Activity-Dependent Synaptic Modifications

Input-Specific Metaplasticity by a

Local Switch in NMDA Receptors

Ming-Chia Lee

Department of Neurobiology Duke University

Date:______

Approved:

______Michael D. Ehlers, Advisor

______Anne E. West, Chair

______Rhohei Yasuda

______Benjamin D. Philpot

Dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Neurobiology in the Graduate School of Duke University

2009

ABSTRACT

Input-Specific Metaplasticity by a

Local Switch in NMDA Receptors

Ming-Chia Lee

Department of Neurobiology Duke University

Date:______

Approved:

______Michael D. Ehlers, Advisor

______Anne E. West, Chair

______Rhohei Yasuda

______Benjamin D. Philpot

An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Neurobiology in the Graduate School of Duke University

2009

Abstract

At excitatory synapses, NMDAR‐mediated synaptic plasticity occurs in response to activity inputs by modifying synaptic strength. While comprehensive studies have been focused on the induction and expression mechanisms underlying synaptic plasticity, it is less clear whether and how synaptic plasticity itself can be subjected to regulations. The presence of “plasticity of plasticity”, or meta‐plasticity, has been proposed as an essential mechanism to ensure a proper working range of plasticity, which may also offer an additional layer of information storage capacity.

However, it remains elusive whether and how meta‐plasticity occurs at single synapses and what molecular substrates are locally utilized. Here, I develop systems allowing for sustained alterations of individual synaptic inputs. By implementing a history of inactivity at single synapses, I demonstrate that individual synaptic inputs control synaptic molecular composition homosynaptically, while allowing heterosynaptic integration along dendrites. Furthermore, I report that subunit‐ specific regulation of NMDARs at single synapses mediates a novel form of input‐ specific metaplasticity. Prolonged suppression of synaptic releases at single synapses enhances synaptic NMDAR‐mediated currents and increases the number of functional NMDARs containing NR2B. Interestingly, synaptic NMDAR composition is adjusted by spontaneous glutamate release rather than evoked activity. I also demonstrate that inactivated synapses with more NMDARs

containing NR2B acquire a lower induction threshold for long‐term synaptic potentiation. Together, these results suggest that at single synapses, spontaneous release primes the synapse by modifying its synaptic state with specific molecular compositions, which in turn determine the synaptic gain in an input‐specific manner.

Dedication

I would like to dedicate my Ph.D. thesis to my dear parents and beloved husband for their invaluable support and unconditional faith in me throughout my life.

Table of Contents

Abstract...... iv

List of Tables...... xii

List of Figures...... xiii

List of Abbreviations...... xv

Acknowledgements ...... xvii

Chapter 1. Introduction ...... 1

Heterogeneous synaptic inputs ...... 3

Synaptic inputs as presynaptic vesicular release ...... 4

Action potential dependent evoked release...... 6

Spontaneous miniature release ...... 7

Dissociable evoked and spontaneous release ...... 8

Activity‐dependent synaptic modifications...... 9

Hebbian plasticity: modifications on synaptic strength...... 10

LTP...... 11

LTD ...... 13

Metaplasticity: modifications on Hebbian plasticity ...... 14

Induction of metaplasticity...... 15

LTP‐facilitation ...... 15

LTP‐inhibition and LTD‐facilitation ...... 16

vii

Synaptic NMDA receptors mediate activity‐dependent metaplastic regulations ...... 17

Subunit‐specific properties of NMDAR ...... 18

Gating and kinetics ...... 19

Synaptic locations ...... 20

Protein interactions...... 22

Activity modifies NMDAR subunit composition ...... 23

Developmental switch from NR2B to NR2A...... 24

Chronic activity influences NMDAR composition...... 25

Spontaneous releases and NMDAR composition ...... 27

Animal models with altered NMDAR composition...... 27

NMDAR composition is modulated in a cell‐wide manner...... 28

NMDAR composition modifies synaptic plasticity ...... 29

Subunit composition determines the induction threshold of Hebbian plasticity...... 30

