurons that were activated during natural memory encoding to express ChR2 we were able to label a specific memory trace and monitor the behavioural response elicited by natural cues (Fig.

4). Specifically, fear engram reactivation by optogenetics during a reward experience decreased the subsequent fear response and increased exploratory and reward-seeking behaviour in the context where the original memory was formed (Fig. 4). Our present study thus provides a new insight into the functional neural circuits underlying the malleability of emotional memory by highlighting the importance of the degrees of behaviourally relevant plasticity inherent to hippocampal-amygdala cells.

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The emerging picture of the circuit for memory valence depicts a series of neutral components of the engram (DG) free to associate with either positive or negative valences coded by nodes downstream in the circuit (BLA) (Figure 3g). The development of new technologies capable of altering the connectivity between the nodes in the circuits of memory valence opens up the possibility of circumventing classical approaches to the treatment of emotional psychopathologies (i.e. PTSD, depression)—a topic that is experimentally taken to task in the next chapter.

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5.1.4 Methods

Subjects

The c-fos-tTA mice were generated from TetTag mice bred with C57BL/6J mice. c-fos- tTA mice carry the c-fos-tTA transgene in addition to a transgene consisting of a c-fos promoter driving the expression of nuclear-localized EGFP. Mice were socially housed from the time of weaning until surgery. Mice 5–10 weeks old underwent stereotaxic surgery and were subsequently singly housed and raised on a 40mg/kg doxycyclin (Dox) diet. All procedures relating to mouse care and treatment were carried out in abidance to protocols and guidelines approved by the Massachusetts Institute of Technology (MIT)

Committee on Animal Care (CAC) and National Institutes of Health (NIH) guidelines.

Viral Constructs

The pAAV‐TRE‐ChR2‐mCherry and pAAV-TRE-mCherry plasmid was constructed as previously described (Ramirez et al. 2013). AAV9 viruses containing these constructs were packaged by the Gene Therapy Center and Vector Core at the University of

Massachusetts Medical School. Viral titers of 8 × 1012 GC/ml for AAV9-TRE-ChR2- mCherry and 1.4 × 1013 GC/ml for AAV9-TRE-mCherry were used in viral injections as previously reported (Ramirez et al. 2013).

Surgical Procedures

Mice underwent surgical procedures anaesthetized under isoflourane. Under stereotaxic guidance, virus was injected using a glass micropipette attached to a 1ml Hamilton

122 microsyringe (701LT Hamilton) through a microelectrode holder (MPH6S WPI) filled with mineral oil. Once the target site was reached, the needle was held in place for 10 minutes prior to the injection of virus at a rate of 70nL/minute. After the full titer of virus was injected, the needle was held in place for an additional 5 minute prior to withdraw.

Dentate gyrus stereotaxic coordinates were -2.0mm anteroposterior (AP), +/-1.3mm mediolateral (ML), -2.0mm dorsoventral (DV), and basolateral amygdala coordinates -

1.4mm AP, +/-3.2mm ML, -4.8mm DV. After withdrawal of the needle, a Doric patchcord optical fibre (Doric Lenses) was lowered .15mm above the site of injection. A screw was placed into the skull anterior to the site of injection. A layer of adhesive cement (C&B Metabond) was applied around the optical fibre. Once the adhesive cement cured, a protect cap, made from a 1.5mL Eppendorf tube, was placed around the adhesive cement. The cap was secured to the optical fibre implant by dental cement (Teets cold cure; A-M Systems). Mice were given 1.5mg/kg metacam as analgesic and remained on a heating pad until recovery from anaesthesia. Mice were allowed to recover for at least 1 week before all subsequent experiments. Viral injection sites were verified at the end of the experiment. 22 out of 319 animals were excluded due to low expression in the target areas.

Dox Mediated Labeling

Prior to conditioning, subjects were Dox restricted for 2 days. During fear conditioning, subjects were placed in a shock chamber (30x35x32cm) scented with .25% benzaldehyde in 70% ethanol for 500s. Foot shocks (.75mA, 2s duration) were administered at 198s,

278s, 358s, and 438s time points. For reward conditioning, each subject was exposed to a single female mouse for 2h in their home cage in a room separate from the housing room.

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Immediately after, in both fear and reward conditioning, subjects returned to a Dox

(40mg/kg) diet.

Optogenetic Induction

In optogenetic fear induction, subjects were placed in a shock chamber (30x35x32cm) scented with .25% benzaldehyde in 70% ethanol with photostimulation (20hz, 15ms) for

500s. Foot shocks (.75mA, 2s duration) were administered at 198s, 278s, 358s, and 438s time points. During optogenetic reward induction, in a separate room from the housing room, home cages were placed inside of a 4-sided (31x25x30cm) box and cage tops were removed. Photostimulation (20hz, 15ms) was applied while exposing each subject to two female mice for 12min.

Optogenetic Conditioned Place Aversion (OptoPA) and Preference (OptoPP) Tests

The testing chamber consists of a custom-built rectangular box (70x25x30cm) with white floors and distinct wall cues placed on each end of the chamber. A neutral zone (no wall cues) spanning 10cm is denoted in between the two ends of the chamber. A video camera resides above the testing chamber where the locations of the subjects were tracked and recorded using Noldus Ethovision XT video tracking software. In the

OptoCPA and OptoCPP tests, subjects freely explored the testing chamber for 12 minutes.

Photostimulation (20hz, 15ms pulse width, 473nm, 15-25mW) was applied using a TTL signal controlled by Ethovision software via a Noldus USB-IO Box when the subject entered one particular side of the chamber at the 3-6min and 9-12min epochs. The target

124 side of photostimulation was determined by the side of greater preference during the 0-

3min epoch in the OptoPA test and the least preferred side for the OptoPP test. As a criteria of only including subjects that spent <90% for the OptoPA test and >10% for the

OptoPP test in the target side during the first 0-3 minutes, 5 out of 319 subjects were excluded from the study.

Daily Behavioral Protocols

Fear to Reward and Reward to Fear Experiments. Subjects underwent behavioral testing at least 1 week post-surgery. 2 days prior to the start of testing, animals were handled and habituated to experimenters. Day 1, subjects were habituated to the OptoPA or OptoPP test, then immediately placed off a Dox diet. Day 3, subjects were exposed to a shock

(context B) or female (context A), then immediately place on a Dox diet. Day 5 subjects were tested in the OptoPA or OPP test. Day 7, subjects underwent optogenetic induction.

Day 8, subjects underwent the OptoPP or OptoPA test, the test opposite to that of the initial test on Day 5. Day 11, subjects of both behavioral paradigms (OptoPA to OptoPP and OptoPP to OptoPA), were reexposed to the fear conditioning box (context B).

DG to BLA functional connectivity experiment (Figure 3). At least one week after surgery, animals were randomly assigned to 3 groups according to the manipulation carried out on day 3: –Light+US, +Light+US, +Light–US. On day 1, cells were labeled as explained above (Dox mediated labeling). On day 3, the +Light+US group experienced induction protocols as those explained above (Optogenetic induction). –

Light+US mice run induction protocols without light stimulation. The lasers drivers in

125 the room were on to control for levels of noise but the light delivery from the laser was switched off. +Light–US mice received light stimulation while running induction protocols that did not include the presence of females or the delivery of foot shocks. On day 5, all mice were placed in a third new neutral context and received blue light into the

DG for 12 minutes. 60 to 90 minutes later, their brains were perfused and extracted for immunohistochemical analysis.

Immunohistochemistry

Subjects were sacrificed by avertin overdose and perfused with 4% paraformaldehyde.

Brains were removed and placed in 4% paraformaldehyde for 24h then stored in PBS at

4°C prior to sectioning. 50µm coronal sections were obtained using a vibratome and stored in a cryoprotectant solution (details) at -20°C. At the time of staining, sections underwent three 10 minutes PBS-T (PBS+ .2% Triton X-100) washes then incubated in blocking buffer (5% goat serum) for 1h. Primary antibodies were applied overnight at

4°C (chicken anti-GFP from Invitrogen, rabbit anti-RFP from Rockland

Immunochemicals). Sections underwent three 10 minute washes in PBST then incubated with secondary antibody solution (goat anti-chicken conjugated with Alexa Fluor 488 and goat anti-rabbit conjugated with Alexa Fluor 568, both from Invitrogen) for 1 hour.

Sections underwent another three 10 minute washes prior to coverslip mounting with

DAPI using VECTASHEILD.

Imaging and Cell Counting

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Images were captured with VS-120 (Olympus) at 20x and imported into cellSens

Dimension software (Olympus). A region of interest (ROI) was defined manually following anatomical landmarks. Neurons stained against mCherry (red) as well as those with an overlap in red and green signal were counted manually. Cells stained against cfos

(green) and DAPI (blue) were counted automatically by the cellSens software after manual adjustment of detection thresholds. An experimenter blind to the conditions each group of animals belonged to performed all counting.

Behavioral Scoring

Freezing scores were assessed via the automated scoring on using the Med Associates Inc.

Video Fear Conditioning software using the default freezing threshold value of 18.

During the optogenetic induction protocol, where the optic fiber interfered with automated scoring, double-blinded manual scoring was used to score freezing levels.

Sniffing scores were also assessed in through double-blinded manual scoring using

JWatcher (c).

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Figure 1. Fear and reward engram reactivation, both in the DG and the BLA, drives place avoidance and place preference, respectively. a, b, c-fos tTA mice were injected with AAV9-TRE-ChR2-mCherry or TRE-mCherry and implanted with optical fibres bilaterally targeting the DG (a) or the BLA (b). c, Similar engram labelling in the DG

(t33 = 0.42, n.s.) and BLA (t26 = 0.35, n.s.) after fear (DG n = 16; BLA n = 14) and reward (DG n = 19; BLA n = 14) conditioning d, Fear memory group experimental protocol. e, On Day 1, Difference Scores (Supplementary Fig. 1) were similar across all DG subgroups (F2,101 = 0.76, n.s.) and across all BLA subgroups (F2,72 = 0.03, n.s.). On day 5, Difference Scores were lower in DG-ChR2 (n = 48) and BLA-ChR2 mice (n = 21) compared to corresponding mCherry-only (DG n = 39; BLA n = 27) and DG- or BLA-

ChR2-NoUS-Day3 mice (DG n = 17; BLA n = 27) (DG F2,101 = 7.99, P < 0.001; BLA

F2,72 = 4.12, P < 0.05). f, Reward memory group experimental protocol. g, On day 1,

Difference Scores were similar across all DG subgroups (F2,111 = 0.02, n.s.) and across all

BLA subgroups (F2,83 = 0.04, n.s.). In the day 5 OptoPP test, Difference Scores were

128 greater in DG-ChR2 (n = 54) and BLA-ChR2 mice (n = 35) compared to corresponding mCherry-only (DG n = 36; BLA n = 31) and DG- or BLA-ChR2-NoUS-Day3 mice (DG n = 24; BLA n = 21) (DG F2,111 = 9.76, P < 0.001; BLA F2,83 = 9.12, P < 0.001). Results show mean ± s.e.m.

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Figure 2. The valence associated with the DG engram is reversed after induction with the US of opposite value. a, The Fear-to-Reward experimental protocol. b, On day 5, Difference Scores of DG-ChR2 (n = 16), DG-ChR2-NoUS-Day7 (n = 20), and BLA- ChR2 mice (n = 19) were lower compared to corresponding mCherry-only mice (DG n =

27; BLA n = 27) (DG F2,59 = 6.16, P < 0.01; BLA t44 = 2.73, P < 0.01). In the day 9 OptoPP test, Difference Scores of DG-ChR2 mice were greater than the control mice

(F2,60 = 4.4, P < 0.05). Difference Scores of BLA-ChR2 mice were similar to those of

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BLA-mCherry-only mice (t44 = 0.16, n.s.). c, On day 9 OptoPA test, DG-ChR2 mice (n = 12) showed less aversive response compared to day 5 while both DG-ChR2-NoUS-Day7 (n = 16) and BLA-ChR2 (n = 17) mice showed similar Difference Scores on these days

(F1,42 = 5.42, P < 0.05). d, Reward-to-Fear experimental protocol. e, On day 5 OptoPP test, Difference Scores of Difference Scores of DG-ChR2 (n = 17), DG-ChR2-NoUS- Day7 (n = 29), and BLA-ChR2 mice (n =30) were greater compared to corresponding mCherry-only mice (DG n = 27; BLA n = 29) (DG F2,70 = 8.97, P < 0.001; BLA t57 = 2.85, P < 0.01) On day 9, Difference Scores of DG-ChR2 mice were lower compared to the control mice (F2,71 = 3.20, P < 0.05) and Difference Scores of BLA-ChR2 mice were similar to those of BLA-mCherry-only mice (t57 = 0.49, n.s.). f, On day 9 OptoPP test, DG-ChR2 mice (n =18) showed a reduced appetitive response compared to day 5 OptoPP test while both DG-ChR2-NoUS-Day7 (n = 21) and BLA-ChR2 mice (n = 18) showed similar Difference Scores on day 9 and day 5 (F1,54 = 6.58, P < 0.05). Results show mean ± s.e.m.

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Figure 3. DG to BLA functional connectivity changes after induction. a, Injection sites and the optic fibre placement. b, Experimental protocol. On day 1, cells active during fear or reward experience were labelled. On day 3, on Dox, mice were randomly assigned to 3 groups: reward or fear conditioning without light reactivation (Light-,US+) (n = 11); full induction protocol (Light+,US+) (n = 16); light stimulation but neither reward nor fear conditioning (Light+,US-) (n = 16). On day 5, all animals received light stimulation in the DG for 12 minutes in a novel context (Context C) before brains were

132 subjected to immunohistochemistry. Similar proportions of neurons were labelled by the fear or reward conditioning on day 3 in all groups, both in c, DG (F2,40 = 0.77, n.s.) and d,

BLA (F2,40 = 2.40, n.s.). Light delivery to the DG on day 5 led to the activation + + (GFP /DAPI ) of similar proportions of cells in the e, DG (F2,40 = 0.21, n.s.) and f, BLA + + + (F2,40 = 0.06, n.s.). g, Levels of reactivation (GFP mCherry /mCherry ) in the DG were similar across all groups (F2,40 = 0.61, n.s.) and h, above levels of chance (one sample t- + + tests against chance overlap: –Light,+US t10 = 4.24, P < 0.01; Light ,US t15 = 8.56, P < + - + + 0.001; Light ,US t15 = 5.5, P < 0.001). i, Levels of reactivation (GFP mCherry / mCherry+) in the BLA were lower in the Light+,US+ compared to Light-,US+ and + - Light ,US (F2,40 = 11.82, P < 0.001) even though overlap levels j, remained above - + + + chance (one sample t-tests: Light ,US t10 = 7.41, P < 0.001; Light ,US t15 = 2.33, P < + - 0.05; Light ,US t15 = 6.94, P < 0.001). k, Representative images of double immunofluorescence for GFP (green) and mCherry (red) in the DG and BLA. Results show mean ± s.e.m.

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Figure 4. Memory induction alters naturally cued fear memory. a, Reward-to-Fear scheme with Context A fear memory tests on day 7 and day 11. b, On day 7, freezing levels during the last 3 minutes of the induction procedure were reduced in DG-ChR2 (n = 18) and BLA-ChR2 mice (n = 19) compared to corresponding mCherry-only (DG n =

21; BLA n = 20) and ChR2-NoUS-Day3 mice (DG n = 27; BLA n = 24) (DG F2, 63 =

8.768, P < 0.001; BLA F2,60 = 8.49, P < 0.001). These reduced freezing levels remained on day 11 (DG F2,63 = 6.25, P < 0.01; BLA F2,60 = 6.86, P < 0.01). c, Fear-to-Reward scheme with Context A fear memory tests on day 3 and day 11. d, Compared to the last three minutes of the fear conditioning on day 3, only DG-ChR2 mice (n =27) showed a reduction of freezing responses on day 11 (Interaction F4,151 = 8.48, P < 0.001). BLA-

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ChR2 mice (n = 29) showed increased levels of freezing on day 11 compared to day 3. DG-ChR2-NoUS-Day7 mice (n = 42) and mCherry-only mice (DG n = 32; BLA n = 29) did not show differences between day 3 and day 11. e, After correcting for the time spent freezing, DG-ChR2 mice spent a larger proportion of time sniffing than any other group in Context A on day 11 (F4,151 = 7.78, P < 0.001). Results show mean ± s.e.m.

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Supplementary Fig. 1. Testing avoidance responses. a-b, Shock Place Avoidance. a, After the 0-3min baseline (BSL), the most preferred zone was established as the target zone. WT-Shock mice receive foot shocks (0.15 mA DC, 2s duration every 5s) when entering the target zone during the ON phases (3-6 and 9-12 min). No shocks were delivered during the OFF phase (6-9 min). WT-No-Shock mice received no shocks. b,

The difference score was reduced in the WT-Shock mice compared to WT-No-Shock (t41

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= 3.76, P < 0.001). c-d, Optogenetic Place Avoidance (OptoPA). c, DG-ChR2 were allowed to explore the arena during BSL and the preferred side determined as the target zone. Light stimulation (20 Hz, 15 ms pulse width, 473 nm, >10 mW) was applied when the mice enters the target zone during the ON phases. Light stimulation was not delivered during the OFF phase. d, The difference score was reduced in the DG-ChR2 mice compared to DG-mCherry-only (t85 = 3.55, P < 0.001). e-h, Testing appetitive responses. e-f, Female Place Preference. e, After the 0-3min baseline (BSL), the least preferred zone was established as the target zone. During the ON phases (3-6 and 9-12 min), a corral containing a female was placed in the less preferred zone (target zone) and an empty corral was placed on the opposite side. Corrals, and the female, were removed during the OFF phase. f, Mice increased the time spent in the target zone compared to mice presented with two empty receptacles (t30 = 2.81, P < 0.01). g-h, Optogenetic Place Preference (OptoPP) g, Reward-labelled mice were allowed to explore the arena during BSL and the less preferred zone determined as the target zone. Light stimulation (20 Hz, 15 ms pulse width, 473 nm, >10 mW) was applied while the subject was in the target zone of the chamber at the 3–6 min and 9–12 min epochs (ON phase). h, , The difference score was greater in the DG-ChR2 mice compared to DG-mCherry-only (t88 = 4.361, P < 0.001). a,c,e,g (right panel), Representative tracks for experimental animals. Dots mark the position of the animal every 5 video frames and accumulate where the mice spend more time.

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Supplementary Fig. 2. Light Stimulation in the OptoPA and OptoPP Tests has no effect during habituation. a, Day 1 OptoPA Habituation. There are no within group differences in the average duration spent in the target zone during the BSL and OFF phases (OFF) and the two light on phases (ON) during day 1 habituation in the OptoPA test, even though there is an overall difference between the two types of phases (F1,173 = 6.46, P < 0.05, 6 n.s. multiple comparisons). b, Day 1 OptoPP Habituation. There are no within group differences in the average time duration spent in the target zone during the BSL and OFF phases (OFF) and the two light on phases (ON) during day 1 habituation in the OptoPP test, even though there is an overall difference between the two types of phases (F1,195 = 8.06, P < 0.01, 6 n.s. multiple comparisons). c-d, There are no differences between experimental groups and wild type mice tested without light stimulation c, In the OptoPA test, the difference scores (ON-OFF) are similar between experimental groups and wild type mice that did not receive light stimulation (F6,205 = 0.19, n.s.). d, In the OptoPP test, the difference scores (ON-OFF) are similar between experimental groups and wild type mice that did not receive light stimulation (F6,227 = 0.21, n.s.)

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Supplementary Fig. 3. Fiber positions in DG and BLA. a, Representative example of the fibre location and the expression of the ChR2-mCherry construct in the DG. b, Representative example of the fibre location and the expression of the ChR2-mCherry construct in the BLA.

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Chapter 6: Activating memories to rescue maladaptive states

A revolution was underway in the 1950s. Precursors and prototypes of some of the most influential psychiatric drugs were discovered, iterated on, and developed for use in humans—antidepressants, antipsychotics, and anxiolytics, for instance. In the decades that followed, treatments for disorders of the mind were viewed as treatments for disorders of the brain. No longer was the brain an impenetrable black box that had a peripheral role in producing profound impairments of mood, perception, and cognition.

Diseases of the mind were diseases of neurotransmitters, of receptors, of modulators, of neuronal architecture. At last, a central theme in the field of psychiatry had materialized: broken brain pieces give rise to broken thoughts. Just as a broken leg requires physical intervention to heal, a broken brain requires physical treatments to heal. Given the immense promise of these novel psychopharmaceuticals, why, then, did this revolution quickly stall (Hyman, 2014)? Why, then, are today’s antidepressants and antipsychotics no more effective at treating depression or schizophrenia then their 1950’s and 60’s drug counterparts?

The answer lies partly in the fact that most of today’s antidepressants and antipsychotics target the same neurotransmitter and modulator systems as the drugs developed half a century ago (Nestler and Hyman, 2010). The psychiatric revolution stalled because most of the subsequent drugs developed were simply “copy cat” versions of previously discovered drugs, albeit with slightly improved safety, tolerability, and mitigated side effects. In this chapter, I argue that it is time to jumpstart a revolution once again with novel approaches to modeling and treating maladaptive states.

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In light of the evolutionary distance between rodents, non-human primates, and humans, a key overarching goal of modern psychiatric research is to identify penetrant genes, well conserved-circuits, and behaviors with face validity that can potentially be coalesced to thread a causal link between these levels of analyses and the cognitively compromised brain. Encouragingly, the development of new technologies that permit the engineering of engrams opens up the possibility of adding a novel twist to the classical approaches for the treatment of psychopathologies. Is it possible, for instance, to modulate mood by artificially jumpstarting cells associated with positive experiences?

More specifically, depression is characterized by a pervasive and persistent low mood that is accompanied by low self-esteem and by a loss of interest or pleasure in normally enjoyable activities. Cognitive interventions by psychotherapy have proven to be promising strategies to alleviate a subset of symptomology associated with depression

(Keller et al. 2000). However, how positive episodes interact with psychiatric disease- related impairments at the neuronal and systems level remains largely unknown. In this chapter, we explore recent advances combining our c-Fos-driven ChR2-labeling strategy to isolate and reactivate positive memories in rodents in an attempt to suppress a subset of symptomologies associated with mood disorders.

Notably, stress is considered a potent environmental risk factor for many behavioral abnormalities, including anxiety and mood disorders. Animal models can exhibit limited but quantifiable behavioral impairments resulting from chronic stress, including deficits in motivation, abnormal responses to behavioral challenges, and anhedonia—rodent correlates thought to model a subset of depression-like symptoms.

The hippocampus is thought to negatively regulate the stress response and to mediate various cognitive and mnemonic aspects of stress-induced impairments, though the

141 neuronal underpinnings sufficient to support behavioral improvements are largely unknown. Here, we acutely rescue stress-induced, depression-related behaviors by optogenetically reactivating DG cells that were previously active during a positive experience. A brain-wide histological investigation, coupled with pharmacological and projection-specific optogenetic blockade experiments, identified glutamatergic activity in the hippocampus-amygdala-nucleus accumbens pathway as a candidate circuit supporting the acute rescue. Finally, chronically reactivating hippocampal cells associated with a positive memory resulted in a rescue of stress-induced behavioral impairments and neurogenesis at time points beyond the light stimulation. Together, our data suggest that activating positive memories artificially is sufficient to suppress depression-like behaviors and point to DG engram cells as potential therapeutic nodes for intervening with maladaptive behavioral states.

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6.1.1 Introduction: Broken thoughts are broken brains

The ancient Greek physician Hippocrates posited that four basic bodily fluids, or humors, are in a physical balance to promote health and well-being. An imbalance leads to disease and mental disorders. Melancholy—one of the four temperaments, each matched to a humor—was characterized by a pervasively low mood and was caused by excess black (melan) bile (chole). While humorism did not accurately predict the pathophysiology of psychiatric disorders, it did provide subsequent experimentalists with the influential notion that chemical imbalances and erratic biological activity lead to physical disorders of the mind—a controversial view greatly expounded centuries later by another influential Greek philosopher, Galen, who held that disorders of the mind were disorders of the brain. In general, however, the neural foundations for these mental disorders remained elusive for almost two millennia.

Psychopathologies heavily and emotionally tax both the individual and society.

Mood disorders such as depression, for example, cost over 20 billion dollars a year to treat and affect more than 350 million people worldwide (Hyman, 2014). The neural contributions to various mental disorders became clearer with John Cade’s serendipitous discovery of lithium’s therapeutic effects in 1949, which launched a revolution in psychopharmacology. Within a decade, psychiatric disorders were no longer being treated as disorders of mysterious psychic abstractions but disorders of physical brain activity—of receptors, neurotransmitters, and neural structure. New drug targets would rapidly emerge in the approaching years: selective serotonin reuptake inhibitors (SSRIs), serotonin–norepinephrine reuptake inhibitors (SNRIs), tricyclic compounds (TCCs), and monoamine oxidase inhibitors (MAOIs). In parallel, new cognitive-behavioral therapies were developed to treat people as individuals and not simply imbalanced soups of

143 monoamines. Quickly, an essential—albeit evident to the modern neuroscientist— principle in psychiatry emerged, championing Galen’s view and unifying the physical processes of the brain with the seemingly ephemeral processes of the mind: broken brains produce broken thoughts.

Yet, despite the tremendous amount of psychiatric research that occurred in the subsequent decades, and despite the joint efforts of academics and pharmaceutical companies to uncover novel psychopharmacological treatments and psychotherapies, the pharmaceutical revolution quickly stalled (Hyman, 2012 and 2014). As Hyman (2012) points out, nearly every drug that has been developed in the interim still targets the same molecular players as the original drugs from the 1950s, and most achieve only the same level of efficacy with marginal improvements on safety and side effects. In retrospect, the lack of progress in developing novel therapeutics is a direct result of building and iterating mostly on “me too” drugs that target the same transmitters and neural pathways as their 1950’s counterparts. By not treating each mental disorder as a heterogeneous constellation of symptoms—each with distinct pathophysiological origins that demand tailored therapeutic interventions—progress in psychiatry decelerates.

Consider, for instance, a patient coming in to the hospital with an irritating cough.

Could it be a cold? The flu? Acute bronchitis? Pneumonia? Emphysema? Congestive heart failure? Now consider a physician who prescribes the same medicine meant to simply suppress the cough, rather than considering the underlying pathophysiology and tailoring the treatment to amelioriate the true source of irritation. Without a physiological understanding of the cough’s source, it may go away, but the anomalous biological cause would remain.

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Soberingly, the field of psychiatry has often treated symptoms of the brain similarly and without taking into account the underlying neuronal circuit elements that are compromised. This is no better demonstrated than DSM’s repeatedly unsuccessful attempts at providing a reliable diagnostic classification system for mental disorders. To achieve a nosolgical framework for mental disorders, the underlying neurobiology must be consulted—ideally, understood—and used to inform any subsequent diagnosis.

Symptoms of mental disorders must be seen in terms of the underlying neurology.

And yet, caveats abound: from a neurotransmitter perspective, depression is not just too little serotonin; anxiety is not just too much noradrenaline; schizophrenia is not just too much dopamine. From a neural architecture standpoint, depression is not just irregular VTA activity; anxiety is not just a hyperactive amygdala; schizophrenia is not just a hypoactive prefrontal cortex. A mechanistic account of mental disorders requires first championing the possibility that they are the dynamic result of maladaptive pathway- specific neural events in parallel with erratic activity of genetic programs, transmitters, and modulators—all within defined sets of cells—which collectively produce maladaptive cognition and behavior. Such a dynamic notion of psychiatric diseases at once seems scientifically impenetrable and overwhelmingly challenging to tackle; however, I argue that with modern tools, these disease-like states are both experimentally tractable and amenable to precise definition (Insel and Landis, 2013).

For example, depression is characterized by a pervasive and persistent low mood that is accompanied by low self-esteem and by a loss of interest or pleasure in normally enjoyable activities (Cryan and Holmes, 2005). Correspondingly, animal models can exhibit limited but quantifiable stress-induced depression-like symptoms, including abnormal responses to behavioral challenges and anhedonia—both precipitated by

145 repeated exposure to stressful experiences (i.e. social defeat, immobilization, numerous mild stressors) (Deisseroth, 2014). Notably, the severity and duration of stress often produces phenotypes that are susceptible to different—and sometimes even contrary— treatments, which underscores the need to tailor interventions to the distinct pathophysiological processes being modeled. I expand on this point below. Other symptoms, such as guilt, suicidality, and sadness, remain experimentally impenetrable in non-human animal models (Berton and Nestler, 2006).

A myriad of optogenetic studies have revealed region- and terminal-specific contributions and dissociations of cell populations to psychiatric disease-related behaviors. For instance, stimulation of mPFC terminals onto the lateral habenula or raphe nucleus achieved a rapid decrease or increase in coping-like behavior, respectively, while direct stimulation of mPFC cells bodies had variable effects, thus highlighting the importance of unmasking neural contributions in a projection-specific manner (Warden et al. 2012; Covington et al. 2010). Similarly, activating VTA dopaminergic neurons achieved a rapid reversal of maladaptive behaviors induced by a 6 week chronic mild stress protocol; however, the same treatment had pro-depressant effects after a 10 day social defeat stress protocol, thus revealing the complex neural states amenable to treatment that can be precipitated by different stress protocols (Tye et al. 2013;

Chaudhury et al. 2013l; Friedman et al. 2014; see Lammel et al. 2013 for an overview).

Even within the same subregions, the types of cells and number of cells activated can yield varying results. For example, globally activating dorsal DG granule cells increased exploratory drive in mice but reactivating a defined set of c-Fos expressing dorsal DG cells did not produce such an effect (Kheirbek et al. 2013; Ramirez et al. 2015). As noted earlier, modulating multiple brain regions, genetically defined subregions, or previously

146 active cell ensembles sometimes yields seemingly contradictory results, which underscores the importance of interpreting results with caution and within the constraints of each experimental protocol implemented (Kheirbek et al. 2013; Denny et al, 2014;

Garner et al. 2012; Liu et al. 2012).

Nonetheless, a fruitful line of inquiry will be to test these systems by modulating defined sets of cells active specifically during relevant periods thought to contribute to the resulting behavior (e.g. epochs of stress, fear or reward conditioning, periods prior to inducing neuropathologies). Caveats notwithstanding, the postulation that defined subsets of brain cells and circuit elements causally contribute to psychiatric disease-related behavioral states has been recently taken to task with the development of pharmaco- and optogenetics in combination with transgenic technologies, which collectively enable causal deconstruction of pathophysiological processes in vivo. In the mammalian brain, the first series of successful demonstrations that selectively targeted stimuli-induced endogenous neuronal activity occurred within the context of fear conditioning and drug- environment learned associations (Han et al. 2009; Noya et al. 2009). The former study targeted roughly 15% of lateral amygdala cells by overexpressing the transcription factor

CREB, which biased them to recruit crucial components of the fear memory trace and, when ablated, concurrently abolished the fear response; the latter study used a c-Fos- based method to target and pharmacologically inactivate 2-3% of NAcc cells that represented a stable trace of a context-specific cocaine-environment association. A stable

“cocaine engram” too was recently isolated in roughly 10% of lateral amygdala cells and subsequently abolished using the aforementioned CREB-based method (Hsiang et al.

2014). These studies provide elegant proof-of-principle demonstrations that defined subsets of cells can be modulated to rescue maladaptive states.

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The remainder of this chapter focuses on our attempt at utilizing optogenetically activated memories to combat various psychiatric disease-related phenotypes. Our recent studies have demonstrated that DG cells that express c-Fos during fear or reward conditioning define an active neural population that is sufficient to elicit both aversive and appetitive responses, and that the mnemonic output elicited by these artificially reactivated cells can be updated with new information. These findings raise the possibility of alleviating stress-induced behavioral impairments via a defined set of DG cells active during a positive experience.

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6.1.2 Results: Positive memories suppress depression-like states

How positive episodes interact with psychiatric disease-related behavioral states, including depression-related impairments, at the neuronal and systems level remains largely unknown, despite the promising cognitive treatments available in humans

(Fredrickson, 2000 and 2001). While previous studies have shown that naturally recalled positive autobiographical memories elicit robust activity in various reward-related structures—and that this increased activity also correlated with individual measures of resiliency (Speer et al. 2014)—the underlying circuitry sufficient to mediate such effects remains poorly delineated. To address this issue, we began by utilizing our recently developed system that enables activity-dependent and inducible control of neurons of interest. In our system, the promoter of c-Fos—an immediately early gene often used as a marker of recent neural activity—is engineered to drive the expression of the tetracycline transactivator (tTA), which in its protein form binds to the tetracycline response element

(TRE). Subsequently, the activated TRE drives the light-responsive channelrhodopsin-2

(ChR2). Importantly, the expression of ChR2 only occurs in the absence of doxycycline

(Dox) from the animals’ diet, thus permitting inducible expression of ChR2 in correspondingly active cells.

We first characterized the expression of ChR2-mCherry in response to experiences of distinct valences that were used in subsequent experiments. Exposing animals that were taken off Dox to a naturally rewarding experience (hereafter referred to as a “positive experience” and further validated in Supplementary Fig. 1), a neutral context (hereafter referred to as a “neutral experience”), or a single bout of immobilization stress (hereafter referred to as a “negative experience”) all elicited comparable levels of ChR2-mCherry in the dentate gyrus (DG; Supplementary Fig. 2).

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As shown in Figure 1a, mice were split into six groups: two groups underwent a chronic immobilization stress (CIS) protocol (Supplementary Fig. 3) and were also pre- exposed to a positive experience while off Dox to label active cells with ChR2-mCherry or mCherry alone; two unstressed (homecage) groups were pre-exposed to a positive experience while off Dox to label active cells with ChR2-mCherry or mCherry alone; and two stressed groups were pre-exposed to a neutral or negative experience while off Dox to label active cells with ChR2-mCherry. After 10 days of CIS or in a homecage, all groups were put through the open field test (OFT) and elevated plus maze test (EPMT) as measures of anxiety-like behaviors, as well as the tail suspension test (TST) as a measure of active/passive escape behavior in response to a challenging situation, and the sucrose preference test (SPT) for anhedonia. In unstressed animals, optogenetic reactivation of cells previously active during a positive experience did not significantly change anxiety- related measures, time spent struggling, or preference for sucrose compared to unstressed mCherry controls (Fig. 1b-e). In the stressed groups, the CIS paradigm elicited a robust decrease in time struggling and preference for sucrose, as well as increased anxiogenic responses, consistent with previous reports (Fig. 1b-e).

However, optically reactivating DG cells that were previously active during a positive experience, but not a neutral or a negative experience, in stressed animals acutely increased time struggling and sucrose preference to levels that matched the unstressed groups’ behavior (Fig. 1b, c). Additionally, optical reactivation of DG cells associated with a positive experience decreased the latency to feed in a novelty-suppressed feeding test15 (NSFT) (Supplementary Fig. 4). Mice from all groups consumed comparable amounts of food after being returned to their home cage, ruling out the possibility that the observed effect on feeding was a direct result of differences in hunger or satiety

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(Supplementary Fig. 5). Once again, the CIS paradigm had an anxiogenic effect across all groups, and all groups failed to show light-induced behavioral changes in the OFT or

EPMT (Fig. 1d, e). Similarly, total distance traveled was consistent across groups

(Supplementary Fig. 6). Taken together, these data argue that reactivating DG cells labeled by a positive experience is sufficient to acutely reverse the behavioral effects of stress in the TST, SPT, and NSFT.

We next investigated the circuit that mediated our DG light-induced effects.

Previous studies have demonstrated that positive experiences elicit coordinated activity among multiple cortical and mesolimbic areas involved in processing motivation and reward. Each of these brain areas and their dysfunction has been implicated in generating a medley of maladaptive behaviors, including anhedonia and decreased escape-related behaviors. To identify potential neural loci that mediate the light-induced reversal of the stress-induced behaviors observed in our experiments, all subjects first underwent the

CIS protocol and then were exposed to the TST while DG cells previously active during a positive experience were optically reactivated. We then performed a brain-wide mapping of c-Fos expression in areas activated by this treatment (Fig. 2a). We chose the TST for these analyses because of its rapid behavioral readout of active vs. passive coping-like behavior and because it is amenable to time-sensitive histological investigation.

Compared to animals that had DG cells labeled by a neutral experience, or a group expressing mCherry alone, optical reactivation of DG cells labeled by a positive experience correlated with a robust increase of c-Fos expression in several brain areas, including the nucleus accumbens shell (NAcc-Sh), lateral septum (LS), basolateral amygdala (BLA), central amygdala (CeA), as well as the dorsomedial, ventromedial, and lateral hypothalamus (Fig. 2b-m and Supplementary Fig. 7, 8). Furthermore, we

151 monitored single-unit activity in the BLA of mice while simultaneously activating DG positive memory-engram cells with blue light and found that ~8% of cells (9/106; n = 3 mice) had excitatory (8/9 cells) or inhibitory (1/9 cells) responses (Fig. 2n-p). We did not detect any change in c-Fos expression in the medial prefrontal cortex (mPFC), nucleus accumbens core (NAcc-C), ventral hippocampus (vHPC), lateral habenula (LH), or ventral tegmental area (VTA), though we cannot rule out the potential modulation of activity in these brain areas that is not reflected by c-Fos expression (Fig. 2b-e, j-m, and

Supplementary Fig. 9-11). A parallel set of experiments in which unstressed animals received optical stimulation of DG cells revealed mostly similar patterns of c-Fos expression, albeit the number of c-Fos-positive cells tended to be greater overall compared to stressed groups across the brain areas analyzed, with a few appreciable differences perhaps due to changes in c-Fos regulation in response to chronic stressors

(Supplementary Fig. 12).

The NAcc in particular has been heavily implicated in stress responses and mood disorders (Lim et al. 2012). It plays a key role in enabling motivational and goal-directed behavior, as well as processing natural rewards. Moreover, pathophysiological dysfunction of the NAcc in response to various stressors has been implicated in anhedonia and reward conditioning—two phenomena partially linked to irregular glutamatergic activity. To test whether glutamatergic transmission within the NAcc is necessary to support our light-induced rescue, we implanted bilateral cannulas over the

NAcc in animals that also had bilateral ChR2-mCherry virus injections and optical fibers targeted to the DG (Fig. 2q). In the TST, the behavioral effects of optically reactivating

DG cells labeled by a positive experience were blocked in the group that concurrently received the glutamate receptor antagonists NBQX and AP5, but not in the group that

152 received saline (Fig. 2r). A within-subjects comparison revealed that switching the pharmacological manipulation (i.e. one group received saline on day 1 and receptor blockade on day 2, and another group received receptor blockade on day 1 and saline on day 2) had a significant effect such that both groups showed the light-induced increase in struggling during the TST only on the day treated with saline (Fig. 2r, s). Glutamate receptor antagonism of the NAcc shell did not alter basal locomotion at the doses utilized

(Supplementary Fig. 6); furthermore, blocking dopaminergic activity yielded a similar blockade of the DG light-induced effects (Supplementary Fig. 13). Together, these findings identify glutamatergic activity within the NAcc as a crucial component through which the light-reactivated DG engram cells can promote an increase in time spent struggling in the TST.

The BLA is known to have robust glutamatergic inputs to the NAcc, and previous studies have implicated BLA projections to the NAcc in enabling reward-seeking behavior (Stuber et al. 2011). We therefore investigated whether the hippocampus (DG)-

BLA-NAcc functional pathway is crucial for the real-time light-induced rescue of depression-related behavior. The c-fos-tTA mice were bilaterally injected with TRE-

ArchT-eGFP into the BLA to allow for activity-dependent ArchT-eGFP labeling of axonal terminals from the BLA to the NAcc in response to a positive experience (Fig. 3a, b). Optic fibers were bilaterally placed over the NAcc and the DG to allow for real-time inhibition of these terminals originating from ~18% (Fig. 3c) of BLA neurons and simultaneous activation of ChR2-mCherry-positive DG cells, respectively, in stressed mice. At the neuronal level, the overlaps of BLA and NAcc cells, but not mPFC cells, that were initially activated by a positive experience (i.e. ArchT-eGFP+, green), and cells in each correspondingly reactivated area (i.e. endogenous c-Fos+, red) were above chance

153 levels after light-induced reactivation of DG cells previously activated by the positive experience (Fig. 3c). These results suggest that the DG engram cells are functionally connected to BLA engram cells and NAcc engram cells. At the behavioral level, inhibition of BLA terminals onto the NAcc blocked the DG light-induced rescue in both the TST and SPT (Fig. 3d-g). Within the same behavioral session for the TST, and across two days for the SPT, when ArchT-mediated inhibition was released (i.e. the green light was turned off), the rescue effects of reactivating DG cells previously active during a positive experience were rapidly observed in all groups (Fig. 3d-g). Arch-T-mediated inhibition of BLA-NAcc terminals alone did not negatively affect behavior in the TST or

SPT beyond the levels of the stressed animals (Fig. 3d-g insets). These results suggest that inhibition of BLA cell terminals in the NAcc ‘clamp’ down on behavior when DG engram cells are simultaneously reactivated, and that this ‘clamp’ can be released in real- time to permit for active DG cells to have their neuronally and behaviorally relevant positive effects. The specificity of the hippocampus (DG)-BLA-NAcc pathway for the rescue was supported by an analogous experiment conducted with bilateral injections of

TRE-ArchT-eGFP into the mPFC. Although the mPFC is also known to provide robust glutamatergic input to the NAcc, the induction of c-Fos expression in this area upon optogenetic activation of DG cells associated with a positive experience was not significantly higher than that observed with a neutral experience (Fig. 2m), and mPFC cells reactivated by DG cell reactivation was at chance level (Fig. 3c). Correspondingly, inhibition of terminals originating from ~12% of the mPFC (Fig. 3c) onto the NAcc did not block the DG light-induced rescue in either the TST or SPT (Fig. 3d-g). Moreover, inhibition of BLA, but not mPFC, terminals onto the NAcc partially inhibited the DG- mediated, light-induced increase of c-Fos+ cells observed in the NAcc shell (Fig. 3h), supporting the conclusion that the hippocampal DG-BLA-NAcc pathway of positive

154 engrams plays a crucial role in the rescue of depression-related behavioral phenotypes.

Recent meta-analyses have suggested that treating psychiatric disorders through prescribed medication or cognitive interventions are capable of producing symptom remission when administered chronically (DeRubeis et al. 2008; Mineur et al. 2015). Still, the neural underpinnings inducing and correlating with long-lasting rescues have remained poorly understood. As our acute intervention did not induce enduring behavioral changes (Supplementary Fig. 14), we next tested the possibility that chronic reactivation of DG engram cells previously active during a positive experience could have behavioral consequences that outlasted acute optical stimulation. Three experimental groups expressing ChR2-mCherry were utilized (Fig. 4a): all cohorts contained DG cells labeled by a positive experience and these cells were either not reactivated (no stimulation group), reactivated only twice in one day (1-day group), or reactivated twice a day for 5 days (5-day group). The 5-day stimulation group, but not the

1-day stimulation or no stimulation group, showed a reversal of the stress-induced behavioral deficits measured in the TST and SPT that was not significantly different from an unstressed control group (Fig. 4b, c). A group in which DG cells labeled by a neutral experience were reactivated for 5-days did not show such effects, nor did a group that was exposed to a natural social reward for 5-days (Fig. 4b-d). Lastly, we investigated the neural underpinnings correlating with the light-induced rescue. Histological analyses revealed decreased levels of neurogenesis as measured both by the polysialylated neuronal cell adhesion molecule (PSA-NCAM) and doublecortin (DCX)—often considered markers of developing and migrating neurons (Sahay and Hen, 2007; Sahay et al. 2011)—in all stressed groups except for the 5-day group that had DG cells associated with a positive experience reactivated or the unstressed control group (Fig. 4d,

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Supplementary Fig. 15). This increase in adult-born neurons positively correlated with the degree to which each group preferred sucrose in the SPT (Supplementary Fig. 16a); moreover, performance levels on the SPT and TST positively correlated with one another on an animal-by-animal basis (Supplementary Fig. 16b).

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6.1.3 Discussion

Our results demonstrate in mice that optogenetic reactivation of engram cells formed in the DG by naturally rewarding experiences was sufficient to acutely and chronically suppress depression-related behavior (Ramirez et al. 2015). Our study further shows that glutamatergic transmission from the amygdala’s axonal terminals, but not from the medial prefrontal cortex (mPFC)’s axonal terminals, to the nucleus accumbens

(NAcc) shell is necessary for the real-time antidepressant-like effects of the reactivated

DG engram cells. Notably, the NAcc has recently been identified as a potential therapeutic node for deep brain stimulation (DBS) to alleviate anhedonia (Schlaepfer et al.

2008) in humans, and previous reports had also identified BLA, but not mPFC, axonal terminals into NAcc as sufficient to support self-stimulation and reward-seeking behavior in a D1 receptor-mediated manner (Britt et al. 2012; Stuber et al. 2011). Thus, our conclusions are threefold: first, hippocampal cells associated with positive memory, when artificially activated, can acutely rescue stress-induced depression-related phenotypes of mice as measured in the tail suspension test and sucrose preference test; second, this optogenetic modulation of behavior is contingent on an intact glutamatergic pathway from BLA terminals to the NAcc in real-time; and third, 5 days of optogenetic reactivation of positive memory engrams rescues depression-related behaviors in a manner that outlasts real-time optogenetic treatment.

Additionally, in humans, positive memories elicit robust activity in the ventral striatum and have been shown to be intrinsically rewarding (Speer et al. 2014). It is important to note, however, that directly reactivating cells associated with a positive experience memory, stimulating terminals onto the NAcc, or applying DBS to NAcc, is qualitatively different from exposing depressed subjects to naturally rewarding

157 experiences which would normally activate these corresponding brain areas in the healthy brain. In the psychiatric diseased-related state, acute administration of naturally rewarding external cues may not have access to, or activate, the internal representations associated with positive experience under the normal state. In agreement, our data demonstrate that exposing stressed subjects to a natural positive experience repeatedly is not as effective as repeated direct reactivations of DG engram cells associated with a previously acquired positive memory (Fig. 4b-d). We speculate that invasively stimulating these DG cells is effective in activating both the internal contextual representation associated with a positive experience as well as associated downstream areas, while exposure to natural exogenous positive cues may not be able to access similar neural pathways in subjects displaying depression-like symptoms such as passive behavior in challenging situations and anhedonia (Fig. 4b-d). Thus, directly activating cells associated with a positive memory may have neuronal and behaviorally relevant effects that may not be attainable by less invasive means.

Furthermore, it is possible that glutamate and dopamine are simultaneously interacting in the NAcc at preferential neuronal subtypes to promote the antidepressant- like effects observed in our experiments (Lammel et al. 2014). This hypothesis remains to be tested by measuring real-time neurotransmitter and modulator release during positive memory reactivation. In our experiments, real-time reactivation of a positive memory increased struggling levels and preference for sucrose on a timescale of seconds. Our data dovetail with this circuit’s proposed role of relaying BLA stimulus-reward associations to a ventral striatal motor-limbic interface. This interface is thought to be capable of coalescing such information with motivational states and finally translating such activity into behaviorally relevant outputs.

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Depression is diagnosed as a constellation of heterogeneous symptoms; their complex etiology and pathophysiology underscore the varied responses to currently available treatments, and the much-needed revisions to currently available diagnostic manuals and methods (Insel and Landis, 2013). In humans, the timeline of psychopharmacological treatments (e.g. fluoxetine, imipramine) is on the order of weeks to months to achieve antidepressant effects. Still, other alternative treatments such as

DBS and the NMDA antagonist ketamine have been reported to have rapid effects in a subset of patients. In recent optogenetic studies, real-time reactivation of mPFC or BLA terminals, ventral tegmental area (VTA) cell bodies, or DG cells all elicited antidepressant-like effects on the timescale of seconds (Nieh et al. 2013). These data support our hypothesis that the acute behavioral changes reflect the degree to which directly stimulating neurons might bypass the plasticity that normally takes antidepressants weeks or months to achieve, thereby temporarily suppressing the depression-like state.

Furthermore, recent meta-analyses have suggested that treating psychiatric disorders through prescribed medication or cognitive interventions are capable of producing symptom remission when administered chronically (DeRubeis et al. 2008).

Still, the neural underpinnings inducing and correlating with long-lasting rescues have remained poorly understood. Ramirez et al. (2015) and Friedman et al. (2014) found that chronic reactivation of DG engram cells previously active during a positive experience, or VTA dopaminergic cells, respectively, had antidepressant-like behavioral consequences that outlasted acute optical stimulation. The latter study identified an optogenetically-induced increase in K+ channels and normalization of VTA firing rates as crucial contributors to the antidepressant-like effects.

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In the our study, while the causal link between chronically reactivated positive memory engrams and the corresponding rescue of behaviors remains elusive, many tantalizing hypotheses surface, including a normalization of VTA firing rates, epigenetic and differential modification of effector proteins (e.g. CREB, BDNF) in areas up- and downstream of the hippocampus, and a reversal of neural atrophy in areas such as CA3 and mPFC or hypertrophy in BLA. These possibilities may presumably occur in concert with additional neuroplastic and homeostatic mechanisms. As optical reactivation of a positive memory correlated with increased c-Fos expression in the hypothalamus

(Supplementary Fig. 8), the aforementioned molecular and homeostatic mechanisms—in addition to our observed increase of adult-born neurons in the 5-day group—could be partly realized in a hormone- or neuromodulator-mediated manner.

While depression and anxiety can show high comorbidity rates, the underlying circuitry is thought to be only partially intersecting and the boundaries remain unclear.

Our data demonstrate that the depression-related readouts of active/passive coping-like behavior and anhedonia, as measured in the TST and SPT, respectively, can be directly modulated by activating cells in the hippocampus associated with a positive memory, while anxiety-related behaviors measured by the OFT and EPMT remained unchanged.

Differential regulation of depression- and anxiety-related behavior could be achieved by leveraging the functional segregation present along the hippocampus dorsal-ventral axis; for instance, activation of ventral hippocampal DG engram cells could reveal heterogeneous, behaviorally relevant roles in the emotional regulation of anxiety and stress responses that our dorsal hippocampus manipulations presumably did not access

(Kheirbeck et al. 2013). To that end, we speculate that, at the engram level, the circuitry sufficient to modulate anxiety-related behavior relies more heavily on a synaptic dialogue

160 within the amygdala, its bidirectional connections with the ventral hippocampus, and its effects on downstream mesolimbic and cortical structures (Feliz-Ortiz et al. 2014).

Collectively, the data described here build a novel experimental bridge between memory engrams in the brain and animal models of psychiatric disorders. We propose that direct activation of DG engram cells associated with a positive memory offers a potential therapeutic node for alleviating a subset of depression-related behaviors and, more generally, that directly activating endogenous neuronal processes may be an effective means to correct maladaptive behaviors.

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6.1.4 Methods

Subjects

The c-fos-tTA mice were generated by crossing TetTag mice with C57BL/6J mice and selecting for those carrying the c-fos‐tTA transgene. Littermates were housed together before surgery and received food and water ad libitum. All mice were raised on a diet containing 40 mg kg–1 doxycycline (Dox) for a minimum of 1 week before receiving surgery at age 12-16 weeks. Post-operation, mice were individually housed in a quiet home cage with a reverse 12 hour light-dark cycle, given food and water ad libitum, and allowed to recover for a minimum of 2-3 weeks before experimentation. All animals were taken off Dox for an undisturbed 42 hours to open a time window of activity-dependent labeling. They were then exposed for two hours to one the following treatments: a negative experience (i.e. a single bout of immobilization stress, see below), a naturally rewarding experience (i.e. exposure to a female conspecific while in the home cage, as previously reported), or a neutral experience (i.e. exposure to a conditioning chamber), and placed back on Dox immediately afterwards. The subjects were then age-matched and split into two groups: a stressed group and a non-stressed group. Non-stressed animals remained in said conditions prior to experimentation. Stressed animals underwent 2-3 hours of chronic immobilization stress (CIS) each day for 10 consecutive days before behavioral testing using Mouse DecapiCone disposable restrainers. All procedures relating to mouse care and treatment conformed to the institutional and

National Institutes of Health guidelines for the Care and Use of Laboratory Animals.

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Virus constructs and packaging

The pAAV9-TRE-ChR2-mCherry and pAAV9-TRE-mCherry plasmids were constructed as previously reported in Ramirez et al. (2013). The pAAV9-TRE-ArchT- eGFP was constructed by replacing the ChR2-eYFP fusion gene in the pAAV9-TRE-

ChR2-eYFP plasmid from Liu et al. (2012) with a fusion gene of ArchT-eGFP form Han et al. (2008). These plasmids were used to generate AAV9 viruses by the Gene Therapy

Center and Vector Core at the University of Massachusetts Medical School. Viral

12 -1 13 titrations were 8 × 10 genome copy ml for AAV9-TRE-ChR2-mCherry, 1.4 × 10

-1 13 -1 genome copy ml for AAV9-TRE-mCherry, and 0.75 to 1.5 × 10 genome copy ml for

AAV9-TRE-ArchT-eGFP.

Stereotactic injection, cannulation, and fiber optic implants

All surgeries were performed under stereotaxic guidance and subsequent coordinates are given relative to bregma. Animals were anaesthetized using 500 mg kg-1

Avertin prior to receiving bilateral craniotomies using a 0.5 mm diameter drill bit at –2.2 mm anterioposterior (AP), ±1.3 mm mediolateral (ML) for DG injections. All mice were

-1 injected with 0.15 µL of AAV9 virus at a controlled rate of 0.6 µL min using a mineral oil-filled glass micropipette joined by a microelectrode holder (MPH6S; WPI) to a

10 µl Hamilton microsyringe (701LT; Hamilton) in a microsyringe pump (UMP3; WPI).

The needle was slowly lowered to the target site at –2.0 mm dorsoventral (DV). The micropipette remained at the target site for another five minutes post-injection before being slowly withdrawn. A bilateral optical fiber implant (200 µm core diameter; Doric

Lenses) was lowered above the injection site (–1.6 mm DV for DG) and three jewelry

163 screws were secured into the skull at the anterior and posterior edges of the surgical site to anchor the implant. For mice used in pharmacological manipulations, bilateral guide cannula (PlasticsOne) were implanted above the NAcc (+1.2 mm AP; ±0.5 mm ML; –

3.25 mm DV). Mice used in the BLA-to-NAcc or mPFC-to-NAcc experiments received bilateral injections (0.2 µL to 0.3µL) of TRE-ArchT-eGFP or TRE-eGFP into the BLA (–

1.46 mm AP; ± 3.20 mm ML; –4.80 mm DV), NAcc (+1.2 mm AP; ± 0.50 mm ML; -4.3 mm DV), or the mPFC (+1.70 mm AP; ± 0.35 mm ML; –2.70 mm DV). These mice were then injected with TRE-ChR2-mCherry into the DG and received bilateral optic fiber implantation as described above (Doric Lenses), as well as bilateral optic fiber implantation over the NAcc (+1.2 mm AP; ± 0.50 mm ML; –3.70 mm DV)

Layers of adhesive cement (C&B Metabond) followed by dental cement (Teets cold cure; A-M Systems) were spread over the surgical site and protective cap to secure the optical fiber implant. The protective cap was made from the top portion of a black polypropylene microcentrifuge tube. Mice received intraperitoneal injections of 1.5 mg kg-1 analgesics and were placed on heating pads throughout the procedure until recovery from anesthesia. Histological studies were used to verify fiber placements and viral injection sites. Only data from mice with opsin or fluorophore expression restricted to the

DG, BLA, or mPFC were used for histological, behavioral, and statistical analyses.

Pharmacological infusion of glutamate or dopamine receptor antagonists

Glutamate antagonists were bilaterally infused into the NAcc as follows: 0.2 µL / hemisphere of NBQX at a concentration of 22.3 mM to antagonize AMPA (a-amino-3- hydroxy-5-methyl-4-isoxazole propionic acid) receptors and 0.2 µL / hemisphere of AP5

164 at a concentration of 38.04 mM to antagonize NMDA (N-methyl-D-aspartate) receptors.

Dopamine receptor antagonists were bilaterally infused into the NAcc as follows: 0.2 µL

SCH23390 at a concentration of 6.16 mM to antagonize D1-like receptors and 0.2 µL raclopride at a concentration of 2.89 mM to antagonize D2-like receptors. A 26-gauge stainless steel double internal cannula (PlasticsOne) was used to bilaterally infuse each drug; the internal cannula was connected with a microsyringe pump by a PE20 tube to control the injection rate at 100 nL min-1. The injection cannula was left connected for 5 minutes before removal to allow for diffusion. Finally, all behavior was performed 20 minutes following drug infusion.

Immunohistochemistry

Mice were overdosed with 750-1000 mg kg-1 Avertin and perfused transcardially with cold PBS, followed by 4% paraformaldehyde (PFA) in PBS. Extracted brains were kept in 4% PFA at 4°C overnight, then transferred to PBS. A vibratome was used to recover 50 µm coronal slices in cold PBS. Slices were washed with PBS-T (PBS + 0.2%

Triton X-100), then incubated with PBS-T + 5% normal goat serum at 4°C for 1 h for blocking. For immunostaining, slices were incubated with one or more primary antibodies (1:1000 dilution) at 4°C for 24 h (600-401-379 Rockland; A10262, Invitrogen;

SC-52, Santa Cruz). Three washes of PBS-T for 10 minutes each were performed on the slices prior to 1 h incubation with secondary antibody at 1:200 dilution (A11039,

Invitrogen; A21429, Invitrogen). Slices were washed three more times in PBS-T for 10 minutes each, stained with 4’, 6-diamidino-2-phenylindole (DAPI; 1:10,000 dilution) to label cell nuclei and mounted with Vectashield H-1200 onto microscope slides.

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Behavioral Assays

All behavior assays were conducted during the light cycle of the day (7 am-7 pm) on animals 12-16 weeks old. Mice were handled for 3-5 days, 2 minutes per day, prior to all behavioral experiments.

Tail suspension test

Fiber optic implants on experimental mice were plugged into a patch cord prior to the tail suspension test. Each subject was hung by its tail from a bar 40 cm from the ground with a single piece of autoclave tape. The animal was positioned such that it had no contact with other objects. Immediately after positioning, video recordings of the animal’s movements were taken (Noldus by Ethovision). Blue light stimulation was given at 20 Hz, 15 ms pulse width, ~15-20mW. For behavioral data appearing in Figure 1, all mice were exposed to a 9 minute tail suspension test with light stimulation occurring at minutes 3-5, inclusive; for histological data appearing in Figure 2, all mice were exposed to a 6-minute tail suspension test with light stimulation occurring throughout the entire session using the same stimulation parameters described above. For data appearing in Figure 3, all animals were given a 9-minute tail suspension test once a day for 2 days to assess the effects of ArchT inhibition on BLA or mPFC terminals in the NAcc while simultaneously activating ChR2-positive cells in the DG. For half of the subjects, on day

1, ArchT-mediated inhibition occurred during minutes 3-5, inclusive, using constant green light at ~25mW; DG stimulation occurred from minutes 3-8, inclusive. For the other half, ArchT-mediated inhibition occurred during minutes 6-8, inclusive; and, DG

166 stimulation occurred from minutes 3-8, inclusive. The treatments occurring on days 1 and 2 were counterbalanced within and across groups. A separate cohort of animals were utilized for the data appearing in the insets of Figure 3d-g. These groups contained TRE-

ChR2-mCherry in the DG, as well as bilateral optic fibers over the DG, and TRE-ArchT- eGFP in the BLA, as 1well as optic fibers over the NAcc to inhibit BLA terminals during the appropriate light-on epochs in the TST and SPT. These cohorts, too, were counterbalanced across sessions and only received green light over the NAcc for 3 minutes during the TST or 15 minutes during the SPT. For the cFos counts appearing in

Figure 3h, all groups underwent a 6-minute tail suspension test with blue light delivered to the DG and green light delivered to the NAcc throughout the entirety of the session.

These groups were sacrificed 1.5 hours later for histological analyses. For data appearing in Figure 4, mice were exposed to a 6-minute tail suspension test without light stimulation. An experimenter blind to each mouse condition and light treatment scored all the tail suspension videos by measuring the total time in seconds that each mouse spent struggling throughout the protocol.

Sucrose preference test

A Med Associates operant chamber—equipped with photolickometers placed on two separate corners of the chamber—was used to count the number of licks made by the mice on lick spouts with direct access to 2% sucrose water solution or water alone. All animals undergoing the sucrose preference protocol were water-restricted for 36 hours prior to each habituation session. These sessions consisted of first plugging the optic fibers on the water-deprived mice to a corresponding patch cord and exposing the mice to the operant chamber, which contained bottles filled only with water. Each exposure

167 occurred on 3 separate days for 30 minutes per day. The 3 habituation sessions occurred interspersed throughout the 10 day chronic immobilization stress protocol (i.e. on days 1,

4, and 7 of stress) at least 6 hours before or after the stress protocol. In pilot experiments,

~90% of water-deprived animals failed to sample both photolickometers in the operant chamber even after multiple 30-minute habituation sessions (data not shown); to address this issue, a glove box was inserted on its side in the operant chamber such that each subject had a narrow ~10 cm corridor to explore and find each lick spout. Upon completing a habituation session, mice were given water only when 2 hours of being placed back into the home cage had elapsed. On the test day (i.e. the day on which optical stimulation occurred), the location of each sucrose or water bottle in the chamber was counterbalanced between animal chambers. A 30-minute protocol—15 minutes light off,

15 minutes light on—was used on all animals. The first 15 minutes were used to detect the baseline preference; blue light stimulation at 20 Hz, 15 ms pulse width, ~15-20mW, occurred during the second 15-minute epoch to detect light-induced changes in preference. For data appearing in figure 3, water-deprived animals were exposed to the same 30-minute protocol on two separate days. On day 1, after the first 15-minute epoch, half of the animals received constant green light stimulation at ~15 mW over the NAcc while simultaneously receiving blue light stimulation over the DG; the other half received only blue light stimulation over the DG. On day 2, the treatments were reversed in a counterbalanced manner. Data was only collected in animals that licked at both spouts in the first 15-minute interval; animals that did not discover both lick spouts (as evidenced by licking only one spout during the first 15-minute interval) were not given light stimulation, the experiment was terminated early, and the test was repeated the following day. Sucrose preferences were calculated as follows: [(total number of licks to sucrose

168 spout) / (total number of licks to sucrose spout + total number of licks to water spout)] x

100.

For the sucrose preference data appearing in Figure 4, mice were first habituated to two water bottles for two days in their home cages. On day 3, two water bottles containing either 2% sucrose or water were placed into the cages in a counter-balanced manner and left undisturbed for 24 hours. Sucrose preferences were calculated as follows: [(Δweight of sucrose water) / (Δweight of sucrose water + Δweight of water)] x 100.

Open field test

An open, metal chamber (Accuscan system, Dayton, OH) with transparent, plastic walls was used for the open field test. Implanted mice were plugged into a patch cord, individually placed into the chamber, and allowed to explore freely for 12 minutes. An automated video-tracking system (Ethovision by Noldus) was used to track the amount of time spent in the center of the chamber compared to the edges, as well as the total distance traveled across a session. Light stimulation, as described above, was given during minutes 3-5 and 9-11, inclusive.

Elevated plus maze test

Implanted animals were plugged into a corresponding patch cord prior to the beginning of the session and subsequently placed in an elevated plus maze. Two pieces of plastic (30 cm long, 5 cm wide) formed the two arms of the maze that intersected at right angles. One arm was enclosed with plastic black walls, and the other arm was open with

169 no walls. The structure was elevated 60 cm above the floor and mice were placed one at a time at the intersection of the maze facing into an arm with walls to start a trial. Video tracking software (EthoVision by Noldus) was used to track the amount of time the mice spent in the enclosed vs. the open arms of the maze throughout a 15-minute session.

Optical stimulation occurred only during the second 5-minute epoch using the same stimulation parameters as noted above.

Novelty Suppressed Feeding

The novelty suppressed feeding paradigm was performed as previously described in

Snyder et al. (2011). In brief, food was removed from the subjects’ home cages 24 hours prior to testing. The next day, mice were placed for 10 minutes in an open field apparatus containing bedding with a food pellet at the center on a 1 cm2 elevated platform. Light stimulation using the parameters described above occurred throughout the entire session.

All behavior was videotaped (Ethovision by Noldus) and latency to feed was scored offline by an experimenter blind to the experimental conditions for each mouse. Once placed back into their home cages, mice were given a single food pellet, which was weighed before and after a 5-minute test to measure for motivation/hunger effects on feeding behavior compared to feeding in a novel environment.

5-day Stimulation Protocol

For data appearing in Figure 4, animals were first split into 6 groups: a group in which

DG cells previously active during a positive experience were reactivated twice a day for 5

170 days (5-day group) after the CIS protocol, a group in which such stimulation occurred twice a day for 1 day (1-day group) after the CIS protocol, a group in which no stimulation was delivered (NoStim group) after the CIS protocol, a group in which DG cells previously active during a neutral experience were reactivated twice a day for 5 days

(Neutral group) after the CIS protocol, a group that did not receive the CIS stress protocol but still had DG cells previously active during a positive experience reactivated twice a day for 5 days (NoStress group), and finally, a group that was exposed to a natural social reward (i.e. female mouse) twice a day for 5 days (Natural group). Optical stimulation first occurred at 10:00 am for 15 minutes (blue laser, 20 Hz, 15 ms pulse width, ~15-20 mW) as animals explored an operant chamber, and then again at 3:00 pm for 15 minutes using the same conditions. The same behavioral schedule was performed for the Natural group. All groups were exposed for an equal amount of time to each chamber, plugged into a corresponding patch cord, and optical stimulation occurred only in the appropriate groups. Each chamber contained dim lighting, white plastic floors, and no artificial odorants. One day after the final stimulation, all groups were exposed to a 6-minute tail suspension or 24-hour sucrose preference test as described above.

Object-Female Association

24 wild type B6 mice were divided in two groups (Neutral-object group and Female-

Object group (n= 12 per group)). Learning and testing phase was conducted on the same day, 6 hours apart. In the learning phase, all mice spent 30 minutes in their homecage in the middle of a well-lit room with the lid of the cage and metal grid holding water and food removed and a 30 cm tall white rectangular frame placed around the homecage to prevent mice from escaping. All the boxes contained one target object (counterbalanced

171 objects within and between groups: empty methanol bottle or cryostat® liquid bottle

(sealed)). After 3 minutes exploring the target object, a wild-type female b6 mouse (age 9 to 16 weeks) was introduced in the boxes of the experimental mice and remained there for the next 27 minutes). The control mice did not experience a female mouse. After a total of 30 minutes from the beginning of the learning phase, all objects and female mice were removed and the male mice returned to their holding rooms. In the testing phase, mice were placed in a rectangular arena (70 × 25 × 30 cm) with white floors. A video camera resides above the testing chamber where the locations of the subjects were tracked and recorded using Noldus EthoVision XT video tracking software. Two zones

(left and right) on either end of the box A (30 × 30 cm) as well as a neutral zone in the center of the box (10 cm) were denoted as part of the arena settings. Mice were introduced in the neutral zone of the empty arena and allowed to explore freely for 3 minutes. The tracking software monitored which of the two zones each individual mouse preferred. After 3 minutes, the experimenter introduced two objects (empty methanol bottle or cryostat® liquid bottle (sealed)) and placed them in the middle of the left and right zones. For each mouse, one of the objects was the same as the one experienced during training (target object in target zone) and was placed in the least preferred zone.

The other object was novel (novel side) and placed in the preferred side. During minutes

6 to 9 objects were absent from the arena. During minutes 9 to 12, the objects were reintroduced in the same positions as minutes 3 to 6.

Cell Counting

The number of mCherry or c-Fos immunoreactive neurons in the DG and downstream areas were counted to measure the number of active cells during defined

172 behavioral tasks in 3-5 coronal slices (spaced 160 µm from each other) per mouse. Only slices that showed accurate bilateral injections in the DG were selected for counting.

Fluorescence images were acquired using a microscope with a x20/0.50 NA objective.

All animals were sacrificed 90 minutes post-assay or optical stimulation for immunohistochemical analyses. The number of c-Fos-positive cells in a set ROI (0.5 mm2 per brain area analyzed) were quantified with ImageJ and averaged within each animal. Background autofluorescence was accounted for by applying an equal cutoff threshold to all images by an experimenter blind to experimental conditions. To calculate the percentage of BLA, mPFC, or NAcc cells expressing ArchT-EGFP in Figure 3c, we counted the number of GFP-positive cells and divided by the total number of DAPI- positive cells in each region. Statistical chance was calculated by multiplying the observed percentage of ArchT-GFP-single-positive cells by the observed percentage of c-

Fos-single-positive cells; overlaps over chance were calculated as observed overlap divided by chance overlap (i.e. [GFP+ cFos+ / DAPI] / [chance overlap]).

A one-way ANOVA followed by Tukey’s multiple comparisons or one-sample t- tests were used to analyze data and later graphed using Microsoft Excel with the Statplus plug-in or Prism.

Neurogenesis

After all the behavior tests, on the 15th day since the first day of light stimulation, the mice were overdosed with Avertin and perfused transcardially with cold phosphate buffer saline (PBS), followed by 4% paraformaldehyde (PFA) in PBS. Brains were extracted from the skulls and kept in 4% PFA at 4 °C overnight. Coronal slices 50 µm thick were

173 taken using a vibrotome and collected in cold PBS. For immunostaining, each slice was placed in PBST (PBS + 0.2% Triton X-100) with 5% normal goat serum for one hour and then incubated with primary antibody at 4 °C for 24 hours (1:250 mouse anti-PSA-

NCAM, Millipore; 1:500 doublecortin, AB2253, Millipore). Slices then underwent three wash steps for 10 minutes each in PBST, followed by a one hour incubation period with secondary antibody (PSA-NCAM: 1:250 AlexaFluor488 anti-mouse, Invitrogen;

Doublecortin: 1:300 A21435, Invitrogen). Slices were then incubated for 15 minutes with

4’, 6-diamidino-2-phenylindole (DAPI; 1:10,000) and underwent three more wash steps of 10 min each in PBST, followed by mounting and coverslipping on microscope slides.

Images were taken using a Zeiss Axio Imager2 microscope. PSA-NCAM+ or doublecortin+ cells in the DG granule cell layer were counted and normalized to the area of the granule cell layer for each brain slice using ImageJ by a researcher blind to the identities of each animal. After all the data were collected, the identities of each animal were revealed and the data were assigned back into each group for statistical analysis.

In vivo electrophysiology

As described above, three mice were first bilaterally injected with an AAV9-TRE-ChR2- mCherry virus into the DG followed by lowering a bilateral optic fiber implant into position and cementing it to the skull. Following 10 days for recovery and viral expression, in a separate surgery, mice were chronically implanted with a hyperdrive that housed six independently moveable tetrodes targeting the BLA. To accommodate the optic fiber implant cemented on the skull, the AP coordinate for the hyperdrive was adjusted slightly (centered at AP = −0.85 mm) and implanted at a ~ 15° angle. The

174 electrical signal recorded from the tips of the tetrodes was referenced to a common skull screw over the cerebellum and differentially filtered for single unit activity (200 Hz to 8 kHz) and local field potentials (1–200 Hz). The amplified signal from each wire is digitized at 40 kHz and monitored with an Omniplex sytem (Plexon; Dallas, TX). Action potentials from single neurons were isolated off-line using time-amplitude window discrimination through Offline Sorter (Plexon; Dallas, TX). Putative single units were isolated by visualizing combinations of waveform features (square root of the power, peak-valley, valley, peak, principal components, and time-stamps) extracted from wires composing a single tetrode. The average firing rate for isolated neurons was 2.25 Hz ±

4.14 Hz (mean ± sd; range 0.01 Hz - 30.15 Hz). However, the firing rate distribution was highly rightward skewed (median: 0.81 Hz) and more than half of the neurons (62%;

66/106) had firing rates under 1 Hz. After the last recording session, small lesions were made near the tips of each tetrode by passing current (30 µA for ~ 10 s) and mice were transcardially perfused and brains extracted for histology using standard procedures.

Recording and light stimulation protocol

Each mouse had two recording sessions that occurred on two different days separated by

72 hours. Mice were first placed into a small recording chamber. In a single recording session, mice were first bilaterally stimulated in the DG with blue light (450 nm; Doric

Lenses; Montreal, PQ) for 10 s over 15 such trials in total. As a control, the blue light was replaced with red light (640 nm; Doric Lenses; Montreal, PQ) and the mice were given twelve 10-s trials under this condition. The power output for the blue and red lights emitted from the tips of each patch cord was adjusted to 15-18 mW as measured with a standard photometer (Thor Labs; New Jersey, NJ). The blue and red lasers were powered

175 using a laser diode driver (Doric Lenses, Montreal, PQ) triggered by TTL pulses emitted from a digital I/O card, and these events were also time-stamped and recorded in the

Omniplex system. The recording session lasted ~20 minutes and each tetrode was lowered ~0.25 mm after the first recording session.

Electrophysiological data analysis

Spiking activity was analyzed using commercial (Neuroexplorer, NEX Technologies) and custom-made software in Matlab (R2014B; Natick, MA). To visualize each neuron’s trial-averaged activity for the blue and red light stimulation period, a peristimulus time histogram (PSTH) with 100 ms time bins was generated with activity time locked to the onset of the blue or red light, and then smoothed with a Gaussian kernel (ɵ = 127 ms). In order to confirm a response during blue or red light stimulation period, 99% confidence intervals were constructed for the trial-averaged activity using a baseline 2.5 s period of spiking activity before the onset each light under the assumption of Poisson spiking statistics (e.g., Neuroexplorer, NEX Technologies). A neuron was considered to have a response for a particular light stimulation condition if trial averaged activity exceeded the upper (excitatory) or lower (inhibitory) bound of the 99% confidence interval. We considered neurons activated from DG stimulation when a neural response was confirmed for the blue light condition but not the red light condition. For each neuron identified as such, we z-scored neural activity depicted in the blue and red light PSTH, then identified the maximum trial-averaged z-score value from the 2.5 s baseline (Pre) and during blue or red light stimulation (Post). The Pre and Post maximum z-score values for the blue and red light stimulation period was compared using paired t-tests (Fig. 2p).

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Figure 1. Activating positive memory engrams rescues depression-related behavior. a Behavior schedule and groups used. b-e, Optical reactivation of dentate gyrus (DG) cells that were previously active during a positive experience significantly increases time struggling in the tail suspension test (b) and preference for sucrose (c), but does not have a significant effect in anxiety-like behavior in the open field test (d) or elevated plus maze test (e). A two-way analysis of variance (ANOVA) with repeated measures revealed a group-by-light epoch interaction in the TST (F5, 276 = 21.20, P < 0.001) or SPT

(F5, 184 = 6.20, P < 0.001) followed by Bonferroni post-hoc tests, which revealed significant increases in struggling or preference for sucrose in the positive memory + stress group. n = 15-18 per group, #P < 0.01 (# used to denote significant differences between the four stressed groups vs. the two non-stressed groups); *P<0.05, **P<0.01 (orange * and ** used to denote significant differences between the stress + positive memory group vs. the other three stressed groups). Data are means +/- SEM.

177

178

Figure 2. Positive memory reactivation increases cFos expression in the nucleus accumbens shell and the amygdala, and requires glutamatergic activity in the accumbens shell. a, Brain diagram illustrating target areas analyzed. b-m, Activation of a positive memory, but not a neutral memory or mCherry only, in the DG elicits robust cFos expression in the nucleus accumbens shell (b-e), basolateral amygdala, and central amygdala (f-i), but not in the medial prefrontal cortex (j-m). Representative images for each area are shown in B-D, F-H, and J-L, and quantifications are shown in E, I, and M, respectively. n-o, Raster plots and peri-stimulus time histograms (PSTH) illustrating a transient excitatory response from a single BLA neuron in response to DG positive memory activation after blue light stimulation (n) but not in response to red light as a control (o). p, Blue bar plots illustrate maximum BLA neural firing rate before (Pre) and after (Post) blue light stimulation in the DG (paired t-test, t(7) = 6.91, P = 0.023. Red bar plots show the maximum neural activity for the same neurons after red light stimulation in the DG that serves as a control (paired t-test, t(7) = 1.62, P = 0.15). q, Brain diagram illustrating target areas manipulated. r-s, Glutamatergic antagonists (Glux), but not saline, in the accumbens shell blocked the light-induced effects of a positive memory in stressed subjects. For histological data, a one-way ANOVA followed by a Bonferroni post-hoc test revealed a significant increase of cFos expression in the positive memory + stress group relative to controls in the NAcc and amygdala, but not the mPFC (NAcc Shell: F2,

30 = 15.2, P < 0.01; BLA: F2, 30 = 11.71, P < 0.01; CeA: F2, 30 = 11.45, P < 0.05; mPFC: F2,

30 = 1.33, P = 0.294. n = 6 per group, 3-5 slices per animal). n.s., not significant, *P<0.05, **P<0.01,***P < 0.001. For behavioral data, a two-way ANOVA with repeated measures followed by Bonferroni post-hoc test revealed a group-by-light epoch interaction on day 1 (F1, 93 = 28.39, P < 0.001; n = 15-18 per group) and day 2 of testing

(F1, 93 = 8.28, P < 0.01). Data are means +/- SEM. Abbreviations for brain areas: medial prefrontal cortex (mPFC), nucleus accumbens (NAcc), lateral septum (LS), hippocampus (HPC), lateral habenula (LH), hypothalamus (Hyp), central amygdala (CeA), basolateral amygdala (BLA), ventral tegmental area (VTA). Scale bars in unexpanded and expanded images correspond to 1mm and 100µm, respectively.

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180

Figure 3. The antidepressant effects of an optically activated positive memory require real-time terminal activity from the BLA to the NAcc. a, Brain diagram illustrating target areas manipulated. b, Representative coronal slices showing TRE-ArchT-eGFP-positive cells in the BLA or mPFC, as well as their corresponding terminals in the NAcc. Scale bars: BLA and mPFC: 500µm, NAcc, 200µm. c, Animals were taken off Dox and initially exposed to a positive experience, which caused labeling of corresponding BLA

(~18%), mPFC (~12%), or NAcc (~9%) cells with eGFP derived from AAV9-TRE- ArchT-eGFP (green, halo-like expression). Light-activation of a positive memory engram in the DG preferentially reactivated the BLA and NAcc shell cells, as measured by endogenous cFos expression (red, nucleus-localized), that were originally labeled by the same positive experience, while no-light stimulation groups showed levels of overlap not significantly different from chance. Arrowheads indicate double-stained cells. Scale bar: 5 µm. d-g, ArchT-mediated inhibition of BLA, but not mPFC, terminals in the NAcc prevents the DG-mediated light-induced increases in struggling (d, e) or preference for sucrose (f, g), while inhibition of BLA terminals in the NAcc without DG stimulation does not affect behavior (insets). h, ArchT-mediated inhibition of BLA, but not mPFC, terminals prevents the DG-mediated light-induced increase of cFos expression in the NAcc. For behavioral data, a two-way ANOVA with repeated measures followed by Bonferroni post-hoc test revealed a group-by-light epoch interaction and significant

ArchT-mediated attenuation of struggling in the TST (d: F2, 84 = 7.30, P < 0.001; e: F2, 84

= 6.61, P < 0.01) or preference for sucrose water in the the SPT (f: F2, 56 = 10.66, P < 0.01). n = 9-12 per behavioral group. *P<0.05, **P<0.01, ***P<0.001; orange ** and *** used to denote significant differences between the stress + positive memory group vs. all other groups. For histological data, one-sample t-tests against chance overlap were performed (n = 4 per group, 3-5 slices per animal). n.s., not significant. Data are means +/- SEM.

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Figure 4. Chronic activation of a positive memory elicits a long-lasting rescue of depression-related behavior. a, Behavioral schedule and groups utilized. b, c, Animals in which a positive memory was reactivated twice a day for five days showed increased struggling in a 6-minute tail suspension test (F5, 75 = 3.34, P < 0.05) (b) and increased preference for sucrose measured over 24 hours (F5, 74 = 6.25, P < 0.01) (c). d, The 5-day positive memory stimulation group showed a significant increase of adult new-born cells in the DG as measured by PSA-NCAM+ cells (F5, 72 = 4.65, P < 0.01; See also Supplementary Fig. 15 for doublecortin data). For these data (b-d), a one-way ANOVA revealed a significant interaction of the experimental-group factor and stimulation- condition factor and was followed by a Bonferroni post-hoc test. e-j, representative images showing PSA-NCAM+ cells in the DG across all groups. n = 12-16 per behavioral group, n = 5 slices per animal for data appearing in (d). Scale bars in expanded images correspond to 5 µm. *P<0.05. Data are means +/- SEM.

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Experimental group Control group 100 )

(s 90 one

t z 80 ge r a

t 70 in

e m i 60 T

50 BSL ON1 OFF ON2

) 50 * 40

10 ference score ON-Bsl (s f Di 0

Supplementary Fig. 1. Male mice spend more time around an object associated with females. a, Time spent in the target zone where the object associated with females is introduced in the ON phases. Female-object mice (experimental group) spend more time in the target zone during the ON phases than the Neutral-object mice (control group; two- way ANOVA with multiple comparisons, ON1 t88 = 2.41; p < 0.05, ON2 t88 = 2.08; p < 0.05). b, Difference score (avg of ON phases – Bsl) also shows the increased preference for the target zone in the female-object group compared to neutral-object group (t22 = 2.37; p < 0.05). See Supplementary Information for detailed methods.

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Supplementary Fig. 2. Positive, neutral, or negative experiences label a similar proportion of dentate gyrus cells with ChR2. a, The c-Fos mice were bilaterally injected with AAV9-TRE-ChR2-mCherry and implanted with optical fibers targeting DG. b-e, Histological quantifications reveal that, while off Dox, a similar proportion of DG cells are labeled by ChR2-mCherry in response to positive (c), neutral (d), or negative experience (e). All animals were sacrificed a day after completing the CIS protocol. One- way ANOVA followed by Bonferroni post-hoc test, P > 0.05, n.s. not significant. Data are means +/- SEM.

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Supplementary Fig. 3. Chronic immobilization leads to a decrease in body weight. Animals were chronically immobilized for 10 days, during which they lost a significant amount of weight compared to an unstressed group (one-way ANOVA followed by Bonferroni post-hoc test, *P<0.05, n = 9 per group). Data are means +/- SEM.

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Supplementary Fig. 4. Reactivation of a positive memory decreases latency to feed in a novelty suppressed feeding paradigm. All groups were food deprived for 24 hours and then underwent a novelty suppressed feeding protocol. While chronic immobilization increased the latency to feed, light-reactivation of a positive memory significantly decreased the latency to feed and at levels that matched the unstressed groups (one-way ANOVA followed by Bonferroni post-hoc test, **P<0.01, n = 15-18 per group). Data are means +/- SEM.

186

No Stress + Positive Memory (ChR2) No Stress + mCherry Stress + Positive Memory (ChR2) Stress + Neutral Memory (ChR2) Stress + mCherry Stress + Negative Memory (ChR2)

300 ) g m ( d 200 me u s on

c 100 ood f 0

Supplementary Fig. 5. All groups consumed comparable levels of food after the novelty suppressed feeding paradigm. Upon completion of the novelty suppressed feeding test, all groups were returned to their home cage and food intake was measured after 5 minutes (one-way ANOVA followed by Bonferroni post-hoc test, n.s. not significant, n = 15-18 per group). Data are means +/- SEM.

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Supplementary Fig. 6. Activation of a positive memory does not alter locomotor activity in the open field test. All groups failed to show significant changes in locomotor activity within a session of open field exploration during either light off or light on epochs, though any trends towards decreases in locomotion are consistent with stress-induced behavioral impairments (two-way ANOVA followed by Bonferroni post- hoc test, n = 15-18 per group, n.s. not significant). Data are means +/- SEM.

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Supplementary Fig. 7. Activating a positive memory in the dentate gyrus produces an increase in c-Fos expression in the lateral septum. a, Diagram of regions analyzed. b-d, c- Fos expression significantly increased in the positive memory group (b) but not in a group in with a neutral memory (c) or expressing mCherry alone (d) was light stimulated (one-way ANOVA followed by Bonferroni post-hoc test *P<0.05, n = 5 per group, 3-5 slices per animal). TS, tail suspension. Data are means +/- SEM.

189

Supplementary Fig. 8. Activating a positive memory in the dentate gyrus produces an increase in c-Fos expression in the dorso-, ventro-medial, and lateral hypothalamus. a, Diagram of regions analyzed and color key. b, c-Fos expression is significantly increased in the dorso- (blue), ventro-medial (red), and lateral hypothalamus (yellow) of the positive memory group. c-d, These increases were not observed in the neutral memory group (c) or in the mCherry alone group (d). Color-coded regions of interest are magnified on the right panels. e, Quantification of histological data (one-way ANOVA followed by Bonferroni post-hoc test **P<0.01, ***P<0.001, n = 5 per group, 3-5 slices per animal). TS, tail suspension. Data are means +/- SEM. Scale bar: 250 µm.

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Supplementary Fig. 9. Activating a positive memory in the dentate gyrus does not produce an increase in c-Fos expression in the trisynaptic circuit of the hippocampus. a, Diagram of regions analyzed. b-d, c-Fos expression is not significantly increased in the DG, CA3, or CA1 of the group in which a positive memory (b) or a neutral memory (c) was activated, nor in the mCherry only group (d). e, Quantification of histological data (one-way ANOVA followed by Bonferroni post-hoc test, n = 5 per group, 3-5 slices per animal). n.s. not significant. TS, tail suspension. Data are means +/- SEM. Scale bars for unexpanded and expanded images correspond to 1 mm and 100 µm, respectively.

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Supplementary Fig. 10. Activating a positive memory in the dentate gyrus does not produce an increase in c-Fos expression in the lateral habenula. a, Diagram of regions analyzed. b, c, c-Fos expression is not significantly increased in the lateral habenula (LH) of the positive memory group (c). d, e, c-Fos expression is not significantly increased in the LH of the neutral memory group (e). f, g, c-Fos expression also is not significantly increased in the LH of the mCherry alone group (g). h, Quantification of histological data (one-way ANOVA followed by Bonferroni post-hoc test, n = 5 per group, 3-5 slices per animal). n.s. not significant. TS, tail suspension. Data are means +/- SEM.

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Supplementary Fig. 11. Activating a positive memory in the dentate gyrus does not produce an increase in c-Fos expression in the ventral tegmental area. a, Diagram of regions analyzed. b, c-Fos expression is not significantly increased in the ventral tegmental area (VTA) of the positive memory group. c, d, Magnification of the VTA with (c) or without (d) tyrosine hydroxylase staining (red). e-g, c-Fos expression is not significantly increased in the VTA of the mCherry only memory group. h-j, c-Fos expression also is not significantly increased in the VTA of the neutral memory group. k, Quantification of histological data (one-way ANOVA followed by Bonferroni post-hoc test, n = 5 per group, 3-5 slices per animal). n.s. not significant. TS, tail suspension. Data are means +/- SEM. Scale bars for unexpanded and expanded images correspond to 1 mm and 100 µm, respectively.

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Supplementary Fig. 12. Activating a positive memory through the dentate gyrus of unstressed animals increases c-Fos expression in various downstream regions. a, Diagram of regions analyzed. b, In the positive compared to the neutral memory group, c-Fos expression is significantly increased in the lateral septum, NAcc shell, BLA, dorsomedial, ventromedial, and lateral hypothalamus, but not in the mPFC, NAcc core, habenula, or ventral hippocampus. Trends were observed in the CeA and VTA. Each brain region was analyzed using an unpaired Student’s t test, n = 5 per group, 3-5 slices per animal; #P= 0.17 for CeA and P=0.09 for VTA; *P<0.05, **P<0.01, ***P<0.001, n.s. not significant. Data are means +/- SEM.

194

Supplementary Fig. 13. Dopamine receptor antagonists block the light-induced effects of positive memory activation. Administration of a cocktail of dopamine receptor antagonists prevented the light-induced increases in struggling during the tail suspension test. When animals were tested again on day 2 and infused with saline, the behavioral effects of optically reactivating a positive memory were observed (two-way ANOVA with repeated measures followed by Bonferroni post-hoc test, *P<0.05, n = 9 per group). Data are means +/- SEM.

195

Supplementary Fig. 14. A single session of activating a positive memory in the dentate gyrus does not produce long-lasting antidepressant-like effects. a, b, Animals in which a positive memory was optically activated during the tail suspension test (a) or sucrose preference test (b) showed acute increases in time struggling or preference for sucrose; this change in behavior did not persist when tested again on day 2 (within subjects ANOVA followed by Bonferroni post-hoc test), n = 9. n.s. not significant. Data are means +/- SEM.

196

a DCX+ Cells n.s. s t

n 4 * * ou c

ll 3 e c

d 2 e z i l

a 1 m r o

N 0

ss tral re St 1-day 1-day Neu Natural No StimNo

b 5-day c 1-day d Neutral

e No Stim f Natural g No Stress

Supplementary Fig. 15. Chronic activation of a positive memory prevents stress- induced decreases in neurogenesis. a, The 5-day positive memory stimulation group showed a significant increase of adult new-born cells in the DG as measured by doublecortin (DCX)-positive cells (F5, 74 = 7.634, P < 0.01) relative to control groups. n = 12-16 per group, n = 5 slices per animal for data appearing in (a). b-g, Representative images of DCX-positive cells in the DG for the 5-day (b), 1-day (c), Neutral (d), No Stimulation (e), Natural (f), and No Stress (g). *P<0.05, n.s. not significant. Data are means +/- SEM.

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a Neurogenesis vs. Sucrose preference b Tail suspension vs. Sucrose preference 1.0 1.0 e c e n 0.8 c 0.8 5-day n 1-day ere f

ere NoStim 0.6 f 0.6 re p re Neutral

p NoStress

se 0.4 0.4 o se Natural o cr u 0.2 cr 0.2 u S r = 0.30, P = 0.011 r = 0.20, P = 0.079 S 0.0 0.0 0 5 10 15 20 25 0 100 200 300 Normalized PSA-NCAM+ cell counts Time struggling (s)

Supplementary Fig. 16. Behavioral and neuronal correlations. a, Performance levels in the SPT and the number of adult-born neurons as measured by PSA-NCAM are positively correlated on an animal-by-animal basis. b, Performance levels between the TST and SPT show strong positive correlation trends on an animal-by-animal basis.

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Conclusion: Engram cells have come of age

As mentioned at the outset of this thesis, Semon’s concept of an engram has a biological realization that our studies—in addition to the rich data provided by numerous previous searches for the engram—begin to reveal. I began by proposing that engrams are biologically possible because the brain is mutable; however, only until recently has this mutability (e.g. Hebbian plasticity) been shown to occur specifically in engram-bearing cells (Ryan et al. 2015). Fittingly, this closing chapter focuses on bridging the phenomenon of plasticity with a modern reconceptualization of Semon’s engram theory.

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Neural plasticity and the Search for Semon’s Engram Complex

Semon’s engram exists as the enduring changes in the brain that occur as a result of learning. The idea that learning leaves a physiological and structural trace in the brain is encapsulated by Hebbian theory, which proposes that neural plasticity supports learning and is summarized in the oft-quoted maxim, “neurons that fire together wire together” (Hebb, 1949). The notion that plasticity between brain cells supports learning was subsequently, albeit partly, demonstrated with Bliss and Lomo’s discovery of long- term potentiation (LTP), which is discussed in earlier chapters. These epoch-making concepts in brain science fueled a substantial number of neuroscientists to characterize the experience-dependent alterations of nervous systems (Flavell and Greenberg, 2008).