NMDAR composition as a substrate for metaplasticity ...... 31

Heterogeneity of synaptic NMDAR composition ...... 32

NMDAR composition as a substrate for metaplasticity: input‐specific? .33

Local activity manipulations...... 34

Acute and local activity manipulations ...... 34

Sustained local activity manipulation at individual synapses ...... 35

Local activity manipulation and NMDAR composition ...... 37

Experimental rationales and specific aims...... 37

viii

AIM#1: To determine if activity inputs modify synaptic states at single synapses ...... 38

AIM#2: To determine if NMDAR composition serves as a substrate for input‐specific metaplasticity ...... 39

Chapter 2. Materials and methods ...... 56

General strategy...... 56

Synaptic inactivation and single synapse resolution...... 56

Identify excitatory synapses...... 57

Materials and methods...... 57

DNA constructs, antibodies and reagents...... 58

Chemical‐based inactivation...... 58

Tetanus toxin‐based inactivation ...... 58

Primary neuronal culture, transfection and viral infection ...... 58

Immunocytochemistry and antibodies...... 59

Chemical‐based inactivation ...... 60

FM loading assay ...... 61

Image analysis and quantification...... 62

Two‐photon microscopy...... 63

Two‐photon uncaging and uEPSC recording...... 64

Two‐photon uncaging and plasticity induction ...... 66

Two‐photon uncaging and spine enlargement...... 66

Chapter 3. Activity inputs modify synaptic states at single synapses...... 74

Activity manipulation at single synapses...... 75

Chemical inactivation: 2FKBP‐VAMP2 ...... 75

Partial suppression of synaptic release...... 76

Slight increases of postsynaptic NMDAR contents ...... 76

TetTX‐mediated synaptic inactivation...... 77

Reduced VAMP2 staining ...... 78

Impaired FM uptake...... 78

Increase in postsynaptic NMDAR contents ...... 79

More effective synaptic inactivation by the TetTX‐based system...... 79

Synaptic connections are maintained under the TetTX‐mediated suppression of synaptic release...... 80

Modified synaptic states at silenced synapses ...... 81

Homosynaptic modification at silenced synapses ...... 82

Heterosynaptic modulations driven by silenced synapses...... 83

Summary and discussion...... 84

Chapter 4. Input‐specific gain control...... 98

Enhanced NMDAR currents at single silenced synapses...... 98

Subunit‐specific regulation of NMDARs at single silenced synapses...... 100

Spontaneous glutamate releases regulate NMDAR composition at single synapses ...... 102

Local synaptic activity reduces NR2B content...... 103

Single silenced synapses acquire a lower threshold for potentiation ...... 104

Model...... 106

Chapter 5. Discussions & future directions ...... 122

Spontaneous glutamate releases and synaptic NMDAR composition ...... 122

Modify NMDAR composition at single synapses...... 124

Altered NR2A/NR2B ratios at single silenced synapses ...... 124

Potential local mechanisms underlie input‐specific changes on NMDAR composition ...... 126

Synapse‐specific synaptic targeting ...... 126

Subunit‐specific endocytosis at single synapses ...... 127

Lateral diffusion ...... 128

Altered plasticity threshold at silenced synapses...... 129

Why modify and probe synaptic plasticity at single synapses?...... 130

How silenced synapses acquire a lower LTP threshold? ...... 131

More NR2B‐containing NMDARs ...... 132

More CaMKIIs ...... 132

Reduced AMPAR/NMDAR ratio ...... 133

Synaptic state determines plasticity threshold...... 134

Afferent‐specific gain control ...... 135

Implications of single‐synapse inactivation systems...... 136

To gain inducibility and reversibility...... 136

Determine the induction threshold for synaptic scaling...... 137

Test afferent‐specific gain control in vivo ...... 139

Spontaneous release, GluR composition and neurological disorders ...... 140

References...... 148

Biography...... 165 xi

List of Tables

Table 1. The subunit‐specific properties of NR2A and NR2B subunits ...... 41

Table 2. NMDAR subunit compositions modify the induction of LTP and LTD ...... 42

Table 3. Afferent‐specific NMDAR composition...... 43

Table 4. Different efficiency of synaptic inactivation...... 86

Table 5. Modified synaptic molecular composition at silenced synapses...... 87

xii

List of Figures

Figure 1. Vesicular recycling and SNAREs at presynaptic boutons ...... 45

Figure 2. The origin of synaptic vesicles for evoked and spontaneous release...... 47