Indeed, a large amount of work has been directed to determine the physiological, molecular and circuit mechanisms of plasticity-related changes in the brain, including

LTP, long-term depression (LTD), and homeostatic plasticity (Malenka and Bear, 2004).

In addition, structural plasticity of synapses and dendritic spines, as well as cell-wide changes in the intrinsic excitability of neurons, has been studied as potential mechanisms for information storage during learning and activity-dependent neural development (e.g.

Yiu et al. 2014). These physiological and structural readouts begin to relate form to function and thereby biologically flesh out the idea of the mutable brain.

As stated earlier, the results of the early pharmacological blockade experiments conducted with the NMDA receptor (NMDAR) antagonist AP5 supported the notion that

LTP is essential for spatial learning (Morris et al. 1986)—a finding that was validated with more specific targeted genetic ablation of NMDARs in the CA1 region of the hippocampus (Tsien et al. 1996). LTP inducible in the CA1 region of the hippocampus by high-frequency stimulation (HFS) in vitro and is NMDA receptor-dependent; accordingly, subsequent experiments sought to test whether this form of synaptic plasticity had an

200 essential role in a variety of hippocampal-dependent memories (reviewed in Malenka and

Bear, 2004). Indeed, mice with NMDAR ablation in DG and CA3 showed impairments of pattern separation and pattern completion at the behavioral level, respectively

(McHugh et al. 1996, 2007; Nakazawa et al. 2003).

These elegant, technological tour-de-forces, however, treated each subregion as a homozygous structure of cells. Indeed, in many of the studies in which links between synaptic changes and memory have been made, these links have been shown by globally investigating one or more broad brain region(s), rather than a specific population of cells that were specifically activated by a given learning task and whose reactivation elicits behavioral recall (i.e. putative engram cells). With the activity-dependent systems described in this thesis (e.g. Liu et al. 2012; Guenther et al. 2013; Denny et al. 2014), subregions of structures such as the hippocampus can be treated as a heterogeneous collection of cells, each perhaps involved in distinct memory-related processes, capable of differentially driving behaviors (Redondo et al. 2014; Ramirez et al. 2015). Semon’s

“Engram Complex”, it seems, is experimentally tractable.

For example, leveraging the notion that activity-dependent systems enable

“snapshots” of neuronal activity in response to learning, in a recent study (Nonaka and

Toyoda, 2014), the authors subjected a transgenic mouse in which the promoter of the

IEG Arc drives the expression of dVenus, a destabilized version of the fluorescent Venus

(Eguchi and Yamaguchi, 2009) to contextual fear conditioning. They found that the fear conditioning induced presynaptic potentiation only in the cortical input to the dVenus+ basolateral amygdala (BLA) cells. These data support the notion that synaptic plasticity in a subset of BLA neurons contribute to fear memory expression. However, they did not offer evidence indicating that reactivation of these dVenus+ cells evoke the specific behavioral recall. In another recent study, researchers conditioned a rat to associate a foot

201 shock with optogenetic stimulation of auditory inputs into the amygdala. Optogenetic delivery of LTD conditioning (i.e. low-frequency stimulation) to the auditory input inactivated memory of the shock, while subsequent optogenetic delivery of LTP conditionings (i.e. HFS) to the auditory input reactivated memory of the shock (Nabavi et al. 2014). These data provided a causal link between such synaptic processes and memory. However, this study did not directly demonstrate that these synaptic processes

(i.e. LTP and LTD) indeed occurred in the specific amygdala cell population that was activated by the initial conditioning (i.e. engram-bearing cells).

Until recently, an outstanding question remained regarding whether or not the cells labeled using our activity-dependent and inducible strategy are actually cells that show enduring plasticity-related changes during learning (Mayford, 2014). More specifically, it remained to be determined whether or not cells that express cFos during learning defined an active neural population that underwent enduring changes in structural and/or physiological plasticity. Our hypothesis—namely, that these DG cells harbor a component of a contextual memory engram—predicts that ChR2-positive DG cells should show such enduring changes compared to quiescent, ChR2-negative cells.

Indeed, we previously proposed that in order to claim that an observed increase of synaptic strength directly reflects a component of learning-dependent physical/chemical changes in engram cells, at least two conditions must be satisfied (Tonegawa et al. 2015).

First, plasticity should be observed only in a population of cells activated by a specific learning process, and second, reactivation of these cells should be sufficient to elicit the neuronal and behavioral expression of the associated memory.

By using the activity-dependent and inducible strategy for labeling cells from Liu et al. (2012), Ryan et al. (2015) addressed this issue by first labeling hippocampal DG granule cells that were activated by contextual fear conditioning. Reactivation of the

202

ChR2+ cells by blue light pulses was sufficient to evoke fear memory expression, consistent with Liu et al. (2012). One day after contextual fear conditioning (CFC), ex vivo cell recordings performed by patch clamping revealed that the AMPA/NMDA current ratio was significantly higher in ChR2+ cells compared to ChR2- cells in the same hippocampal slices. Thus, this increase in synaptic strength directly reflected a physical change that occurred only in memory engram cells.

Semon’s “Engram Complex” also can be realized in terms of structural plasticity; the dynamics of the formation and elimination of individual dendritic spines has been heavily implicated as a physical readout of learning-induced changes. For instance, changes in neocortical spine numbers in response to sensory stimulation and motor learning were investigated using two-photon laser scanning microscopy in vivo. Under baseline conditions, newly formed spines in the apical tufts of layer 5B pyramidal neurons in the barrel cortex were transient, lasting no more than a week; whisker trimming stabilized these new spines and destabilized previously persistent spines

(Holtmaat et al. 2006). Two subsequent studies reinforced the intimate association between synaptic structural plasticity in the neocortex with motor learning and novel sensory experiences. In one study (Xu et al. 2009), training in a forelimb reaching task resulted in rapid (within an hour) formation of post-synaptic dendritic spines on the output pyramidal neurons in the motor cortex. Selective elimination of spines that existed before training gradually returned the overall spine density back to the original level. The new spines induced during learning were preferentially stabilized during subsequent training and endured long after training stopped. Moreover, different motor skills were encoded by a different set of synapses. In another study (Yang et al. 2009), training on an accelerated rotarod (but not on a slowly rotating rotarod) over two days led to a ~5-7% increase in spine formation in the primary motor cortex. A novel sensory experience

203 provided by switching animals from a standard to enriched housing environment also resulted in a ~5% increase in spine density in 1-2 days in the barrel cortex. These newly formed spines survived experience-dependent elimination during subsequent periods.

Thus, these three studies conducted by long-term optical imaging of the cortex revealed that rapid, long-lasting synaptic structural plasticity is tightly associated with motor learning and novel sensory experiences. These data also suggest that durable motor memories are stored largely in stable, connected synaptic networks.

While the aforementioned studies were conducted for relatively slow-forming motor skill memories, structural plasticity associated with explicit memory was investigated by employing tone-fear conditioning and extinction (Lai et al. 2012). By imaging postsynaptic dendritic spines of layer V pyramidal neurons in the mouse frontal association cortex, these authors found correlations between fear memory expression and spine elimination, as well as fear memory extinction and spine formation. Remarkably, spine elimination and formation induced by fear conditioning and extinction, respectively, occurred on the same dendritic branches in a cue- and location-specific manner within a distance of 2 µm. Furthermore, reconditioning following extinction eliminated spines formed during extinction, suggesting that within vastly complex neuronal networks, fear conditioning, extinction, and reconditioning lead to opposing changes at the level of individual synapses.

Do these spine dynamics reflect what occurs in the cell populations that store the engrams for tone-shock association memory? If so, the observed direction of synaptic structural plasticity (i.e. spine elimination for conditioning and spine formation for extinction) seems to be contrary to what one might predict. Indeed, it is thought that the tone-fear conditioning memory is stored in the LA (Blair et al. 2001), and fear extinction is based on a formation of new memory that inhibits the expression of the fear memory in

204 the amygdala circuit (Ehrlich et al. 2009; Trouche et al. 2013). Frontal areas such as the infralimbic cortex are thought to be a part of the neural circuit that regulates expression of a conditioned fear memory during extinction schedules (Mercado et al. 2011), and the observed elimination and formation of postsynaptic spines in this area of the brain may reflect synaptic structural plasticity necessary for the behavioral regulation of fear rather than that associated with fear memory engrams per se. In contrast, other frontal areas such as the prelimbic cortex are thought to be a part of the neural circuit that regulates fear memory expression by coordinating activity with the hippocampus and BLA. Testing whether or not the spine-specific changes that occur in infralimbic cells truly reflect that they harbor a component of an engram (or extinction engram) requires directly activating and inactivating these cells to test for their causal contributions to such behaviors. Indeed, one would predict that activation of infralimbic, as opposed to prelimbic, cortex engram- bearing neurons would elicit the context-specific recall of an extinction memory, while inhibiting these cells may prevent extinction learning or directly disinhibit an extinguished fear memory.

In Ryan et al. (2015), the nature of the enduring changes that occur in DG engram cells confirmed the long-held hypothesis that synaptic strengthening—manifested by increased AMPA/NMDA current ratio as well as a change in structural plasticity indicated by increased density of dendritic spines—occurred specifically in ChR2- positive cells as opposed to ChR2-negative cells in the same hippocampal subregion.

This this study also suggested that for CFC, the preferential connectivity of DG engram cells with engram cells in downstream CA3 and BLA is the crucial, interconnected anatomical substrate for the consolidated memory (Ryan et al. 2015). Thus, Semon’s

“Engram Complex” has a biological basis partly realized in DG, CA3, and BLA cells that previously expressed cFos during a defined learning period.

205

Moreover, Semon’s use of the phrase “Engram Complex” suggests that he was considering that the entire engram for a particular memory is composed of multiple components. In line with his proposal, the data collected to date indicate the contextual memory engrams are directly processed in multiple hippocampal subregions including

DG, CA3, and CA1, each contributing to the overall memory of a context (Ji and Maren,

2008; Lee and Kesner, 2004; Leutgeb et al. 2004). For contextual fear or reward memory, distinct subpopulations of BLA cells are also recruited to provide engrams for negative or positive valence (Redondo et al. 2014; Namburi et al. 2015). How each engram component in these circuits contributes to the overall engram complex is a matter of great interest, studies of which have begun only recently and which are summarized in Figure 1.

It is important to note that the circuits engaged during learning and recall are not necessarily linear; parallel pathways can contribute to both processes and compensate for one another. For instance, one study has shown that blocking the CA1 activity by prolonged optogenetic inhibition during the recall of remote memory caused elevated activity in the anterior cingulate cortex (ACC). This compensation mechanism bypassed the requirement of CA1 and resulted in normal remote memory recall (Goshen et al.

2011). Another recent study also showed that blocking dorsal hippocampus by local microinfusion of glutamic receptor antagonists interrupted the natural contextual fear memory recall when the animal was returned to the original fear-conditioned context

(Cowansage et al. 2014). However, light activation of retrosplenial cortex cells previously active during fear conditioning was sufficient to overcome this impairment and nonetheless induced both the neuronal and behavioral expression of fear (Cowansage et al. 2014). Thus, these results suggest the existence of multiple functional engram pathways for a given memory. The animals may preferentially use one default pathway for natural memory recall, but under certain conditions other latent pathways could be

206 brought on line and compensate for the default pathways. Cowansage et al. (2014) also showed robust concurrent reactivation of several downstream cortical and subcortical areas, including the basolateral amygdala, central amygdala, and entorhinal cortex, thus demonstrating optical leverage over a stable memory trace. Furthermore, other data obtained by applying pharmacogenetic methods to CREB-overexpressing LA cells, which are known to be required for tone fear conditioning, too were sufficient to reinstate freezing behavior, although these studies did not demonstrate that the cells manipulated were initially activated by learning (Kim et al. 2014; Yiu et al. 2014).

A modern approach to deconstructing Semon’s engram requires a reconceptualization that takes into account the technical limitations that may restrict whether or not engram-related processes are impaired or activated. For instance, spatially, non-selective inhibition of all dorsal DG neurons had no effect on memory recall, making these cells seem unnecessary for this process (Kheirbek et al. 2013). But, if a sparse population of these DG neurons previously active during the training were inhibited during recall, the memory was modestly impaired (Denny et al. 2014), indicating the DG engram cells are partially necessary for memory recall. This study compliments our previous efforts demonstrating that selective activation of a sparse cell population in DG induced the recall of a previous fear memory (Liu et al. 2012); interestingly, non- selective activation of dorsal DG neurons not only failed to induce artificial memory recall, it instead suppressed natural memory recall in the original context (Kheirbek et al.

2013), masking the sufficiency of DG engram cells for memory recall. These seemingly conflicting results can be potentially explained by neuronal competition and lateral inhibition among different populations of engram cells within the same region as reported by other studies (Han et al. 2007; Tanaka et al. 2014), and they illustrate the spatial resolution needed to properly characterize the contribution of engram cells.

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Geneticists often perform epistasis analysis to map out the molecular pathways inside cells, and similar principles can also be applied to testing a population of cells’ contributions to Semon’s overall engram complex. For example, future studies may activate engram cells in one part of the brain while simultaneously blocking engram cells in another part of the brain to examine the interactions among different engram components and gain further knowledge about the structure and layout of the associated pathways. When we try to map a specific component of Semon’s “Engram Complex”, it is crucial to consider the flexible and dynamic nature of recall, and thus non-rigid models assuming non-fixed necessity and sufficiency for different components of the pathways are required. Similar conceptual caveats abound: for example, the ability to activate memory-related processes via the hippocampus does not mean that this is how memory works. Rather, I propose that our activity-dependent and inducible methods of intervention effectively commandeer cells harboring components of an engram and thus force the cellular and behavioral expression of a specific memory. In other words, we’ve successfully hijacked the brain’s mental time machine.

Collectively, in this thesis we have shown that a population of hippocampus cells is sufficient to activate a context-specific fear memory (Liu et al. 2012), a neutral memory amenable for subsequent updating (Ramirez et al. 2013), and a positive memory to suppress depression-related behavior (Ramirez et al. 2015). Moreover, the mnemonic information elicited by the activation of these cells, which specifically undergo various forms of plastic-related changes (Ryan et al. 2015), can drive, as well as manipulate the contents of, both appetitive and aversive behaviors (Redondo et al. 2014). Indeed, by combining multiple technologies (e.g. optogenetics, transgenics, in vivo physiology), neuroscience has now reached a point where discrete components of Semon’s “Engram

208

Complex” can be isolated and manipulated in the brain. Hereafter, the mental time machine can be tinkered with to artificially induce and modulate recollection. We have, in essence, illuminated a previously unlit corner of the mental memoriam.

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Figure 1. Anatomical locations of memory engram cell populations identified. Memory engram cell populations in different areas of the brain, as indicated by different types of supporting evidence (observational, loss-of-function, and gain-of-function) and studies published. Abbreviations: OB: olfactory bulb; PFC: prefrontal cortex; RSC: retrosplenial cortex; NAcc: nucleus accumbens; SC: sensory cortex; LA: lateral amygdala; BLA: basolateral amygdala.

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Table 1. Three lines of evidence for memory engram cell populations. A non- exhaustive list of representative studies on memory engram cell populations categorized by types of supporting evidence (observational, loss-of-function, and gain-of-function), with methods used, brain areas involved, and publication listed.

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Acknowledgements:

Science is a beautiful international dialogue that transcends gender, ethnicity, orientation, and even time—it transcends us. It's a privilege to be a part of a community, filled with solidarity, that aims to make the unknown known. I’m deeply grateful for and indebted to the multiple communities home and abroad that have enabled such a dialogue in general and our team’s search for the engram in particular—the inimitable Team X, our Herculean T-lab, my unconditionally supportive friends, my infinitely loving family. You all have given me the kinds of memories worth leaving intact.

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LETTER doi:10.1038/nature11028

Optogenetic stimulation of a hippocampal engram activates fear memory recall

Xu Liu1*, Steve Ramirez1*, Petti T. Pang1, Corey B. Puryear1, Arvind Govindarajan1, Karl Deisseroth2 & Susumu Tonegawa1

3 A specific memory is thought to be encoded by a sparse population of mice with the AAV9-TRE-ChR2-EYFP virus and an optical fibre neurons1,2. These neurons can be tagged during learning for sub- implant (Fig. 1a). This approach directly couples the promoter of sequent identification3 and manipulation4–6. Moreover, their ablation c-fos, an immediate early gene often used as a marker of recent neuronal or inactivation results in reduced memory expression, suggesting activity21, to the tetracycline transactivator (tTA), a key component of their necessity in mnemonic processes. However, the question of suf- the doxycycline (Dox) system for inducible expression of a gene of ficiency remains: it is unclear whether it is possible to elicit the beha- interest22. In our system, the presence of Dox inhibits c-fos-promoter- vioural output of a specific memory by directly activating a driven tTA from binding to its target tetracycline-responsive element population of neurons that was active during learning. Here we show (TRE) site, which in turn prevents it from driving ChR2–EYFP in mice that optogenetic reactivation of hippocampal neurons acti- (enhanced yellow fluorescent protein) expression. In the absence of vated during fear conditioning is sufficient to induce freezing beha- Dox, training-induced neuronal activity selectively labels active viour. We labelled a population of hippocampal dentate gyrus c-Fos-expressing DG neurons with ChR2–EYFP, which can then be neurons activated during fear learning with channelrhodopsin-2 reactivated by light stimulation during testing (Fig. 1b, c). We con- (ChR2)7,8 and later optically reactivated these neurons in a different firmed that our manipulation restricts the expression of ChR2–EYFP context. The mice showed increased freezing only upon light stimu- largely to the DG area of the hippocampus (Fig. 1d–g). lation, indicating light-induced fear memory recall. This freezing was not detected in non-fear-conditioned mice expressing ChR2 in a similar proportion of cells, nor in fear-conditioned mice with cells a b d labelled by enhanced yellow fluorescent protein instead of ChR2. ITRTRE ChR2–EYFP ITR Training AAV Finally, activation of cells labelled in a context not associated with c-fos tTA feardidnotevokefreezinginmicethatwerepreviouslyfear- CA1 conditioned in a different context, suggesting that light-induced fear memory recall is context-specific. Together, our findings indicate that TRE ChR2–EYFP DG activating a sparse but specific ensemble of hippocampal neurons that CA3 contribute to a memory engram is sufficient for the recall of that memory. Moreover, our experimental approach offers a general c-fos tTA method of mapping cellular populations bearing memory engrams. Dentate gyrus c e f g An important question in neuroscience is how a distinct memory is Doxycycline No doxycycline Doxycycline formed and stored in the brain. Recent studies indicate that defined Context A ContextContext B B Context A populations of neurons correspond to a specific memory trace1, sug- Habituation FC Testing gesting a cellular correlate of a memory engram. Selective ablation or inhibition of such neuronal populations erased the fear memory res- 5 days 2 days 1 day 5 days ponse5,6, indicating that these cells are necessary for fear memory expression. However, to prove that a cell population is the cellular basis of a specific fear memory engram it is necessary to conduct a mimicry experiment to show that direct activation of such a popu- Figure 1 | Basic experimental protocols and selective labelling of DG cells by lation is sufficient for inducing the associated behavioural output9,10. ChR2–EYFP. a, The c-fos-tTA mouse was injected with AAV9-TRE-ChR2- The hippocampus is thought to be critical in the formation of the EYFP and implanted with an optical fibre targeting the DG. b, When off Dox, training induces the expression of tTA, which binds to TRE and drives the contextual component of fear memories11–14. Modelling15 and experi- 16,17 expression of ChR2–EYFP, labelling a subpopulation of activated cells (yellow) mental studies have demonstrated an essential role of the dentate in the DG. c, Basic experimental scheme. Mice were habituated in context A gyrus (DG) of the hippocampus in discriminating between similar with light stimulation while on Dox for 5 days, then taken off Dox for 2 days and contexts. Cellular studies of immediate early gene expression showed fear-conditioned (FC) in context B. Mice were put back on Dox and tested for 5 that sparse populations of DG granule cells (2–4%) are activated in a days in context A with light stimulation. d, Representative image showing the given context18. Moreover, although the same population of DG expression of ChR2–EYFP in a mouse that was taken off Dox for 2 days and granule cells is activated repeatedly in the same environment, different underwent FC training. e–g, An image of each rectangular area in d is environments19 or different tasks20 activate different populations of magnified, showing the DG (e), CA1 (f) and CA3 (g). The green signal from DG granule cells. These lines of evidence point to the DG as an ideal ChR2–EYFP in the DG spreads throughout entire granule cells, including dendrites (e), whereas the green signal confined to the nuclei in CA1 and CA3 is target for the formation of contextual memory engrams that represent due to a 2-h half-life EGFP (shEGFP) expression from the c-fos-shEGFP discrete environments. construct of the transgenic mouse (f, g). Blue is nuclear marker 49,6-diamidino- To label and reactivate a subpopulation of DG cells active during the 2-phenylindole (DAPI). Panel d is at 310 magnification and panels e–g are at encoding of a memory, we targeted the DG of c-fos-tTA transgenic 350 magnification.

1RIKEN-MIT Center for Neural Circuit Genetics at the Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. 2Department of Bioengineering and Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California 94305, USA. *These authors contributed equally to this work.

First, to characterize the inducible and activity-dependent expres- the FC or NS groups was not due to the low infection rate of the virus, sion of ChR2–EYFP, we examined its expression timeline under but reflected the naturally low activity of DG neurons during the various treatments (Fig. 2a–h). We observed a complete absence of training sessions18,23. Notably, NS and FC treatments resulted in ChR2–EYFP expression in DG neurons while mice were on Dox similar proportions of ChR2–EYFP-positive cells (Fig. 2h). ChR2– (Fig. 2a). Two days off Dox was sufficient to induce ChR2–EYFP EYFP expression after FC seemed to be restricted to the excitatory expression in home-caged mice (Fig. 2b). The number of ChR2– neurons, as no overlap was detected between ChR2–EYFP-positive neu- EYFP-positive cells increased substantially in response to 2 days off rons and GABA-positive inhibitory neurons (Supplementary Fig. 2). Dox followed by fear conditioning (FC; Fig. 2c). We found that the vast We injected c-fos-tTA mice with either AAV9-TRE-ChR2-EYFP or majority of c-Fos-positive cells were also ChR2–EYFP positive AAV9-TRE-EYFP, subjected them to FC while off Dox, and then put (Supplementary Fig. 1), confirming that activity-dependent labelling them back on Dox to test for light-evoked responses from DG cells the with ChR2–EYFP recapitulated the induction of endogenous c-Fos. A following day. The mice were anaesthetized for in vivo recordings, and similar increase in ChR2–EYFP expression was seen in a group of mice blue light pulses (473 nm, 0.1 Hz, 15 ms pulse duration) were delivered that were exposed to the same context and tone as the FC group but to the DG. Consistent with the sparse labelling of DG neurons had no shocks delivered (NS; Fig. 2d). ChR2–EYFP expression lasted (Fig. 2h), we identified only ten DG neurons that responded to light at least 5 days (Fig. 2e) and was gone by 30 days (Fig. 2f). Kainic- stimulation from nine c-fos-tTA mice injected with AAV9-TRE- acid-induced seizures resulted in complete labelling of DG cells with ChR2-EYFP (the ChR2 group). In these neurons, we detected a reliable ChR2–EYFP (Fig. 2g), indicating that the relatively sparse labelling in increase of spike probability precisely time-locked to the onset of light pulses (Fig. 2l, m). These cells also showed robust responses to trains of a b c 20 Hz light stimulation, with a slight decrease in spike probability over time that remained higher above baseline (Fig. 2n). We did not find any light-responsive cells in the ten c-fos-tTA mice injected with AAV9-TRE-EYFP (the EYFP group; data not shown). Most of the d e f ChR2–EYFP-positive cells in the ChR2 group of mice were also positive for endogenous c-Fos after optical stimulation, although not all c-Fos- positive cells expressed ChR2–EYFP. Very few neurons expressing EYFP in the EYFP group of mice were c-Fos positive (Fig. 2i–k and i *** Supplementary Fig. 3). The proportion of c-Fos-positive cells in the g ijk 100 downstream CA3 region was greater in the ChR2 group compared with 50 the EYFP group after optical stimulation of DG neurons, and this

0 number was comparable to the proportion of CA3 c-Fos-positive cells c-Fos-positive (%) ChR2 EYFP obtained by exposing a separate group of mice to the conditioned h l m n 5 Latency (ms) 100.0 1 1 = 10 *** 0.8 0.8 4 context after FC (Supplementary Fig. 4). 0.6 0.6 3 Next, we tested whether activating a population of DG neurons 98.0 0.4 0.4 2 0.2 Probability 0.2 1 labelled by ChR2–EYFP during the encoding of a fear memory was 0 0 0 8.0 *** *** 30 sufficient for memory recall. The experimental group (Exp) consisted *** N.S. * 20 of c-fos-tTA mice unilaterally injected with AAV9-TRE-ChR2-EYFP 6.0 10

*** Sweep no. Spike probability and implanted with an optical fibre targeting the DG (Fig. 1a). Mice 0 Peak latency 4.0 –50 –40 –30 –20 –10 0 10 20 30 40 50 were kept on Dox and underwent 5 days of habituation to record their *** n Time (ms) Spike probability 2.0 1 basal level of freezing in one context (context A) during both light-off

Percentage ChR2+ cells of DAPI+ and light-on epochs. Next, they were taken off Dox and underwent FC 0.0 0.5 in a distinct chamber (context B) in which a tone was paired with FC NS Spike probability 0 30 shock. The mice were then subjected to 5 days of testing with light- On Dox Seizure 20 off and light-on epochs in context A while on Dox (Fig. 1c). During the Home cage 10 Sweep no. 5 days post-FC 0 habituation sessions, the Exp mice showed very little freezing during

1 month post-FC –0.5 010.5 Time (s) either light-off or light-on epochs. In contrast, after FC, freezing levels Figure 2 | Activity-dependent expression and stimulation of ChR2–EYFP. during light-on epochs were higher compared with light-off epochs, a–g, Representative images of the DG from c-fos-tTA mice injected with AAV9- which indicated light-induced fear memory recall (Fig. 3a). Increased TRE-ChR2-EYFP and killed after the following treatments: on Dox (a); off Dox freezing during light-on epochs was observed over all 5 days of test for 2 days in home cage (b); same as b followed by FC (c); same as c except no sessions with no discernible day-dependent difference (Supplemen- shock was delivered (NS; d); same as c, 5 days after training (e); same as c,30 tary Fig. 5g). These data suggest that DG cells that express endogenous days after training (f); same as b followed by kainic acid injection to induce c-Fos during training, and therefore become labelled by ChR2–EYFP, seizure (g). Residual green signal in a and f is from nuclear-localized c-fos- define an active neural population that is sufficient for memory recall shEGFP (see Fig. 1 legend). h, Percentage of ChR2–EYFP-positive cells after upon subsequent reactivation. various treatments represented by a–g (n 5 5 subjects each; F6,28 5 94.43, *P , 0.05; ***P , 0.001). N.S., not significant. i, j, Representative DG cells after To rule out the possibility that post-training freezing by optical light stimulation in c-fos-tTA mice injected withAAV9-TRE-ChR2-EYFP (i)or stimulation was due to the activation of DG cells unrelated to fear AAV9-TRE-EYFP (j). k, Percentage of c-Fos-positive cells among ChR2– learning, we injected another group of mice (NS) with AAV9-TRE- EYFP-positive cells or EYFP-positive cells after light stimulation (n 5 3 subjects ChR2-EYFP and administered the same habituation, training, and test each; ***P , 0.001). l, Light-evoked single unit activity of a DG neuron from a sessions as the Exp group, except that no shock was delivered during c-fos-tTA mouse injected with AAV9-TRE-ChR2-EYFP. Peri-event histogram the training session. Despite the fact that a similar level of ChR2–EYFP (top) and raster plot (bottom) show reliable and precisely time-locked spiking expression was detected in the NS group compared with the Exp relative to the onset of 15 ms light pulses (blue bar). Inset shows an overlay of group, both in terms of proportion of cells labelled (Fig. 2h) and waveforms for all the spikes during light stimulation. m, Spike probability and peak latency for all the light-responsive cells (n 5 10) recorded as in l. n, Multi- ChR2–EYFP fluorescence intensity per cell (Supplementary Fig. 6), light did not induce post-training freezing in the NS group (Fig. 3b). unit activity in the DG from a c-fos-tTA mouse injected with AAV9-TRE- ChR2-EYFP in response to trains of 10 light pulses (15 ms; blue bars) at 20 Hz. This indicates that the freezing observed in the Exp group requires Scale bar in a, 250 mm. Panels a–g are at 310 magnification and panels i, j are at optical activation of a specific subset of ChR2–EYFP-positive DG cells 380 magnification. Error bars show mean 6 s.e.m. that are associated with FC and that activating a population of DG cells

abc similar or distinct populations of DG cells, we took the mice off Dox 20 *** 20 20 Test *** 20 20 20 Habituation 15 15 N.S. 15 N.S. for 2 days and then exposed them to a novel context (context C, an 10 15 Exp 15 NS 10 15 EYFP 10 5 5 5 open field) to label the active DG cells with ChR2–EYFP. After being n n = 12 n = 12 = 12 0 0 0 10 Off On 10 Off On 10 Off On put back on Dox, the mice were fear-conditioned in a different context

Freezing (%) 5 5 5 (context B) and killed 1.5 h later (Fig. 4a). The expression of ChR2–

0 0 0 EYFP was used to identify cells previously activated in context C Off On Off On Off On Off On Off On Off On whereas endogenous c-Fos was used to identify cells recently activated 3 min 3 min 3 min 3 min d e f *** in context B. Immunohistochemical analyses revealed a chance level of 40 40 *** *** *** 40 overlap between ChR2–EYFP-positive and c-Fos-positive cells, sug- 40 *** 40 *** *** 30 Exp-Bi 30 * gesting that two independent DG cell populations were recruited for Exp-1day 20 20 n n = 6 30 30 = 5 10 30 10 the representation of the two distinct contexts (Fig. 4b–g). To test the 0 0 Off On Off On context specificity of light-induced recall of a fear memory, we sub- 20 *** 20 20 jected a new group of mice (an open field fear-conditioned group; OF-

Freezing (%) 10 FC) to habituation sessions in context A, followed by 2 days off Dox

10 10 and exposure to context C to label neurons active in context C with 0 ChR2–EYFP. Next, we put the mice back on Dox and performed FC in Exp-Bi Exp- Exp NS EYFP 1day context B (Fig. 4h). These mice were then placed back in context A and 0 0 Off On Off On Off On Off On tested for light-induced freezing. Light failed to evoke an increase in Figure 3 | Optical stimulation of engram-bearing cells induces post- freezing responses (Fig. 4i). Similarly low levels of freezing were training freezing. a, c-fos-tTA mice injected with AAV9-TRE-ChR2-EYFP observed in another group of mice (FC-OF) in which FC in context and trained with FC (Exp group) showed increased freezing during 3-min light- B while on Dox preceded exposure to context C while off Dox on epochs. Freezing for each epoch represents 5-day average (Supplementary (Supplementary Fig. 10). Together, these results indicate that light Fig. 5a, g). Freezing levels for the two light-off and light-on epochs are further reactivation of cells labelled in context C did not induce fear memory averaged in the inset (n 5 12, F1,22 5 37.98, ***P , 0.001). b, Mice trained similarly to the conditions in a but without foot shock (NS group) did not show recall associated with context B. increased light-induced freezing (n 5 12). N.S., not significant. c, Mice injected with AAV9-TRE-EYFP and trained with FC (EYFP group) did not show a increased light-induced freezing (n 5 12). d, Mice trained similarly to the Doxycycline No doxycycline Doxycycline bc conditions in a but kept off Dox for 1 day before FC training (Exp-1day group) Context C Context B showed greater freezing during test light-on epochs compared to Exp group Exposure FC (n 5 5, F1,8 5 38.26, ***P , 0.001). e, Mice trained similarly to the conditions in a but bilaterally injected with AAV9-TRE-ChR2-EYFP and implanted with optical fibres (Exp-Bi group) showed even higher levels of freezing during test 2 days 1 day 1 day light-on epochs (n 5 6, F1,10 5 85.14, ***P , 0.001). f, Summary of freezing d e levels of the five groups during test light-on epochs (F4,42 5 37.62, *P , 0.05; fg ***P , 0.001). Error bars show mean 6 s.e.m. 10 1.0 N.S 8 0.8 6 0.6 4 not associated with FC does not induce freezing. Yet another group of 0.4 2

DAPI+ cells 0.2 mice (EYFP) were injected with AAV9-TRE-EYFP and underwent 0 DAPI+ cells Percentage of Percentage Percentage of Percentage 0 identical habituation, training, and testing sessions as the Exp group. The proportion of cells expressing EYFP was comparable to that seen ChR2 c-Fos i in the Exp group expressing ChR2–EYFP (Supplementary Fig. 7). h Observed Expected 20 OF-FC 20 ChR2+c-Fos N.S However, the EYFP group did not show increased post-training freez- 15 Doxycycline No doxycycline Doxycycline 15 Test 10 ing (Fig. 3c). This result rules out the possibility that increased freezing Context A Context C Context B Context A Habituation 5 Habituation Exposure FC Testing 10 0 in the Exp group was due to any non-specific effects of post-training Off On optical stimulation. Freezing (%) 5 The light-induced freezing levels of the Exp group were relatively 5 days 2 day 1 day 1 day 5 daydaysys 0 low (,15%) compared with those typically reported from exposure to Off On Off On a conditioned context (,60%)3. One possibility is that light activation of background-activity-induced ChR2–EYFP (Fig. 2b) interfered with the expression of the specific fear memory. We confirmed that limiting Figure 4 | Labelling and stimulation of independent DG cell populations. the off-Dox period from 2 days to 1 day reduced the background a, c-fos-tTA mice injected with AAV9-TRE-ChR2-EYFP were taken off Dox expression of ChR2–EYFP by at least twofold (compare Sup- and exposed to context C to label activated cells with ChR2–EYFP (yellow), then put back on Dox and trained with FC in context B to activate endogenous plementary Fig. 8a home cage with Fig. 2h home cage). A group of c-Fos (red). b–e, Representative images of DG from these mice are shown. mice (Exp-1day) that went through the same design outlined in Fig. 1c b, ChR2–EYFP-labelled cells activated in context C. c, c-Fos-labelled cells but with this modification showed greater freezing levels (,25%) activated in context B. d, Nuclear marker DAPI. e, Merge. The white and red during the light-on epoch of test sessions compared to the Exp group circles show examples of ChR2–EYFP-positive and c-Fos-positive cells, (Fig. 3d, f). Another possible factor contributing to the modest light- respectively. The c-Fos-positive cells in e appear yellow because they express induced freezing in the Exp group may be the limited number of cells both endogenous c-Fos (red) and the nuclear-localized c-fos-shEGFP (green) optically stimulated. To test this possibility, we bilaterally injected a (see Fig. 1 legend). f, Percentage of ChR2–EYFP-positive, endogenous c-Fos- positive, and double-positive cells among total cells (DAPI1)(n 5 5). g,The group of mice (Exp-Bi) with AAV9-TRE-ChR2-EYFP and bilaterally implanted optical fibres targeting the DG, and then subjected these observed percentage of double-positive cells is the same as what would be mice to the same scheme as that shown in Fig. 1c. During the light-on expected if the two cell populations were independent (that is, a product of the observed percentage of ChR2–EYFP single-positive and c-Fos single-positive epochs of the test sessions, the Exp-Bi group exhibited levels of freezing cells). h, Behaviour setup for mice exposed to an open field in context C while (,35%) that were almost as high as those induced by the conditioned off Dox and subsequently fear-conditioned in context B while on Dox (OF-FC). context (Fig. 3e, f, Supplementary Fig. 9 and Supplementary Movies). i, OF-FC mice (n 5 5) do not show increased light-induced freezing. N.S., not We next examined whether the light-induced fear memory recall was significant. Panels b–e are at 380 magnification. Scale bar in b,10mm. Error context-specific. First, to test whether two different contexts activate bars show mean 6 s.e.m.

We have shown that optical activation of hippocampal cells that and extracellular electrical recordings in head-fixed, isoflurane-anaesthetized were active during FC elicits freezing behaviour. To our knowledge, mice. this is the first demonstration that directly activating a subset of cells Behavioural tests. Mice used for behavioural tests were injected with AAV9 virus and implanted with an optical fibre targeting the DG. All mice were habituated in involved in the formation of a memory is sufficient to induce the 21 behavioural expression of that memory. Our results and previous context A while on 40 mg kg Dox for 5 days for 12 min per day with light stimulation (473 nm, 20 Hz, 15 ms) during minutes 4–6 and 10–12. The groups studies that addressed the necessity of similarly sparse cell populations of mice were taken off Dox for 1 (Exp-1day) or 2 days (Exp, Exp-Bi, EYFP and NS) 5,6 in the amygdala argue that defined cell populations can form a and fear-conditioned in context B with a tone, with (Exp, Exp-1day, Exp-Bi and cellular basis for fear memory engrams. The memory engram that EYFP) or without (NS) shock. The OF-FC group was taken off Dox for 2 days and we selectively labelled and manipulated is probably contextual in exposed to context C without shock, then fear-conditioned in context B while on nature, as previous studies have demonstrated that hippocampal inter- Dox. The FC-OF group was fear-conditioned in context B while on Dox, then ventions affect conditioned freezing responses to a context but not a taken off Dox for 2 days and exposed to context C without shock. All groups were tone12,13,24. Indeed, recent findings show that optogenetic inhibition of put back on Dox and tested in context A for 5 days in a manner similar to that used the hippocampal CA1 region during training or testing inhibited the in the habituation sessions. All groups except the NS group were then put back to recall of a contextual fear memory, while leaving auditory-cued fear context B for a contextual fear probe trial 1 day after the last light stimulation, 25 followed by a cued tone probe trial in context D the next day. Freezing levels were memory recall intact . However, we cannot completely rule out the scored by experimenters blind to all treatment conditions. possibility that the fear memory recalled in our experiments may have some tone memory component. Full Methods and any associated references are available in the online version of Our observation that freezing responses were elicited by optical the paper at www.nature.com/nature. stimulation in the experimental groups (Exp, Exp-1day and Exp-Bi), Received 1 November 2011; accepted 15 March 2012. but not in the OF-FC or FC-OF group, strongly supports a dual Published online 22 March 2012. memory engram hypothesis of contextual FC26–28. In this hypothesis, hippocampal cells are recruited to form contextual memory engrams, 1. Josselyn, S. A. Continuing the search for the engram: examining the mechanism of but these contextual engrams alone do not represent a complete fear fear memories. J. Psychiatry Neurosci. 35, 221–228 (2010). 2. Silva, A. J. et al. Molecular and cellular approaches to memory allocation in neural memory. For a fear memory to be formed, the information from the circuits. Science 326, 391–395 (2009). contextual memory engram must be transferred to the basolateral 3. 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Science 334, 1669–1675 (2011). in one region may not necessarily block the expression of the fear 15. Treves, A. & Rolls, E. T. Computational analysis of the role of the hippocampus in memory. For instance, disruption of contextual memory engrams in memory. Hippocampus 4, 374–391 (1994). the DG could be circumvented by CA1 engrams, which could be 16. McHugh, T. J. et al. Dentate gyrus NMDA receptors mediate rapid pattern generated through the direct input from the entorhinal cortex and separation in the hippocampal network. Science 317, 94–99 (2007). 17. Nakashiba, T. et al. Young dentate granule cells mediate pattern separation may be sufficient to activate the fear memory engram in the BLA. whereas old granule cells facilitate pattern completion. Cell doi:10.1016/ Indeed, we recently generated a mouse mutant, which permitted us j.cell.2012.01.046 (23 February 2012). to demonstrate that the DG input to the CA3 is dispensable in the 18. Schmidt, B., Marrone, D. F. & Markus, E. J. 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Diverse strategies for tetracycline-regulated inducible gene expression. Proc. Natl Acad. Sci. USA 93, 5173–5176 (1996). Virus-mediated gene expression. The pAAV-TRE-ChR2-EYFP and pAAV- 23. Leutgeb, J. K., Leutgeb, S., Moser, M. B. & Moser, E. I. Pattern separation in the TRE-EYFP plasmids were constructed by standard methods and packed as dentate gyrus and CA3 of the hippocampus. Science 315, 961–966 (2007). AAV9 viruses. The viruses were stereotaxically injected into the DG (0.15 ml). 24. Lee, I. & Kesner, R. P. Differential contributions of dorsal hippocampal subregions Immunohistochemistry. Mice were killed after various treatments and brain to memory acquisition and retrieval in contextual fear-conditioning. Hippocampus slices were prepared for immunohistochemistry and confocal microscopy. 14, 301–310 (2004). Coronal sections were immunostained for EYFP and/or c-Fos. All imaging and 25. Goshen, I. et al. Dynamics of retrieval strategies for remote memories. 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27. Schafe, G. E., Doyere, V. & LeDoux, J. E. Tracking the fear engram: the lateral Author Contributions X.L., S.R., A.G. and S.T. contributed to the study design. X.L., S.R. amygdala is an essential locus of fear memory storage. J. Neurosci. 25, and P.T.P. contributed to the data collection and interpretation. X.L. cloned all 10010–10014 (2005). constructs. X.L. and S.R. conducted the surgeries and the behaviour experiments. S.R. 28. Rogan, M. T., Staubli, U. V. & LeDoux, J. E. Fear conditioning induces associative conducted the expression timeline experiments. P.T.P. conducted the long-term potentiation in the amygdala. Nature 390, 604–607 (1997). electrophysiology experiments. C.B.P. contributed to the setup of the electrophysiology apparatus and wrote the Matlab software to analyse the data. K.D. provided the original Supplementary Information is linked to the online version of the paper at ChR2 construct. X.L., S.R. and S.T. wrote the paper. All authors discussed and www.nature.com/nature. commented on the manuscript. Acknowledgements We thank S. Huang, G. Lin, M. Ragion and X. Zhou for help with the Author Information Reprints and permissions information is available at experiments, T. Ryan, A. Rivest, J. Young, R. Redondo and G. Dragoi for comments and www.nature.com/reprints. The authors declare no competing financial interests. discussions on the manuscript, and all the members of the Tonegawa laboratory for Readers are welcome to comment on the online version of this article at their support. This work is supported by National Institutes of Health grants www.nature.com/nature. Correspondence and requests for materials should be R01-MH078821, P50-MH58880 to S.T. and RIKEN Brain Science Institute. addressed to S.T. ([email protected]).