Figure 3. Metaplasticity...... 49

Figure 4. Activity‐dependent regulations on NMDAR subunit composition...... 51

Figure 5. NMDAR subunit composition modifies synaptic plasticity ...... 53

Figure 6. Activity manipulations with distinct spatial resolution ...... 55

Figure 7. Identify excitatory synapses...... 69

Figure 8. Normalized synaptic content...... 71

Figure 9. Two‐photon glutamate uncaging...... 73

Figure 10. Chemical inactivation partially blocks presynaptic vesicular recycling....89

Figure 11. TetTX‐based synaptic inactivation ...... 91

Figure 12. Silenced synapses show similar spine morphology as active synapses ....93

Figure 13. The spatial profile of NR1 accumulation...... 95

Figure 14. Spatial integration among inactivation events ...... 97

Figure 15. Enhanced NMDAR‐uEPSCs from silenced synapses...... 109

Figure 16. Accumulation of NR1 and NR2B at single silenced synapses ...... 111

Figure 17. Spontaneous glutamate release tunes NMDAR composition at single synapses...... 113

Figure 18. Local synaptic activity reduces NR2B content ...... 115

Figure 19. Subthreshold stimuli potentiated silenced synapses...... 117

Figure 20. Subthreshold stimuli induce structural plasticity at silenced synapses ..119

xiii

Figure 21. Model of input‐specific metaplasticity ...... 121

Figure 22. Surface accumulation of NR2B at silenced synapses...... 143

Figure 23. Local mechanisms account for NMDAR composition at single synapses ...... 145

Figure 24. Afferent‐specific gain control...... 147

xiv

List of Abbreviations

AMPAR α‐amino‐3‐hydroxyl‐5‐methyl‐4‐isoxazole‐propionate receptor

AP action potential

AP5 2‐amino‐5‐phosphonopentanoate

A active synapses

AZ active zones

Ca++ calcium

CaMKII Calcium/calmodulin‐dependent protein kinase II

GluR glutamate receptors

HFS high frequency stimulation

IRES internal ribosome entry site

LFS low frequency stimulation

LTD long‐term depression

LTP long‐term potentiation

MAGUK membrane‐associated guanylate kinase mEPSCs miniature‐release‐induced‐EPSCs

NMDA N‐methyl D‐aspartate

NMDAR N‐methyl D‐aspartate receptors

NL‐1 Neuroligin‐1

NO nitric oxide

NS neighboring spine

PP perforant pathway

PSDs postsynaptic densities

S silenced synapses

SC Shaffer‐collateral pathway

SNARE SNAP and NSF attachment receptors

Sph Synaptophysin

TetTX tetanus toxin

TexTxLC Tetanus toxin light chain

TTX tetrodotoxin uEPSCs 2‐photon‐uncaging induced excitatory postsynaptic currents

VAMP2 vesicle associated membrane protein 2, or synaptobrevin

VGCC voltage‐gated calcium channel vGlut vesicular glutamate transporter

xvi

Acknowledgements

I completed this work under the guidance of my advisor, Mike Ehlers, and I am very grateful for the support encouragement, and patience he has had for my project and me. I would like to thank my thesis committee (Anne West, Ryohei

Yasuda and Ben Philpot) who has been very helpful and supportive throughout. I really appreciate their critical insight and valuable suggestions. Special thanks to

Ryohei Yasuda who generously provided two‐photon microscope system and valuable technical advices. I also would like to thank Dr. George Augustine who served my committee chair for nearly five years for his kind and generous support.

Thanks to all Ehlers lab members, past and present, who provide advice, assistance, and create a fun and supportive working environment. Thanks to excellent technical assistance of Haiwei Zhang, Marguerita Klein and Irina Lebedeva. Finally, I thank my parents –Sui‐Wei Lee and Chi‐Mei Lee‐Hsu‐ and my husband Shih‐Chieh Lin for their patience, support and encouragement along this journey.

xvii

Chapter 1. Introduction

Synapses are specialized junctions that allow information transmission from a neuron to another neuron. At individual synapses, information is directionally transmitted from the presynaptic bouton through the synaptic cleft to the postsynaptic site. At chemical synapses, synaptic transmission is mediated by neurotransmitters, which are released from presynaptic terminals and detected by postsynaptic receptors. It is well established that the strength of synaptic transmission can be enhanced or reduced by neuronal activity. Such activity‐ dependent synaptic plasticity has been considered as a key component of the cellular machinery for learning and memory in the brain.