METHODS every 5–10 mm throughout the DG. After light responsive cells were detected, two Subjects. The c-fos-tTA mice were generated from TetTag mice by breeding them types of light stimuli were tested: 15 ms light pulse every 10 s and a train of ten with C57BL/6J mice and selecting those carrying only the c-fos-tTA transgene and 15 ms light pulses at 20 Hz every 10 s. Unit activity was band-pass filtered (500 Hz– not the bi-cistronic tetO promoter driving tau-LacZ and tTAH100Y transgenes. 5 KHz) and acquired with an Axon Digidata 1440A acquisition system running These mice also contained a separate transgene consisting of a c-fos promoter Clampex 10.2 software. Data were analysed with custom software written in driving the expression of nuclear-localized 2-h half-life EGFP (shEGFP), which Matlab. After the recording, endogenous c-Fos expression was induced by deliver- is distinct from the whole-cell-localized ChR2–EYFP. Mice had food and water ing two epochs of 3-min light stimulation (9 mW, 20 Hz, 15 ms), separated by ad libitum and were socially housed until the beginning of the surgery. The mice 3 min, to the DG, the same as in behavioural experiments (see below). Mice were were 8–12 weeks old at the time of surgery and had been raised on food containing killed and perfused 90 min later. 40 mg kg21 Dox for 4 weeks before surgery. Mice were single housed post-surgery Immunohistochemistry. Mice were overdosed with avertin and perfused trans- and throughout the rest of the experiments. All procedures relating to mouse care cardially with cold PBS, followed by 4% paraformaldehyde (PFA) in PBS. Brains and treatment conformed to the institutional and National Institutes of Health were extracted from the skulls and kept in 4% PFA at 4 uC overnight. Fifty- guidelines. micrometre coronal slices were taken using a vibrotome and collected in cold Virus construct and packaging. The pAAV-TRE-ChR2-EYFP plasmid was con- PBS. For immunostaining, each slice was placed in PBST (PBS 1 0.2% Triton structed by cloning TRE-ChR2-EYFP into an AAV backbone using the SpeI X-100) with 5% normal goat serum for 1 h and then incubated with primary restriction site at the 59 terminus and the blunt end at the 39 terminus of the insert. antibody at 4 uC for 24 h (rabbit anti-c-Fos 1:5,000, Calbiochem; rabbit anti- The pAAV-TRE-EYFP plasmid was constructed by removing the ChR2 fragment GABA 1:5,000, Abcam; chicken anti-GFP 1:500, Invitrogen). Slices then from the pAAV-TRE-ChR2-EYFP plasmid using NheI and AgeI restriction sites, underwent three wash steps for 10 min each in PBST, followed by 1 h incubation blunting with T4 DNA polymerase, and self-ligation of the vector, which retained with secondary antibody (1:200 AlexaFlour488 anti-chicken, Invitrogen; 1:200 the ATG start codon of the EYFP gene from the ChR2-EYFP fusion gene. The AlexFlour568 anti-rabbit, Invitrogen). Slices were then incubated for 15 min with DAPI (1:10,000) and underwent three more wash steps of 10 min each in PBST, recombinant AAV vectors were serotyped with AAV9 coat proteins and packaged by the Gene Therapy Center and Vector Core at the University of Massachusetts followed by mounting and coverslipping on microscope slides. 13 21 Cell counting. To characterize the expression timeline of ChR2–EYFP and EYFP, Medical School. Viral titres were 1 3 10 genome copy ml for AAV9-TRE- 13 21 the number of EYFP immunoreactive neurons in the DG were counted from six ChR2-EYFP and 1.5 3 10 genome copy ml for AAV9-TRE-EYFP. Stereotactic injection and optical fibre implant. All surgeries were performed coronal slices (spaced 120 mm from each other) per mouse (n 5 5 for ChR2 group, under stereotaxic guidance. Mice were anaesthetized using 500 mg kg21 avertin. n 5 3 for EYFP group). Coronal slices were taken from dorsal hippocampus The virus was injected using a glass micropipette attached to a 10 ml Hamilton centred on coordinates covered by our optical fibre implants (21.94 mm to microsyringe (701LT; Hamilton) through a microelectrode holder (MPH6S; WPI) 22.46 mm AP; Supplementary Fig. 11). Confocal fluorescence images were filled with mineral oil. A microsyringe pump (UMP3; WPI) and its controller acquired on a Leica TCS SP2 AOBS scanning laser microscope using a 320/ (Micro4; WPI) were used to control the speed of the injection. The needle was 0.70 NA oil immersion objective. The image analysis module Visiomorph DP slowly lowered to the target site and remained for 10 min before the beginning of within VIS (Visiopharm) calculated the number of ChR2–EYFP-positive or the injection. Mice for timeline studies and head-fixed electrophysiology recordings EYFP-positive cells per section by thresholding EYFP immunoreactivity above were injected bilaterally (22.2 mm anterioposterior (AP); 6 1.3 mm mediolateral background levels and using DAPI staining to distinguish between nuclei. The 29 (ML); –2.0 mm dorsoventral (DV) ) with 0.15 mlAAV9 virus at a rate of 0.1 ml analysis module also permitted isolation of only ChR2–EYFP-positive and EYFP- min21. After the injection the needle stayed for five additional minutes before it was positive neurons by setting size and fluorescence thresholds to filter out nuclear- slowly withdrawn. The mice used for behaviour tests were unilaterally or bilaterally localized c-fos-shEGFP-positive cells. The cell body layer of DG granule cells was injected with the virus same as described above. After withdrawing of the needle, a outlined as a region of interest (ROI) according to the DAPI signal in each slice. A Doric patchcord optical fibre (200 mm core diameter; Doric Lenses) precisely cut to similar protocol was followed for c-Fos-positive cell counts in DG and CA3, except the optimal length was lowered above the injection site (–2.2 mm AP; 6 1.3 mm a Cy3 filter was applied for the latter. For quantification comparisons, we used a ML; –1.6 mm DV). Three jewelry screws were screwed into the skull surrounding one-way ANOVA followed by Tukey’s multiple comparisons using a 5 0.05. Data the implant site of each hemisphere to provide extra anchor points. A layer of were analysed using Microsoft Excel with the Statplus plug-in and Prism adhesive cement (C&B Metabond) was applied followed with dental cement (GraphPad Software). (Teets cold cure; A-M Systems) to secure the optical fibre implant. A cap made To analyse the overlap between c-Fos and ChR2–EYFP-expressing or EYFP- from the bottom part of a 15 ml Falcon tube (for unilateral implant) or the top part expressing cells, a z-stack method was used in conjunction with ImageJ30 to mont- of an Eppendorf tube (for bilateral implant) was inserted to protect the implant and age ten optical stacks (1 mm each, step size 10 mm) taken under a 320/0.70 NA oil the incision was closed with sutures. Mice were given 1.5 mg kg21 metacam as immersive objective. Separate GFP and Cy3 filtered images were digitally com- analgesic and remained on a heating pad until fully recovered from anaesthesia. bined to produce composite images. Equal cutoff thresholds were applied to all Mice were allowed to recover for 2 weeks before all subsequent experiments. All captures to remove background autoflouresence. All imaging and analyses were fibre placements (Supplementary Fig. 11) and viral injection sites were verified performed blind to the experimental conditions. To quantify the expression levels histologically. As criteria we only included mice with ChR2–EYFP expression of ChR2–EYFP per cell, an experimenter blind to each condition used ImageJ to limited to the DG, which led to the exclusion of two mice throughout the study. calculate the fluorescence intensity signal as integrated density for ten randomly ChR2–EYFP and EYFP expression timeline. Fourteen days after surgery, sub- chosen DG cells per hippocampal slice (n 5 3 slices per mouse, 5 mice per con- jects were either kept on Dox and immediately killed or taken off Dox for 1 or 2 days. dition; Supplementary Fig. 6). The mice from the latter two groups were either killed with no further treatments Behaviour assays. All the behaviour tests were conducted during the light cycle of (home cage),or underwent FC or NSprotocols as described in the behaviour section the day. Four different contexts were used in the behaviour assays. Context A was a below. After each treatment, mice were killed 1.5 h, 24 h, 5 days or 30 days later, as 30 3 25 3 33 cm conditioning chamber within a room with black walls, black described in the main text, and underwent immunohistochemistry procedures. curtains, and dim lighting. The chamber had a white plastic floor and was scented For seizure experiments, mice were taken off Dox for 2 days and injected intra- with 0.25% benzaldehyde. Context B was a 29 3 25 3 22 cm conditioning chamber peritoneally with 20 mg kg21 kainic acid. The mice were killed 6 h after the first within a second room with white walls and bright lighting. The chamber had a behavioural onset of seizure. gridded floor and a triangular roof, and was scented with 1% acetic acid. Context C In vivo recording. Mice were anaesthetized by isoflurane inhalation and placed in was a 41 3 41 3 31 cm unscented open field arena within a third room with white the stereotactic system with anaesthesia maintained with 0.5–1% isoflurane walls and intermediate lighting. Context D was a 29 3 25 3 22 cm conditioning throughout the recording. An optrode consisting of a tungsten electrode (1 MV) chamber in the same room as context C. It had a white acrylic glass floor and was glued to an optical fibre (200 mm core diameter; Doric Lenses), with the tip of the unscented. The experimental groups (Exp, Exp-1day and Exp-Bi) and EYFP electrode extending beyond the tip of the fibre by 500 mm was used for simultan- control (EYFP) groups underwent exactly the same training protocol. During eous optical stimulation and extracellular recordings. The optrode was lowered to the habituation session, each mouse was introduced to context A daily for 5 days the dentate gyrus (22.2 mm AP; 1.3 mm ML; 22.0 mm DV) using a hydraulic while on 40 mg kg21 Dox food. Each day the mouse was loaded into the chamber micromanipulator (Model 640; David Kopf Instruments). The optical fibre was and the optical fibre implant was connected to a 473 nm laser (MBL F473; Opto connected to a 200 mW 473 nm laser (MBL F473; Opto Engine) and controlled by Engine) controlled by a function generator (33220A; Agilent Technologies). The a function generator (33220A; Agilent Technologies). The power intensity of light mouse was then allowed to explore the chamber for 12 min. The 12 min session emitted from the optrode was calibrated to about 9 mW, which was consistent with was divided into four 3-min epochs, with the first and third epochs as the light-off the power intensity used in the behavioural assays. To identify ChR2-labelled cells, epochs, and the second and fourth epochs as the light-on epochs. During the light- light pulses of 15 ms were delivered at 0.1 Hz at the recording sites approximately on epochs, the mouse received light stimulation (9 mW, 20 Hz, 15 ms) for the

©2012 Macmillan Publishers Limited. All rights reserved LETTER RESEARCH entire 3-min duration. At the end of the 12 min, the mouse was immediately same habituation sessions. The day after the fifth habituation, the mouse was kept detached from the laser and returned to its home cage. Following the fifth habitu- on 40 mg kg21 Dox food and went through the FC procedure in context B as ation session, the mouse was kept on regular food without Dox for 1 (Exp-1day) or described above. The mouse was placed off Dox for 2 days after FC. Then the mouse 2 (Exp, Exp-Bi and EYFP) days until the training session. On the training day the was exposed to the open field arena in context C and allowed to freely explore for mice received three training trials separated by 3 h in their home cages. For each 10 min, after which the mouse was returned to their home cage with 1 g kg21 Dox training trial, the mouse was kept in the conditioning chamber in context B for food overnight, followed by test sessions over 5 days in context A on 40 mg kg21 500 s. A tone (20 s, 75 dB, 2,000 Hz) was turned on at 180 s, 260 s, 340 s and 420 s, Dox food. Freezing behaviour for training, context, and tone probe trials was each of which co-terminated with a foot shock (2 s, 0.75 mA). After the third recorded with a digital camera and measured with FreezeFrame software training trial, the mouse was returned to its home cage and placed on food contain- (ActiMetrics). Light stimulation during the habituation and test sessions interfered 21 ing 1 g kg Dox overnight to rapidly turn off any additional ChR2–EYFP or EYFP with the motion detection of the program, and thus the freezing of these sessions expression. The test session started the next day and the mouse was switched back was manually scored. Two experimenters scored each video independently in a 21 to food containing 40 mg kg Dox. The procedure for the 5-day test session was double-blinded manner. The overall scores showed a ,3% difference between the exactly the same as the habituation session in context A. The day after the last test two experimenters and for simplicity only one set of scores from one experimenter session, the mouse was returned to the original context B and exposed to the was reported.The manual scoring and computer scoring of the same training videos chamber for 300 s for a retrieval session to assay contextual fear memory. The next gave similar freezing scores. For each group, within each session (habituation and day, the mouse was introduced to context D for cued fear memory retrieval. This test) and within each epoch (light-on and light-off), a one-way ANOVA with session lasted for 780 s, with a tone (60 s, 75 dB, 2,000 Hz) turned on at 180 s, 420 s repeated measures followed by Tukey’s multiple comparisons (a 5 0.05) revealed and 660 s. The no shock (NS) group went through the same habituation, training no difference over 5 days (Supplementary Fig. 5). We therefore averaged the freez- and test sessions as the Exp group, except that no foot shock was given during the ing level over 5 days for each mouse. A two-way ANOVA with repeated measures training session. The open field fear-conditioned (OF-FC) group went through the followed by Tukey’s multiple comparisons (a 5 0.05) revealed that only the experi- same habituation sessions. After the fifth habituation session, Dox was removed mental groups (Exp, Exp-1day and Exp-Bi) showed increases in averaged freezing from the mouse’s diet for 2 days, followed by exposure to the open field arena in levels for light-on epochs of test sessions compared to light-off epochs of test context C to allow for 10 min of active exploration. The mouse was subsequently sessions and light-on epochs of habituation sessions (Fig. 3a, d, e). returned to its home cage and placed on 1 g kg21 Dox food overnight. The following day, the mouse was fear-conditioned in context B in the same manner as described 21 29. Paxinos, G. & Franklin, K. The Mouse Brain in Stereotaxic Coordinates (Academic, above. Test sessions were administered over 5 days in context A on 40 mg kg Dox 2001). food, and the OF-FC group also underwent context and tone probe trials after the 5 30. Rasband, W. S. Image J. http://imagej.nih.gov/ij/ (National Institutes of Health, days of testing. The fear-conditioned open field (FC-OF) group went through the 1997–2011).

In colony allorecognition assays, three of four the other colony’s genome or may produce a chi- 20. L. J. Dishaw, G. W. Litman, Curr. Biol. 19, R286 isogenic pairs receiving control morpholinos fused meric colony with mixed genotypes. To date, induc- (2009). 21. D. S. Stoner, I. L. Weissman, Proc. Natl. Acad. Sci. U.S.A. within 24 hours of ampullae contact. By contrast, tion of chimerism using hematopoietic stem-cell 93, 15254 (1996). no reactions were observed in isogenic pairs re- transplantation is the only way to achieve long-term 22. D. S. Stoner, B. Rinkevich, I. L. Weissman, Proc. Natl. ceiving BHF translation-blocking morpholinos donor-specific tolerance to human organ allografts Acad. Sci. U.S.A. 96, 9148 (1999). (n = 6), despite constant physical contact over (25). Chimerism can be short-lived, and if lost, the 23. D. J. Laird, A. W. De Tomaso, I. L. Weissman, Cell 123, B. schlosseri 1351 (2005). observational periods ranging from 2 to 7 days threat of allograft rejection emerges. 24. A. Voskoboynik et al., Cell Stem Cell 3, 456 (2008). (Fig. 3D, fig. S19, and table S8). To exclude is a unique species for studying stem cell–mediated 25. D. H. Sachs, M. Sykes, T. Kawai, A. B. Cosimi, Semin. nonspecific effects, we also tested BHF splice- chimerism, and such research will be facilitated Immunol. 23, 165 (2011). inhibiting morpholinos, using the progeny of by BHF. wild-type colonies (15). Within 2 days of ampul- Acknowledgments: We thank B. Rinkevich for pointing out the difficulty with the original cFuHC assignments and n References and Notes lae contact, all control pairs had fused ( =2)or T. Snyder, J. Okamoto, L. Me, L. Ooi, A. Dominguez, C. Lowe, 1. A. Nakashima, T. Shima, K. Inada, M. Ito, S. Saito, rejected (n = 1), whereas colony pairs receiving K. Uhlinger, L. Crowder, S. Karten, C. Patton, L. Jerabek, Am. J. Reprod. Immunol. 67, 304 (2012). n and T. Storm for invaluable technical advice and help. splice-inhibiting morpholinos did not react ( =5) 2. G. Girardi, Z. Prohászka, R. Bulla, F. Tedesco, S. Scherjon, A. De Tomaso provided the fosmid sequence used to (figs. S20 and S21, table S9, and movies S1 and Mol. Immunol. 48, 1621 (2011). characterize cFuHC (12) (table S5). D.P., A.V., and S.R.Q. have 3. M. Colonna, S. Jonjic, C. Watzl, Nat. Immunol. 12, 107 S2). These data support our genomic analysis and filed U.S. and international patent applications (61/532,882 (2011). “ indicate that BHF participates in fusion and re- 4. D. F. LaRosa, A. H. Rahman, L. A. Turka, J. Immunol. 178, and 13/608,778, respectively) entitled Methods for obtaining ” jection initiation. 7503 (2007). a sequence. This invention allows for the sequencing of In the jawed vertebrates, the MHC is a haplo- 5. F. Delsuc, H. Brinkmann, D. Chourrout, H. Philippe, long continuous (kilobase scale) nucleic acid fragments using conventional short read–sequencing technologies, useful type, each sublocus of which specifies a different Nature 439, 965 (2006). 6. H. Oka, H. Watanabe, Proc. Jpn. Acad. 33, 657 (1957). for consensus sequencing and haplotype determination. This recognition process, usually by unique subsets of 7. H. Oka, H. Watanabe, Bull. Mar. Biol. Stat. Asamushi. 10, study was supported by NIH grants 1R56AI089968, cells (18–20). By contrast, the B. schlosseri Fu/HC 153 (1960). R01GM100315, and 1R01AG037968 awarded to I.L.W., A.V., locusisasinglegene(BHF) embedded in a hap- 8. A. Sabbadin, Rend. Accad. Naz. Lincei. Ser. 32, 1031 and S.R.Q., respectively, and the Virginia and D. K. Ludwig lotype of several genes with high polymorphism. (1962). Fund for Cancer Research awarded to I.L.W. D.S. was supported 9. V.L.Scofield,J.M.Schlumpberger,L.A.West,I.L.Weissman, by NIH grant K99CA151673-01A1 and Department of Defense Unlike the secreted (sFuHC) and membrane- Grant W81XWH-10-1-0500, and A.M.N., D.M.C., D.S., and I.K.D. mFuHC BHF Nature 295, 499 (1982). bound ( )genes, has none of the do- 10. A. W. De Tomaso, Y. Saito, K. J. Ishizuka, K. J. Palmeri, were supported by a grant from the Siebel Stem Cell Institute mains expected for a cell surface–recognition I. L. Weissman, Genetics 149, 277 (1998). and the Thomas and Stacey Siebel Foundation. The data in this protein or, in fact, domains that are conserved 11. A. W. De Tomaso, I. L. Weissman, Immunogenetics 55, paper are tabulated in the main manuscript and in the supplementary materials. BHF, sFuHC, and mFuHC sequences throughout protein evolution. Because BHF 480 (2003). 12. A. W. De Tomaso et al., Nature 438, 454 (2005). are available in GenBank under accession numbers does not follow biological precedence by either 13. A. Voskoboynik et al., eLife 2, e00569 (2013). KF017887-KF017889, and the RNA-Seq data are available sequence or domains, future investigations of 14. I. Letunic, T. Doerks, P. Bork, SMART 7: recent updates to on the Sequence Read Archive (SRA) database: BioProject this gene will likely reveal new mechanisms of the protein domain annotation resource. Nucleic Acids SRP022042. recognition. Res. 40, D302 and (2012). 15. Materials and methods are available as supplementary Supplementary Materials www.sciencemag.org/cgi/content/full/341/6144/384/DC1 The ability to reliably predict histocompati- materials on Science Online. Materials and Methods bility outcomes on the basis of a single gene has 16. B. Rinkevich, J. Douek, C. Rabinowitz, G. Paz, Dev. Comp. Figs. S1 to S21 broad implications for the study of allorecogni- Immunol. 36, 718 (2012). 17. M. Oren, J. Douek, Z. Fishelson, B. Rinkevich, Dev. Comp. Tables S1 to S9 tion. For example, after vasculature fusion, stem References (26–42) Immunol. 31, 889 (2007). B. schlosseri Movies S1 and S2 cells from each colony compete to 18. The MHC sequencing consortium, Nature 401, 921 (1999). overtake germline and/or somatic lineages (21–24). 19. M. Hirano, S. Das, P. Guo, M. D. Cooper, Adv. Immunol. 19 March 2013; accepted 30 May 2013 Stem cell competition may lead to elimination of 109, 125 (2011). 10.1126/science.1238036

whether these internal representations can be com- Creating a False Memory bined with external stimuli to generate new memories has not been vigorously studied. in the Hippocampus Damage to the hippocampus impairs episodic memory (3–8). Recently, using fear conditioning Steve Ramirez,1* Xu Liu,1,2* Pei-Ann Lin,1 Junghyup Suh,1 Michele Pignatelli,1 in mice as a model of episodic memory, we iden- Roger L. Redondo,1,2 Tomás J. Ryan,1,2 Susumu Tonegawa1,2† tified a small subpopulation of granule cells in the dentate gyrus (DG) of the hippocampus as Memories can be unreliable. We created a false memory in mice by optogenetically manipulating contextual memory-engram cells. Optogenetic memory engram–bearing cells in the hippocampus. Dentate gyrus (DG) or CA1 neurons activated stimulation of these cells is sufficient to activate by exposure to a particular context were labeled with channelrhodopsin-2. These neurons were behavioral recall of a context-dependent fear mem- later optically reactivated during fear conditioning in a different context. The DG experimental ory formed by a delivery of foot shocks. This group showed increased freezing in the original context, in which a foot shock was never delivered. finding provided an opportunity to investigate how The recall of this false memory was context-specific, activated similar downstream regions engaged the internal representation of a specific context can during natural fear memory recall, and was also capable of driving an active fear response. be associated with external stimuli of high valence. Our data demonstrate that it is possible to generate an internally represented and behaviorally In particular, a hypothesis of great interest is expressed fear memory via artificial means. 1RIKEN–Massachusetts Institute of Technology (MIT) Center for euroscience aims to explain how brain see how various cognitive processes are affected. Neural Circuit Genetics at the Picower Institute for Learning and Memory, Department of Biology and Department of Brain and activity drives cognition. Doing so requires More specifically, humans have a rich repertoire Cognitive Sciences, MIT, Cambridge, MA 02139, USA. 2Howard Nidentification of the brain regions that are of mental representations generated internally by HughesMedicalInstitute,MIT,Cambridge,MA02139,USA. specifically involved in producing internal men- processes such as conscious or unconscious re- *These authors contributed equally to this work. tal representations and perturbing their activity to call, dreaming, and imagination (1, 2). However, †Corresponding author. E-mail: [email protected]

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whether artificially activating a previously formed F). Furthermore, optical stimulation of ChR2- half of the animals were exposed to context C, and contextual memory engram while simultaneously mCherry–expressing DG cells induced cFos ex- the other half were reexposed to context A as a delivering foot shocks can result in the creation of pression throughout the anterior-posterior axis of control. Both groups were euthanized 1.5 hours a false fear memory for the context in which foot the DG (fig. S1, A to I). later. DG cells activated by the first exposure to shocks were never delivered. To address this, we We first took virus-infected and fiber-implanted context A were identified by ChR2-mCherry ex- investigated whether a light-activated contextual animals off Dox to open a time window for la- pression, and cells activated by the exposure to con- memory in the DG or CA1 can serve as a functional beling cells activated by the exploration of a novel text C or the reexposure to context Awere identified conditioned stimulus (CS) in fear conditioning. context (context A) with ChR2-mCherry. The by the expression of endogenous c-Fos. The c-Fos Our system uses c-fos-tTA transgenic mice, animals were then put back on Dox to prevent any generated by the first exposure to context A had in which the promoter of the c-fos gene drives the further labeling. The next day, we fear-conditioned been degraded by the time the animals underwent expression of the tetracycline transactivator (tTA) this group in a distinct context (context B) while their second context exposure (11). Contexts A to induce expression of a gene of interest down- optically reactivating the cells labeled in context A. and C recruited statistically independent popula- stream of the tetracycline-responsive element (TRE) On the following 2 days, we tested the animals’ tions of DG cells. In contrast, two exposures to (8–12). We injected an adeno-associated virus fear memory in either the original context A or a context A recruited substantially overlapping cell (AAV) encoding TRE-ChR2-mCherry into the novel context C (Fig. 1G). If the light-reactivated populations in the dorsal DG (Fig. 2, A to E). DG or CA1 of c-fos-tTA animals (Fig. 1A). cells labeled in context A can produce a function- When DG cells activated by the exposure to Channelrhodopsin-2 (ChR2)–mCherry expres- al CS during fear conditioning in context B, then context A were reactivated with light during fear sion was completely absent in the DG of animals the animals should express a false fear memory conditioning in a distinct context B, the animals sub- that had been raised with doxycycline (Dox) in by freezing in context A, but not in context C. sequently froze in context A at levels significantly the diet (on Dox) (Fig. 1B). Exploration of a novel First, we examined the degree of overlap of higher than the background levels, whereas freezing context under the condition of Dox withdrawal the cell populations activated in contexts A and C in context C did not differ from background lev- (off Dox) elicited an increase in ChR2-mCherry (8, 11). We injected a group of c-fos-tTA mice els (Fig. 2F). This increased freezing in context A expression (Fig. 1C). We confirmed the func- with an AAV virus encoding TRE-ChR2-mCherry was not due to generalization, because a control tionality of the expressed ChR2-mCherry by and exposed them to context A while off Dox so group expressing only mCherry that underwent the recording light-induced spikes in cells expressing as to label activated DG cells with ChR2-mCherry. exact same training protocol did not show the same ChR2-mCherry from both acute hippocampal These animals were then immediately placed back effect (Fig. 2F). A separate group of animals express- slices and in anaesthetized animals (Fig. 1, D to on Dox to prevent further labeling. The next day, ing ChR2–enhanced yellow fluorescent protein

Fig. 1. Activity-dependent labeling and light- activation of hippocampal neurons, and the basic experimental scheme. (A) The c-fos-tTA mice were bilaterally injected with AAV9-TRE-ChR2-mCherry and implanted with optical fibers targeting DG. (B)Whileon Dox, exploration of a novel context did not induce expression of ChR2-mCherry. (C) While off Dox, exploration of a novel context induced expression of ChR2-mCherry in DG. (D) Light pulses induced spikes in a CA1 neuron expressing ChR2-mCherry. The recorded neuron is shown labeled with biocytin in (E). (F) Light pulses induced spikes in DG neurons recorded from a head-fixed anesthetized c-fos-tTA animal expressing ChR2-mCherry. (G)Basicex- perimental scheme. Post-surgery mice were taken off Dox and allowed to explore context A in order to let DG or CA1 cells become labeled with ChR2-mCherry. Mice were put back on Dox and fear conditioned in context B with simultaneous delivery of light pulses. Freezing levels were then measured in both the original context A and a novel context C. The light green shading indicates the presence of Dox in the diet during corresponding stages of the scheme. Prime indicates the second exposure to a given context. The yellow lightning symbol and blue shower symbol indicate foot shocks and blue light delivery, respectively. Red circles represent neurons encoding context A that are thus labeled with ChR2-mCherry. Gray and white circles represent neurons encoding context B and C, respectively. Asterisks indicate neurons activated either by exposure to context or light stimulation.

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(EYFP) instead of ChR2-mCherry in the DG that experiments as above. These animals showed The simultaneous availability of two CSs can underwent the same behavioral schedule also showed freezing in context C but not context A (fig. S2B). sometimes result in competitive conditioning; the increased freezing in context A (fig. S2A). The hippocampus processes mnemonic infor- memory for each individual CS is acquired less New experimental and control groups of mice mation by altering the combined activity of sub- strongly as compared with when it is presented were taken off Dox in context A in order to label sets of cells within defined subregions in response alone, and the presentation of two simultaneous activated cells and then placed in context C on to discrete episodes (11–13). Therefore, we in- CSs to animals trained with a single CS can also the following day while back on Dox. In this vestigated whether applying the same parameters lead to decrement in recall (14). In our experi- experiment, although conditioning took place and manipulations to CA1 as we did to the DG ments, it is possible that the light-activated DG after the formation of both context A and context could form a false memory. We first confirmed cells encoding context A interfered with the ac- C memories, only those cells encoding context A that light could activate cells expressing ChR2- quisition or expression of the genuine fear mem- were reactivated by light during fear condition- mCherry along the anterior-posterior axis of the ory for context B. Indeed, upon reexposure to ing. Subsequently, all groups of mice displayed CA1 similar to the DG (fig. S1, J to R). Also context B, the experimental group froze signifi- background levels of freezing in context C. In similar to the DG (Fig. 2, A to E), the overlap of cantly less than the group that did not receive contrast, in the context A test the next day, the active CA1 cells was significantly lower across light during fear conditioning or the group ex- experimental group showed increased freezing contexts (A and C) as compared with that of a pressing mCherry alone (Fig. 3A and fig. S4). levels as compared with those of the mCherry- reexposure to the same context (A and A). How- During light-on epochs in the context B test, only group, confirming that the recall of the false ever, the degree of overlap for the two contexts freezing increased in the experimental group and memory is specific to context A (Fig. 2G). This was much greater in CA1 (30%) than in the DG decreased in the group that did not receive light freezing was not observed in another ChR2- (~1%). When we labeled CA1 cells activated in during fear conditioning (Fig. 3A and fig. S2C). mCherry group that underwent the same behav- context A and reactivated these cells with light We conducted similar experiments with mice in ioral protocol but without light stimulation during during fear conditioning in context B, no increase which the manipulation was targeted to the CA1 fear conditioning in context B, or in a group in in freezing was observed in the experimental group region and found no differences in the experi- which an immediate shock protocol was admin- expressing ChR2-mCherry as compared with the mental or control groups during either light-off or istered in context B with light stimulation of con- mCherry-only control group in either context A light-on epochs of the context B test (fig. S5A). text A cells (Fig. 2G and fig. S3). In a separate or context C, regardless of whether the animals Memory recall can be induced for a genuine group of animals, we labeled cells active in con- were exposed to context C or not before fear con- fear memory by light reactivation of the corre- text C rather than context A and repeated similar ditioning in context B (Fig. 2, M and N). sponding engram in the DG (8). To investigate

Fig. 2. Creation of a false contextual fear memory. (A to E) c-fos-tTA mCherry or AAV9-TRE-mCherry. One control group injected with AAV9-TRE- mice injected with AAV9-TRE-ChR2-mCherry in the DG were taken off Dox and ChR2-mCherry did not receive light stimulation during fear conditioning exposed to context A in order to label the activated cells with mCherry (red), (ChR2-mCherry, no light). (Bottom) Animals’ freezing levels in context A and C then put back on Dox and exposed to the same context A [(A) and (C)] or a before and after fear conditioning (n = 11 subjects for ChR2-mCherry group, novel context C [(B) and (D)] 24 hours later so as to let activated cells express n =12subjectsformCherry,andn = 9 subjects for ChR2-mCherry, no-light c-Fos (green). Images of the DG from these animals are shown in (A) to (D), groups; ***P < 0.001, two-way ANOVA with repeated measures followed by and the quantifications are shown in (E) (n = 4 subjects each; ***P <0.001, Bonferroni post-hoc test). (H to L) Animals underwent the same protocol as in unpaired Student’s t test). Blue and red dashed lines indicate the chance level (A)to(E),exceptthevirusinjectionwas targeted to CA1. Representative im- of overlap for A-A and A-C groups, respectively. (F) (Top) Training and testing ages of CA1 from these animals are shown in (H) to (K), and the quantifications scheme of animals injected with AAV9-TRE-ChR2-mCherry or AAV9-TRE- are shown in (L) (n = 4 subjects each; *P = 0.009, unpaired Student’s t test). mCherry. Various symbols are as explained in Fig. 1. (Bottom) Animals’ (M) Same as (F), except the viral injection and implants were targeted to CA1 freezing levels in context A before fear conditioning and in context A and C (n = 8 subjects for ChR2-mCherry and mCherry groups; n.s., not significant; after fear conditioning [n = 8 subjects for ChR2-mCherry group, and n =6 two-way ANOVA with repeated measures followed by Bonferroni post-hoc subjects for mCherry group; ***P < 0.001, two-way analysis of variance test). (N) Same as (G), except the viral injection and implants were targeted to (ANOVA) with repeated measures followed by Bonferroni post-hoc test]. (G) CA1 (n = 6 subjects for ChR2-mCherry group and n = 5 subjects for mCherry (Top) Training and testing scheme of animals injected with AAV9-TRE-ChR2- group). Scale bar in (A) and (H), 250 mm.

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whether this applies to a false fear memory, we examined fear-memory recall of experimental and control groups of mice in a distinct context (context D) with light-off and light-on epochs (Fig. 3B). All groups exhibited background levels of freezing during light-off epochs. The experimental group, however, froze at significantly higher levels (~25%) during light-on epochs. This light- induced freezing in context D was not observed in control animals that underwent the same behavioral schedule but did not receive light during fear conditioning in context B, in animals expressing mCherry alone, in animals receiving immediate shock, or in animals in which CA1 was manipulated instead (Fig. 3B and figs. S2D, S3C, S4C, and S5B). Moreover, we quantified the levels of c-Fos expression in the basolateral amygdala (BLA) and the central amygdala (CeA) during the recall of a false and genuine fear memory (15–20). Both sessions elicited a significant increase in c-Fos–positive cells in the BLA and CeA compared with a control group exploring a neutral context (Fig. 3, C to F). Last, a new cohort of mice was trained in a conditioned place avoidance (CPA) paradigm (21). Naïve animals did not show an innate preference for either chamber across multiple days (fig. S6A). An experimental group injected with the ChR2- mCherry virus and a control group injected with the mCherry-only virus were taken off Dox and Fig. 3. The false and genuine fear memories interact with each other, and both recruit the exposed to one chamber of the CPA apparatus amygdala. (A) Animals that underwent the behavioral protocol shown in Fig. 2G were reexposed to in order to label the DG cells activated in this context B, and the freezing levels were examined both in the absence and presence of light stimulation chamber. These animals were then placed back (n = 11 subjects for ChR2-mCherry group and n = 9 subjects for ChR2-mCherry, no-light group; *P = on Dox and on the following day were exposed 0.027; ***P <0.001;#P = 0.034, two-way ANOVA with repeated measures followed by Bonferroni post- to the opposite chamber. Next, the mice were fear hoc test). (B) Animals that underwent the behavioral protocol shown in (A) were placed in a novel context conditioned in a different context with light stim- D, and the freezing levels were examined both in the absence and presence of light stimulation (n =11 ulation. The following day, they were placed back subjects for ChR2-mCherry group and n = 9 subjects for ChR2-mCherry, no-light group; **P =0.007,two- into the CPA apparatus, and their preference be- way ANOVA with repeated measures followed by Bonferroni post-hoc test). (C) Three groups of mice tween the chambers was measured (Fig. 4A). underwent the training shown in (A) and were euthanized after testing in either context B (natural recall), – After conditioning, the experimental group showed A (false recall), or C (neutral context). The percentage of c-Fos positive cells was calculated for each group in basolateral amygdala (BLA) and central amygdala (CeA) (n = 6 subjects each; ***P <0.001).(D to F) a strong preference for the unlabeled chamber Images for natural recall, false recall, or neutral context. over the labeled chamber, whereas the mCherry- only group spent an equal amount of time exploring both chambers (Fig. 4, B to D, and fig. susceptible to modification (23, 24). In humans, experimental group of animals showed increased S6B). Exposure to the two chambers activated a memory distortions and illusions occur frequent- freezing in a context in which they were never statistically independent population of DG cells ly. These phenomena often result from the incor- shocked (context A). Although our design for the (Fig. 4, E to K). We conducted similar behavioral poration of misinformation into memory from formation and expression of a false memory was tests targeting the CA1 subregion of the hippo- external sources (25–27). Cognitive studies in for a laboratory setting, and the retrieval of the campus, and the experimental group did not show humans have reported robust activity in the hip- contextual memory during conditioning occurred any chamber preference (Fig. 4, L and M). pocampus during the recall of both false and by artificial means (light), we speculate that the Our results show that cells activated previously genuine memories (28). However, human studies formation of at least some false memories in in the hippocampal DG region can subsequently performed using behavioral and functional mag- humans may occur in natural settings through the serve as a functional CS in a fear-conditioning netic resonance imaging techniques have not been internally driven retrieval of a previously formed paradigm when artificially reactivated during the able to delineate the hippocampal subregions and memory and its association with concurrent ex- delivery of a unconditioned stimulus (US). The circuits that are responsible for the generated false ternal stimuli of high valence. consequence is the formation of a false associa- memories. Our experiments provide an animal Our experiments also allowed us to examine tive fear memory to the CS that was not naturally model in which false and genuine memories can the dynamic interaction between the false and available at the time of the US delivery. This is be investigated at the memory-engram level (29). genuine memories at different stages of the mem- consistent with previous findings that high- We propose that optical reactivation of cells that ory process. During the acquisition phase, the ar- frequency stimulation of the perforant path, an were naturally activated during the formation of a tificial contextual information (context A by light input to DG, can serve as a CS in a conditioned contextual memory induced the retrieval of that activation) either competed with the genuine con- suppression paradigm (22). memory, and the retrieved memory became as- textual cues (context B by natural exposure) for Memory is constructive in nature; the act of sociated with an event of high valence (a foot the valence of the US (foot shock), or may have recalling a memory renders it labile and highly shock) to form a new but false memory. Thus, the interfered with the perception of the genuine

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ing in context A). In CA1, the overlap of the cell populations activated by consecutive exposures to a pair of contexts is much greater than in the DG. Although additional work is needed to reveal the nature of CA1 engrams, we hypothesize that our negative CA1 behavioral data could be a result of contextual engrams relying less on a population code and increasingly on a temporal code as they travel through the trisynaptic circuit (4, 11–13).

References and Notes 1. D. L. Schacter, D. R. Addis, R. L. Buckner, Nat. Rev. Neurosci. 8, 657–661 (2007). 2. E. Pastalkova, V. Itskov, A. Amarasingham, G. Buzsáki, Science 321, 1322–1327 (2008). 3. H. Gelbard-Sagiv, R. Mukamel, M. Harel, R. Malach, I. Fried, Science 322,96–101 (2008). 4. C. J. MacDonald, K. Q. Lepage, U. T. Eden, H. Eichenbaum, Neuron 71, 737–749 (2011). 5. G. Buzsáki, E. I. Moser, Nat. Neurosci. 16, 130–138 (2013). 6. T. J. McHugh et al., Science 317,94–99 (2007). 7. D. Tse et al., Science 316,76–82 (2007). 8. X. Liu et al., Nature 484, 381–385 (2012). 9. A. R. Garner et al., Science 335, 1513–1516 (2012). 10. L. G. Reijmers, B. L. Perkins, N. Matsuo, M. Mayford, Science 317, 1230–1233 (2007). 11. S. Kubik, T. Miyashita, J. F. Guzowski, Learn. Mem. 14, 758–770 (2007). 12. J. F. Guzowski, B. L. McNaughton, C. A. Barnes, P. F. Worley, Nat. Neurosci. 2, 1120–1124 (1999). 13. J. K. Leutgeb, S. Leutgeb, M. B. Moser, E. I. Moser, Science 315, 961–966 (2007). Fig. 4. The false memory supports active fear behavior. (A) The scheme for conditioned place- 14. S. E. Brandon, E. H. Vogel, A. R. Wagner, Behav. Brain Res. avoidance paradigm. Various symbols are as explained in Fig. 1. (B) Locomotion traces during testing 110,67–72 (2000). 15. J. H. Han et al., Science 323, 1492–1496 (2009). from animals injected with AAV9-TRE-mCherry (top), or animals injected with AAV9-TRE-ChR2-mCherry and DG cells subsequently labeled, corresponding to either the left (middle) or right (bottom) chamber. 16. M. T. Rogan, U. V. Stäubli, J. E. LeDoux, Nature 390, 604–607 (1997). (C and D) ChR2-mCherry and mCherry group preferences for the labeled versus unlabeled chambers as shown 17. J. P. Johansen et al., Proc. Natl. Acad. Sci. U.S.A. 107, by the ratio (C) or the difference in duration of the time spent in each chamber (D). (n = 8 subjects; *P = 0.013; 12692–12697 (2010). **P = 0.008, unpaired Student’s t test). The red dashed line indicates no preference. (E to K), c-fos-tTA mice 18. S. Maren, G. J. Quirk, Nat. Rev. Neurosci. 5, 844–852 (2004). 19. H. Li et al., Nat. Neurosci. 16, 332–339 (2013). injected with AAV9-TRE-EYFP in the DG were taken off Dox and exposed to one chamber in order to label the activated cells with EYFP (green) then put back on Dox and exposed to the opposite chamber 24 hours later to 20. S. Ciocchi et al., Nature 468, 277–282 (2010). 21. S. Lammel et al., Nature 491, 212–217 (2012). let activated cells express c-Fos (red). Expression of EYFP [(E) and (H)], expression of c-Fos [(F) and (I)], and a 22. V. Doyère, S. Laroche, Hippocampus 2,39–48 (1992). merged view [(G) and (J)] are shown. Solid arrows indicate cells expressing EYFP. Open arrows indicate cells 23. K. Nader, G. E. Schafe, J. E. Le Doux, Nature 406, expressing c-Fos. These cells appear yellow because they express both endogenous c-Fos (red) and the nuclear- 722–726 (2000). localized c-fos-shEGFP (green) from the mouse line (10). Quantifications from the dorsal blades of the DG are 24. F. C. Bartlett, Remembering: A Study in Experimental and shownin(K)(n = 4 subjects). Red dashed lines indicate the chance level of overlap. (L and M) Same as (C) and Social Psychology (Cambridge Univ. Press, Cambridge, (D), except the viral injection and implants were targeted to CA1 (n = 6 subjects each group). 1932). 25. E. F. Loftus, Nat. Rev. Neurosci. 4, 231–234 (2003). 26. D. L. Schacter, E. F. Loftus, Nat. Neurosci. 16, 119–123 (2013). contextual cues. This resulted in reduced expres- to either context A or context B. Instead, they 27. H. L. Roediger, K. B. McDermott, J. Exp. Psychol. Learn. sion of both false and genuine fear memories observed a synthetic memory that could only be Mem. Cogn. 24, 803–814 (1995). 28. R. Cabeza, S. M. Rao, A. D. Wagner, A. R. Mayer, compared with the strength of recall attainable retrieved by the combination of both contexts A D. L. Schacter, Proc. Natl. Acad. Sci. U.S.A. 98, after normal fear conditioning (Fig. 3A, the two and B (9). A key difference in their system is that 4805–4810 (2001). groups during the light-off epoch). This could the c-Fos–expressing cells in the entire forebrain 29. S. M. McTighe, R. A. Cowell, B. D. Winters, T. J. Bussey, also be related to the overshadowing effects for were labeled and reactivated over an extended L. M. Saksida, Science 330, 1408–1410 (2010). 30 30. I. P. Pavlov, Conditioned Reflexes (Oxford University Press, multiple CSs ( ). During the recall phase in con- period by a synthetic ligand. We propose that ac- Oxford, 1927). text B, the false memory and the genuine memory tivating neurons in much wider spatial and tem- were either additive (Fig. 3A, the with-light group poral domains may favor the formation of a Acknowledgments: We thank S. Huang, M. Serock, during light-off and light-on epochs) or compet- synthetic memory, which may not be easily re- A. Mockett, J. Zhou, and D. S. Roy for help with the itive (Fig. 3A, the no light group during light-off trievable by the cues associated with each indi- experiments; J. Z. Young and K. L. Mulroy for comments and discussions on the manuscript; and all the members and light-on epochs). All of these observations vidual memory. In contrast, activating neurons in of the Tonegawa lab for their support. This work was are consistent with the predictions of an updated a more spatially (only small populations of DG supported by the RIKEN Brain Science Institute. Rescorla-Wagner componential model for two cells) and temporally restricted manner (only a independent CSs and suggest that the light- few minutes during light stimulation) may favor Supplementary Materials activated artificial CS is qualitatively similar to the formation of two distinct (false and genuine) www.sciencemag.org/cgi/content/full/341/6144/387/DC1 14 Materials and Methods the genuine CS ( ). memories as observed in our case. In line with Figs. S1 to S6 A previous study applied a similar experimen- this hypothesis, when we manipulated CA1 cells References tal protocol with pharmacosynthetic methods and by the same procedures as the ones used for DG 12 April 2013; accepted 2 July 2013 failed to see increased freezing upon reexposure cells, we could not create a false memory (freez- 10.1126/science.1239073

www.sciencemag.org SCIENCE VOL 341 26 JULY 2013 391 REVIEW ARTICLE published: 17 January 2014 BEHAVIORAL NEUROSCIENCE doi: 10.3389/fnbeh.2013.00226 Identiﬁcation and optogenetic manipulation of memory engrams in the hippocampus

Steve Ramirez1, Susumu Tonegawa1,2 and Xu Liu1,2*

1 Department of Biology and Department of Brain and Cognitive Sciences, RIKEN-MIT Center for Neural Circuit Genetics at the Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA 2 Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA

Edited by: With the accumulation of our knowledge about how memories are formed, consolidated, Anton Ilango, National Institutes of retrieved, and updated, neuroscience is now reaching a point where discrete memories Health, USA can be identified and manipulated at rapid timescales. Here, we start with historical Reviewed by: studies that lead to the modern memory engram theory. Then, we will review Mazahir T. Hasan, Charité-Universitätsmedizin, Germany recent advances in memory engram research that combine transgenic and optogenetic Yu Zhou, Medical College of Qingdao approaches to reveal the underlying neuronal substrates sufficient for activating University, China mnemonic processes. We will focus on three concepts: (1) isolating memory engrams at *Correspondence: the level of single cells to tag them for subsequent manipulation; (2) testing the sufficiency Xu Liu, Department of Biology and of these engrams for memory recall by artificially activating them; and (3) presenting new Department of Brain and Cognitive Sciences, RIKEN-MIT Center for stimuli during the artificial activation of these engrams to induce an association between Neural Circuit Genetics at the Picower the two to form a false memory. We propose that hippocampal cells that show activity- Institute for Learning and Memory and dependent changes during learning construct a cellular basis for contextual memory Howard Hughes Medical Institute, engrams. Massachusetts Institute of Technology, 77 Massachusetts Avenue, Building Keywords: optogenetics, memory engram, IEG, ChR2, false memory 46-5261, Cambridge, MA 02139, USA e-mail: [email protected]

A BIOLOGICAL LOCUS FOR MEMORY later, the Canadian Neurosurgeon Penfield and Rasmussen (1950) Memories thread and unify our overall personal narrative. Dis- observed the first tantalizing hint that certain memories could ruption of the putative neural correlates for memories in humans be localized in defined brain regions. During his surgeries for leads to devastating maladies and dramatically impairs cognition. patients with epilepsy, Penfield applied small jolts of electricity to Even when they are not subject to experimenter manipulations or the brain to reveal which regions were centers for causing seizures. natural insults, memories are not fully veridical representations Remarkably, while stimulating parts of the medial temporal lobe of past experiences. Recalling a memory makes it labile, which (MTL), he observed that 8% of his patients reported vivid recall can distort the mental representation of an event, incorporate of random episodic memories (Penfield and Rasmussen, 1950). misinformation, and sometimes even fabricate illusory episodes This finding suggests that the MTL region harbors the biological entirely (Schacter and Loftus, 2013). Despite the importance of locus for episodic memory. memories in our daily lives and the comprehensive studies on Then in 1953, the American Neurosurgeon William Scoville this subject, the process by which memories emerge through the and British Neuropsychologist Brenda Milner tested the con- interactions of neurons distributed across various brain regions jecture that the MTL had distinct contributions to episodic is a poorly understood phenomenon (Eichenbaum, 2004; Squire memories (Scoville and Milner, 1957). To treat the epilep- et al., 2007). tic convulsions that incapacitated his patient Henry Molaison The biological conceptualization of a memory was given a (H.M.), Scoville and Milner (1957), like Penfield and Rasmussen name—an “engram”, by the German Zoologist Richard Semon in (1950), resected the problematic neural tissue, which involved 1921 (Semon, 1921). A decade later, the American Psychologist removal of large sections of the hippocampus and adjacent Lashley et al. (1932) pioneered a systematic hunt for engrams areas in this case. For the decades to come, H.M. lost his abil- in the rodent brain by lesioning various parts of cerebral cortex ity to form new memories—to bridge personal events across and relating the size and the location of the lesion to behav- large spans of time (anterograde amnesia)—while simulta- ioral performance on a maze task. His experiments lead him neously failing to recall events for years leading up to his to formulate the mass action principle, which posits that mem- surgery (retrograde amnesia). Scoville and Milner (1957) work ories are spread throughout the cortex and not localized to on H.M. also pointed to the MTL in general and to the discrete brain regions (Lashley et al., 1932). For Lashley, the hippocampus in particular as an essential locus for episodic biological locus for a single memory remained elusive. Years memory.

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Since then, a large number of subsequent studies in humans targeted genetic manipulations (Nakashiba et al., 2008, 2009, (Rempel-Clower et al., 1996; Schmolck et al., 2002), as well as 2012; Clelland et al., 2009; Drew et al., 2010; Suh et al., 2011). in non-human primates and rodents (Jarrard, 1993; Zola and While these past studies have been pivotal in our understanding Squire, 2001), have established that the hippocampus is cru- of the role of the different subfields and circuits in learning and cial for the formation of memories that include “what-where- memory, they were conducted without distinguishing between when” components, or context-temporal-informational domains, cells that were activated by specific sensory or cognitive stimuli which are known as episodic memories (Eichenbaum, 2004). and cells that remained inactive. Additionally, the hippocampus’ structure and function has been To identify which cells are active during the formation of extraordinarily conserved across mammalian clades, permitting a memory, one can rely on the activity-dependent nature of a thorough experimental interrogation and deconstruction of its immediate early genes (IEGs). It is believed that the formation functions in animal models (Eichenbaum, 2003). of long-term memory (LTM) requires gene transcription and As a candidate mechanism supporting mnemonic processes, protein translation at the time of training to alter neural mor- the strengths of synapses throughout the hippocampus are phology, receptor densities, and overall excitability of the cells thought to be altered in an experience-dependent manner. The (Jones et al., 2001). Multiple rounds of transcription have been idea of neural plasticity dates back to Plato, who originally identified after learning and most studies focus on IEGs, which are conjectured that memories leave a stamp or trace in the mind transcribed within minutes in an experience-dependent manner analogous to the impression on a wax tablet left by a signet by transcription factor proteins already present in the cytoplasm ring (Campbell, 1883). In the 21st Century, Hebb(1949) put a of a neuron (Guzowski, 2002). modern spin on Plato’s dialogue and hypothesized that neurons The most well characterized IEGs are zif268, c-fos, and that “fire together” also “wire together” (Hebb, 1949)—a concep- Arc/Arg3.1, and all of them have been implicated in supporting tual antecedent of long-term potentiation (LTP). Bliss and Lomo memory formation. Mice with a deletion of zif268 show deficits (1973) experimental demonstration of LTP (Bliss and Lomo, in contextual fear conditioning (CFC) and the hidden platform 1973), followed by the essential role of NMDA receptors in LTP variant of the Morris Water Maze (MWM) test (Jones et al., 2001). induction (Collingridge et al., 1983) opened a way to investigate A similar result was obtained in mice lacking the c-fos gene in LTP as synaptic mechanism underlying certain forms of learning the central nervous system (Fleischmann et al., 2003). These mice and memory. The result of the initial pharmacological block- also had impaired LTP, but the developmental effects of c-fos gene ade experiments conducted with an NMDA receptor (NMDAR) deletion could not be excluded from contributing to the observed antagonist, AP5, were consistent with the notion that LTP is essen- phenotypes. Post-developmental antisense oligodeoxynucleotide tial for spatial learning (Morris et al., 1986), and the validity of this (As-ODN)-mediated blockade of c-fos translation in the hip- notion was demonstrated with the more definite targeted genetic pocampus caused impaired consolidation of inhibitory avoid- ablation of the NMDAR in the CA1 region of the hippocampus ance, MWM, and socially transmitted food preference behaviors (Tsien et al., 1996), although the cortical NMDAR may also have (Guzowski and McGaugh, 1997; Guzowski, 2002; Countryman contributed to the phenotype (Fukaya et al., 2003). A subsequent et al., 2005), all of which are tasks thought to depend on the report concluded that CA1 NMDAR were dispensable for spatial integrity of the hippocampus. Translational inhibition of Arc by learning per se, but the same report showed an easily detectable As-ODN, and mice with global genetic deletion of Arc, have level of NMDAR RNA in CA1 and hence the possibility that the demonstrated an obligatory role for this IEG in memory consol- remaining CA1 NMDAR supported spatial learning cannot be idation for MWM, fear conditioning, conditioned taste aversion, excluded (Bannerman et al., 2012). The authors reactivated an old and novel object recognition tasks (Guzowski et al., 2000; Plath hypothesis (Vinogradova, 1975) that ascribes CA1/DG NMDAR a et al., 2006). different role in learning and memory processes. However, this In addition, studies of Arc and c-fos expression after behavioral provocative and controversial hypothesis would require careful training have shown that the proportion of cells expressing these and critical examination and further investigation in the future. IEGs in DG (2–6%), CA3 (20–40%), and CA1 (40–70%) after Mice with NMDAR ablation in DG and CA3 showed impair- exposure to a novel environment resembles the proportion of ments of pattern separation and pattern completion, respectively hippocampal excitatory cells physiologically active in a given envi- (McHugh et al., 1996, 2007; Nakazawa et al., 2003). Another ronment, which further validates the use of IEGs as an indicator study did not detect the effect of NMDAR deletion in the DG of recent neural activity (Vazdarjanova and Guzowski, 2004). cells on pattern separation (Niewoehner et al., 2007), but this The cellular expression pattern of c-fos and Arc is different for may be due to the fact that different behavioral paradigms were different contexts, but remains stable upon re-exposure to the used. Overall, these observations supported the role of NMDAR- same context. These observations indicate that memory engram is dependent synaptic plasticity, including LTP, in hippocampal- highly conjunctive in nature but with remarkably labile synaptic dependent memory. properties that allow flexible memory updating (Guzowski et al., 2006; Richards and Frankland, 2013). It is in light of these studies MOLECULAR SIGNATURES OF MEMORIES that our first hypothesis for memory engrams emerges—namely, In more recent years, the role of the different circuits within cells expressing c-fos after a training episode are participating the hippocampal-entorhinal cortex network, as well as young in the encoding of the memory for that specific experience. vs. old DG granule cells, in specific aspects of hippocampal- Therefore, these cells may represent a component of the stored dependent learning and memory has been identified by using memory engram.

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EXPERIMENTAL EVIDENCE FOR MEMORY ENGRAMS IDENTIFYING MEMORY ENGRAMS To pinpoint a biological process as the underlying mechanism To selectively activate a cell population bearing an engram for a for a specific phenomenon, three types of evidence are normally particular memory, one needs to be able to isolate and label these required. These are: correlation, blockade, and mimicry. Correla- cells for future manipulation. Our first goal was to develop and tion is to record the parallel occurrence between the phenomenon characterize an activity-dependent and inducible system to label and the process, which will show an indirect relationship between only the cells involved in the formation of a specific memory with these two; blockade means interrupting the candidate process, channelrhodopsin-2 (ChR2). ChR2 is a light-sensitive channel and if this also interferes with the phenomenon, then this shows that allows the influx of cations when illuminated by ∼470 nm the necessity of the process for the expression of the phenomenon; blue light (Nagel et al., 2003), resulting in the activation of the mimicry is to artificially generate the process, and if by doing neurons expressing this channel. We began by expressing ChR2- so one can recreate the phenomenon, then this demonstrates EYFP fusion protein in an activity dependent, doxycycline (Dox)- sufficiency. regulated manner. This approach ensures that only neurons active These principles also apply if one wants to demonstrate that during a defined episode become labeled for subsequent control engram-bearing cells are the basis for memories. For correlation by light stimulation. experiments, molecular and physiological changes were found in We used the TetTag mouse (Reijmers et al., 2007), which specific neuronal ensembles accompanying memory formation harbors a pivotal transgene of interest, c-fos- tetracycline transac- from insects to humans. In the Drosophila olfactory learning cir- tivator (tTA). This transgene contains the c-fos promoter, which cuit, defined neuronal populations or even single neurons change drives the expression of the tTA. In this transgenic line, tTA can their response properties selectively towards odors used in train- mimic the expression pattern of endogenous c-fos and only tran- ing after olfactory conditioning (Yu et al., 2006; Liu and Davis, siently appear in activated cells. The tTA protein will bind to the 2009). In mice, overlapping populations of cells in the amygdala tetracycline-responsive element (TRE) to trigger the expression of are activated during the acquisition and recall of a fear memory a downstream target gene. The binding of tTA to TRE is blocked (Reijmers et al., 2007). IEGs are expressed in largely overlapping by Dox, which can be administered through an animal’s diet. If populations of neurons in the rat hippocampus and neocortex Dox is removed from the food, a window for activity-dependent during repeated exposure to the same environment (Guzowski labeling is opened and tTA can bind to TRE to turn on the et al., 1999; Vazdarjanova et al., 2002). In addition, single neurons expression of a gene of interest—ChR2-EYFP in this case—only recorded from the human hippocampus and MTL are shown to in activated cells (Figure 1A). respond reliably to the same images or episodes (Quiroga et al., Consistent with its role in processing various aspects of spa- 2005; Gelbard-Sagiv et al., 2008). These observations suggest that, tial and temporal information, the hippocampus is known to if there is a cellular basis for memory across different species, then be critical for the formation of the contextual component of it is sparsely encoded in a stable population of neurons. fear memories (Kim and Fanselow, 1992; Phillips and Ledoux, Researchers have also conducted blockade experiments on selected cells to show the necessity of engram-bearing cells for different types of memories. In two studies, researchers pioneered a novel loss-of-function approach to perturb a component of a memory engram. By selectively ablating or inhibiting sparse population of cells in the amygdala that are preferentially recruited into the representation of a fear memory, the researchers interfered with the recall of that memory in mice (Han et al., 2009; Zhou et al., 2009). Moreover, in rats, selective inactivation of a small population of neurons in the nucleus accumbens that were previously activated by cocaine has also been shown to attenuate the memory for the drug-associated environment (Koya et al., 2009). Compared to the observation and blockade experiments, the mimicry experiments for memory engram studies remained a considerable challenge. Although it had been widely recognized and agreed that such experiments are essential to test the engram FIGURE 1 | Activity-dependent labeling of neurons. (A) Training-induced hypothesis (Martin and Morris, 2002; Gerber et al., 2004), the lack neuronal activity drives the expression of tTA, which in turn activates of tools that could precisely label and control selected neurons downstream gene expression through TRE promoter and labels active cells with ChR2-EYFP (yellow). This process can be blocked by the presence of involved in a particular memory posed a formidable obstacle Dox. (B) The animals are kept on Dox (green background) before the to carry out these experiments. Demonstrating the existence of training, so any irrelevant stimuli (represented by various symbols) during memory engrams at the cellular level requires a system that this period will not cause cells to express ChR2-EYFP.The animals are taken can selectively label and activate the memory engram-bearing off Dox during training, so cells active during the memory formation will be cells to induce the predicted behavioral changes caused by labeled. Animals are put back on Dox diet post-training and during testing, so no further labeling happens. learning.

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1992). Of the various hippocampal subregions, computational positive after either condition. This group demonstrated that the models predict that DG in particular orthogonalizes inputs from freezing in the experimental groups was not due to the optical entorhinal cortex into separate spatial representations (Treves activation of a population of hippocampal neurons unrelated to a and Rolls, 1994). Behavioral data support DG’s essential role in fear memory. The second control group underwent the exactly discriminating between similar contexts (McHugh et al., 2007), same training as the experimental group but expressed EYFP and in vivo recordings in freely moving animals show that DG alone instead of ChR2-EYFP. This control demonstrated that the granule cells are exquisitely sensitive to subtle changes in con- light-induced freezing in the experimental groups was not due to textual information (Leutgeb et al., 2007). Cellular studies of changes in the salience of light after fear conditioning or other IEG expression show that sparse populations of DG granule cells non-specific effects induced by light. (2–6%) are activated in a given context (Chawla et al., 2005; We also tested whether the light-activated memory recall was Schmidt et al., 2012). Moreover, whereas a largely overlapping context-specific. We began by exposing animals that were off Dox population of DG granule cells is activated repeatedly in the same to context A and label DG cells with ChR2-EYFP,then the animals environment, different environments or even different tasks in the were placed back on Dox to prevent any further labeling. They same environment activate different populations of DG (Kubik were then fear conditioned the next day in context B. Thus, these et al., 2007; Satvat et al., 2011). These lines of evidence point to animals have both a ChR2-labeled non-fear memory engram the DG as an ideal target for the formation of contextual memory for neutral context A and an unlabeled fear memory engram engrams that represent discrete environments, guiding us to select for context B. Crucially, our neuronal data showed that two the DG as our target for potential engram cell labeling. statistically independent populations of DG cells were recruited We targeted the DG of c-fos-tTA transgenic mice with an AAV to encode two discrete environments. These observations argue virus vector carrying TRE-ChR2-EYFP and implanted an optical that DG orthogonalizes input at the neuronal ensemble level and fiber directly above the site of injection for light delivery. The recruits distinct sets of cells for distinct experiences. As predicted, mice were raised on a Dox diet to prevent any tTA-dependent this group of animals did not show increased freezing upon light transcription. This ensures that tTA produced by unintended stimulation, despite the presence of a fear memory from context activity throughout development or other experiences prior to B. This result argues that DG memory engram cell populations our behavioral training will not induce the expression of ChR2- are context-specific. EYFP. When the mice are fear conditioned while on a Dox-free Together, these data suggest that re-activating DG cells that diet, the tTA expresses in a similar pattern as c-fos and enables the were active during fear conditioning training is sufficient to transcription of ChR2-EYFP, thus tagging putative fear engram- induce the recall and behavioral expression of that fear memory. bearing cells. Then the mice are put back on diet containing Dox Accordingly, we propose that these cells form a cellular basis of a right after training to prevent the labeling of new cells in response memory engram, and that two different contexts are parsed out to experiences after training (Figure 1B). as independent experiences represented by independent neuronal ensembles in DG. ACTIVATING MEMORY ENGRAMS Our study provides a methodological framework to study how Prior to fear conditioning, we performed habituation sessions an animal’s environment is represented in neuronal ensembles in to measure the animals’ basal freezing levels to a novel context the hippocampus. The strength of our system lies in its precision (context A), during which they were on Dox diet and ChR2-EYFP of tagging only relevant cells for future manipulation. This system was not expressed. As expected, the animals showed minimal can target specific brain regions, specific cell types, and also amounts of freezing behavior during both light-on and light- specific cell populations involved in a particular memory, which off epochs. They were then taken off Dox to open a window for are otherwise indistinguishable from their neighboring cells. It activity-dependent labeling and fear conditioned in a different focuses the tremendous power of optogenetics onto behaviorally context (context B) to label fear memory engram-bearing cells, relevant cell ensembles and enables the circuit and functional and placed back on Dox diet immediately after training. A day mapping of multiple memory engrams throughout the brain. later, the animals were placed back into context A and stimulated with light to activate the neurons labeled during fear conditioning FALSE MEMORIES IN THE BRAIN in context B and test the behavioral consequences. In the early 1930s, the British psychologist Frederic Bartlett con- This experiment directly tests the hypothesis that the c-fos- structed and recited short but slightly inconsistent fables, most expressing cells in the hippocampus activated during training are famously The War of the Ghosts, to test subjects from various sufficient for memory recall. Indeed, optogenetic reactivation of cultural backgrounds (Bartlett, 1932). Strikingly, when asked to these cells resulted in freezing behavior indicative of fear memory recall the fable, many subjects unknowingly modified the fable recall (Liu et al., 2012), thus demonstrating their causal contribu- into a logical story that also contained new elements that fit within tions to activating the behavioral expression of a memory. their cultural milieu. Bartlett(1932) discovered that memory Two control groups were also tested, and none of them showed distortion can occur in such a way that contextual information any light induced freezing before or after training. The first currently in mind (i.e., information being recalled) can act as a control group did not receive foot shocks during the training. backdrop for the addition of new information. Histological data suggested that simply exposing mice to a novel The integration of new information into an already con- context elicited as much DG activity as exposure to a novel context structed memory has been shown to occur in both humans plus shock, as similar numbers (∼6%) of DG cells became c-fos and animals. Mnemonic processes are reconstructive in nature,

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as the act of recalling a memory renders it labile and highly To test this, we began by taking the animals off Dox and susceptible to modifications (Nader et al., 2000; Debiec et al., labeling cells active during the exploration of a neutral context 2002; Tse et al., 2007). Memory’s imperfections are not limited (context A) with ChR2-mCherry. We then put the animals back to pathological cases, as they are also present in healthy humans, on Dox and fear conditioned them in a different context (context in whom distortions and illusions of memories occur frequently. B) while optically activating the labeled cells involved in encoding Such modifications can occur through the incorporation of mis- the context A. We hypothesized that light-activated context A cells information into memory from external sources, such as leading could produce an artificial CS while the mice were simultaneously questions, deception, and other causes—a phenomenon termed administered an US to form an artificial associative fear memory. suggestibility. They can also occur through the phenomenon of Indeed, when placed back in context A, the experimental group misattribution, when retrieved information is assigned to the of animals displayed increased freezing levels and hence were wrong source. Striking examples abound demonstrating the dra- freezing to a context in which they were never actually shocked matic instances in which suggestibility and misattribution errors before (Ramirez et al., 2013)—a result that perhaps parallels some distort memories of crime scenes, childhood events, and trau- types of false recognition memories in humans. Importantly, matic experiences, which were often recalled under interrogation when placed in a novel context (context C), the animals showed in the court of law or during psychotherapy sessions (Loftus et al., low freezing levels, which indicated that the freezing is context- 1978; Schacter and Loftus, 2013). specific and is not simply a result of generalization (Figure 2). Interestingly, the activity of the anterior MTL in general and It is possible that the light-induced activity from context A the hippocampus in particular have been positively correlated cells interfered with natural fear memory acquisition of context with the strength of both veridical and false memory recall B. To test this possibility, we re-exposed the trained animals (Cabeza et al., 2001), thus making the hippocampus an ideal to context B and measured freezing levels across groups. Three candidate region for interrogating the neuronal conditions that findings emerged: (1) the experimental group of animals showed support false memory formation. Amnesic patients with MTL decreased freezing compared to control groups of animals trained atrophy, likewise, are sometimes less susceptible to false recogni- in context B alone, suggesting that the activity of context A cells tion than normal controls (Schacter et al., 1996). Taken together, interfered with the animal’s ability to form a representation of these results suggest that MTL networks participating in gen- context B normally; (2) when given light-on epochs, the experi- erating episodic imagery are also involved in misremembering mental group displayed an increase in freezing, which indicated imagined events as previously experienced episodes. that a natural fear memory (for context B) and an artificially- Human studies utilizing behavioral and fMRI techniques, inducted false fear memory (for context A) can have an additive however, have not been able to delineate which hippocampal effect; and (3) in a group of animals that had context A cells subregions are sufficient for false memory formation, thus neces- labeled with ChR2-mCherry but in which light was omitted sitating animal models for a more spatially and temporally precise during fear conditioning in context B (so that context A cells analysis of these neural circuits. While cognitive psychology has still represent a neutral context), light-on epochs decreased the greatly enhanced our understanding of false memories through freezing responses while re-exposed to context B, suggesting that functional neuroimaging and behavioral studies, the underlying the activity of cells representing a neutral context A may have a neuronal and circuit level processes that enable these cognitive competitive effect on natural fear memory recall for context B. quirks remain vastly unexplored. Few studies to date have utilized rodent models specifically to study the neural substrates underlying false memories. Two studies (McTighe et al., 2010; Romberg et al., 2012) investigated object recognition memory in rats with surgical or pathological perirhinal cortex lesions and found that experimental rats tended to treat novel experiences as familiar, thus leading to the false recognition of objects. Three caveats abound, however: such lesions are difficult to restrict spatially and to reproduce reliably across subjects in terms of volume of brain damaged; these lesions are temporally imprecise; and finally, they do not directly target the cells that participate in forming the engram under investigation. FIGURE 2 | Inception of a false fear memory. Top: The behavior paradigm for the experimental animals. Animals were kept on Dox post-surgery (green background), then taken off Dox and allowed to explore context A to label active cells with ChR2. Then they were put back on Dox and fear OPTOGENETIC INCEPTION OF A FALSE MEMORY conditioned (lightening symbol) in context B while receiving light Building on our previous finding that DG hippocampal cells stimulation (blue shower symbol) to activate cells representing context A. When they were put back to context A, they showed a false fear memory recruited during learning define an active neural population that for A (freezing indicated by wavy lines) where they were never actually is sufficient for memory recall upon subsequent activation (Liu shocked. They showed no fear memory for a control context C and a et al., 2012), we asked the following question: can an artificially genuine fear memory for context B where they were shocked. Bottom: activated contextual memory engram serve as a conditioned stim- Cellular activity. Red, gray, and white circles indicate neurons representing ulus (CS) and become associated with an unconditioned stimulus contexts A, B, and C respectively. Asterisks indicate neurons activated either naturally by contextual exposure or artificially by light stimulation. (US) to form an artificial CS-US association?

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We could now also probe the behavioral relevance of the DG to act as a discrete CS during the presentation of an US to cells that were artificially associated with an aversive event of construct an association between the two, as was observed in the high valence (e.g., US). If an artificial CS-US association was DG(Ramirez et al., 2013). generated using our experimental parameters, then activation of Together, these experiments showed that optical activation of a these labeled cells should now be sufficient to elicit the associated hippocampal contextual memory engram could act as an artificial behavioral output (i.e., freezing). Indeed, when placed in a novel CS during fear conditioning to form an artificial CS-US associa- context D and stimulated with light, the experimental group tion, or a putative false memory, because the artificial memory displayed light-induced freezing, suggesting that these activated never had its contiguous experiences naturally linked. Along DG cells have become part of a fear engram as a result of being similar lines, a recent optogenetic study elegantly showed that associated with an US. In a sense, the false memory became a real pairing lateral amygdala (LA) stimulation—such that activated memory. LA cells substituted as an US—with an auditory CS was sufficient To map the downstream brain areas involved in light-induced to induce freezing responses later when the CS was presented false memory formation, we measured c-fos expression after three alone (Johansen et al., 2010), while a second study demonstrated different treatments: the false fear memory recall in context A, the that activating a random population of piriform cortex neurons natural fear memory recall in context B, and the neutral memory paired with rewards or shocks could elicit the associated appeti- recall in context C. We measured the number of c-fos positive tive or aversive behavioral output upon stimulation of the same cells in the amygdala, which is an essential site for forming fear neurons (Choi et al., 2011). These two studies provide strong memories (Rogan et al., 1997). Previous electrophysiological and evidence that CS and US information can be artificially driven in immunohistochemical studies have shown positive correlations subpopulations of neurons, and our data expand these findings by between amygdala IEG activity and freezing levels (Holahan providing activity-dependent and context-specific leverage over a and White, 2004; Knapska and Maren, 2009). Accordingly, we defined memory. observed that natural fear memory recall in context B and false While the relationship between our animal model and human memory recall in context A elicited similarly robust levels of c-fos false memories remains unclear presently, it does enable future expression in the basolateral amygdala (BLA) as well as in the study of memory-updating processes at the level of discrete central amygdala (CeA), whereas animals exploring context C engrams. Notably, the formation of false memories in humans showed low basal c-fos levels. Quantifications revealed that the often occurs as a result of recombining mnemonic elements of recall of a natural and false memory both activated 25% of BLA discrete experiences into a new, reconstructed memory that is and CeA (Ramirez et al., 2013). These results show that natural not a veridical representation of the past. These memories are fear memory recall and false fear memory recall activate similar often not de novo and require pre-existing memories as a scaffold proportions of amygdala cells, arguing that both memories recruit onto which distinct experiences can be incorporated to update the similar circuits involved in producing fear memories. memory itself (Gershman et al., 2013). Similarly, in our mouse Interestingly, a previous study attempted a similar experi- model, our artificial memory is not a de novo construction; rather, mental schedule to generate an artificial memory using pharma- it is a result of artificially linking a pre-existing memory and an cosynthetic methods, and failed to see increased freezing upon event of high valence. Whether or not the reactivated memory is re-exposure to either context A or context B alone. Instead, purely Pavlovian in nature or contains episodic components is a a synthetic memory was observed, which can be recalled only topic currently under investigation. with the presence of both context A (artificially activated by a pharmacosynthetic ligand) and context B (naturally occurring CONCLUSIONS during re-exposure; Garner et al., 2012). Compared to our viral- In summary, we have shown that hippocampal engram-bearing based optogenetic manipulations, a key difference in their system cell populations underlying previously acquired memories can is that all c-fos-expressing cells in the forebrain and midbrain activate the recall of the associated memories upon subsequent were labeled and activated over the span of minutes to hours stimulation, and that this activity can form a functional CS, with a synthetic ligand. The differences observed here have which in turn can be integrated into the simultaneous formation two implications: the region-specific optogenetic manipulations of a discrete fear memory. Our work also suggests that IEG- with millisecond precision, when compared to forebrain-wide expressing neurons can form a cellular basis for memory engrams pharmacogenetic perturbations that last several minutes, per- and that these cells have direct, causal relevance in producing haps more reliably recapitulates the endogenous neural activity memory recall. Identifying the neural underpinnings behind required for behavioral expression; and, perhaps not all c-fos- engram formation may yield important clues into the treatment expressing brain regions are sufficient to elicit the recall of a of patients with pathological MTL atrophy, in whom episodic CS. To further explore this conjecture, we performed the same memory is profoundly impaired (Carlesimo and Oscar-Berman, experiments described above but targeted CA1 instead. We found 1992; Fleischman and Gabrieli, 1999). that 40–70% of CA1 neurons are labeled with ChR2-mCherry in Since episodic memory is essential to a normal life, an under- response to context exposure, and we hypothesized that optical standing of the normal circuitry underlying hippocampal func- activation of such a large population of CA1 neurons, which are tion is crucial if we are to understand the diseased state in also known to utilize highly precise temporal codes to encode disorders that give rise to episodic memory impairments (Hodges information, may not activate a context-specific representation. et al., 1990; Storandt et al., 2002; Tamminga, 2013). The findings Indeed, optical stimulation of CA1 engram-bearing cells failed presented here enable the cellular and functional mapping of

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memories in different brain regions and the causal dissection of Bartlett, F. C. (1932). Remembering: A Study in Experimental and Social Psychology. their role in producing associated behaviors. New York, Cambridge, England: The Macmillan Company; The University Indeed, the DG cells we activated to produce recall could Press. Bliss, T. V., and Lomo, T. (1973). Long-lasting potentiation of synaptic transmission also serve as both a technical and conceptual gateway to access in the dentate area of the anaesthetized rabbit following stimulation of the memory engrams distributed throughout the brain to produce a perforant path. J. Physiol. 232, 331–356. variety of behaviors. Such activity-dependent neuronal ensembles Cabeza, R., Rao, S. M., Wagner, A. D., Mayer, A. R., and Schacter, D. L. (2001). are not limited to the DG of the hippocampus, and their roles Can medial temporal lobe regions distinguish true from false? An event-related are not limited to contextual memory either. 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Hippocampus: cognitive processes and neural represen- AUTHOR CONTRIBUTIONS tations that underlie declarative memory. Neuron 44, 109–120. doi: 10.1016/j. Steve Ramirez, Susumu Tonegawa and Xu Liu wrote the paper. neuron.2004.08.028 Felix-Ortiz, A. C., Beyeler, A., Seo, C., Leppla, C. A., Wildes, C. P., and Tye, K. M. (2013). BLA to vHPC inputs modulate anxiety-related behaviors. Neuron 79, ACKNOWLEDGMENTS 658–664. doi: 10.1016/j.neuron.2013.06.016 We thank R. L. Redondo and T. J. Ryan for their comments on the Fleischman, D. A., and Gabrieli, J. (1999). Long-term memory in Alzheimer’s disease. Curr. Opin. Neurobiol. 9, 240–244. doi: 10.1016/S0959-4388(99)80034-8 manuscript. This work was supported by RIKEN Brain Science Fleischmann, A., Hvalby, O., Jensen, V., Strekalova, T., Zacher, C., Layer, L. E., Institute and Howard Hughes Medical Institute. et al. (2003). Impaired long-term memory and NR2A-type NMDA receptor- dependent synaptic plasticity in mice lacking c-Fos in the CNS. J. 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Seman- 11, 92–98. doi: 10.1002/hipo.1027 tic knowledge in patient H.M. and other patients with bilateral medial and lateral temporal lobe lesions. Hippocampus 12, 520–533. doi: 10.1002/hipo. Conflict of Interest Statement: The authors declare that the research was con- 10039 ducted in the absence of any commercial or financial relationships that could be Scoville, W. B., and Milner, B. (1957). Loss of recent memory after bilateral hip- construed as a potential conflict of interest. pocampal lesions. J. Neurol. Neurosurg. Psychiatry 20, 11–21. doi: 10.1136/jnnp. 20.1.11 Received: 22 November 2013; paper pending published: 06 December 2013; accepted: Semon, R. W. (1921). The mneme. London, New York: G. Allen and Unwin Ltd.; 27 December 2013; published online: 17 January 2014. The Macmillan Company. Citation: Ramirez S, Tonegawa S and Liu X (2014) Identification and optogenetic Squire, L. R., Wixted, J. T., and Clark, R. E. (2007). 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Neurobiol. 23, 339–345. journal is cited, in accordance with accepted academic practice. No use, distribution doi: 10.1016/j.conb.2013.01.007 or reproduction is permitted which does not comply with these terms.

Frontiers in Behavioral Neuroscience www.frontiersin.org January 2014 | Volume 7 | Article 226 | 9 Downloaded from http://rstb.royalsocietypublishing.org/ on July 1, 2015

Inception of a false memory by optogenetic manipulation of a hippocampal memory engram

Xu Liu†, Steve Ramirez† and Susumu Tonegawa rstb.royalsocietypublishing.org RIKEN-MIT Center for Neural Circuit Genetics at the Picower Institute for Learning and Memory, Howard Hughes Medical Institute, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA

Memories can be easily distorted, and a lack of relevant animal models has lar- Review gely hindered our understanding of false-memory formation. Here, we first identified a population of cells in the dentate gyrus (DG) of the hippocampus Cite this article: Liu X, Ramirez S, Tonegawa that bear the engrams for a specific context; these cells were naturally activated S. 2014 Inception of a false memory during the encoding phase of fear conditioning and their artificial reactivation using optogenetics in an unrelated context was sufficient for inducing the fear by optogenetic manipulation of a hippocampal memory specific to the conditioned context. In a further study, DG or CA1 memory engram. Phil. Trans. R. Soc. B 369: neurons activated by exposure to a particular context were labelled with 20130142. channelrhodopsin-2 (ChR2). These neurons were later optically reactivated http://dx.doi.org/10.1098/rstb.2013.0142 during fear conditioning in a different context. The DG experimental group showed increased freezing in the original context in which a foot shock was never delivered. The recall of this false memory was context specific, activated One contribution of 35 to a Discussion Meeting similar downstream regions engaged during natural fear-memory recall, and Issue ‘Synaptic plasticity in health and disease’. was also capable of driving an active fear response. Together, our data demonstrate that by substituting a natural conditioned stimulus with optogenetically Subject Areas: reactivated DG cells that bear contextual memory engrams, it is possible to neuroscience incept an internally and behaviourally represented false fear memory.

Keywords: memory engram, false memory, optogenetics, 1. Introduction hippocampus Hebb’s [1] pioneering conceptualization of synaptic plasticity in 1949 followed by Bliss & Lomo’s [2] discovery of long-term potentiation (LTP) has provided the principal framework with which neuroscientists have pursued the neural mech- Author for correspondence: anisms subserving learning and memory. Additional mechanisms, including Susumu Tonegawa alterations in membrane excitability and activation of immediately early genes e-mail: [email protected] (IEGs) at the whole single-cell level, as well as biochemical and structural alterations of dendritic spines have been recognized [3]. In neuropsychology, Semon [4] put forward the ‘engram’ theory of memory in the early twentieth century, which in current terms could be roughly stated as: when a memory is formed, a subpopulation of neurons will be excited and stay excited latently for the storage of the memory information (engram). When part of the total information at the time of storage is subsequently available, it will re-excite the engram for recall. Figure 1 presents a conceptual diagram of an engram-bearing neuronal population that incorporates neurobiological mechanisms including LTP. A recent study showed that a selective post-training ablation of an IEG (i.e. CREB)-rich cell population in the amygdala that was activated during a fear- memory task results in a loss of that fear memory [5]. These data are consistent with the engram theory, but the final test of any hypothesis concerning memory engrams must be a mimicry experiment, in which apparent memory is generated (expressed) artificially without the usual requirement for sensory experience [6]. We recently reported such an experiment. In this article, we first provide a brief † These authors contributed equally to this summary of this work. As the main body of this article, we then proceed to our work. more recent work on a mouse model of false memory that was made possible by the identification of memory engram-bearing cells. We routinely use memories as guides for cognition and behaviour [6–9]. Memory, however, can often be unreliable because it is not a carbon copy

2 rstb.royalsocietypublishing.org

downstream upstream area area

: in case of recurrent network

synaptic plasticity B Soc. R. Trans. Phil. enhanced excitability IEG expression (transient) gene activation protein synthesis structural spine changes 369 20130142 : Figure 1. Conceptual diagram of engram-bearing neuronal subpopulation. Engram theory of memory posits that when a memory of a certain experience is formed, a subpopulation of neurons, including their synapses, are activated and undergo enduring though primarily latent physical and chemical changes. These changes, referred to as the ‘engram’ of that memory, are induced by a patterned activity of the cells in the upstream area. The memory engram-bearing cells (red) may be mutually connected (dotted line) or independent. The changes that occurred in these cells include synaptic plasticity including LTP and LTD, enhanced excitability of whole single cells, transient activation of IEGs and other selected genes, new rounds of protein synthesis, and structural changes (both growth and contraction) of dendritic spines. When part of the total information at the time of storage is subsequently available, it may re-excite the engram-bearing cells and memory recall may ensue.

but rather a reconstruction of the past [10–14]. The preva- to bind to its target tetracycline-responsive element (TRE) site, lence of false memories permeates our day-to-day lives. which in turn drives channelrhodopsin-2 (ChR2)–enhanced Moreover, false memories also play a pivotal role in social yellow fluorescent protein (EYFP) expression in neurons and legal settings and have often resulted in grave and active during this defined period. These neurons can then be costly consequences. For instance, in a famous case, a jury reactivated by light stimulation during testing (figure 2b,c). In convicted Ronald Cotton of assaulting Jennifer Thompson the presence of Dox, however, tTA is blocked from binding to based on her faulty personal testimony that she genuinely TRE and neurons active during this Dox-on period remains believed to be true. Cotton was sentenced to two lifetimes unlabelled by ChR2–EYFP. in jail. A decade later, new DNA evidence became available We first tested whether the reactivation of a population of and proved Cotton’s innocence. Strikingly, one study reports DG neurons active during the encoding phase of a fear that about 75% of the first 251 people exonerated by DNA memory was sufficient for the reinstatement of that memory. evidence were victims of faulty eyewitness testimony (for The experimental group (Exp) consisted of c-fos–tTA mice reviews, see [10,11]). Cognitive studies in humans have injected with TRE-ChR2-EYFP and implanted with an optical reported robust activity in the hippocampus during the fibre targeting the dorsal DG (figure 2a). Mice were kept on recall of both false and genuine memories [15]. However, Dox and underwent a habituation period to record their human studies using behavioural and fMRI techniques basal level of freezing in one context (context A) during have not been able to delineate the mechanistic relationship which they received both light-off and light-on epochs. Next, between genuine and false memories. To resolve these they were taken off Dox and underwent fear conditioning in issues, we have investigated these two types of memories at a distinct chamber (context B) in which a tone was paired the memory engram level. with shock. The mice were then subjected to testing sessions with light-off and light-on epochs in context A while being back on Dox to prevent any subsequent labelling of active DG cells (figure 2c–g). During the habituation sessions, the 2. Identification of contextual memory engrams Exp mice showed very little freezing during either light-off in the dentate gyrus (see [16] for complete or light-on epochs. By contrast, after fear conditioning— during which putative fear memory engram-bearing DG text and methods) cells were labelled with ChR2–EYFP—freezing levels during To label and reactivate a subpopulation of dentate gyrus (DG) light-on epochs were higher compared with light-off epochs, cells active during the encoding of a memory, we targeted the which indicated light-induced fear-memory recall (figure 3a). DG of c-fos–tTA transgenic mice [17] with a TRE-ChR2-EYFP A group of mice (NS group) that went through exactly the virus and an optical fibre implant (figure 2a). This approach same procedures as the experimental group except that no couples the promoter of c-fos, an IEG often used as a marker shock was delivered during the training session did not of recent neuronal activity [18,19], to the tetracycline transacti- freeze above background levels when the light was shone vator (tTA), a key component of the doxycycline (Dox) system during the post-training session (figure 3b). Another group for inducible expression of a gene of interest [20]. In our of mice (EYFP group) that went through the same experimen- system, the absence of Dox permits c-fos-promoter-driven tTA tal protocol except that the virus had no ChR2 gene also Downloaded from http://rstb.royalsocietypublishing.org/ on July 1, 2015

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ITR TRE ChR2–EYFP ITR training rstb.royalsocietypublishing.org AAV

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c-fos tTA dentate gyrus (c) (e) ( f ) (g) 369 doxycycline no doxycycline doxycycline 20130142 : context A context B context A habituation FC testing

5 days 2 days 1 day 5 days

Figure 2. Basic experimental protocols and selective labelling of the DG cells by ChR2–EYFP. (a) The c-fos–tTA mouse was injected with AAV9-TRE-ChR2-EYFP and implanted with an optical fibre targeting the DG. (b) When off Dox, training induces the expression of c-fos–tTA, which binds to TRE and drives the expression of ChR2–EYFP, labelling a subpopulation of activated cells (yellow) in the DG. (c) Basic experimental scheme. Mice were habituated in context A with light stimulation while on Dox for 5 days, then taken off Dox for 2 days and fear conditioned (FC) in context B. Mice were put back on Dox and tested for 5 days in context A with light stimulation. (d) Representative image showing the expression of ChR2–EYFP in a mouse that was taken off Dox for 2 days and underwent fear conditioning training. An image of each rectangular area in (d) is magnified showing (e) DG, (f) CA1 and (g) CA3. The green signal from ChR2–EYFP in the DG spreads throughout granule cells, including dendrites (e), while the green signal confined to the nuclei in CA1 and CA3 is owing to shEGFP expression from the c- fos–shEGFP construct of the transgenic mouse (f,g). Blue is the nuclear marker DAPI.

showed no augmented post-training freezing upon the light fibre-implanted animals off Dox to open a time window for lab- delivery (figure 3c). On the other hand, the post-training freez- elling cells activated by the exploration of a novel context ing levels were increased even more than those of the (context A) with ChR2–mCherry. The animals were then experimental group when the Dox-off training period was immediately put back on Dox to prevent any further labelling. reduced to 1 day (Exp-1 day group, figure 3d), presumably The next day, we fear-conditioned this group in a distinct context because non-specific environmental stimuli, which compete (context B) while optically reactivating the cells labelled in con- with the specific context stimuli, were reduced. The level of text A. In the following 2 days, we tested the animals’ fear freezing was increased further when the manipulation was memory in either the original context A or a novel context C. performed bilaterally (Exp-Bi group, figure 3e). If the light-reactivated cells labelled in context A can produce The overall results (figure 3f) suggest that DG cells that a functional CS during fear conditioning in context B, then express endogenous c-Fos during training, and therefore the animals should express a false fear memory by freezing in become labelled by ChR2–EYFP, define an active neural popu- contextA,butnotincontextC. lation that is sufficient for memory recall upon subsequent Prior to conducting the behavioural experiments, we con- reactivation [16]. firmed that distinct populations of cells in the DG represent contexts A and C (figure 4a–e), enabling the manipulation of context-specific memories at the level of defined neural popu- 3. Inception of a false memory (see [21] for lations. When DG cells activated by the exposure to context A were reactivated with light during fear conditioning in a complete text and methods) distinct context B, the animals subsequently froze in context Having identified contextual engram-bearing cells in the DG, we A at levels significantly higher than the background levels went on to test whether an artificial conditioned (CS)–uncondi- (figure 4f). Freezing in context C did not differ from back- tioned stimulus (US) association—what we refer to as a false ground levels (figure 4f). This increased freezing in context A memory—could be formed. We first took virus-infected and was not due to generalization because a control group Downloaded from http://rstb.royalsocietypublishing.org/ on July 1, 2015

(a) 20 *** (b) (c) 4 20 test *** 20 20 20 20 15 n.s. n.s. habituation 15 15 rstb.royalsocietypublishing.org 15 10 15 10 15 10 Exp 5 NS EYFP n =12 n =12 5 n =12 5 0 0 0 10 off on 10 off on10 off on

freezing (%) 5 5 5

0 0 0 off on off on off on off on off on off on 3 min 3 min 3 min 3 min (d)(e)(f ) *** *** *** 40 B Soc. R. Trans. Phil. 40 *** 40 40 *** 40 *** *** 30 Exp-Bi 30 * Exp-1 day 20 20 n =6 30 n =5 10 30 10 30 0 0 off on off on ***

20 369 20 20 20130142 :

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0 Exp-Bi Exp- Exp NS EYFP 0 0 off on off on off on off on 1 day

Figure 3. Optical stimulation of engram-bearing cells induces post-training freezing. (a) c-fos–tTA mice injected with AAV9-TRE-ChR2-EYFP and trained with fear conditioning (Exp group) show elevated freezing during 3 min light-on epochs. Freezing for each epoch represents 5-day average. Freezing levels for the two light-off and light-on epochs are further averaged in the inset. (n ¼ 12, F1,22 ¼ 37.98, ***p , 0.001). (b) Mice trained similar to (a) but without foot shock (NS group) do not show increased light-induced freezing (n ¼ 12). (c) Mice injected with AAV9-TRE-EYFP and trained with fear conditioning (EYFP group) do not show increased light-induced freezing (n ¼ 12). (d) Mice trained similar to (a) but kept off Dox for 1 day before fear conditioning training (Exp-1 day group) showed greater freezing during test light-on epochs compared with Exp group (n ¼ 5, F1,8 ¼ 38.26, ***p , 0.001). (e) Mice trained similar to (a) but bilaterally injected with AAV9-TRE-ChR2-EYFP and implanted with optical fibres (Exp-Bi group) showed even higher levels of freezing during test light-on epochs (n ¼ 6, F1,10¼ 85.14, ***p , 0.001). (f) Summary of freezing levels of the five groups during test light-on epochs (F4,42 ¼ 37.62, *p , 0.05; ***p , 0.001). expressing only mCherry that underwent the exact same train- 6% of DG cells. When we labelled CA1 cells activated in con- ing protocol did not show the same effect (figure 4f ). These text A and reactivated these cells with light during fear results indicate that artificial reactivation of DG cells initially conditioning in context B, no increase in freezing was observed activated by exposure to a particular context (context A) can in the experimental group expressing ChR2–mCherry com- serve as a functional CS during fear conditioning in a distinct pared with the mCherry-only control group in either context context (context B) and results in the formation of a false AorcontextC(figure4l ). These data suggest that applying memory [21]. the same behavioural and stimulation parameters as we did in the DG does not result in the inception of a false memory in CA1. 4. No false-memory inception by CA1 engram manipulation 5. Competition between false and genuine It is possible that not all c-Fos-expressing brain regions are sufficient to elicit the recall of a CS. Indeed, the hippocampus memory processes mnemonic information by shifting the combined According to classical learning theory, the simultaneous acqui- activity of subsets of cells within defined subregions in sition of two CSs can sometimes be a competitive phenomenon response to discrete episodes [19,22]. Given that each subregion such that a memory for a single CS is acquired optimally when differentially contributes to an overall memory, we investigated it is presented alone, whereas the presentation of two simul- whether a false memory could be formed by applying the same taneous CSs can lead to an overall decrement in behavioural parameters and manipulations to CA1 as we did to the DG. output [23]. In our experiments, it is possible that the light- Similar to the DG (figure 4a–e), the overlap was significantly activated DG cells encoding context A interfered with the lower across contexts (A and C) compared with a re-exposure acquisition or expression of the genuine fear memory for con- to the same context (A and A) in CA1 (figure 4g–k). However, text B. Indeed, upon re-exposure to context B, the experimental the degree of overlap for the two contexts was much greater in group froze significantly less than the group that did not CA1 (30%) than in the DG (approx. 0.4%; figure 4e,k). Notably, receive light during fear conditioning or the group expressing exposure to a single context (A or C) consistently labelled mCherry alone (figure 5a). During light-on epochs in the con- approximately 50% of CA1 cells compared with approximately text B test, freezing increased in the experimental group and Downloaded from http://rstb.royalsocietypublishing.org/ on July 1, 2015