While comprehensive studies of synaptic plasticity at excitatory synapses have been focused on its induction and expression mechanisms (Malenka and Nicoll

1999; Bear 2003; Lisman 2003; Malenka and Bear 2004), it has been suggested that the presence of “plasticity of plasticity”, or meta‐plasticity, is essential to ensure a proper working range for plasticity to occur and likely offers another layer of information storage capacity (Montgomery and Madison 2004; Fusi, Drew et al. 2005; Fusi and

Abbott 2007; Abraham 2008). However, it is less clear whether and how meta‐ plasticity occurs at single synapses and what molecular substrates are locally utilized.

N‐methyl D‐aspartate (NMDA) receptors (NMDARs) are glutamate‐gated ion channels that are calcium (Ca++)‐permeable and are essential for the induction of most types of synaptic plasticity. Due to their crucial role in plasticity induction,

NMDARs represent an excellent target in order to modify synaptic plasticity.

Among ways of modulating synaptic NMDARs, the subunit composition of

NMDARs has been reported under the regulation of neuronal activity (Philpot,

Sekhar et al. 2001; Barria and Malinow 2002; Yashiro and Philpot 2008). Moreover, changes of NMDAR composition have been shown to modify synaptic plasticity

(Tang, Shimizu et al. 1999; Liu, Wong et al. 2004; Barria and Malinow 2005; Jung,

Kim et al. 2008; Gardoni, Mauceri et al. 2009). Although it is reasonable to consider that NMDAR composition may serve as a molecular substrate for input‐specific synaptic gain control, very few studies were able to implement input‐specific chronic activity alterations, which cause changes in NMDAR composition, and directly test the corresponding modifications on synaptic plasticity at single synapses. Moreover, up to date, changes in NMDAR subunit composition have been mostly reported to express in a cell‐wide manner, which not only contradicts the heterogeneity of NMDAR composition found in different afferents (Arrigoni and

Greene 2004; Sobczyk, Scheuss et al. 2005) but also compromises its suitability for implementing input‐specific regulations on synaptic plasticity.

In this chapter, I will discuss three basic notions that found my thesis work, including activity‐dependent synaptic modifications, the role of subunit 2

composition on NMDAR‐mediated synaptic modifications and input‐specific activity manipulations. First, I will describe the molecular makeup of synaptic inputs (i.e., presynaptic release) and provide an overview on activity‐dependent synaptic modifications, including both synaptic plasticity and metaplasticity. Second,

I will describe the subunit‐specific properties of NMDARs. I will briefly review the current literature regarding the cell‐wide expression of activity‐dependent regulations on NMDARs composition, followed by reviewing the subunit‐specific contribution on synaptic plasticity. Third, I will provide an overview on the literature regarding the heterogeneity of NMDAR composition at individual synapses and review existing local manipulation techniques that have been utilized in the past. Finally, I will describe the experimental rationales and specific aims for my thesis work.

Heterogeneous synaptic inputs

In the brain, neurons receive and integrate information from thousands of synaptic inputs from multiple afferents. In single neurons, synapses receiving different afferent inputs have been reported to show specific molecular composition, morphology or even different expression of synaptic plasticity (Kumar and

Huguenard 2003; Arrigoni and Greene 2004; Humeau, Herry et al. 2005).

Specific patterns of activity are synapse‐specific information that individual inputs carry (Craig and Boudin 2001; French and Totterdell 2004). Since individual

afferents are originated from specific regions of the brain, activity inputs can be different from afferent to afferent. For instance, synaptic release has shown to be regulated either by activity or through development (Dumas and Foster 1995;

Murthy, Schikorski et al. 2001; Nelson, Kavalali et al. 2008), which may contribute to the heterogeneity of afferent‐specific information. Moreover, afferent‐specific release probability has been reported (Smeal, Gaspar et al. 2007; Ding, Peterson et al. 2008).