(e)(f ) (i) 5 (a) (c) A–C ABA¢ C

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c-Fos+ mCherry+ cells 0 0 ACA¢ hl rn.R o.B Soc. R. Trans. Phil. (k)(l) (i) g i ABA¢ C ( ) ( ) CA1 80 A–C A–A 60 (ii) 40 CA1 * 30 ChR2–mCherry, n = 8 (h) (j) 40 mCherry, n = 8 369 20 n.s. 20130142 : percentage of 20

freezing (%) 10 c-Fos+ mCherry+ cells 0 0 ACA¢

Figure 4. Inception of a false contextual fear memory. (a–e) c-fos–tTA mice injected with AAV9-TRE-ChR2-mCherry in the DG were taken off Dox and exposed to context A to label the activated cells with mCherry (red), then put back on Dox and exposed to the same context A (a,c) or a novel context C (b,d) 24 h later to let activated cells express c-Fos (green). Representative images of the DG from these animals are shown in (a–d), and the quantifications from the dorsal or ventral blades of the DG are shown in (e)(n ¼ 4 subjects each; ***p , 0.001, unpaired Student’s t-test). Blue and red dashed lines indicate the chance level of overlap for A–A and A–C groups, respectively, which is calculated by multiplying observed percentage of ChR2–mCherry-single-positive and c-Fos-single-positive cells. (f)(i) Training and testing scheme of animals injected with AAV9-TRE-ChR2-mCherry or AAV9-TRE-mCherry. The light green shading indicates the presence of Dox in the diet during corresponding stages of the scheme. Prime (0) indicates the second exposure to a given context. The yellow lightning symbol and blue shower symbol indicate foot shocks and blue light delivery, respectively. (ii) Animals’ freezing levels in context A before fear conditioning, and in context A and C after fear conditioning (n ¼ 8 for ChR2–mCherry group and n ¼ 6 for mCherry group; ***p , 0.001, two-way analysis of variance (ANOVA) with repeated measures followed by Bonferroni posthoc test). (g–k) Animals underwent the same protocol as in (a–e), except the virus injection was targeted to CA1. Representative images of CA1 from these animals are shown in (g–j), and the quantifications are shown in (k)(n ¼ 4 subjects each; *p ¼ 0.009, unpaired Student’s t-test). (l ) Same as (f), except the viral injection and implants were targeted to CA1 (n ¼ 8 for ChR2–mCherry and mCherry groups; n.s., not significant, two-way ANOVA with repeated measures followed by Bonferroni posthoc test). Scale bar in (a,g) 250 mm. decreased in the group that did not receive light during fear behavioural schedule but did not receive light during fear con- conditioning (figure 5a). We conducted similar experiments ditioning in context B, in animals expressing mCherry alone, with mice in which the manipulation was targeted to the or in animals in which CA1 was manipulated instead (figure 5b). CA1 region and found no differences in the experimental or To map the downstream brain areas involved during control groups during either light-off or light-on epochs of false-memory recall, in separate groups of animals we also the context B test. performed histological analyses measuring c-Fos expression during three sessions: the false-memory recall test in context A, the context B natural fear-memory recall session and the 6. The false memory is a real memory context C control session. We predicted that the recall of a false memory engages neural substrates known to underlie We could now probe the behavioural relevance of the DG cells genuine fear-memory recall, and therefore quantified the that were artificially associated with an aversive event of high levels of c-Fos expression in the basolateral amygdala (BLA) valence (e.g. US). If an artificial CS–US association was gener- and the central amygdala (CeA) [24–29]. Indeed, false- and ated using our experimental parameters, then activation of the genuine-memory recall sessions elicited a significant increase CS should now be sufficient to elicit the associated behavioural in c-Fos-positive cells in the BLA and CeA compared with a output (i.e. freezing). To test whether a false fear memory can be control group exploring a neutral context (figure 5c–f). artificially recalled by light-reactivation of the corresponding These results indicated that similar circuit mechanisms DG cells in a similar way as a genuine fear memory can be underlie false memory as they do genuine-memory recall. light-activated [16], we examined fear-memory recall in experimental and control groups of mice in a distinct context (context D) by administering light-off and light-on epochs (figure 5b). All groups exhibited background levels of freezing 7. Discussion during light-off epochs. The experimental group, however, Our data indicate that hippocampal DG cells activated pre- froze at significantly higher levels (approx. 25%) during light- viously during context exploration can subsequently serve on epochs. This light-induced freezing in context D was not as a functional CS in a fear-conditioning paradigm when observed in control animals that underwent the same artificially reactivated during the delivery of a US. The Downloaded from http://rstb.royalsocietypublishing.org/ on July 1, 2015

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# 80 40 ChR2–mCherry, n =11 ChR2–mCherry, no light, n =9 60 30 *** B Soc. R. Trans. Phil. 40 20 ** freezing (%) freezing (%) 20 * 10 ChR2–mCherry, n =11 ChR2–mCherry, no light, n =9 0 0 369

light-off light-on light-off light-on 20130142 :

c-Fos+ cells 10 percentage of 0 BLA BLA CeA Figure 5. The false- and genuine-fear memories interact with each other and both recruit the amygdala. (a) Animals that underwent the behavioural protocol shown in figure 2g were re-exposed to context B and the freezing levels were examined both in the absence and presence of light stimulation (n ¼ 11 for ChR2– mCherry group and n ¼ 9 for ChR2–mCherry, no light group; *p ¼ 0.027; ***p , 0.001; #p ¼ 0.034, two-way ANOVA followed by Bonferroni posthoc test). (b) Animals that underwent the behavioural protocol shown in (a) were placed in a novel context D and the freezing levels were examined both in the absence and presence of light stimulation (n ¼ 11 for ChR2–mCherry group and n ¼ 9 for ChR2–mCherry, no light group; **p ¼ 0.007, two-way ANOVA followed by Bonferroni posthoc test). (c) Three groups of mice underwent the training shown in (a) and were sacrificed after testing in either context B (natural recall), A (false recall) or C (neutral context). The percentage of c-Fos-positive cells was calculated for each group in BLA and CeA (n ¼ 6 subjects each; ***p , 0.001). Representative images for natural recall, false recall or neutral context are shown in (d), (e) and (f), respectively. consequence is the encoding of an artificial associative fear naturally linked. Thus, the experimental group of animals memory to the CS that was not naturally available at the showed increased freezing in a context in which they were time of the US delivery [30]. never shocked (context A). Although our design for the forma- Memory is reconstructive in nature; the act of recalling tion and expression of a false memory was for a laboratory a memory renders it labile and highly susceptible to setting, and the retrieval of the contextual memory during con- modification [10–14]. In humans, memory distortions and illu- ditioning occurred by artificial means (i.e. light), we suggest sions occur frequently. These modifications often result from that the formation of at least some false memories may occur the incorporation of misinformation into memory from exter- in natural settings by internally driven retrieval of previous nal sources [10,11,13,14]. Interestingly, cognitive studies in experiences and their association with external stimuli of humans have reported robust activity in the hippocampus high valence. during the recall of both false and genuine memories [15]. A previous study applied a similar experimental protocol However, human studies using behavioural and fMRI tech- with pharmacosynthetic methods and failed to see increased niques have not been able to delineate the hippocampal freezing upon re-exposure to either context A or context subregions and circuits that are responsible for generating B. Instead, they observed a synthetic memory that could false memories. To help to resolve these issues, our exper- only be retrieved by the combination of both contexts A iments provide an animal model in which false and genuine and B [32]. A key difference in their system is that the memories can be investigated at the memory engram level c-Fos-expressing cells in the entire forebrain were labelled [31]. We propose that optical reactivation of cells that were and reactivated over an extended period by a synthetic naturally activated during the formation of a contextual ligand. Moreover, the discrepancy observed here suggests memory induced the retrieval of that memory and, more two methodological caveats: the spatial and millisecond pre- importantly, the retrieved memory became associated with cision of region-specific optogenetic manipulations, when an event of high valence (i.e. a foot shock) to form a new but compared to forebrain-wide pharmacogenetic perturbations false memory that never had its component experiences that last several minutes, perhaps more reliably recapitulates Downloaded from http://rstb.royalsocietypublishing.org/ on July 1, 2015

the endogenous neural activity required for behavioural behavioural data could be a result of contextual engrams rely- 7 expression of a memory; and perhaps not all c-Fos-expressing ing less on a population code and increasingly on a temporal rstb.royalsocietypublishing.org brain regions are sufficient to elicit the recall of a CS. We pro- code as they travel through the trisynaptic circuit [8,9,22]. pose that activating neurons in much wider spatial and Together, our findings provide a foundation for an exper- temporal domains may favour the formation of a synthetic imental bridge between the traditions of rodent behavioural memory, which may not be easily retrievable by the cues neuroscience and human cognitive neuroscience in the study associated with each individual memory. By contrast, activat- of memory by illuminating the underlying circuits supporting ing neurons in a more spatially (only small populations of internally generated representations and their contribution to DG cells) and temporally restricted manner (only a few min- the formation of false memories. utes during light stimulation) may favour the formation of two distinct (false and genuine) memories as observed in our case. In line with this hypothesis, when we manipulated Acknowledgements. We thank P. Lin, J. Suh, M. Pignatelli, R. L. Redondo, B Soc. R. Trans. Phil. CA1 cells by the same procedures as the ones used for DG T. J. Ryan, S. Huang, M. Serock, J. Zhou, D. S. Roy and A. Mockett for help with the experiments, J. Z. Young and K. L. Mulroy for com- cells, we could not incept a false memory (i.e. freezing in con- ments and discussions on the manuscript, and all the members of text A). In CA1, the overlap of the cell populations activated the Tonegawa lab for their support. by consecutive exposures to a pair of contexts is much greater Funding statement. This work is supported by NIH grant nos. R01- than that in the DG. We hypothesize that our negative CA1 MH078821, P50-MH58880 to S.T. and RIKEN Brain Science Institute. 369 20130142 : References

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Bidirectional switch of the valence associated with a hippocampal contextual memory engram

Roger L. Redondo1,2*, Joshua Kim1*, Autumn L. Arons1,2, Steve Ramirez1, Xu Liu1,2 & Susumu Tonegawa1,2

The valence of memories is malleable because of their intrinsic recon- behaviour and the optogenetic place preference (OptoPP) test for assess- structive property1. Thispropertyof memory has been used clinically ing appetitive behaviour (see Methods and the characterization of these to treat maladaptive behaviours2. However, the neuronal mechan- tests in Extended Data Fig. 1). isms and brain circuits that enable the switching of the valence of On day 1 of the protocol, the mice underwent a habituation session memories remain largely unknown. Here we investigated these mech- while on doxycycline in the OptoPA or OptoPP test (Fig. 1d, f). During anisms by applying the recently developed memory engram cell- habituation, light activation had similar effects on both the ChR2- manipulation technique3,4.Welabelledwithchannelrhodopsin-2 expressing mice and the mCherry-only controls (Fig. 1e, g) and was (ChR2) a population of cells in either the dorsal dentate gyrus (DG) not sufficient to produce a change in preference (Extended Data Fig. 2). of the hippocampus or the basolateral complex of the amygdala (BLA) On day 3, off doxycycline, mice habituated to the OptoPA test were fear that were specifically activated during contextual fear or reward con- conditioned in context A (fear memory group), whereas the mice ha- ditioning. Both groups of fear-conditioned mice displayed aversive bituated to the OptoPP test were reward conditioned, by spending 2 h light-dependent responses in an optogenetic place avoidance test, in context B with one female mouse (reward memory group). As a neg- whereas both DG- and BLA-labelled mice that underwent reward ative control, groups of DG ChR2 or BLA ChR2 mice did not receive the conditioning exhibited anappetitiveresponse in an optogenetic place US (foot shock in context A or female exposure in context B) on day 3 preference test. Next, in an attempt to reverse the valence of memory (DG ChR2, no US on day 3 or BLA ChR2, no US on day 3 mice). At the within a subject, mice whose DG or BLA engram had initially been end of day 3, all animals were returned to a doxycycline diet, closing the labelled by contextual fear or reward conditioning were subjected time window for labelling for the remainder of the experiment. On day 5, to a second conditioning of the opposite valence while their original both DG ChR2 and BLA ChR2 mice of the fear memory group exhibited DG or BLA engram was reactivated by blue light. Subsequent opto- greater aversive responses in the OptoPA test than the corresponding genetic place avoidance and preference tests revealed that although mCherry-only and ChR2, no US on day 3 mice (Fig. 1e). Both DG ChR2 the DG-engram group displayed a response indicating a switch of and BLA ChR2 mice of the reward memory group showed greater appe- the memory valence, the BLA-engram group did not. This switch titive response than corresponding mCherry-only mice (Fig. 1g), DG was also evident at the cellular level by a change in functional con- ChR2, no US on day 3 mice or BLA ChR2, no US on day 3 mice in the nectivity between DG engram-bearing cells and BLA engram-bearing OptoPP test (Fig. 1g). Therefore, the US is necessary on day 3 for the cells. Thus, we found that in the DG, the neurons carrying the mem- engram neurons to drive the appropriate response on day 5 tests. ory engram of a given neutral context have plasticity such that the To investigate whether the valence of the memory associated with the valence of a conditioned response evoked by their reactivation can DG or BLA engram can be reversed, we conducted within-subject lon- be reversed by re-associating this contextual memory engram with gitudinal experiments. For this purpose, both the fear and reward mem- a new unconditioned stimulus of an opposite valence. Our present ory groups were returned to a doxycycline diet immediately after day 3 work provides new insight into the functional neural circuits under- conditioning, preventing the expression of ChR2 by other neurons that lying the malleability of emotional memory. may upregulate c-fos promoter-driven ChR2 after day 3. In a ‘fear-to- The amygdala can encode both negative and positive valence5–10 and reward’ experiment (Fig. 2a, b), the fear memory group was subjected the DG encodes contextual information3,11,12. It is unknown whether to an OptoPA test on day 5, and as expected, DG-ChR2 and BLA-ChR2 the DG drives expression of memories irrespective of the valence of the mice exhibited aversive responses that were greater than DG mCherry- unconditioned stimulus (US). Therefore we investigated the roles of DG only mice and BLA mCherry-only mice, respectively (Fig. 2b). On day 7, and BLA engrams in determining the valence of contextual memories these mice received light stimulation while interacting with 2 female and its possible switch. We targeted engram-bearing cells by infecting mice in their home cage. This procedure on day 7 is hereafter referred DG and BLA neurons of c-fos-tTA male mice with AAV9 virus express- to as ‘induction’. Another group of DG ChR2 mice received light stim- ing, under the control of the tetracycline response element (TRE), ChR2 ulation but no female mice (DG ChR2, no US on day 7 mice). On day 9, and mCherry fusion protein (DG and BLA ChR2 mice, respectively) or the OptoPP test was used in the fear-to-reward experiment to test whether mCherry-only (DG mCherry-only and BLA mCherry-only mice, respec- the neurons activated by the light stimulation during the induction pro- tively) (Fig. 1a, b and Methods). This method targets the expression of cedure could now drive an appetitive response. The DG ChR2 mice ChR2 to neurons in which the immediate early gene c-fos is activated showed a greater appetitive response than the DG mCherry-only or DG during the encoding of a memory in the absence of the antibiotic doxy- ChR2, no US on day 7 mice (Fig. 2b). Light reactivation of the original cycline (dox) in the diet3,13. A similar proportion of neurons expressed fear memory engram-bearing cells labelled in theBLA(BLA ChR2mice) ChR2 after encoding a fear memory (foot shock) or a reward memory failed to exhibit an appetitive response in the day 9 OptoPP test. For the (interaction with a female mouse in the home cage) (Fig. 1c). To test the fear-to-reward experiment, we introduced another protocol for DG ChR2 capability of the ChR2-labelled neurons to drive an aversive or appeti- and BLA ChR2 mice consisting of OptoPA tests on day 5 and day 9. The tive response, we developed two real-time optogenetic place memory tests: DG ChR2 mice displayed lower aversive responses on day 9 than the the optogenetic place avoidance (OptoPA) test for assessing aversive day 5 test, whereas the DG ChR2, no US on day 7 mice and the BLA ChR2

1RIKEN–MIT Center for Neural Circuit Genetics at the Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. 2Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. *These authors contributed equally to this work.

c 4 a DG c-fos tTA (%) Transgenic + 3 mouse 2 / DAPI + a DG 1 mCherry ITR TRE ChR2-mCherryChR2-mCherry ITR 200 μm 0 F On dox Off dox On dox Induction AAV Fear Reward b 9 4 A B OptoPA OptoPA OptoPP

(%) +/– + 3 BLA

Day 1 Day 3 Day 5 Day 7 Day 9 / DAPI 2 + b Day 5 OptoPA Day 9 OptoPP c Day 5 OptoPA 1 vs

mCherry Day 9 OptoPA BLA 200 μm 0 10 40 Fear Reward ** * ** * 10 ** Fear engram Reward engram d f 0 30 ** 0

On dox Off dox On dox On dox Off dox On dox –10 –10 20 A B OptoPA OptoPA OptoPP OptoPP +/– +/– –20 –20 10 Day 1 Day 3 Day 5 Day 1 Day 3 Day 5 –30 –30

e Day 1 Day 5 g Day 1 Day 5 Difference score (s) 0 Difference score (s) –40 –40 10 10 ** * 40 40 ** *** *** * ** –50 –10 –50 0 30 *** 0 30 D5 D9 D5 D9 D5 D9

–10 –10 20 20 DG ChR2 DG mCherry-only DG ChR2, no US on day 7

–20 –20 10 10 BLA ChR2 BLA mCherry-only

Difference score (s) score Difference –30 –30 Difference score (s) 0 0 d –40 –40 –10 –10 DG ChR2 DG mCherry-only DG ChR2, no US on day 3 BLA ChR2 BLA mCherry-only BLA ChR2, no US on day 3 On dox Off dox On dox Induction B A Figure 1 | Fear and reward engram reactivation, both in the DG and the OptoPP OptoPP OptoPA BLA, drives place avoidance and place preference, respectively. a, b, c-fos- +/– tTA mice were injected with AAV9–TRE–ChR2–mCherry or TRE–mCherry Day 1 Day 3 Day 5 Day 7 Day 9 and implanted with optical fibres bilaterally targeting the DG (a) or the BLA Day 5 OptoPP Day 9 OptoPA Day 5 OptoPP (b). c, Similar engram labelling in the DG (t33 5 0.42, NS (not significant)) and e f vs Day 9 OptoPP BLA (t26 5 0.35, NS) after fear (DG n 5 16; BLA n 5 14) and reward (DG 40 10 n 5 19; BLA n 5 14) conditioning. d, Fear memory group experimental *** 40 ** protocol. e, On day 1, difference scores (time in target zone during the on phase 0 30 ** *** minus time in target zone during baseline phase) (Extended Data Fig. 1) 30 5 –10 were similar across all DG subgroups (F2,101 0.76, NS) and across all BLA 20 5 subgroups (F2,72 0.03, NS). On day 5, difference scores were lower in DG –20 20 ChR2 (n 5 48) and BLA ChR2 mice (n 5 21) compared to the corresponding 10 mCherry-only (DG n 5 39; BLA n 5 27) and DG or BLA ChR2, no US on –30 Difference score (s) Difference score (s) 10 day 3 mice (DG n 5 17; BLA n 5 27) (DG F2,101 5 7.99, P , 0.001; BLA 0 –40 F2,72 5 4.12, P , 0.05). f, Reward memory group experimental protocol. g,On ** –10 –50 0 day 1, difference scores were similar across all DG subgroups (F2,111 5 0.02, NS) D5 D9 D5 D9 D5 D9 and across all BLA subgroups (F2,83 5 0.04, NS). In the day 5 OptoPP test, difference scores were greater in DG ChR2 (n 5 54) and BLA ChR2 mice Figure 2 | The valence associated with the DG engram is reversed after (n 5 35) compared to corresponding mCherry-only (DG n 5 36; BLA n 5 31) induction with the unconditioned stimulus of opposite value. a, The fear-to- and DG or BLA ChR2, no US on day 3 mice (DG n 5 24; BLA n 5 21) reward experimental protocol. b, On day 5, difference scores of DG ChR2 (DG F2,111 5 9.76, P , 0.001; BLA F2,83 5 9.12, P , 0.001). Significance for (n 5 16); DG ChR2, no US on day 7 (n 5 20); and BLA ChR2 mice (n 5 19) multiple comparisons: *P , 0.05; **P , 0.01; ***P , 0.001. Results show were lower compared to corresponding mCherry-only mice (DG n 5 27; BLA mean 6 s.e.m. n 5 27) (DG F2,59 5 6.16, P , 0.01; BLA t44 5 2.73, P , 0.01). In the day 9 OptoPP test, difference scores of DG ChR2 mice were greater than the control mice showed similar aversive responses on day 5 and day 9 (Fig. 2c), indi- mice (F2,60 5 4.4, P , 0.05). Difference scores of BLA ChR2 mice were cating that the DG ChR2 mice not only acquired reward memory by the similar to those of BLA mCherry-only mice (t44 5 0.16, NS). c, On the day 9 5 induction procedure but also lost much of the fear memory acquired OptoPA test, DG ChR2 mice (n 12) showed a less aversive response compared to day 5, whereas both DG ChR2, no US on day 7 (n 5 16) and BLA previously. In contrast, BLA ChR2 mice neither acquired a reward mem- ChR2 (n 5 17) mice showed similar difference scores on these days ory nor lost the fear memory. (F1,42 5 5.42, P , 0.05). d, Reward-to-fear experimental protocol. e, On day 5 In the reward-to-fear experiment (Fig. 2d, e), DG ChR2 and BLA OptoPP test, difference scores of DG ChR2 (n 5 17); DG ChR2, no US on ChR2 mice as well as the DG ChR2, no US on day 7 mice displayed day 7 (n 5 29); and BLA ChR2 mice (n 5 30) were greater compared to the greater appetitive responses in the OptoPP test on day 5 than the cor- corresponding mCherry-only mice (DG n 5 27; BLA n 5 29) (DG F2,70 5 8.97, responding mCherry-only mice (Fig. 2e). On day 7, these mice received P , 0.001; BLA t57 5 2.85, P , 0.01). On day 9, difference scores of DG ChR2 light stimulation either while being subjected to fear conditioning in mice were lower compared to the control mice (F2,71 5 3.20, P , 0.05) and context A (DG ChR2 and BLA ChR2 mice) or while exploring context difference scores of BLA ChR2 mice were similar to those of BLA mCherry- only mice (t57 5 0.49, NS). f, On the day 9 OptoPP test, DG ChR2 mice (n 5 18) Awithoutfootshocks(DGChR2,noUSonday7mice).DGChR2mice, showed a reduced appetitive response compared to day 5 OptoPP test, whereas but not DG ChR2, no US on day 7 mice displayed a greater aversive both DG ChR2, no US on day 7 (n 5 21) and BLA ChR2 mice (n 5 18) response in theday 9 OptoPAtest than DG mCherry-only mice (Fig.2e). showed similar difference scores on day 9 and day 5 (F1,54 5 6.58, P , 0.05). Among several groups of mice, only in the DG ChR2 mice did the same Significance for multiple comparisons: *P , 0.05; **P , 0.01; ***P , 0.001. neuronal ensemble whose reactivation led to an appetitive response Results show mean 6 s.e.m.

during the OptoPP test on day 5 produced an aversive response on day 9. a AAV9-TRE-ChR2–mCherry b +/– For the reward-to-fear experiment, we introduced another protocol for cFos-tTA mouse DG ChR2 and BLA ChR2 mice consisting of OptoPP tests on day 5 and On dox Off dox On dox Fear-to- A B day 9. The DG ChR2 mice displayed lower appetitive responses on reward +/– +90 min DG Home perfusion day 9 than the day 5 OptoPP test, whereas the DG ChR2, no US on day Reward- cage B A C 7 mice and the BLA ChR2 mice showed similar appetitive responses on to-fear +/– day 5 and day 9 (Fig. 2f), mirroring the results obtained by the fear-to- BLA Day –1 Day 1 Day 3 Day 5 reward experiment described above (Fig. 2c). cge h We next investigated the effect of our manipulations at the cellular 5 20 60 4 *** (%) +

level (Fig. 3a, b; see Methods for the experimental design details). Three + NS NS NS 4 15 3 *** *** (%) + (%) groups were defined by whether, on day 3 of the protocol, mice experi- 3 + 40

/ DAPI 10 2 + enced an event of the opposite valence without engram reactivation DG 2 mCherry +

2 1 1 1 / DAPI (light US ), induction (light US ), or received optogenetic stimu- + 20 1 5 1 1 2 GFP / mCherry lation but no US delivery (light US ). On day 5, the effect of DG en- GFP mCherry gram reactivation on the BLA was assessed. The proportions of cells 0 0 0 Overalap (chance = 1) 0 1 1 dif j (mCherry / DAPI ) (Fig. 3c, d) labelled on day 1 as well as the pro- 5 40 4 1 1 60 *** *** + portion of cells activated on day 5 (GFP / DAPI )(Fig. 3e, f) were sim- (%) + 4 NS (%) 30 3 *** *** +

NS (%) ilar across experimental groups in both the DG and BLA. The proportion 3 + 40 of DG engram cells labelled on day 1 that were light-reactivated on day 5 / DAPI 20 2 mCherry + * BLA + 1 1 1 2 / DAPI + 20 (GFP mCherry / mCherry ) was similar in all groups (Fig. 3g) and 10 1 2 1 1 2 1 GFP / mCherry above chance (Fig. 3h). In the light US and the light US groups, GFP mCherry the proportion of BLA engram cells labelled on day 1 that were reacti- 0 0 0 Overalap (chance = 1) 0 vated on day 5 (GFP1mCherry1 / mCherry1)byartificialreactivation k Light– US+ Light+ US+ Light+ US– of DG engram cells were similar (Fig. 3i, k) and significantly greater DG DG DG 1 1 than chance (Fig. 3j). In the light US group, this proportion, though 200 μm 200 μm 200 μm greater than chance overlap (Fig. 3j), was significantly lower compared to the light2 US1 and the light1 US2 groups (Fig. 3i, k). This suggests that the induction procedure decreased the ability of the DG engram to activate the BLA engram, indicating a change in their functional connectivity14,15. Using the reward-to-fear scheme, we next investigated the effect of the lightreactivation of a previously labelled (that is,day 3) reward memory engram on subsequent encoding of a fear memory (that is, day 7) 200 μm 200 μm 200 μm BLA BLA BLA and whether this procedure affects the recall of the fear memory by – + + + + – natural cues (day 11) (Fig. 4a). On day 7, during induction, DG ChR2 Light US Light US Light US and BLA ChR2 mice displayed significantly lower freezing than DG Figure 3 | DG to BLA functional connectivity changes after induction. mCherry-only and BLA mCherry-only mice, respectively (Fig. 4b). In a, Injection sites and the optic fibre placement. b, Experimental protocol. On addition, DG ChR2 and BLA ChR2 mice displayed significantly lower day 1, cells active during fear or reward experience were labelled. On day 3, on freezing compared to DG ChR2, no US on day 3 and BLA Ch2, no US doxycycline, mice were randomly assigned to 3 groups: reward or fear on day 3 mice, respectively on day 7 and day 11 (Fig. 4b), indicating that conditioning without light reactivation (light2 US1)(n 5 11); full induction 1 1 the reduced encoding and recall of the fear memory in DG ChR2 and protocol (light US )(n 5 16); light stimulation but neither reward nor fear 1 2 BLA ChR2 depends on the rewarding experience on day 3. Finally, we conditioning (light US )(n 5 16). On day 5, all animals received light studied the integrity of the originally acquired memory after the induction stimulation in the DG for 12 min in a novel context (context C) before the of a memory of the opposite valence. For this purpose, in the fear-to- brains were used for immunohistochemistry. c, d, Similar proportions of neurons were labelled by the fear or reward conditioning on day 3 in all groups, reward scheme, we investigated the effect of the reward memory induc- both in DG (F2,40 5 0.77, NS) (c) and BLA (F2,40 5 2.40, NS) (d). e, f, Light tion on day 7 on the original fear memory by testing the freezing response delivery to the DG on day 5 led to the activation (GFP1 / DAPI1) of similar to the original context on day 11 (Fig. 4c). DG ChR2 mice, but not DG proportions of cells in DG (F2,40 5 0.21, NS) (e) and BLA (F2,40 5 0.06, NS) (f). mCherry-only and DG ChR2, no US on day 7 mice, showed a significant g, h, Levels of reactivation (GFP1mCherry1 / mCherry1) in the DG were reduction in their freezing response even though these mice were never similar across all groups (F2,40 5 0.61, NS) (g) and above levels of chance 2 1 re-exposed to the original context between encoding of the original fear (one sample t-tests against chance overlap: light ,US t10 5 4.24, P , 0.01; 1 1 1 2 memory on day 3 and testing on day 11 (Fig. 4d). In contrast, BLA ChR2, light US t15 5 8.56, P , 0.001; Light US t15 5 5.5, P , 0.001) (h). i, j, Levels of reactivation (GFP1 mCherry1 / mCherry1) in the BLA but not BLA mCherry-only mice, showed elevated freezing during the 1 1 2 1 1 2 day 11 test session compared to the encoding session on day 3, consis- were lower in the light US compared to light US and light US (F2,40 5 11.82, P , 0.001), even though overlap levels (j) remained above tent with earlier observations that BLA engram reactivation leads to the 2 1 1 1 chance (one sample t-tests: light US t10 5 7.41, P , 0.001; light US sensitization of fear responses16,17. 1 2 t15 5 2.33, P , 0.05; light US t15 5 6.94, P , 0.001). k, Representative During the context A test on day 11, DG ChR2 mice spent more time images of double immunofluorescence for GFP (green) and mCherry (red) sniffing, a behavioural response that increases in the presence of female in the DG and BLA. Significance for multiple comparisons: *P , 0.05; cues and decreases after fear training18,19 (corrected for freezing peri- ***P , 0.001. Results show mean 6 s.e.m. ods) (see Methods), than any other groups of mice (Fig. 4e), suggesting that our reward memory induction procedure increased the positive memory valence associated with the test context (that is, context A) on that these neurons have undergone enduring changes as a consequence day 11. of memory training, validating their engram-bearing nature. We have Here we have shown that both the DG and BLA neurons activated also shown that artificially reactivating contextual fear-labelled neurons during context-specific fear or reward conditioning can drive aversive in the DG, but not in the BLA, during a subsequent reward conditioning and appetitive responses, respectively, upon optogenetic reactivation was sufficient to reverse the dominant valence associated with the memory. of these cells two days after training. This confirms our previous finding Reciprocally,artificially reactivatingcontextualreward-labelled neurons

00 MONTH 2014 | VOL 000 | NATURE | 3 ©2014 Macmillan Publishers Limited. All rights reserved RESEARCH LETTER a the corresponding BLA engram-bearing cells active during encoding— a hypothesis that was supported by the data in Fig. 3 (light2 US1). We On dox Off dox On dox Induction B A hypothesized that optogenetic reactivation of the DG engram-bearing OptoPP +/– OptoPP OptoPA/P A cells during the presentation of a US with a valence opposite to the orig-

Day 1 Day 3 Day 5 Day 7 Day 9 Day 11 inal one would strengthen the connectivity, albeit indirectly, of these b ** ** DG cells with a new subset of BLA neurons while weakening the con- 80 ** ** 80 nections established during the original learning. This hypothesis is sup- * DG ChR2 DG mCherry-only ported by the finding that the overlap of BLA neurons activated by DG ChR2, no US on day 3 60 60 stimulation of the DG engram-bearing cells was reduced after induc- BLA ChR2 BLA mCherry-only tion compared to the overlap observed in no induction controls (Fig. 3i, k). BLA ChR2, no US on day 3 The observation that the levels of c-fos activation were similar across

Freezing (%) 40 Freezing (%) 40 groups suggests that a new population of BLA neurons was functionally recruited in the light1 US1 group. Byapplyingoptogeneticmanipulations to two interacting brainareas, 20 20 Day 7 Day 11 our study provides a new type of neural circuit analysis that elucidates c functional relationships between brain areas with respect to the expression ofmemories.Previously, others haveshown that neuronsthat artificially On dox Off dox On dox Induction upregulate CREB24 and express TRPV116 in the BLA can be associated A B OptoPA OptoPA +/– OptoPP/A A with fear. Also, randomly labelled populations of neurons in the piriform cortex can drive opposing behaviours after their stimulation is paired Day 1 Day 3 Day 5 Day 7 Day 9 Day 11 with a US of positive or negative valence25. Here, because our engram d e 50 *** * *** labelling technology allows for the targeting of neurons that were acti- 80 40 vated during natural memory encoding to express ChR2, we were able to label a specific memory trace and monitor the behavioural response 60 30 elicited by natural cues (Fig. 4a, b). Our present study provides a new 20 insight into the functional neural circuit underlying the malleability of

Freezing (%) 40 emotional memory by highlighting the importance of the plasticity in 10 the hippocampal–amygdala connections.

20 Snif ! ng when not freezing (%) 0 Day 11 D3 D3 D3 D3 D3 Online Content Methods, along with any additional Extended Data display items D11 D11 D11 D11 D11 and Source Data, are available in the online version of the paper; references unique DG ChR2 DG mCherry-only DG ChR2, no US on day 7 to these sections appear only in the online paper. BLA ChR2 BLA mCherry-only Figure 4 | Memory induction alters naturally cued fear memory. a, Reward- Received 19 December 2013; accepted 30 July 2014. to-fear scheme with context A fear memory tests on day 7 and day 11. b,On Published online 27 August 2014. day 7, freezing levels during the last 3 min of the induction procedure were 1. Pavlov, I. P. Conditioned Reflexes: An Investigation of the Physiological Activity of the reduced in DG ChR2 (n 5 18) and BLA ChR2 mice (n 5 19) compared to Cerebral Cortex (Oxford Univ. Press, 1927). corresponding mCherry-only (DG n 5 21; BLA n 5 20) and ChR2, no US on 2. Wolpe, J. Psychotherapy by Reciprocal Inhibition (Stanford Univ. Press, 1958). day 3 mice (DG n 5 27; BLA n 5 24) (DG F2, 63 5 8.768, P , 0.001; BLA 3. Liu, X. et al. Optogenetic stimulation of a hippocampal engram activates fear F2,60 5 8.49, P , 0.001). These reduced freezing levels remained on day 11 (DG memory recall. Nature 484, 381–385 (2012). F2,63 5 6.25, P , 0.01; BLA F2,60 5 6.86, P , 0.01). c, Fear-to-reward scheme 4. Ramirez, S. et al. Creating a false memory in the hippocampus. Science 341, with context A fear memory tests on day 3 and day 11. d, Compared to the 387–391 (2013). last three minutes of the fear conditioning on day 3, only DG ChR2 mice 5. Muramoto, K., Ono, T., Nishijo, H. & Fukuda, M. Rat amygdaloid neuron responses during auditory discrimination. Neuroscience 52, 621–636 (1993). (n 5 27) showed a reduction of freezing responses on day 11 (interaction 6. Schoenbaum, G., Chiba, A. A. & Gallagher, M. Neural encoding in orbitofrontal F4,151 5 8.48, P , 0.001). BLA ChR2 mice (n 5 29) showed increased levels of cortex and basolateral amygdala during olfactory discrimination learning. freezing on day 11 compared to day 3. DG ChR2, no US on day 7 mice (n 5 42) J. Neurosci. 19, 1876–1884 (1999). and mCherry-only mice (DG n 5 32; BLA n 5 29) did not show differences 7. Paton, J. J., Belova, M. A., Morrison, S. E. & Salzman, C. D. The primate amygdala between day 3 and day 11. e, After correcting for the time spent freezing, represents the positive and negative value of visual stimuli during learning. Nature DG ChR2 mice spent a larger proportion of time sniffing than any other group 439, 865–870 (2006). 5 , 8. Shabel, S. J. & Janak, P. H. Substantial similarity in amygdala neuronal activity in context A on day 11 (F4,151 7.78, P 0.001). Significance for multiple during conditioned appetitive and aversive emotional arousal. Proc. Natl Acad. Sci. comparisons: *P , 0.05; **P , 0.01; ***P , 0.001. Results show USA 106, 15031–15036 (2009). mean 6 s.e.m. 9. Amano, T., Duvarci, S., Popa, D. & Pare´, D. The fear circuit revisited: contributions of the basal amygdala nuclei to conditioned fear. J. Neurosci. 31, 15481–15489 (2011). in the DG, but not in the BLA, during a subsequent contextual fear con- 10. Sangha, S., Chadick, J. Z. & Janak, P. H. Safety encoding in the basal amygdala. ditioning was sufficient to reverse the dominant valence associated with J. Neurosci. 33, 3744–3751 (2013). 11. Teyler, T. J. & DiScenna, P. The hippocampal memory indexing theory. Behav. the original memory (Fig. 2). We conclude that the valence associated Neurosci. 100, 147–154 (1986). with the hippocampal memory engram is bidirectionally reversible. In 12. Rudy, J. W. & O’Reilly, R. C. Contextual fear conditioning, conjunctive contrast, the inability of the BLA engram to reverse the valence of the representations, pattern completion, and the hippocampus. Behav. 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modulate consolidation of inhibitory avoidance memory in rats. Proc. Natl Acad. Acknowledgements We thank X. Zhou, C. Potter, D. Plana, J. Martin, M. Tsitsiklis, Sci. USA 110, 3597–3602 (2013). H. Sullivan, W. Yu and A. Moffa for help with the experiments; K. L. Mulroy, T. Ryan and 18. Malkesman, O. et al. The female urine sniffing test: a novel approach for assessing D. Roy for comments and discussions on the manuscript, and all the members of the reward-seeking behavior in rodents. Biol. Psychiatry 67, 864–871 (2010). Tonegawa laboratory for their support. This work was supported by the funds from 19. Kiyokawa, Y., Hiroshima, S., Takeuchi, Y. & Mori, Y. Social buffering reduces male the RIKEN Brain Science Institute, the Howard Hughes Medical Institute and The JPB rats’ behavioral and corticosterone responses to a conditioned stimulus. Horm. Foundation to S.T., and the National Institutes of Health Pre-doctoral Training Grant Behav. 65, 114–118 (2014). T32GM007287 to J.K. 20. Maren, S. & Fanselow, M. S. Synaptic plasticity in the basolateral amygdala induced by hippocampal formation stimulation in vivo. J. Neurosci. 15, Author Contributions R.L.R., J.K. and S.T. contributed to the study design. R.L.R., J.K. 7548–7564 (1995). and S.R. contributed to the data collection. X.L. cloned all constructs. R.L.R., J.K. and 21. Maren, S. & Hobin, J. A. Hippocampal regulation of context-dependent neuronal A.L.A. conducted the surgeries. R.L.R. and J.K. conducted the behavioural experiments. activity in the lateral amygdala. Learn. Mem. 14, 318–324 (2007). R.L.R. conducted the functional connectivity experiments. J.K. conducted the reversal 22. Herry, C. et al. Switching on and off fear by distinct neuronal circuits. Nature 454, experiments. R.L.R. contributed to the setup of the behavioural and optogenetic 600–606 (2008). apparatus and programmed the behavioural software to run the experiments. R.L.R., 23. Stuber, G. D. et al. Excitatory transmission from the amygdala to nucleus J.K. and S.T. wrote the paper. All authors discussed and commented on the manuscript. accumbens facilitates reward seeking. Nature 475, 377–380 (2011). 24. Han, J. H. et al. Neuronal competition and selection during memory formation. Author Information Reprints and permissions information is available at Science 316, 457–460 (2007). www.nature.com/reprints. The authors declare no competing financial interests. 25. Choi, G. B. et al. Driving opposing behaviors with ensembles of piriform neurons. Readers are welcome to comment on the online version of the paper. Correspondence Cell 146, 1004–1015 (2011). and requests for materials should be addressed to S.T. ([email protected]).

METHODS was tested at the beginning of every experiment to ensure that at least 10 mW of power was delivered at the end of the optic fibre pathcord (Doric lenses). Subjects. The c-fos-tTA mice were generated from the TetTag mice (Jackson Labs As criteria for inclusion in the behavioural studies, during the baseline phases stock# 008344)bredwith C57BL/6J mice13. c-fos-tTA micecarry thec-fos-tTA trans- (0–3 min), mice that spent more than 90% of the time in one single zone were ex- gene in addition to a transgene consisting of a c-fos promoter driving the expression cluded. 6 out of 376 subjects were excluded from the study. Additionally, mice that of nuclear-localized enhanced GFP. Mice were socially housed from the time of spent 100% of the time in one zone in any 3 min phase of the test were also excluded weaning until surgery and raised on a 40 mg per kg doxycycline (doxycycline) diet. in 8 out of 376 subjects. Male mice 5–10-weeks-old underwent stereotaxic surgery and were subsequently To characterize the responses to unconditioned stimuli in our setup and proto- single-housed. All procedures relating to mouse care and treatment were carried cols, a series of experiments were conducted with wild-type mice. In the shock place out in abidance to protocols and guidelines approved by the Massachusetts Insti- avoidance test, mice were allowed to freely explore the testing chamber (70 3 25 tute of Technology (MIT) Committee on Animal Care (CAC) and National Insti- 330 cm)during the 0–3 minbaseline epoch, and the preferredzone wasdetermined tutes of Health (NIH) guidelines. as the target zone. During the 3–6 min and 9–12 min epochs (on phases), foot Viral constructs. The pAAV-TRE-ChR2–mCherry and pAAV-TRE-mCherry plas- shocks (0.15 mA, 2 s duration every 5 s) were administered when the mice entered mid was constructed as previously described4.AAV viruses containing these con- 9 the target zone and every 5 s for as long as they remained in the target zone (wild- structs were packaged by the Gene Therapy Center and Vector Core at the University type, shock mice) or no foot shocks were administered (wild-type, no shock mice). of Massachusetts Medical School. Viral titres of8 3 1012 genome copies (GC) per ml (Extended Data Fig. 1a, b). In the female place preference test, mice were allowed to for AAV -TRE-ChR2–mCherry and 1.43 1013 GC per ml for AAV -TRE-mCherry 9 9 freely explore the testing chamber during the 0–3 min baseline epoch, and the less were used in viral injections as previously reported4. preferred zone was determined as the target zone. During the 3–6 min and 9–12 min Surgical procedures. Mice underwent surgical procedures anaesthetized under epoch (on phases), a corral (upside-down pencil holder) containing a female was isoflourane. Under stereotaxic guidance, virus was injected using a glass micropi- placed in the target zone, while an empty corral was placed in the opposite side of pette attached to a 1 ml Hamilton microsyringe (701LT; Hamilton) through a mi- the apparatus (wild-type, female mice) or two empty corrals were place on both croelectrode holder (MPH6S; WPI) filled with mineral oil. Once the target site was ends of the apparatus (wild-type, no female mice) (Extended Data Fig. 1e, f). reached, the needle was held in place for 5 min before the injection of 200 nl of 27 21 As often seen in biased protocols , ceiling effects prevent preference from being virus at a rate of 70 nl min . After the full titre of virus was injected, the needle was detected in avoidance tests (OptoPA) and floor effects prevent avoidance perform- held in place for an additional 5 min before withdrawal. Dentate gyrus stereotaxic ance in preference tests (OptoPP). OptoPA and OptoPP could only detect avoid- coordinates were 22.0 mm anteroposterior (AP), 6 1.3 mm mediolateral (ML), ance or preference, respectively, or their absence. 2 2 2.0 mm dorsoventral (DV), and basolateral amygdala coordinates 1.4 mm AP, From test to test, in between days, mice chose a preferred side independently of 6 2 26 3.2 mm ML, 4.8 mm DV . After withdrawal of the needle, a Doric patchcord their performance on previous days (Extended Data Table 1). optical fibre (Doric Lenses) was lowered 0.15 mm above the site of injection. For Daily behavioural protocols (Figs 1, 2 and 4). For both fear-to-reward and implants targeting the dentate gyrus of the hippocampus, Doric implants TFC_ reward-to-fear experiments, subjects underwent behavioural testing at least 1-week 200/240-0.22_2.4mm_TF2.6_FLTwere used. For implants targeting the BLA, Doric post-surgery. The experimental group (that is, ChR2, mCherry-only, ChR2, no US) implants MFC_200/240-0.22_5.5mm_Z1.25_FLT were used. A screw was placed was pseudo-randomly assigned and mice grouped into cohorts (n of 8 to 12) with into the skull anterior to the site of injection. A layer of adhesive cement (C&B surgery-type determining the group assignment (DG or BLA). Two days before Metabond) was applied around the optical fibre. Once the adhesive cement cured, the start of testing, animals were handled and habituated to experimenters. On day 1, a protect cap, made from a 1.5 ml black eppendorf tube, was placed around the subjects were habituated to the OptoPA or OptoPP test, then immediately placed adhesive cement. The cap was secured to the optical fibre implant by dental cement off doxycycline. On day 3, subjects were exposed to a shock (context B) or female (Teets cold cure; A-M Systems). Mice were given 1.5 mg per kg Metacam as an an- (context A), then immediately placed on a doxycycline diet. On day 5 subjects were algesic and remained on a heating pad until recovery from anaesthesia. Mice were tested in the OptoPA or OPP test. For experiments described in Fig. 2, on day 7, allowed to recover for at least 1 week before all subsequent experiments. Viral injec- subjects underwent optogenetic induction. On day 9, subjects underwent the OptoPP tion sites were verified atthe end ofthe experiments (Extended Data Fig. 3). Twenty- or OptoPA test, the test opposite to that of the initial test on day 5. For the fear-to- two out of 319 animals were excluded due to low expression in the target areas. reward experiment, we introduced another protocol for DG ChR2; DG ChR2, no Engram labelling. Prior to conditioning, subjects were given food without doxycy- US on day 7; and BLA ChR2 mice consisting of OptoPA tests on day 5 and also on cline for 2 days. During fear conditioning, subjects were placed in a shock chamber day 9. For the reward-to-fear experiment, we introduced another protocol for DG (30 3 35 3 32 cm) scented with 0.25% benzaldehyde in 70% ethanol for 500 s (con- ChR2; DG ChR2, no US on day 7 and BLA ChR2 mice consisting of OptoPP tests text A). Foot shocks (0.75 mA, 2 s duration) were administered at the 198 s, 278 s, on day 5 and also on day 9. For experiments described in Fig. 4, on day 11, subjects 358 s and 438 s time points. For reward conditioning, each subject was exposed to a of both behavioural paradigms (Fear to Reward and Reward to Fear), were re-exposed single female mouse for 2 h in their home cage in a room separate from the housing to the fear conditioning box (context B). room (context B). Immediately after, in both fear and reward conditioning, subjects DG to BLA functional connectivity experiment (Fig. 3). Animals were injected returned to a doxycycline (40 mg per kg) diet. with TRE-ChR2–mCherry virus in both the BLA and the DG, and implanted with Optogenetic induction. In optogenetic fear induction, subjects were placed in a optic fibres only above the DG (Fig. 3a). At least one week after surgery, animals shock chamber (303 35 3 32 cm) scented with 0.25% benzaldehyde in 70% eth- were randomly assigned to 3 groups according to the manipulation carried out on anol with light stimulation (20 Hz, 15 ms) for 500 s (context A). Foot shocks (0.75 mA, day 3: light2 US1, light1 US1 and light1 US2. While off doxycycline on day 1, 2 s duration) were administered at the 198 s, 278 s, 358 s and 438 s time points. Dur- mice experienced foot shocks or a female, which labelled the active cells in both the ing optogenetic reward induction, in a separate room from the housing room, home DG and the BLA (Fig. 3b). On day 3, while back on doxycycline, the mice experienced cages were placed inside of a 4-sided (31 3 25 3 30 cm) box and cage tops were either an event of the opposite valence without engram reactivation (light2 US1), removed (context B). Light stimulation (20 Hz, 15 ms pulses) was applied while induction (light1 US1), or received optogenetic stimulation but no US delivery exposing each subject to two female mice for 12 min. (light1 US2). Light2 US1 mice went through induction protocols without light Optogenetic conditioned place aversion (OptoPA) and preference (OptoPP) stimulation. The power supply for the lasers was on to produce noise at the same tests. The testing chamber consisted of a custom-built rectangular box (70 3 25 levels as the light1 US1 group, but the light delivery from the laser was switched 3 30 cm) with white floors and distinct wall cues placed on each end of the cham- off. Light1 US2 mice received light stimulation while running induction proto- ber. A video camera resides above the testing chamber where the locations of the cols that did not include the presence of females or the delivery of foot shocks. On subjects were tracked and recorded using Noldus EthoVision XT video tracking day 5, all mice were placed in a third, new context (context C) and received light software. Two zones on either end of the box A (30 3 30 cm) as well as a neutral (20 Hz, 15 ms pulse width, 473 nm, 10–25 mW) into the DG for 12 min. Ninety zone in the centre of the box (10 cm) were denoted as part of the arena settings. In minutes later, the mice were perfused and brain sections were collected for immu- the OptoPA and OptoPP tests, subjects freely explored the testing chamber for 12 min. nohistochemistry against mCherry to visualize the engram-bearing cells labelled A baseline (BSL) phase lasting 3 min was followed by an on phase (3 min), an off on day 1 and against GFP derived from a c-fos–shGFP transgene3, which we use as phase (3 min) and another on phase (3 min). The target zone of light stimulation a surrogate for endogenous c-fos to reveal cells that have been active recently4. was determined by the zone of greater preferenceduring the 0–3 min baseline epoch Immunohistochemistry. Mice were euthanized by avertin overdose and perfused in the OptoPA test and the least preferred side for the OptoPP test. Only during the with 4% paraformaldehyde. Brains were removed and placed in 4% paraformalde- onphases, when the mouse entered the target zone, a TTL signal fromthe EthoVision hyde for 24 h then stored in PBS at 4uC before sectioning. 50-mm coronal sections software via a NoldusUSB-IO Box triggered a stimulus generator (STG-4008,Multi- were obtained using a vibratome and stored at 220uC. At the time of staining, sec- channel Systems). The signal from the stimulus generator drove the lasers (Opto- tions underwent three 10-min PBS-T (PBS1 0.2% Triton X-100) washes, then in- Engine) to produce light (473 nm) in 15 ms pulses delivered at 20 Hz. Laser output cubated in blocking buffer (5% normal goat serum) for 1 h. Primary antibodies

©2014 Macmillan Publishers Limited. All rights reserved LETTER RESEARCH were applied overnight at 4uC: chicken anti-GFP from Invitrogen A10262 (1:1,000 during the two on phases. Negative difference scores denote that the preference for dilution) and rabbit anti-RFP from Rockland Immunochemicals 600-401-379 the target zone during on phases is lower than the preference during the BSL phase, (1:2,000 dilution). Sections underwent three 10-min washes in PBS-T, then were whereas positive difference scores denote that the preference for the target zone incubated with secondary antibody solution (goat anti-chicken conjugated with during on phases is higher than the preference during the baseline phase. Alexa Fluor 488 Invitrogen A11039 (1:200 dilution) and goat anti-rabbit conjugated In the reward-to-fear experiment, during the optogenetic induction protocol, with Alexa Fluor 568 Invitrogen A11011 (1:500 dilution)) for 2 h. Sections under- where the optic fibre interferedwithautomated scoring,blindedmanual scoring was went another three 10-min washes before coverslip mounting using Vectashield used to score freezing levels. In the fear-to-reward experiment, freezing scores were with DAPI. assessed via the automated scoring on using the Med Associates video fear condi- Imaging and cell counting. Images for cell counting were captured with VS-120 tioning software. Sniffing scores28 were also assessed blindly through manual scor- (Olympus) at 203 and imported into cellSens Dimension software (Olympus). A ing using JWatcher. region of interest (ROI) was defined manually following anatomical landmarks. Statistical analysis. GraphPad Prism version 6.00 for Mac OS X, GraphPad Soft- Neurons stained against mCherry (red) as well as those with an overlap in red and ware, La Jolla California USA was used for statistical analysis. Statistical signifi- green signal were counted manually. Cells stained against GFP (green) and DAPI cance was assessed by two-tailed unpaired Student’s t-tests, one-way ANOVA, or (blue) were counted automatically by the cellSens software after manual adjustment two-way repeated-measures ANOVA where appropriate. Significant main effects of detection thresholds. or interactions were followed up with multiple comparison testing with the use of All counting was performed blind as to the group and condition that the spec- Holm–Sidak’s correction where specified in the legends. Significance levels were set imen belonged to. For BLA DAPI counts, thresholds were set up so as to only count 13 to P 5 0.05. Significance for multiple comparisons: *P , 0.05; **P , 0.01; ***P , large DAPI nuclei to exclude non-neuronal small nuclei as described previously . 0.001. Sample sizes were chosen on the basis of previous studies. Data met assump- For Fig. 3h, j, chance overlap is calculated as (mCherry1 /DAPI)3 (GFP1 /DAPI). tions of statistical tests, and variancewas similar between groups for all metrics mea- Overlaps over chance were calculated as GFP1 mCherry1 / DAPI divided by chance sured except for one differencescore comparison (Fig. 2b,BLAOptoPA to OptoPP), overlap. freezing data (Fig. 4b, day 5), and sniffing data (Fig. 4e) (Brown–Forsythe test). The representative overlap images presented in Fig. 3 were obtained in a confocal microscope (Zeiss AxioImager M2). Behavioural scoring. In the OptoPA and OptoPP tests, automated tracking by 26. Franklin, K. B. J. & Paxinos, G. The Mouse Brain in Stereotaxic Coordinates Noldus EthoVision was used to track the position of the mice. Raw data was ex- (Academic Press, 2008). 27. Calcagnetti, D. J. & Schechter, M. D. Nicotine place preference using the biased tracted and analysed with Microsoft Excel and GraphPad Prism version 6.00 for method of conditioning. Prog. Neuropsychopharmacol. Biol. Psychiatry 18, Mac OS X, GraphPad Software, La Jolla California USA. The difference scores (DS) 925–933 (1994). reported in the main figures were obtained by subtracting the time spent in the 28. Blumstein, D. T. & Daniel, J. C. Quantifying Behavior the JWatcher Way (Sinauer target zone during the baseline phase from the average time spent in the target zone Associates, 2007).

Extended Data Figure 1 | Light-induced avoidance and preference tests. 0–3 min baseline, the less preferred zone was established as the target zone. a, b, Shock place avoidance test. a, After the 0–3 min baseline (BSL), the most During the on phases (3–6 and 9–12 min), a corral containing a female was preferred zone was established as the target zone. Wild-type, shock mice placed in the less preferred zone (target zone) and an empty corral was placed (n 5 11) received foot shocks (0.15 mA DC (direct current), 2 s duration every on the opposite side. Corrals, and the female, were removed during the off 5 s) when entering the target zone during the on phases (3–6 and 9–12 min). phase. f,Mice(n 5 24) increased the time spent in the target zone compared to No shocks were delivered during the off phase (6–9 min). Wild-type, no shock mice presented with two empty receptacles (n 5 8) (t30 5 2.81, P , 0.01). mice (n 5 24) received no shocks. b, The difference score was lower in the g, h, Optogenetic place preference (OptoPP) test. g, Reward-labelled mice were wild-type, shock mice compared to wild-type, no shock (t41 5 3.76, P , 0.001). allowed to explore the arena during baseline and the less preferred zone c, d, Optogenetic place avoidance (OptoPA) test. c, Mice were allowed to designated as the target zone. Light stimulation (20 Hz, 15 ms pulse width, explore the arena during baseline and the preferred side determined as the 473 nm, . 10 mW) was applied while the subject was in the target zone of the target zone. Light stimulation (20 Hz, 15 ms pulse width, 473 nm, . 10 mW) chamber at the 3–6 min and 9–12 min epochs (on phase). h, The difference was applied when the mice entered the target zone during the on phases. Light score was increased in the DG ChR2 mice (n 5 54) compared to DG mCherry- stimulation was not delivered during the off phase. d, The difference score was only mice (n 5 36) (t88 5 4.361, P , 0.001). a, c, e, g (right panel), lower in the DG ChR2 mice (n 5 48) compared to DG mCherry-only mice Representative tracks for experimental animals. Dots mark the position of the (n 5 39) (t85 5 3.55, P , 0.001). e, f, Female place preference test. e, After the animal every 5 video frames and accumulate where the mice spend more time.

Extended Data Figure 2 | Light stimulation in the OptoPA and OptoPP habituation in the OptoPP test, even though there is an overall difference tests has no effect during habituation. a, Day 1 OptoPA habituation. There between the two types of phases (F1,195 5 8.06, P , 0.01, 6 NS multiple are no within group differences in the average duration spent in the target zone comparisons. DG ChR2 n 5 54; DG mCherry-only n 5 36; DG ChR2, no US during the average of the baseline and off phases (off) and the averages of on day 3 n 5 24; BLA ChR2 n 5 35; BLA mCherry-only n 5 31; BLA ChR2, no the two light on phases (on) during day 1 habituation in the OptoPA test, even US on day 3 n 5 21). c, d, There are no differences between experimental though there is an overall difference between the two types of phases groups and wild-type mice tested without light stimulation. c, In the OptoPA (F1,173 5 6.46, P , 0.05, 6 NS multiple comparisons. DG ChR2 n 5 48; DG test, the difference scores (on minus off) are similar between experimental mCherry-only n 5 39; DG ChR2, no US on day 3 n 5 17; BLA ChR2 n 5 32; groups (same as panel a) and wild-type mice (n 5 33) that did not receive light BLA mCherry-only n 5 27; BLA ChR2, no US on day 3 n 5 27). b,Day1 stimulation (F6,205 5 0.19, NS). d, In the OptoPP test, the difference scores OptoPP habituation. There are no within group differences in the average time (on minus off) are similar between experimental groups (same as panel b) duration spent in the target zone during the average of the baseline and off and wild-type mice (n 5 33) that did not receive light stimulation phases (off) and the average of the two light on phases (on) during day 1 (F6,227 5 0.21, NS).

Extended Data Figure 3 | Fibre positions in DG and BLA. a, Representative construct in the DG. b, Representative example of the fibre location and the example of the fibre location and the expression of the ChR2–mCherry expression of the ChR2–mCherry construct in the BLA.

Extended Data Table 1 | Mice chose a preferred side on day 9 irrespective of their choice of preferred side on day 5 in both fear-to-reward and reward-to-fear experiments

To determine whether mice switched (switch) or not (no switch) their preferred side between tests, the preferred side during the baseline phase on day 5 tests was compared to the preferred side during the 2 baseline phase on day 9 tests. Across groups, there is no difference between animals that switched sides between day 5 and 9 and those that did not across groups (x 9 5 3.74, NS)

Identification and Manipulation of Memory Engram Cells

1,2,3 1 1,2 1,2 XU LIU, STEVE RAMIREZ, ROGER L. REDONDO, AND SUSUMU TONEGAWA 1RIKEN-MIT Center for Neural Circuit Genetics at the Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 2Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 Correspondence: [email protected]

How memories are formed and stored in the brain remains a fascinating question in neuroscience. Here we discuss the memory engram theory, our recent attempt to identify and manipulate memory engram cells in the brain with optogenetics, and how these methods are used to address questions such as how false memory is formed and how the valence of a memory can be changed in the brain.

How and where memory is stored in the brain network When a subject undergoes or encounters an episode, a is one of the fundamental questions in brain and cognitive set of selected stimuli from the experience or episode sciences. At the onset of the 20th century, a German activate populations of neurons to induce enduring phys- biologist Richard Semon proposed the engram theory of ical and/or chemical changes (engrams) in them and their memory (Semon 1923), but the theory was nearly com- connections, each contributing to the storage of memory. pletely ignored by his contemporary and subsequent brain Subsequently, when a part of the original stimuli returns, researchers, until Daniel Schactor, James Eich, and Endel these cells (engram cells) are reactivated to evoke the Tulving revived the theory in the late 1970s (Schacter recall of the specific memory. et al. 1978). Semon’s memory engram theory was built A half-century after Semon’s book was published, Karl on two fundamental postulates termed the “Law of En- Lashley pioneered a systemic hunt for engram cells in the graphy” and the “Law of Ecphory” for memory storage rodent brain by introducing lesions of varying sizes into and memory retrieval, respectively. The Law of Engra- different areas of the cerebral cortex, attempting to find phy posits: “All simultaneous excitations (derived from an engram for a maze task. However, Lashley found that experience) ...with in our organisms form a connected memory was impaired in many of these lesioned animals, simultaneous complex of excitations which, as such, acts and the severity of the impairments was proportional to engraphically, that is to say leaves behind it a connected, the sizes of the lesions. On the basis of these findings, and to that extent, unified engram-complex” (Semon Lashley concluded that the engrams for maze-resolving 1923). The Law of Ecphory on the other hand posits: memory are spread throughout the cerebral cortex with no “The partial return of an energetic situation which has obvious localization (Mass Action Principle) (Lashley fixed itself engraphically acts in an ecphoric sense upon 1950). However, soon after Lashley’s study, Wilder Pen- a simultaneous engram-complex” (Semon 1923). field and Theodor Rasmussen obtained the first evidence Semon’s conceptualizations of the memory process suggesting that the engrams of episodic memories are were novel for his time and were remarkably predictive stored in the medial temporal lobes (MTLs) (Penfield of the contemporary concepts of memory storage and and Rasmussen 1950). This chance finding was support- retrieval. For instance, Semon’s memory retrieval pro- ed several years later by William Scoville and Brenda cess contained the concept of “pattern completion,” Milner, who discovered that a patient H.M., who lost a which was advanced years later (Marr 1970; Nakazawa large portion of his MTLs as a result of surgery, had et al. 2003; Leutgeb et al. 2004). However, Semon did not severe anterograde amnesia for episodes as well as a grad- elaborate the biological basis of the “simultaneous ex- ed retrograde amnesia. These studies were consistent with citations” nor “a connected, unified engram-complex.” the notion that episodic memories are stored in the MTLs. This is not surprising considering that his theory was As to the nature of memory engrams—enduring phys- put forward nearly a century before the development of ical and chemical changes induced by learning—the molecular, cellular, and genetic biology and sophisticated guiding hypothesis has been Donald Hebb’s theory, imaging and electrophysiological technologies for the which posits that neurons encoding memory stimuli un- analysis of the nervous system. dergo enduring strengthening of some of their synapses Incorporating the current knowledge about neurons, through their coactivation with presynaptic cells: neurons synaptic connections, and neuronal circuits, Semon’s En- that “fire together wire together” (Hebb 1949). Starting gram Theory of Memory can be rephrased as follows: with Tim Bliss and Terje Lomo’s discovery of long-term

3Present address: Department of Neurobiology, Northwestern University, Evanston, Illinois 60208. Copyright # 2014 Cold Spring Harbor Laboratory Press; all rights reserved; doi: 10.1101/sqb.2014.79.024901 Cold Spring Harbor Symposia on Quantitative Biology, Volume LXXIX 1 Downloaded from symposium.cshlp.org on July 1, 2015 - Published by Cold Spring Harbor Laboratory Press

2 LIU ET AL. potentiation (Bliss and Lomo 1973), which supports such as optogenetics (Fenno et al. 2011; Goshen 2014) Hebb’s hypothesis, a large number of studies have been enabled such experiments. directed to the characterization of LTP and other facets of To achieve this goal, we combined activity-dependent, synaptic plasticity and their potential role in learning and drug-regulatable expression system with optogenetics memory. However, none of these studies could link these (Liu et al. 2012). We used a transgenic mouse model activity-dependent alterations of synapses and neurons where the artificial tetracycline transactivator (tTA), directly to engram cells, which are activated by specific which can be blocked by doxycycline (Dox), is driven learning and whose reactivation by the specific recall by the promoter of immediate early gene (IEG) c-fos cues elicited behavioral responses. (Reijmers et al. 2007). The activity dependency of c-fos In this review, we shall outline our recent attempt to promoter poses a natural spatial constrain on the identi- identify memory engram cells and to manipulate them by ties of the neurons that can be labeled, reflecting the optogenetics to investigate several thus far unresolved normal biological selection process of the brain during issues associated with episodic memory. memory formation, whereas the Dox-dependency of the system poses an artificial temporal constrain as to when these neurons can be labeled, which can be controlled by OPTOGENETIC ACTIVATION the experimenters. With these two constraints, the down- OF MEMORY ENGRAM CELLS stream effector of tTA can express selectively in neurons Previous studies have linked selected neuronal popula- that are active during a particular behavior episode, only tions with particular memory events by correlational if the animals are off Dox diet. Using this system, we evidence (Reijmers et al. 2007) and loss-of-function ev- expressed channelrhodopsin-2 (ChR2) delivered by a vi- idence (Han et al. 2009; Zhou et al. 2009), but a critical ral vector AAV-TRE-ChR2-EYFP targeting the dentate piece of evidence was largely missing. The most direct gyrus (DG) of the hippocampus and implanted optical evidence of engram cells should come from gain-of-func- fibers right above the infected areas (Fig. 1A). These tion experiments, where a population of neurons that are animals were habituated in one context A with light stim- considered responsible for a particular memory are selec- ulation while on Dox, and then taken off Dox and fear tively labeled and activated artificially to mimic their conditioned in context B, where DG neurons active dur- natural activity. If such manipulation causes the recall ing the formation of this context-fear association memory of that memory, then this provides evidence that the se- were labeled by ChR2 (Fig. 1B). After which they were lected population of neurons is sufficient for the memory, put back on Dox diet to stop further labeling and tested and thus argues the selected neuronal population is the again in context A by light stimulation of the labeled neuronal basis for the engram of this particular memory neurons (Fig. 1C). (Martin and Morris 2002). However, this type of gain-of- Although light had no effect on the test subjects in function experiment is technically challenging, as one context A before training, these animals showed revers- has to be able to correctly isolate the neurons involved in ible, light-dependent freezing in context A after training one particular memory from their seemingly indistin- (Fig. 1D), indicating light-induced recall of fear memory guishable neighbors and activate them with proper spatial associated with fear conditioning, which happened in and temporal precision. Recent advances in technology context B. Because these animals did not freeze in con-

Figure 1. Optogenetic activation of memory engram cells induced memory recall. (A) Basic composition of the system. Virus expressing TRE-ChR2 and optic fibers are targeted bilaterally into the dentate gyrus (DG) of transgenic mouse line expressing c-fos-tTA. (B) In the absence of Dox, DG neurons that are active during the formation of a memory are labeled with ChR2. (C) Behavior schedules. Animals were habituated to context A with light stimulation while on Dox, trained in context B while off Dox, and texted again in context A with light stimulation while on Dox. (D) Although light had no effect during pretraining habituation sessions, the animals showed light-dependent freezing behavior post- training, indicating the light-induced recall of a fear memory. Downloaded from symposium.cshlp.org on July 1, 2015 - Published by Cold Spring Harbor Laboratory Press

MEMORY ENGRAM CELLS 3 text A in the absence of light posttraining, this ruled out subsequent studies to test long-standing hypotheses about the possibility that the freezing was due to generalization the malleability of memory with unprecedented spatial– between context A and B. Control animals underwent temporal resolution (Ramirez et al. 2013). These notions similar treatments except did not receive footshock in began in the early 1930s when the British psychologist context B did not show light-induced freezing after train- Frederic Bartlett recited slightly inconsistent fables to ing, although a similar number of DG neurons were la- people from several cultural backgrounds, most famously beled after exposure to context B with or without shock The War of the Ghosts (Bartlett 1932). While recalling (Liu et al. 2012). This indicated that simply activating a the fable, many subjects unintentionally modified the population of DG neurons not associated with a contex- contents of the story into a logical narrative that contained tual fear memory by light stimulation was not the cause of new elements that fit within their cultural milieu. Bartlett freezing. Another control group underwent the same discovered that streams of recalled contextual informa- treatment as the experimental group including the foot- tion could act as a modifiable scaffold onto which infor- shock in B, but expressed only EYFP instead of ChR2 and mation is added or distorted. Indeed, memories are not also failed to show light-induced freezing after training, immutable video records of the experienced past that are indicating that potential sensitization of light after fear projected onto a mental theater; they are mnemonic rivers conditioning also could not account for the behavior. that ebb and flow and thereby reconstruct the neuronal These two controls reflected the requirement of both riverbeds that structurally support various streams of the presence of a fear memory and light activation of information. Bartlett had discovered the labile nature of neurons associated with that memory for the observed memory. light-induced freezing, and thus supported the idea that Since Bartlett, the process of memory “updating” has in the experimental group, activation of neurons associ- been experimentally shown in both humans and rodents. ated with a previous fear memory by light indeed caused Rats given electroconvulsive shocks shortly after recall- the ectopic recall of that memory in an otherwise neutral ing an aversive memory subsequently display profound context (Liu et al. 2012). Taken together, these experi- amnesia for the original event (Misanin et al. 1968). This ments provided the gain-of-function evidence for the process of memory updating, later termed “reconsolida- memory engram cells, suggesting these cells are suffi- tion,” was rediscovered in 2000 and shown to be depen- cient for the memory. dent on protein synthesis in the lateral amygdala (Nader The artificial recall of the memory was also faithful to et al. 2000) or hippocampus depending on the type of some extent, as it showed contextual specificity. Experi- memory recalled (Debiec et al. 2002). Examples abound ments have shown that two statistically independent (Liu in humans that highlight the dramatic instances in which et al. 2012) or even distinct (Deng et al. 2013) popula- distorted memories of crime scenes, childhood events, tions of DG neurons are active in two different contexts. and traumatic experiences—often recalled under interro- We examined the cross talk between neuronal ensembles gation in the court of law or during psychotherapy ses- representing different contexts by testing if artificial ac- sions—disrupt both individual well-being and modern tivation of neurons representing one context could induce jurisprudence (Loftus 2003; Schacter and Loftus 2013). the recall of memory associated with another context. If Of course, although the rich repertoire of human false the neurons active in a neutral context A were labeled memories is difficult to fully model in animals, a starting while the animals were off Dox, followed by fear condi- point is to take a Pavlovian approach and deconstruct tioned in a different context B while on Dox, the animals the learning process into conditioned stimuli (CSs) and did not display freezing behavior upon light stimulation unconditioned stimuli (USs) associations. A series of re- in a third context (Liu et al. 2012). This results showed cent studies have successfully showed the proof of prin- that light activation of a neuronal population associated ciple of artificially linking CSs and USs to form novel with a neutral context will not elicit the recall of another associative memories. For instance, Johansen et al. fear-conditioned context, as long as the neuronal repre- (2010) showed that optically activated lateral amygdala sentation of these two contexts are orthogonal, thus (LA) cells were sufficient to substitute as a US during supporting the context specificity of the light-induced tone (CS) presentations and, upon subsequent tone pre- fear memory recall. This observation is also consistent sentations, animals displayed fear behavior despite the with the proposed patter separation function of the DG CS and US having never been naturally, or exogenously, (Leutgeb et al. 2004). This study showed that the behavior presented. Another study showed that an activated popu- expression of a memory could be controlled from the lation of pyriform cortex neurons, when paired with re- neuronal ensemble level and opened possibilities for fur- wards or shocks, could drive the associated appetitive or ther memory manipulations using the engram cell meth- aversive behavioral output upon stimulation of the same od, as we will discuss below. neurons (Choi et al. 2011). Moreover, pairing footshocks with optogenetically reactivated secondary auditory cortex and medial geniculate nucleus (MGN) inputs to the LA was also sufficient to form an associative fear mem- GENERATING FALSE MEMORIES BASED ory to the optically activated terminals (Kwon et al. ON MEMORY ENGRAM CELLS 2014). A more recent study elegantly showed that opti- The experimental realization of reactivating discrete cally inducing long-term potentiation (LTP) or long-term memories in the rodent brain (Liu et al. 2012) enabled depression (LTD) from MGN terminals into the LA was Downloaded from symposium.cshlp.org on July 1, 2015 - Published by Cold Spring Harbor Laboratory Press

4 LIU ET AL. sufficient to promote or inhibit a previously formed mem- created displayed robust freezing behavior only during ory, thus engineering the inactivation and reactivation of light-on epochs (Fig. 2B). In other words, the expression a specific memory and causally linking its expression to of the false memory was behaviorally similar to the light- these types of synaptic plasticity (Nabavi et al. 2014). induced expression of a natural fear memory as previous- Finally, a context-specific artificial memory was rely reported (Liu et al. 2012). cently achieved using the “engram-labeling” technology Together, these data suggest that optical reactivation of (Ramirez et al. 2013). Animals were first taken off Dox hippocampal dentate gyrus cells that were previously ac- to open a window for activity-dependent labeling and tive during context exploration is sufficient to act as an exposed to a neutral environment (context A). Thus, artificial, context-specific CS during fear conditioning. DG cells active during the exploration of context A This thereby forms an artificial CS–US association, or became ChR2-positive (Fig. 2A). While back on Dox— a putative false memory, because the artificially construct- and thus the window for activity-dependent labeling was ed memory never had its contiguous experiences naturally closed—animals were then exposed to context C. The linked (Ramirez et al. 2013). These results are consistent following day, fear conditioning occurred in context B with the temporal context model (TCM) in humans, which with or without light stimulation of DG cells. In this positsthat contextual memory reactivation can be linked to experiment, even though the animals had a memory for novel information that is presented at the time of reactiva- both context A and C, only the neuronal populations action (Gershman et al. 2013; St Jacques and Schacter 2013). tivated by the former was ChR2-positive and presumably Notably, the formation of false memories in humans often reactivated during fear conditioning in context B. We occurs as a result of recombining mnemonic elements of hypothesized that, if DG cells previously active during discrete experiences into a new, reconstructed memory context A exploration defined an active neural population that is not a veridical representation of the past. These sufficient for memory recall, then optogenetic activation memories are not de novo and require preexisting mem- of these cells during fear conditioning in context B should ories as a scaffold onto which distinct experiences can be form an artificial association between the light-induced incorporated to update the memory itself (Tse et al. 2007; context A memory and aversive information (e.g., foot- Gershman et al. 2013). Similarly, in all rodent studies to shocks). To test this possibility, animals were first placed date, any artificial memories generated were not de novo back in context C (C0) and showed low basal levels of constructions; rather, they are results of artificially link- freezing (Fig. 2A). However, when placed back in context ing either a preexisting memory or concurrent learning A(A0), only the animals in which DG cells were reacti- processes with events of high valence. vated displayed robust freezing behavior, indicating that a false memory for context A had been artificially formed. CHANGING MEMORY VALENCE THROUGH Moreover, when placed in another neutral environment MEMORY ENGRAM CELLS (context D), control animals showed basal levels of freezing during light-off and light-on epochs, whereas the ex- After demonstrating the possibility to assign negative perimental group in which an artificial memory had been valence to an original neutral DG engram (Ramirez et al.

Figure 2. Creation of a false memory. (A)(Top) c-fos-tTA mice injected with AAV9-TRE-ChR2-mCherry in the DG were taken off Dox and exposed to context A to label correspondingly activate DG cells with ChR2-mCherry and then put back on Dox and exposed to context C the following day. A control group injected with AAV9-TRE-ChR2-mCherry did not receive light stimulation during fear conditioning (ChR2-mCherry, no light). (Bottom) animals’ freezing levels in context A and C before and after fear conditioning with or without light revealed that a false memory had been formed only in the group in which DG stimulation occurred during fear conditioning in context B; (P , 0.001). (B) Animals that underwent the behavioral protocol shown in the top panel were exposed to a novel context D, and the freezing levels were examined both in the absence and presence of light stimulation (P ¼ 0.007). Downloaded from symposium.cshlp.org on July 1, 2015 - Published by Cold Spring Harbor Laboratory Press

MEMORY ENGRAM CELLS 5

2013), we set out to identify the nodes of the circuit positive emotion (i.e., female contact, day 7 in Fig. 3A), capable of associating valence to contextual representa- the circuit changed so that subsequent activation of the tions. If the DG processes contextual information, the DG ensemble drove an appetitive behavioral response on main hub for emotional learning in the brain is the amyg- day 9 (Fig. 3A,B) and no longer produced an aversive dala, a group of nuclei deep in the temporal lobe that response (Fig. 3C). After the induction protocol on day when lesioned impairs emotion but spares memory in 7, the BLA engram failed to produce an appetitive re- tasks without emotional components (Zola-Morgan sponse on day 9 (Fig. 3B) and retained the ability to drive et al. 1991; Anderson and Phelps 2001). What are the an aversive response upon its activation (Fig. 3C). A contributions of the DG and the amygdala to the memory symmetrical result was obtained when DG ensembles engram? In Redondo et al.’s (2014) study, neuronal en- originally linked to an appetitive memory were optoge- sembles that up-regulated c-fos at the time of memory netically reactivated during fear learning: The output of encoding were manipulated in the DG or in the basolat- the DG engram then drove an aversive response (Redondo eral amygdala (BLA). Active avoidance responses were et al. 2014). detected when mice reduced the time spent in a side of a To understand how the functional connectivity be- maze where laser stimulation was delivered (OptoPA tween the DG and the BLA had changed, the DG and test). Active appetitive responses were identified by an the BLA engram were simultaneously labeled in a group increase in the time spent inside the zone targeted with of mice during memory encoding (Fig. 3D). On day 3, laser (OptoPP test). First, we showed that both DG and mice were divided into three groups: one experienced a BLA engrams are capable of driving an aversive response US of opposite valence to that encoded on day 1 without (day 5; Fig. 3A,B). Then, after pairing the optogenetic laser stimulation (USþ, Light2); another received an in- reactivation of the DG engram while mice experience a duction protocol pairing the presentation of a US of op-

Figure 3. Reversal of the valence associated with the hippocampal memory engram. (A) Daily protocol with labeling of fear memory engram (day 3) and later its reactivation during a pleasurable experience (day 7). (B) Only in the DG engram but not in the BLA engram, the aversive response driven on Day 5 (reduction in time spent in the area where the memory engram is reactivated) is reversed into an appetitive response on day 9. (C) Only in the DG engram but not in the BLA engram, the aversive response on day 5 is eliminated on day 9. (D) Daily protocol depicting the labeling of an engram (day 1) followed by induction (day 3) and ending in the reactivation of the DG engram and brain extraction (day 5). (E) Representative images of the BLA showing engram neurons labeled on day 1 (red) and neurons reactivated on day 5 (green). All groups show high overlap except the group that underwent the valence reversal protocol. (F) Bar graphs quantifying similar levels of labeling and activation in the BLA across groups. However, only the group that underwent induction shows a reduced reactivation score that approximates to chance levels. (G) Summary graph depicting the potential of contextual information from the hippocampus to associate with amygdala neurons specialized in driving appetitive or aversive responses. Downloaded from symposium.cshlp.org on July 1, 2015 - Published by Cold Spring Harbor Laboratory Press

6 LIU ET AL. posite value to that encoded with optogenetic stimulation memory (Ramirez et al. 2013). This could be a potential (Lightþ,USþ), and the last group received optogenetic mechanism whereby false memories are formed. Third, stimulation without US delivery (Lightþ,US2). On day 5 pairing the activation of a memory of certain valence all animals had the DG ensembles reactivated optogeneti- while experiencing an event of opposite valence can re- cally and 90 min later the brains were collected and pro- verse the valence originally associated with the memory. cessed for immunohistochemistry. Green fluorescence This alteration of memory valence is possibility due to revealed those neurons that had recently up-regulated c- changes of functional connectivity between the hippo- fos, whereas red fluorescence identified the neurons ex- campus and the amygdala (Redondo et al. 2014). pressing ChR2-mCherry labeled on day 1 (Fig. 3E). The What we discussed here are just some examples of laser stimulation delivered to the DG was equally effec- memory-related questions that can be answered by this tive across groups at reactivating the DG engram (data not new engram cell–based technology. There are ample shown). Also in the BLA, the three experimental groups equally exciting yet unexplored topics waiting to be ad- had the same amount of cells labeled (mCherryþ/ dressed. For example, what plasticity changes are hap- DAPIþ) and the same levels of c-fos activation (GFPþ/ pening inside these cells harboring memory engrams? DAPIþ) (Fig. 3F). However, although the control groups What are other memory engram pathways inside the (USþ, Light2 and Lightþ,US2) showed high levels of brain? Can we use this technology to tackle disease mod- reactivation, the animals that experienced the induction els for mental disorders, such as depression and anxiety? protocol on day 3 had a decreased level of reactivation With the fast evolving new technology, we have reason to very close to the levels expected by chance (Fig. 3E,F). believe that the memory engram cell–related studies will Two main conclusions can be drawn from these data: continue to bring deeper insights and exciting new dis- First, activating the DG ensemble reactivates the BLA coveries in the years to come. neuronal population colabeled during memory encoding; and second, the induction protocol changes the connectivity between the DG and the BLA in such a way that ACKNOWLEDGMENTS even though the DG drives a similar number of neurons in the BLA, the identity of the activated BLA population has We thank P. Pang, C. Puryear, A. Govindarajan, P. Lin, changed and no longer corresponds to those neurons that J. Suh, M. Pignatelli, T.J. Ryan, J. Kim, and A. Arons for were active during memory encoding. That is, after re- help with the experiments and all the members of the versing the valence associated with a DG ensemble, the Tonegawa laboratory for their support. This work was output from the DG drove a different population of amyg- supported by RIKEN Brain Science Institute and Howard dala neurons. Hughes Medical Institute to S.T. The emerging picture of the circuit for memory valence depicts a series of neutral components of the engram (DG) free to associate with either positive or REFERENCES negative valences coded by nodes downstream in the cir- Anderson AK, Phelps EA. 2001. Lesions of the human amyg- cuit (BLA) (Fig. 3G). The development of new technol- dala impair enhanced perception of emotionally salient ogies capable of altering the connectivity between the events. Nature 411: 305–309. nodes in the circuits of memory valence opens up the Bartlett FC. 1932. 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Identification and Manipulation of Memory Engram Cells

Xu Liu, Steve Ramirez, Roger L. Redondo, et al.

Cold Spring Harb Symp Quant Biol published online January 30, 2015 Access the most recent version at doi:10.1101/sqb.2014.79.024901

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Activating positive memory engrams suppresses depression-like behaviour

Steve Ramirez1, Xu Liu{, Christopher J. MacDonald1, Anthony Moffa1, Joanne Zhou1, Roger L. Redondo1,2 & Susumu Tonegawa1,2

Stress is considered a potent environmental risk factor for many active/passive escape behaviour in response to a challenging situation, behavioural abnormalities, including anxiety and mood disor- and the sucrose preference test (SPT) for anhedonia10–14. In unstressed ders1,2. Animal models can exhibit limited but quantifiable beha- animals, optogenetic reactivation of cells previously active during a vioural impairments resulting from chronic stress, including positive experience did not significantly change anxiety-related mea- deficits in motivation, abnormal responses to behavioural sures, time spent struggling, or preference for sucrose compared to challenges, and anhedonia3–5. The hippocampus is thought to unstressed mCherry controls (Fig. 1b–e). In the stressed groups, the negatively regulate the stress response and to mediate various cog- CIS paradigm elicited a robust decrease in time struggling and pref- nitive and mnemonic aspects of stress-induced impairments2,3,5, erence for sucrose, as well as increased anxiogenic responses, consist- although the neuronal underpinnings sufficient to support beha- ent with previous reports13,14 (Fig. 1b–e). vioural improvements are largely unknown. Here we acutely rescue However, optically reactivating dentate gyrus cells that were prev- stress-induced depression-related behaviours in mice by optogen- iously active during a positive experience, but not a neutral or a nega- etically reactivating dentate gyrus cells that were previously active tive experience, in stressed animals acutely increased time struggling during a positive experience. A brain-wide histological investiga- and sucrose preference to levels that matched the unstressed group’s tion, coupled with pharmacological and projection-specific opto- behaviour (Fig. 1b, c). Additionally, optical reactivation of dentate genetic blockade experiments, identified glutamatergic activity in gyrus cells associated with a positive experience decreased the latency the hippocampus–amygdala–nucleus-accumbens pathway as a to feed in a novelty-suppressed feeding test (NSFT)14 (Extended Data candidate circuit supporting the acute rescue. Finally, chronically Fig. 3a) without affecting hunger or satiety (Extended Data Fig. 3b). reactivating hippocampal cells associated with a positive memory Once again, the CIS paradigm had an anxiogenic effect across all resulted in the rescue of stress-induced behavioural impairments groups, and all groups failed to show light-induced behavioural and neurogenesis at time points beyond the light stimulation. changes in the OFT or EPMT (Fig. 1d, e). Similarly, total distance Together, our data suggest that activating positive memories arti- travelled was consistent across groups (Extended Data Fig. 4c). ficially is sufficient to suppress depression-like behaviours and Taken together, these data argue that reactivating dentate gyrus cells point to dentate gyrus engram cells as potential therapeutic nodes labelled by a positive experience is sufficient to acutely reverse the for intervening with maladaptive behavioural states. behavioural effects of stress in the TST, SPT and NSFT. Our recent studies have demonstrated that dentate gyrus cells that To identify potential neural loci that mediate the light-induced express c-Fos during fear or reward conditioning define an active reversal of the stress-induced behaviours observed in our experiments, neural population that is sufficient to elicit both aversive and appetitive all subjects first underwent the CIS protocol and then were exposed to responses, and that the mnemonic output elicited by these artificially the TST while dentate gyrus cells previously active during a positive reactivated cells can be updated with new information6–8. These find- experience were optically reactivated. We then performed a brain-wide ings raise the possibility of alleviating stress-induced behavioural mapping of c-Fos expression in areas activated by this treatment impairments via a defined set of dentate gyrus cells that are active (Fig. 2a). during a positive experience. Indeed, how positive episodes interact Optical reactivation of dentate gyrus cells labelled by a positive with psychiatric-disease-related behavioural states, including depres- experience correlated with a robust increase of c-Fos expression in sion-related impairments, at the neuronal and systems level remains several brain areas, including the nucleus accumbens (NAcc) shell, largely unknown, despite the promising cognitive treatments available lateral septum, basolateral amygdala (BLA), central amygdala, as well in humans9. as the dorsomedial, ventromedial, and lateral hypothalamus (Fig. 2b–i To address this issue, we used our recently developed method that and Extended Data Fig. 5a, b), but not in the medial prefrontal cortex enables labelling and manipulation of memory engram cells (see (mPFC) (Fig. 2j–m) or in several other loci (Extended Data Fig. 5c–e). Methods)6–8. Exposing animals that were taken off doxycycline to a Furthermore, we monitored single-unit activity in the BLA of mice naturally rewarding experience8 (that is, exposure to a female mouse in while simultaneously activating dentate gyrus positive memory- a modified home cage, hereafter referred to as a ‘positive experience’ engram cells with blue light and found that ,8% of cells (9/106; and further validated in Extended Data Fig. 1), a neutral context (here- n 5 3 mice) had excitatory (8/9 cells) or inhibitory (1/9 cells) responses after referred to as a ‘neutral experience’), or a single bout of immob- (Extended Data Fig. 4a). A parallel set of experiments in which ilization stress (hereafter referred to as a ‘negative experience’) all unstressed animals received optical stimulation of dentate gyrus cells elicited comparable levels of ChR2–mCherry expression in the dentate revealed mostly similar patterns of c-Fos expression (Extended Data gyrus (Extended Data Fig. 2a–e). Fig. 6). As shown in Fig. 1a, mice were split into six groups (see Methods). The NAcc has been heavily implicated in stress responses, mood After 10 days of chronic immobilization stress (CIS) (Extended Data disorders, and processing natural rewards2,5,10–12,15–20.Moreover,patho- Fig. 2f) or in a home cage, all groups were put through the open field physiological dysfunction of the NAcc in response to various stressors test (OFT) and elevated plus maze test (EPMT) as measures of anxiety- has been implicated in anhedonia and reward conditioning17–20.Our like behaviours, as well as the tail suspension test (TST) as a measure of within-subject experiments revealed that, in the TST, the behavioural

1RIKEN-MIT Center for Neural Circuit Genetics at the Picower Institute for Learning and Memory, Department of Biology and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. 2Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA. {Deceased.

a Positive Neutral Behaviour Group Label period ChR2 Stress a memory context Stress tests mPFC HPC On Dox Off Dox On Dox Positive memory + + LS LH Positive memory + stress (ChR2) × 1 1 10 Nacc Hyp. Neutral memory + stress (ChR2) Positive memory – (mCherry) + VTA Positive memory + stress (mCherry) BLA On Dox Off Dox On Dox Positive memory + – 2 Home cage 2 NAcc shell 250 Positive memory – (mCherry) – b NS ** On Dox Off Dox On Dox 200 150 3 × 3 Neutral memory + + 10 100 cells in field + 50 On Dox Off Dox On Dox 0 4 Positive c-Fos ×1 ×9 4 Negative memory + + Neutral mCherry Nacc core Nacc shell c CeA b TSTc SPT 100

** 80 250

# Positive Neutral mCherry # 200 ** * 60 * BLA 150 50 100

40 cells in field + 50 20

Time struggling (s) 0 Positive Neutral mCherry c-Fos BLA CeA 0 Sucrose preference (%) 0 LightOff On Off Light Off On d mPFC 3 min 3 min 3 min 15 min 15 min d e OFT EPMT NS 50 30 400 40 300 20 30 200

cells in field

# 100 20 # 10 0 10 Positive Neutral mCherry c-Fos mPFC

0 Duration in open arms (s) 0 Average time in centre (s) Light OffO Onn Off Light Off On Off Figure 2 | Positive memory reactivation increases c-Fos expression in the 3 min 3 min 3 min 5 min 5 min 5 min nucleus accumbens shell and the amygdala. a, Brain diagram illustrating Figure 1 | Activating positive memory engrams rescues depression-related target areas analysed. b–d, Activation of a positive memory, but not a neutral behaviour. a, Behaviour schedule and groups used. Dox, doxycycline. memory or mCherry only, in the dentate gyrus during the TST elicits robust Female symbols represent exposure to a female conspecific, white hexagons c-Fos expression in the nucleus accumbens shell (b), basolateral amygdala, and represent neutral contexts, and mice in the ‘stress’ condition are depicted central amygdala (c), but not in the medial prefrontal cortex (d). For undergoing an immobilization protocol. b–e, Optical reactivation of dentate histological data, a one-way ANOVA followed by a Bonferroni post hoc test gyrus cells that were previously active during a positive experience significantly revealed a significant increase of c-Fos expression in the positive memory plus increases time struggling in the tail suspension test (b) and preference for stress group relative to controls in the NAcc and amygdala, but not the mPFC 5 , 5 , sucrose (c), but does not have a significant effect in anxiety-like behaviour in the (NAcc shell, F2,30 15.2, P 0.01; BLA, F2,30 11.71, P 0.01; central 5 , 5 5 5 open field test (d) or elevated plus maze test (e). A two-way analysis of variance amygdala, F2,30 11.45, P 0.05; mPFC, F2,30 1.33, P 0.294. n 6 * , (ANOVA) with repeated measures revealed a group-by-light epoch interaction animals per group, 3–5 slices per animal). NS, not significant; P 0.05, **P , 0.01. Data are means 6 s.e.m. Scale bars correspond to 100 mm. HPC, in the TST (F5,294 5 21.20, P , 0.001) or SPT (F5,196 5 6.20, P , 0.001) followed by Bonferroni post hoc tests, which revealed significant increases in hippocampus; LH, lateral habenula; LS, lateral septum; Hyp., hypothalamus. struggling or preference for sucrose in the positive memory plus stress group. #P , 0.01. # used to denote significant differences between the four stressed of BLA neurons and simultaneous activation of ChR2–mCherry- groups (n 5 18 per group) versus the two non-stressed groups (n 5 16 per positive dentate gyrus cells, respectively, in stressed mice. At the neur- group); *P , 0.05, **P , 0.01 (orange asterisks used to denote significant onal level, light-induced reactivation of dentate gyrus cells previously differences between the stress plus positive memory group versus the other activated by a positive experience also reactivated BLA8 and NAcc18, three stressed groups). Data are means 6 s.e.m. but not mPFC, cells (that is, endogenous c-Fos1 cells, red) previously activated by the same positive experience (that is, ArchT–eGFP1 cells, effects of optically reactivating dentate gyrus cells labelled by a positive green) (Fig. 3c). These results suggest that the dentate gyrus engram experience were blocked in the group of mice that concurrently received cells are functionally connected to BLA engram cells and NAcc engram the glutamate receptor antagonists NBQX and AP5 in the NAcc, but not cells. At the behavioural level, inhibition of BLA terminals onto the in the group that received saline, without altering basal locomotion NAcc blocked the dentate gyrus light-induced rescue in both the TST (Extended Data Fig. 4b, c). Blocking dopaminergic activity yielded a and SPT (Fig. 3d–g). Within the same behavioural session for the TST, similar blockade of the dentate gyrus light-induced effects (Extended and across 2 days for the SPT, when ArchT-mediated inhibition was Data Fig. 7a). released (that is, the green light was turned off), the rescue effects of The BLA is known to have robust glutamatergic inputs to the reactivating dentate gyrus cells previously active during a positive NAcc19, and previous studies have implicated BLA projections to the experience were rapidly observed in all groups (Fig. 3d–g). ArchT- NAcc in enabling reward-seeking behaviour19. We therefore investi- mediated inhibition of BLA–NAcc terminals alone did not negatively gated whether the hippocampus (dentate gyrus)–BLA–NAcc func- affect behaviour in the TST or SPT beyond the levels of the stressed tional pathway is crucial for the real-time light-induced rescue of animals (Fig. 3d–g insets). The specificity of the hippocampus (dentate depression-related behaviour. Our transgenic mice were bilaterally gyrus)–BLA–NAcc pathway for the rescue was supported by an ana- injected with TRE–ArchT–eGFP into the BLA to allow for activity- logous experiment conducted with bilateral injections of TRE–ArchT– dependent ArchT–eGFP labelling of axonal terminals from the BLA to eGFP into the mPFC. Although the mPFC is also known to provide theNAccinresponsetoapositiveexperience21 (Fig.3a,b).Opticfibres robust glutamatergic input to the NAcc19, the induction of c-Fos were bilaterally placed over the NAcc and the dentate gyrus to allow for expression in this area upon optogenetic activation of dentate gyrus real-time inhibition of these terminals originating from ,18% (Fig. 3c) cells associated with a positive experience was not significantly higher

336 | NATURE | VOL 522 | 18 JUNE 2015 G2015 Macmillan Publishers Limited. All rights reserved LETTER RESEARCH than that observed with a neutral experience (Fig. 2m), and mPFC cells Recent meta-analyses have suggested that treating psychiatric reactivated by dentate gyrus cell reactivation was at chance level disorders through prescribed medication or cognitive interventions (Fig. 3c). Correspondingly, inhibition of terminals originating from are capable of producing symptom remission when administered ,12% of the mPFC (Fig. 3c) onto the NAcc did not block the dentate chronically20, though the neural underpinnings inducing and correl- gyrus light-induced rescue in either the TST or SPT (Fig. 3d–g). ating with long-lasting rescues are poorly understood20,22,23. The afore- Moreover, inhibition of BLA, but not mPFC, terminals onto the mentioned acute intervention did not induce enduring behavioural NAcc partially inhibited the dentate-gyrus-mediated, light-induced changes (Extended Data Fig. 7b). We therefore investigated whether increase of c-Fos1 cells observed in the NAcc shell (Fig. 3h), supporting chronic reactivation of dentate gyrus engram cells could attenuate the conclusion that the hippocampal (dentate gyrus)–BLA–NAcc path- depression-related behaviours in a manner that outlasted acute optical way of positive engrams plays a crucial role in the rescue of depression- stimulation following the protocol depicted in Fig. 4a (Methods). A related behavioural phenotypes. group in which dentate gyrus cells associated with a positive experience were optically reactivated across 5 days, but not 1-day or no stimulation groups, showed a reversal of the stress-induced beha- ab vioural deficits measured in the TST and SPT that was not significantly HPC mPFC different from an unstressed control group (Fig. 4b, c). A group LH LS in which dentate gyrus cells associated with a neutral experience Hyp. Nacc VTA were optically reactivated across 5 days did not show such effects, BLA BLA NAcc nor did a group that was exposed to a natural social reward for 5 days

mPFC HPC (Fig. 4b–d). Histological analyses revealed decreased levels of neuro-

LH genesis as measured both by the polysialylated neuronal cell adhesion LS Hyp. VTA molecule (PSA-NCAM) and doublecortin (DCX)—often considered Nacc 24,25 BLA mPFC NAcc markers of developing and migrating neurons —in all stressed

c Positive DG light groups except for the positive experience and 5-day stimulation group, experience reactivation Overlap ArchT–eGFP+ cells (ArchT–eGFP+) (c-Fos–RFP+) (ArchT and c-Fos) (percentage of DAPI) and the unstressed control group (Fig. 4d and Extended Data Fig. 8). This increase in adult-born neurons positively correlated with the 20 degree to which each group preferred sucrose in the SPT (Extended Data Fig. 9a); moreover, performance levels on the SPT and TST 10 positively correlated with one another on an animal-by-animal basis mPFC (Extended Data Fig. 9b). NAcc mPFC 0 BLA Our data demonstrate that the depression-related readouts of active/passive coping-like behaviour and anhedonia, as measured in ArchT and c-Fos overlap (1 = chance) the TST and SPT, respectively, can be ameliorated by activating cells in the hippocampus associated with a positive memory, while anxiety- No light related behaviours measured by the OFT and EPMT remained BLA 1.0 unchanged. Differential regulation of depression- and anxiety-related behaviour could have been achieved by leveraging the functional 0

Light Figure 3 | The antidepressant effects of an optically activated positive memory require real-time terminal activity from the BLA to the NAcc. **

NAcc 2.0 * a, Brain diagram illustrating target areas manipulated. b, Representative 1.0 coronal slices showing TRE–ArchT–eGFP-positive cells in the BLA or mPFC, as well as their corresponding terminals in the NAcc. Scale bars: BLA and 0 mPFC, 500 mm; NAcc, 200 mm. c, Animals were taken off Dox and initially mPFC–NAcc (ArchT); DG (ChR2) BLA–NAcc (ArchT); DG (ChR2) BLA–NAcc (eGFP); DG (ChR2) exposed to a positive experience, which caused labelling of corresponding BLA (,18%), mPFC (,12%), or NAcc (,9%) cells with eGFP derived from d e 80 *** 80 AAV9-TRE-ArchT-eGFP (green, halo-like expression). Light-activation of a positive memory engram in the dentate gyrus (DG) preferentially reactivated 60 60 the BLA and NAcc shell cells, as measured by endogenous c-Fos expression (red, nucleus-localized), that were originally labelled by the same positive 40 40 80 80 * experience, while groups with no light stimulation showed levels of overlap not 20 20 significantly different from chance. Arrowheads indicate double-stained cells. Time struggling (s) 0 Time struggling (s) 0 Scale bar, 5 mm. d–g, ArchT-mediated inhibition of BLA, but not mPFC, ArchT Off On Off ArchT Off Off On 0 0 terminals in the NAcc prevents the dentate-gyrus-mediated light-induced ArchT Off On Off ArchT Off Off On increases in struggling (d, e) or preference for sucrose (f, g), while inhibition of ChR2 Off ChR2 Off On On On On BLA terminals in the NAcc without dentate gyrus stimulation does not affect 3 min 3 min 3 min 3 min 3 min 3 min behaviour (insets). h, ArchT-mediated inhibition of BLA, but not mPFC, f g h terminals prevents the dentate-gyrus-mediated light-induced increase of c-Fos 80 80 expression in the NAcc. For behavioural data, a two-way ANOVA with NS repeated measures followed by a Bonferroni post hoc test revealed a group-by- 200 60 60 light epoch interaction and significant ArchT-mediated attenuation of * ** struggling in the TST (d: F2,99 5 7.30, P , 0.001; e: F2,99 5 6.61, P , 0.01) or 40 40 80 80 100 preference for sucrose water in the the SPT (f: F2,66 5 10.66, P , 0.01). n 5 12 cells in field + per behavioural group. *P , 0.05, **P , 0.01, ***P , 0.001; orange asterisks 20 20 0 0 Sucrose preference (%) Sucrose preference (%) used to denote significant differences between the stress plus positive memory c-Fos mPFC–NAcc BLA–NAcc (eGFP) ArchT Off On ArchT On Off BLA–NAcc 0 0 0 group versus all other groups. For histological data, one-sample t-tests against NAcc shell ArchT Off On ArchT Off Off chance overlap were performed (n 5 4 per group, 3–5 slices per animal). NS, ChR2 Off On ChR2 Off OOnn not significant. HPC, hippocampus; LH, lateral habenula; LS, lateral septum; 15 min 15 min 15 min 15 min Hyp., hypothalamus. Data are means 6 s.e.m.

a the effects of optically stimulating a positive memory are contingent On Dox Off Dox On Dox on active glutamatergic projections from the amygdala to the NAcc in 18 None real time, as well as intra-NAcc dopamine activity . Our data dovetail with this circuit’s proposed role of relaying BLA stimulus-reward or ×10 associations to a ventral striatal motor-limbic interface. This interface is thought to be capable of coalescing such information with motivational states and finally translating such activity into behaviourally Surgery and Positive or +/– Stress +/– Stimulation, 1 d or 5 d Behaviour 5,17–19 recovery neutral memory tests relevant outputs . Moreover, our chronic stimulation data reveal that repeatedly activ- Group Memory labelled Stress Stimulation ating dentate gyrus engram cells associated with a positive experience 5-day Positive Yes 5 days elicits an enduring reversal of stress-induced behavioural abnormal- 1-day Positive Yes 1 day NoStim Positive Yes None ities and an increase in neurogenesis. While future experiments are Neutral Neutral Yes 5 days required to identify the causal link between chronically reactivated Natural No label Yes 5 days positive memory engrams and the corresponding rescue of behaviours, No stress Positive No 5 days many tantalizing hypotheses surface, including a normalization of VTA firing rates29, epigenetic and differential modification of effector b Tail suspension cdSucrose preference PSA-NCAM+ cells NS NS NS proteins (for example, CREB, BDNF) in areas upstream and down- 10 30 * * ** ** stream of the hippocampus , and a reversal of neural atrophy in areas 80 26 150 8 such as CA3 and mPFC or hypertrophy in BLA . The aforementioned molecular and homeostatic mechanisms—in addition to our observed 60 6 100 increase of adult-born neurons in the 5-day stimulation group—could 40 4 be partly realized in a hormone- or neuromodulator-mediated manner 50 20 2 (Extended Data Fig. 5). Finally, our data demonstrate that exposing stressed subjects to a natural positive experience repeatedly is not Normalized cell counts

Total time struggling (s) 0 0 Sucrose preference (%) 0 effective, while repeated direct reactivations of dentate gyrus engram Figure 4 | Chronic activation of a positive memory elicits a long-lasting cells associated with a previously acquired positive memory is effective rescue of depression-related behaviour. a, Behavioural schedule and groups (Fig. 4b–d). We speculate that invasively stimulating these dentate used. NoStim, no stimulation. Female symbols represent exposure to a female gyrus cells is effective in activating both the internal contextual rep- conspecific, white hexagons represent neutral contexts, and mice in the ‘stress’ resentation associated with a positive experience as well as associated condition are depicted undergoing an immobilization protocol. b, c, Animals in downstream areas, while exposure to natural exogenous positive cues which a positive memory was reactivated twice a day for 5 days showed may not be able to access similar neural pathways in subjects display- increased struggling in a 6-min tail suspension test (F 5 3.34, P , 0.05) 5,78 ing depression-like symptoms such as passive behaviour in challen- (b) and increased preference for sucrose measured over 24 h (F5,84 5 6.25, P , 0.01) (c). d, The 5-day positive memory stimulation group showed a ging situations and anhedonia (Fig. 4b–d). significant increase of adult newborn cells in the dentate gyrus as measured by Collectively, the data described here build a novel experimental 1 PSA-NCAM cells (F5,72 5 4.65, P , 0.01; see Extended Data Fig. 8 for bridge between memory engrams in the brain and animal models of doublecortin data and PSA-NCAM images). For these data (b–d), a one-way psychiatric disorders. We propose that direct activation of dentate ANOVA revealed a significant interaction of the experimental-group factor gyrus engram cells associated with a positive memory offers a potential and stimulation-condition factor and was followed by a Bonferroni post therapeutic node for alleviating a subset of depression-related beha- hoc test. n 5 14 per TST behavioural group, n 5 15 per SPT behavioural viours and, more generally, that directly activating endogenous neur- group, n 5 5 slices per animal for data appearing in d. *P , 0.05. Data are means 6 s.e.m. onal processes may be an effective means to correct maladaptive behaviours. segregation present along the hippocampus dorsal–ventral axis; for Online Content Methods, along with any additional Extended Data display items instance, activation of ventral hippocampal dentate gyrus engram cells and Source Data, are available in the online version of the paper; references unique to these sections appear only in the online paper. could reveal heterogeneous, behaviourally relevant roles in the emotional regulation of anxiety and stress responses that our dorsal hip- Received 14 October 2014; accepted 1 May 2015. pocampus manipulations presumably did not access26,27. To that end, we speculate that, at the engram level, the circuitry sufficient to modu- 1. Caspi, A. et al. Influence of life stress on depression: moderation by a late anxiety-related behaviour relies more heavily on a synaptic dia- polymorphism in the 5-HTT gene. Science 301, 386–389 (2003). 2. 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Dopamine neurons modulate neural encoding and expression of reflect the degree to which directly stimulating positive-memory- depression-related behaviour. Nature 493, 537–541 (2013). engram-bearing cells might bypass the plasticity that normally takes 11. Warden, M. R. et al. A prefrontal cortex-brainstem neuronal projection that controls response to behavioural challenge. Nature 492, 428–432 (2012). antidepressants weeks or months to achieve, thereby temporarily 12. Deisseroth, K. Circuit dynamics of adaptive and maladaptive behaviour. Nature suppressing the depression-like state. In support, we observed that 505, 309–317 (2014).

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METHODS Layers of adhesive cement (C&B Metabond) followed by dental cement (Teets Subjects. The c-fos-tTA mice were generated by crossing TetTag31 mice with cold cure; A-M Systems) were spread over the surgical site and protective cap to C57BL/6J mice and selecting for those carrying the c-fos-tTA transgene. secure the optical fibre implant. The protective cap was made from the top portion of a black polypropylene microcentrifuge tube. Mice received intraperitoneal Littermates were housed together before surgery and received food and water 21 ad libitum. All mice were raised on a diet containing 40 mg kg21 doxycycline injections of 1.5 mg kg analgesics and were placed on heating pads throughout (Dox) for a minimum of 1 week before receiving surgery at age 12–16 weeks. Post- the procedure until recovery from anaesthesia. Histological studies were used to operation, mice were individually housed in a quiet home cage with a reverse 12 h verify fibre placements and viral injection sites. Only data from mice with opsin or light–dark cycle, given food and water ad libitum, and allowed to recover for a fluorophore expression restricted to the dentate gyrus, BLA or mPFC were used for minimum of 2–3 weeks before experimentation. All animals were taken off Dox histological, behavioural and statistical analyses. for an undisturbed 42 h to open a time window of activity-dependent labelling. In Pharmacological infusion of glutamate or dopamine receptor antagonists. our system, the promoter of c-Fos—an immediately early gene often used as a Glutamate antagonists were bilaterally infused into the NAcc as follows: 0.2 ml marker of recent neural activity—is engineered to drive the expression of the per hemisphere of NBQX at a concentration of 22.3 mM to antagonize AMPA tetracycline transactivator (tTA), which in its protein form binds to the tetracy- (a-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptors and 0.2 ml cline response element (TRE). Subsequently, the activated TRE drives the light- per hemisphere of AP5 at a concentration of 38.04 mM to antagonize NMDA responsive channelrhodopsin-2 (ChR2). Importantly, the expression of ChR2 only (N-methyl-D-aspartate) receptors. Dopamine receptor antagonists were bilaterally occurs in the absence of doxycycline (Dox) from the animal’s diet, thus permitting infused into the NAcc as follows: 0.2 ml SCH23390 at a concentration of 6.16 mM inducible expression of ChR2 in correspondingly active cells. to antagonize D1-like receptors and 0.2 ml raclopride at a concentration of 2.89 Each group of male mice was exposed to all three subsequent treatments for 2 mM to antagonize D2-like receptors. A 26-gauge stainless steel double internal hours and randomly assigned which experience would occur while off Dox; a cannula (PlasticsOne) was used to bilaterally infuse each drug; the internal cannula negative experience (that is, a single bout of immobilization stress, see below), was connected with a microsyringe pump by a PE20 tube to control the injection a naturally rewarding experience (that is, exposure to a female conspecific while in rate at 100 nl min21. The injection cannula was left connected for 5 min before a modified home cage, as previously reported32), and a neutral experience (that is, removal to allow for diffusion. Finally, all behaviour was performed 20 min fol- exposure to a conditioning chamber). For female exposure, single-caged male mice lowing drug infusion. were moved to a behaviour room distinct from the housing room and with dim Immunohistochemistry. Mice were overdosed with 750–1000 mg kg21 Avertin lighting conditions. Next, the cage tops were removed and a 4-sided (31 3 25 3 30 and perfused transcardially with cold PBS, followed by 4% paraformaldehyde cm) white box was placed over the home cage, after which a female mouse was (PFA) in PBS. Extracted brains were kept in 4% PFA at 4 uC overnight, then introduced to the home cage. Importantly, this modification to the home cage transferred to PBS. A vibratome was used to recover 50-mm coronal slices in cold during female exposure ensured similar levels of dentate gyrus labelling as the PBS. Slices were washed with PBS-T (PBS 1 0.2% Triton X-100), then incubated neutral and negative memory exposure groups (Extended Data Fig. 2). Each group with PBS-T 1 5% normal goat serum at 4 uC for 1 h for blocking. For immuno- was taken off Dox only during one of the aforementioned treatments and placed staining, slices were incubated with one or more primary antibodies (1:1000 back on Dox immediately afterwards. The subjects were age-matched and split dilution) at 4 uC for 24 h (600-401-379 Rockland; A10262, Invitrogen; SC-52, into two groups: a stressed group and a non-stressed group. Non-stressed animals Santa Cruz). Three washes of PBS-T for 10 min each were performed on the slices remained in their home cages before experimentation. Stressed animals under- before 1 h incubation with secondary antibody at 1:200 dilution (A11039, went 2–3 h of chronic immobilization stress (CIS) each day for ten consecutive Invitrogen; A21429, Invitrogen). Slices were washed three more times in PBS-T days before behavioural testing using Mouse DecapiCone disposable restrainers. for 10 min each, stained with 49,6-diamidino-2-phenylindole (DAPI; 1:10,000 All procedures relating to mouse care and treatment conformed to the institutional dilution) to label cell nuclei and mounted with Vectashield H-1200 onto micro- and National Institutes of Health guidelines for the Care and Use of Laboratory scope slides. 32–34 Animals. Sample sizes were chosen on the basis of previous studies ; variance Behavioural assays. All behaviour assays were conducted during the light cycle of was similar between groups for all metrics measured. No statistical methods were the day (7:00–19:00) on animals 12–16 weeks old. Mice were handled for 3–5 days, used to predetermine sample size. 2 min per day, before all behavioural experiments. Virus constructs and packaging. The pAAV -TRE-ChR2-mCherry and pAAV - 9 9 Tail suspension test. Fibre optic implants on experimental mice were plugged TRE-mCherry plasmids were constructed as previously reported33. The pAA into a patch cord before the tail suspension test. Each subject was hung by its tail V -TRE-ArchT-eGFP was constructed by replacing the ChR2-eYFP fusion gene 9 from a bar 40 cm from the ground with a single piece of autoclave tape. The animal in the pAAV -TRE-ChR2-eYFP plasmid from Liu et al.34 with a fusion gene of 9 was positioned such that it had no contact with other objects. Immediately after ArchT-eGFP from Han et al.35. These plasmids were used to generate AAV viruses 9 positioning, video recordings of the animal’s movements were taken (Noldus by by the Gene Therapy Center and Vector Core at the University of Massachusetts 12 Ethovision). Blue light stimulation was given at 20 Hz, 15 ms pulse width, ,15–20 Medical School. Viral titrations were 8 3 10 genome copy per ml for AAV9- 13 mW. For behavioural data appearing in Fig. 1, all mice were exposed to a 9 min tail TRE-ChR2-mCherry, 1.4 3 10 genome copy per ml for AAV9-TRE-mCherry, 13 suspension test with light stimulation occurring at minutes 3–5, inclusive; for and 0.75 to 1.5 3 10 genome copy per ml for AAV9-TRE-ArchT-eGFP. Stereotactic injection, cannulation, and fibre optic implants. All surgeries were histological data appearing in Fig. 2, all mice were exposed to a 6 min tail suspen- performed under stereotaxic guidance and subsequent coordinates are given rela- sion test with light stimulation occurring throughout the entire session using the tive to bregma. Animals were anaesthetized using 500 mg kg21 Avertin before same stimulation parameters described above. For data appearing in Fig. 3, all receiving bilateral craniotomies using a 0.5 mm diameter drill bit at –2.2 mm animals were given a 9 min tail suspension test once a day for 2 days to assess the anterioposterior (AP), 61.3 mm mediolateral (ML) for dentate gyrus injections. effects of ArchT inhibition on BLA or mPFC terminals in the NAcc while simul- All mice were injected with 0.15 ml of AAV9 virus at a controlled rate of 0.6 ml taneously activating ChR2-positive cells in the dentate gyrus. For half of the sub- min21 using a mineral oil-filled glass micropipette joined by a microelectrode jects, on day 1, ArchT-mediated inhibition occurred during minutes 3–5, holder (MPH6S; WPI) to a 10 ml Hamilton microsyringe (701LT; Hamilton) in inclusive, using constant green light at ,25 mW; dentate gyrus stimulation a microsyringe pump (UMP3; WPI). The needle was slowly lowered to the target occurred from minutes 3–8, inclusive. For the other half, ArchT-mediated inhibi- site at –2.0 mm dorsoventral (DV). The micropipette remained at the target site for tion occurred during minutes 6–8, inclusive; and dentate gyrus stimulation another 5 minutes post-injection before being slowly withdrawn. A bilateral occurred from minutes 3–8, inclusive. The treatments occurring on days 1 and optical fibre implant (200 mm core diameter; Doric Lenses) was lowered above 2 were counterbalanced within and across groups. A separate cohort of animals the injection site (–1.6 mm DV for dentate gyrus) and three jewellery screws were were used for the data appearing in the insets of Fig. 3d–g. These groups contained secured into the skull at the anterior and posterior edges of the surgical site to TRE–ChR2–mCherry in the dentate gyrus, as well as bilateral optic fibres over the anchor the implant. For mice used in pharmacological manipulations, bilateral dentate gyrus, and TRE–ArchT–eGFP in the BLA, as well as optic fibres over the guide cannula (PlasticsOne) were implanted above the NAcc (11.2 mm AP; 60.5 NAcc to inhibit BLA terminals during the appropriate light-on epochs in the TST mm ML; –3.25 mm DV). Mice used in the BLA-to-NAcc or mPFC-to-NAcc and SPT. These cohorts, too, were counterbalanced across sessions and only experiments received bilateral injections (0.2 ml to 0.3 ml) of TRE-ArchT-eGFP received green light over the NAcc for 3 min during the TST or 15 min during or TRE-eGFP into the BLA (–1.46 mm AP; 63.20 mm ML; –4.80 mm DV), NAcc the SPT. For the c-Fos counts appearing in Fig. 3h, all groups underwent a 6 min (11.2 mm AP; 60.50 mm ML; 24.3 mm DV), or the mPFC (11.70 mm AP; tail suspension test with blue light delivered to the dentate gyrus and green light 60.35 mm ML; –2.70 mm DV). These mice were then injected with TRE–ChR2– delivered to the NAcc throughout the entirety of the session. These groups were mCherry into the dentate gyrus and received bilateral optic fibre implantation as sacrificed 1.5 h later for histological analyses. For data appearing in Fig. 4, mice described above (Doric Lenses), as well as bilateral optic fibre implantation over were exposed to a 6 min tail suspension test without light stimulation. An experi- the NAcc (11.2 mm AP; 60.50 mm ML; –3.70 mm DV). menter blind to each mouse condition and light treatment scored all the tail

G2015 Macmillan Publishers Limited. All rights reserved LETTER RESEARCH suspension videos by measuring the total time in seconds that each mouse spent blind to the experimental conditions for each mouse. Once placed back into their struggling throughout the protocol. home cages, mice were given a single food pellet, which was weighed before and Sucrose preference test. A Med Associates operant chamber—equipped with after a 5-min test to measure for motivation/hunger effects on feeding behaviour photolickometers placed on two separate corners of the chamber—was used to compared to feeding in a novel environment. count the number of licks made by the mice on lick spouts with direct access to 2% 5-day stimulation protocol. For data appearing in Fig. 4, animals were first split sucrose water solution or water alone. All animals undergoing the sucrose pref- into six groups: a group in which dentate gyrus cells previously active during a erence protocol were water-restricted for 36 h before each habituation session. positive experience were reactivated twice a day for 5 days (5-day group) after These sessions consisted of first plugging the optic fibres on the water-deprived the CIS protocol, a group in which such stimulation occurred twice a day for 1 mice to a corresponding patch cord and exposing the mice to the operant chamber, day (1-day group) after the CIS protocol, a group in which no stimulation was which contained bottles filled only with water. Each exposure occurred on three delivered (NoStim group) after the CIS protocol, a group in which dentate gyrus separate days for 30 min per day. The three habituation sessions occurred inter- cells previously active during a neutral experience were reactivated twice a day spersed throughout the 10-day chronic immobilization stress protocol (that is, on for 5 days (Neutral group) after the CIS protocol, a group that did not receive the days 1, 4 and 7 of stress) at least 6 h before or after the stress protocol. In pilot CIS stress protocol but still had dentate gyrus cells previously active during a experiments, ,90% of water-deprived animals failed to sample both photolick- positive experience reactivated twice a day for 5 days (NoStress group), and ometers in the operant chamber even after multiple 30-min habituation sessions finally, a group that was exposed to a natural social reward (that is, female (data not shown); to address this issue, a glove box was inserted on its side in the mouse) twice a day for 5 days (Natural group). Optical stimulation first occurred operant chamber such that each subject had a narrow ,10 cm corridor to explore at 10:00 for 15 min (blue laser, 20 Hz, 15 ms pulse width, ,15–20 mW) as and find each lick spout. With this modification, .90% of animals found both lick animals explored an operant chamber, and then again at 15:00 for 15 min using spouts during the first and subsequent habituation sessions. Upon completing a the same conditions. The same behavioural schedule was performed for the habituation session, mice were given water only when 2 h of being placed back into Natural group. All groups were exposed for an equal amount of time to each the home cage had elapsed. On the test day (that is, the day on which optical chamber, plugged into a corresponding patch cord, and optical stimulation stimulation occurred), the location of each sucrose or water bottle in the chamber occurred only in the appropriate groups. Each chamber contained dim lighting, was counterbalanced between animal chambers. A 30 min protocol—15 min light white plastic floors, and no artificial odorants. One day after the final stimu- off, 15 min light on—was used on all animals. The first 15 min were used to detect lation, all groups were exposed to a 6 min tail suspension or 24 h sucrose the baseline preference; blue light stimulation at 20 Hz, 15 ms pulse width, ,15–20 preference test as described above. mW, occurred during the second 15 min epoch to detect light-induced changes in Object–female association. Twenty-four wild-type B6 mice were divided in two preference. For data appearing in Fig. 3, water-deprived animals were exposed to groups (neutral-object group, that is, control group, and female-object group, that the same 30-min protocol on two separate days. On day 1, after the first 15-min is, experimental group (n 5 12 per group)). The learning and testing phases were epoch, half of the animals received constant green light stimulation at ,15 mW (as conducted on the same day, 6 h apart. In the learning phase, all mice spent 30 min 36 previously reported ) over the NAcc while simultaneously receiving blue light in their home cage in the middle of a well-lit room with the lid of the cage and stimulation over the dentate gyrus; the other half received only blue light stimu- metal grid holding water and food removed and a 30 cm tall white rectangular lation over the dentate gyrus. On day 2, the treatments were reversed in a counter- frame placed around the home cage to prevent mice from escaping. All the boxes balanced manner. Data was only collected in animals that licked at both spouts in contained one target object (counterbalanced objects within and between groups: the first 15-min interval; animals that did not discover both lick spouts (as evi- empty methanol bottle or cryostat liquid bottle (sealed)). After 3 min exploring the denced by licking only one spout during the first 15-min interval) were not given target object, a wild-type female b6 mouse (age 9 to 16 weeks) was introduced in light stimulation, the experiment was terminated early, and the test was repeated the boxes of the experimental mice and remained there for the next 27 min). The the following day. Sucrose preferences were calculated as follows: control mice did not experience a female mouse and only experienced the object. total number of licks to sucrose spout |100: After a total of 30 min from the beginning of the learning phase, the object and total number of licks to sucrose spoutztotal number of licks to water spout female mouse were removed and the male mice returned to their holding rooms. For the sucrose preference data appearing in Fig. 4, mice were first habituated to In the testing phase, mice were placed in a rectangular arena (70 3 25 3 30 cm) two water bottles for 2 days in their home cages. On day 3, two water bottles with white floors. A video camera resides above the testing chamber where the containing either 2% sucrose or water were placed into the cages in a counter- locations of the subjects were tracked and recorded using Noldus EthoVision XT balanced manner and left undisturbed for 24 h. Sucrose preferences were calcu- video tracking software. Two zones (left and right) on either end of the box (30 3 lated as follows: 30 cm) as well as a neutral zone in the centre of the box (10 cm) were denoted as part of the arena settings. Mice were introduced in the neutral zone of the empty Dweight of sucrose water |100: arena and allowed to explore freely for 3 min. The tracking software monitored Dweight of sucrose water z Dweight of water which of the two zones each individual mouse preferred. After 3 min, the experi- Open field test. An open, metal chamber (Accuscan system) with transparent, menter introduced two objects (empty methanol bottle or cryostat liquid bottle plastic walls was used for the open field test. Implanted mice were plugged into a (sealed)) and placed them in the middle of the left and right zones. For each mouse, patch cord, individually placed into the chamber, and allowed to explore freely for one of the objects was the same as the one experienced during training (target 12 min. An automated video-tracking system (Ethovision by Noldus) was used to object in target zone) and was placed in the least preferred zone. The other object track the amount of time spent in the centre of the chamber compared to the edges, was novel (novel side) and placed in the preferred side. During minutes 6 to 9, as well as the total distance travelled across a session. Light stimulation, as objects were absent from the arena. During minutes 9 to 12, the objects were described above, was given during minutes 3–5 and 9–11, inclusive. reintroduced in the same positions as minutes 3 to 6. Elevated plus maze test. Implanted animals were plugged into a corresponding Cell counting. The number of mCherry or c-Fos immunoreactive neurons in the patch cord before the beginning of the session and subsequently placed in an dentate gyrus and downstream areas were counted to measure the number of elevated plus maze. Two pieces of plastic (30 cm long, 5 cm wide) formed the active cells during defined behavioural tasks in 3–5 coronal slices (spaced 160 two arms of the maze that intersected at right angles. One arm was enclosed with mm from each other) per mouse. Only slices that showed accurate bilateral injec- plastic black walls, and the other arm was open with no walls. The structure was tions in the dentate gyrus were selected for counting. Fluorescence images were elevated 60 cm above the floor and mice were placed one at a time at the inter- acquired using a microscope with a 320/0.50 NA objective. All animals were section of the maze facing into an arm with walls to start a trial. Video tracking sacrificed 90 min post-assay or optical stimulation for immunohistochemical software (EthoVision by Noldus) was used to track the amount of time the mice analyses. The number of c-Fos-positive cells in a set region of interest (0.5 mm2 spent in the enclosed versus the open arms of the maze throughout a 15-min per brain area analysed) were quantified with ImageJ and averaged within each session. Optical stimulation occurred only during the second 5-min epoch using animal. Background autofluorescence was accounted for by applying an equal cut- the same stimulation parameters as noted above. off threshold to all images by an experimenter blind to experimental conditions. Novelty-suppressed feeding. The novelty suppressed feeding paradigm was per- To calculate the percentage of BLA, mPFC, or NAcc cells expressing ArchT–eGFP formed as previously described37. In brief, food was removed from the subjects’ in Fig. 3c, we counted the number of GFP-positive cells and divided by the total home cages 24 h before testing. The next day, mice were placed for 10 min in an number of DAPI-positive cells in each region. Statistical chance was calculated by 2 open field apparatus containing bedding with a food pellet at the centre on a 1 cm multiplying the observed percentage of ArchT–GFP-single-positive cells by the elevated platform. Light stimulation using the parameters described above observed percentage of c-Fos-single-positive cells; overlapsÀÁ over chance were cal- occurred throughout the entire session. All behaviour was videotaped GFPz|c-Fosz DAPI (Ethovision by Noldus) and latency to feed was scored offline by an experimenter culated as observed overlap divided by chance overlap: chance overlap .

A one-way ANOVA followed by Tukey’s multiple comparisons or one-sample into a small recording chamber. In a single recording session, mice were first t-tests were used to analyse data and later graphed using Microsoft Excel with the bilaterally stimulated in the dentate gyrus with blue light (450 nm; Doric Statplus plug-in or Prism. Lenses) for 10 s over 15 such trials in total. As a control, the blue light was replaced Neurogenesis. After all the behaviour tests, on the 15th day since the first day of with red light (640 nm; Doric Lenses) and the mice were given twelve 10-s trials light stimulation, the mice were overdosed with Avertin and perfused transcar- under this condition. The power output for the blue and red lights emitted from dially with cold phosphate buffer saline (PBS), followed by 4% paraformaldehyde the tips of each patch cord was adjusted to 15–18 mW as measured with a standard (PFA) in PBS. Brains were extracted from the skulls and kept in 4% PFA at 4 uC photometer (Thor Labs). The blue and red lasers were powered using a laser diode overnight. Coronal slices 50-mm thick were taken using a vibratome and collected driver (Doric Lenses) triggered by transistor–transistor logic (TTL) pulses emitted in cold PBS. For immunostaining, each slice was placed in PBST (PBS 1 0.2% from a digital I/O card, and these events were also time-stamped and recorded in Triton X-100) with 5% normal goat serum for 1 h and then incubated with primary the Omniplex system. The recording session lasted ,20 min and each tetrode was antibody at 4 uC for 24 h (1:250 mouse anti-PSA-NCAM, Millipore; 1:500 dou- lowered ,0.25 mm after the first recording session. blecortin, AB2253, Millipore). Slices then underwent three wash steps for 10 min Electrophysiological data analysis. Spiking activity was analysed using commer- each in PBST, followed by a 1 h incubation period with secondary antibody (PSA- cial (Neuroexplorer, NEX Technologies) and custom-made software in Matlab NCAM: 1:250 AlexaFluor488 anti-mouse, Invitrogen; Doublecortin: 1:300 (R2014B). To visualize each neuron’s trial-averaged activity for the blue and red A21435, Invitrogen). Slices were then incubated for 15 min with 49,6-diami- light stimulation period, a peristimulus time histogram (PSTH) with 100-ms time dino-2-phenylindole (DAPI; 1:10,000) and underwent three more wash steps of bins was generated with activity time locked to the onset of the blue or red light, 10 min each in PBST, followed by mounting and coverslipping on microscope and then smoothed with a Gaussian kernel (h 5 127 ms). In order to confirm a slides. Images were taken using a Zeiss Axio Imager2 microscope. PSA-NCAM1 1 response during blue or red light stimulation period, 99% confidence intervals or doublecortin cells in the dentate gyrus granule cell layer were counted and were constructed for the trial-averaged activity using a baseline 2.5 s period of normalized to the area of the granule cell layer for each brain slice using ImageJ by spiking activity before the onset of each light under the assumption of Poisson a researcher blind to the identities of each animal. After all the data were collected, spiking statistics (for example, Neuroexplorer, NEX Technologies). A neuron was the identities of each animal were revealed and the data were assigned back into considered to have a response for a particular light stimulation condition if trial each group for statistical analysis. averaged activity exceeded the upper (excitatory) or lower (inhibitory) bound of In vivo electrophysiology. As described above, three mice were first bilaterally the 99% confidence interval. We considered neurons activated from dentate injected with an AAV -TRE-ChR2-mCherry virus into the dentate gyrus followed 9 gyrus stimulation when a neural response was confirmed for the blue light by lowering a bilateral optic fibre implant into position and cementing it to the condition but not the red light condition. For each neuron identified as such, skull. Following 10 days for recovery and viral expression, in a separate surgery, we z-scored neural activity depicted in the blue and red light PSTH, then iden- mice were chronically implanted with a hyperdrive that housed six independently tified the maximum trial-averaged z-score value from the 2.5 s baseline (Pre) and moveable tetrodes targeting the BLA. To accommodate the optic fibre implant during blue or red light stimulation (Post). The Pre and Post maximum z-score cemented on the skull, the AP coordinate for the hyperdrive was adjusted slightly values for the blue and red light stimulation period was compared using paired (centred at AP 520.85 mm) and implanted at a , 15u angle. The electrical signal t-tests (Fig. 2p). recorded from the tips of the tetrodes was referenced to a common skull screw over the cerebellum and differentially filtered for single unit activity (200 Hz to 8 kHz) 31. Reijmers, L. G., Perkins, B. L., Matsuo, N. & Mayford, M. Localization of a stable and local field potentials (1–200 Hz). The amplified signal from each wire is neural correlate of associative memory. Science 317, 1230–1233 (2007). digitized at 40 kHz and monitored with an Omniplex sytem (Plexon). Action 32. Redondo, R. L. et al. Bidirectional switch of the valence associated with a potentials from single neurons were isolated off-line using time–amplitude win- hippocampal contextual memory engram. Nature 513, 426–430 (2014). dow discrimination through Offline Sorter (Plexon). Putative single units were 33. Ramirez, S. et al. Creating a false memory in the hippocampus. Science 341, isolated by visualizing combinations of waveform features (square root of the 387–391 (2013). 34. Liu, X. et al. Optogenetic stimulation of a hippocampal engram activates fear power, peak–valley, valley, peak, principal components, and time-stamps) memory recall. Nature 484, 381–385 (2012). extracted from wires composing a single tetrode. The average firing rate for iso- 35. Han, X. et al. A high-light sensitivity optical neural silencer: development and lated neurons was 2.25 Hz 6 4.14 Hz (mean 6 s.d.; range 0.01–30.15 Hz). application to optogenetic control of non-human primate cortex. Front. Syst. However, the firing rate distribution was highly rightward skewed (median: 0.81 Neurosci. 5, 18 (2011). Hz) and more than half of the neurons (62%; 66/106) had firing rates under 1 Hz. 36. Huff, M. L., Miller, R. L., Deisseroth, K., Moorman, D. E. & LaLumiere, R. T. After the last recording session, small lesions were made near the tips of each Posttraining optogenetic manipulations of basolateral amygdala activity m , modulate consolidation of inhibitory avoidance memory in rats. Proc. Natl Acad. tetrode by passing current (30 Afor 10 s) and mice were transcardially perfused Sci. USA 110, 3597–3602 (2013). and brains extracted for histology using standard procedures. 37. Snyder, J. S., Soumier, A., Brewer, M., Pickel, J. & Cameron, H. A. Adult Recording and light stimulation protocol. Each mouse had two recording ses- hippocampal neurogenesis buffers stress responses and depressive behaviour. sions that occurred on two different days separated by 72 h. Mice were first placed Nature 476, 458–461 (2011).

Extended Data Figure 1 | Male mice spend more time around an object associated with females. Top, Time spent in the target zone where the object associated with females is introduced in the ON phases. Female-object paired mice (experimental group) spend more time in the target zone during the ON phases than the neutral-object paired mice (control group; two-way ANOVA with multiple comparisons, ON1 t88 5 2.41; P , 0.05, ON2 t88 5 2.08; P , 0.05). Bottom, Difference score (average of ON phases 2 baseline (Bsl)) also shows the increased preference for the target zone in the female-object group compared to neutral-object group (t22 5 2.37; *P , 0.05). n 5 12 per group. See the Methods section for detailed methods.

Extended Data Figure 2 | Positive, neutral, or negative experiences label were sacrificed a day after completing the CIS protocol. One-way ANOVA a similar proportion of dentate gyrus cells with ChR2; stress prevents followed by Bonferroni post hoc test, P . 0.05, n.s., not significant. f, Animals weight gain over 10 days. a, The c-Fos mice were bilaterally injected with were chronically immobilized for 10 days, during which they lost a significant AAV9-TRE-ChR2-mCherry and implanted with optical fibres targeting the amount of weight compared to an unstressed group (one-way ANOVA dentate gyrus. b–e, Histological quantifications reveal that, while off Dox, a followed by Bonferroni post hoc test, *P , 0.05, n 5 9 per group). Data are similar proportion of dentate gyrus cells are labelled by ChR2–mCherry in means 6 s.e.m. response to a positive (c), neutral (d), or negative (e) experience. All animals

Extended Data Figure 3 | Reactivation of a positive memory decreases at levels that matched the unstressed groups. b, Upon completion of the latency to feed in a novelty suppressed feeding paradigm. a, All groups were novelty suppressed feeding test, all groups were returned to their home cage food deprived for 24 h and then underwent a novelty-suppressed feeding and food intake was measured after 5 min (one-way ANOVA followed protocol. While chronic immobilization increased the latency to feed, light- by Bonferroni post hoc test, **P , 0.01, n 5 16 per group). Data are reactivation of a positive memory significantly decreased the latency to feed means 6 s.e.m.

Extended Data Figure 4 | Activation of a positive memory elicits BLA manipulated. Within-subjects experiments revealed that glutamatergic spiking activity, requires NAcc glutamatergic activity in the tail suspension antagonists (Glux), but not saline, in the accumbens shell blocked the light- test, but does not alter locomotor activity in the open field test. a, Raster induced effects of a positive memory in stressed subjects. For behavioural data, plots and peri-stimulus time histograms (PSTH) illustrating a transient a two-way ANOVA with repeated measures followed by a Bonferroni post hoc excitatory response from a single BLA neuron out of the nine neurons test revealed a group-by-light epoch interaction on day 1 (F1,90 5 28.39, responsive to dentate gyrus positive memory activation during 10 s of blue light P , 0.001; n 5 16 per group) and day 2 of testing (F1,90 5 8.28, P , 0.01). stimulation, but not in response to 10 s of red light as a control. Blue bar plots on Data are means 6 s.e.m. c, All groups failed to show significant changes in the right illustrate maximum BLA neural firing rate before (Pre) and after locomotor activity within a session of open field exploration during either (Post) blue light stimulation in the dentate gyrus (paired t-test, t7 5 6.91, light off or light on epochs, though any trends towards decreases in *P 5 0.023). Red bar plots show the maximum neural activity for the same locomotion are consistent with stress-induced behavioural impairments. neurons after red light stimulation in the dentate gyrus that serves as a control *P , 0.05, **P , 0.01, ***P , 0.001. (paired t-test, t7 5 1.62, P 5 0.15). b, Brain diagram illustrating target areas

Extended Data Figure 5 | Activating a positive memory in the dentate gyrus stimulated or in a group expressing mCherry alone. c–e, c-Fos expression did produces an increase in c-Fos expression in the lateral septum and not significantly increase in the lateral habenula (c), various ventral hypothalamus, but not the lateral habenula, ventral hippocampus, or VTA. hippocampus subregions (d), or VTA, identified by tyrosine hydroxylase a, Diagram of regions analysed. b, c, c-Fos expression significantly increased in staining (red) stainings in the images expanded on the right (e) (one-way the lateral septum (b) and subregions of the hypothalamus including the ANOVA followed by Bonferroni post hoc test *P , 0.05, **P , 0.01, n 5 5 dorsomedial (DM), ventromedial (VM), and lateral hypothalamus (c) in the animals per group, 3–5 slices per animal). TS, tail suspension. Data are positive memory group but not in a group in which a neutral memory was means 6 s.e.m.

Extended Data Figure 6 | Activating a positive memory through the dentate ventral hippocampus. Trends were observed in the central amygdala (CeA) gyrus of unstressed animals increases c-Fos expression in various and VTA. Each brain region was analysed using an unpaired Student’s t test, downstream regions. a, Diagram of regions analysed. b, In the positive n 5 5 animals per group, 3–5 slices per animal; #P 5 0.17 for central amygdala compared to the neutral memory group, c-Fos expression is significantly and P 5 0.09 for VTA; *P , 0.05, **P , 0.01, ***P , 0.001, n.s., not increased in the lateral septum, NAcc shell, BLA, dorsomedial, ventromedial significant. Data are means 6 s.e.m. and lateral hypothalamus, but not in the mPFC, NAcc core, habenula, or

Extended Data Figure 7 | Dopamine receptor antagonists block the light- memory were observed (two-way ANOVA with repeated measures followed induced effects of positive memory activation; a single session of activating a by Bonferroni post hoc test, *P , 0.05, n 5 9 per group). b, Animals in which positive memory in the dentate gyrus does not produce long-lasting a positive memory was optically activated during the tail suspension test or antidepressant-like effects. a, Administration of a cocktail of dopamine sucrose preference test showed acute increases in time struggling or preference receptor antagonists (DAx) prevented the light-induced increases in struggling for sucrose; this change in behaviour did not persist when tested again on during the tail suspension test. When animals were tested again on day 2 and day 2 (within subjects ANOVA followed by Bonferroni post hoc test), infused with saline, the behavioural effects of optically reactivating a positive n 5 9. n.s., not significant. Data are means 6 s.e.m.

Extended Data Figure 8 | Chronic activation of a positive memory prevents dentate gyrus for the 5-day (b), 1-day (c), neutral (d), no stimulation (e), stress-induced decreases in neurogenesis. a, The 5-day positive memory natural (f), and no stress (g) groups. h–m, Representative PSA-NCAM images stimulation group showed a significant increase of adult newborn cells in the corresponding to data appearing in Fig. 4d. n 5 5 slices per animal, 13 animals dentate gyrus as measured by doublecortin (DCX)-positive cells (one-way per group for data appearing in a. *P , 0.05, n.s., not significant. Data are ANOVA followed by Bonferroni post hoc test, F5,72 5 7.634, P , 0.01) relative means 6 s.e.m. to control groups. b–g, Representative images of DCX-positive cells in the

Extended Data Figure 9 | Behavioural and neuronal correlations. basis. b, Performance levels between the TST and SPT show strong positive a, Performance levels in the SPT and the number of adult-born neurons as correlation trends on an animal-by-animal basis. n 5 14 per TST behavioural measured by PSA-NCAM are positively correlated on an animal-by-animal group, n 5 15 per SPT behavioural group.