Therefore, it is reasonable to hypothesize that the constant differences among afferents actively modulate synapse‐specific states to code information in temporally distinct ways.

Synaptic inputs as presynaptic vesicular release

In the presynaptic boutons, synaptic vesicles that store neurotransmitters are constantly recycled to maintain a sustained supply for neurotransmitter release. For each cycle of vesicle release, individual synaptic vesicles undergo a sequence of events, including vesicle priming/docking, vesicle fusion, exocytosis and clathrin– dependent endocytosis, to be shuttled between the reserve pool (PR) and the active zone (AZ) (Sudhof 2004; Atasoy, Ertunc et al. 2008) (Figure 1A).

Vesicle docking is facilitated by SNARE complex (SNAP and NSF attachment receptors) through the complementary action between v‐SNARES (i.e., synaptobrevin‐2, VAMP2) on the vesicle membrane and t‐SNAREs (i.e., SNAP25 and syntaxin) on the target membrane Figure 1B. In excitatory synapses, docked

vesicles are concentrated at the regions of presynaptic plasma membrane called active zones (AZ), which are apposed to postsynaptic densities (PSDs) containing neurotransmitter receptors. Assembly of the SNARE complexes functions as a zipper to bring synaptic vesicle and plasma membrane in proximity and lead to efficient membrane fusion. Since the completion of the SNARE assembly is facilitated by a rise of intracellular calcium (Ca++) concentration, activity that activates voltage‐gated calcium channel (VGCCs) allows Ca++ entry and promotes synchronous synaptic release of docked vesicles. After membrane fusion, clathrin‐ dependent endocytosis recycles exocytosed membrane to reform synaptic vesicles

(Schweizer and Ryan 2006). Reformed vesicles are then equipped with neurotransmitter and replenished back to the reserve pool to complete a cycle

(Sudhof 2004).

Synaptic release is required for effective synaptic transmission that shapes functional neuronal circuits. Synaptic release can be triggered by action potential

(action potential‐dependent evoked release) or occur spontaneously (spontaneous release). While traditionally these two processes are thought to originate from the same cellular machinery and highly coupled, recent evidence suggests that these two forms of synaptic release may be dissociable and could serve different biological functions.

Action potential dependent evoked release

Evoked release has been considered as the predominant if not the only information carried by synaptic input, since its highly regulated and precisely timed nature are recognized to be crucial for reliable information encoding. Moreover, repetitive evoked releases activate synapses and can lead to the induction of synaptic plasticity.

Evoked neurotransmitter release is a mode of synchronous vesicular release triggered by an action potential (or action potentials, APs) in presynaptic terminals.

Upon incoming APs, the associated membrane depolarization activates VGCCs within the terminal, leading to Ca++ influx that promotes fusion of synaptic vesicles with the plasma membrane. Modulations on evoked release are tightly coupled with regulations of VGCCs and intracellular Ca++ stores (Emptage, Reid et al. 2001;

Sharma and Vijayaraghavan 2003; Engelman and MacDermott 2004). Multiple types of VGCCs with differential spatial distributions have been found at presynaptic boutons (Edmonds, Klein et al. 1990; Dietrich, Kirschstein et al. 2003). Moreover,

VGCCs activation is gated by membrane potential, which reflects an integrated modulation from all presynaptic receptors (i.e., both ionotropic and metabotropc receptors). Thus, while transferring activity across synapses, action‐potential evoked release is under constant and dynamic modulation.

Spontaneous miniature release

In the absence of APs, transmitter release can also occur in an unsynchronized way by the spontaneous fusion of vesicles to the presynaptic plasma membrane. Spontaneous neurotransmitter release is a common property of all synapses (Katz and Miledi 1969; Katz and Miledi 1969). Individual spontaneous events usually correspond to a single quantum of neurotransmitter that presumably originates from the fusion of a single synaptic vesicle (Frerking, Borges et al. 1997).

Although the spontaneous release has been shown to be modulated by extracellular

Ca++ and fluctuations of intracellular Ca++, the presence of Ca++ is not required for spontaneous events to occur (Dittman and Regehr 1996) (Llano, Gonzalez et al. 2000;

Angleson and Betz 2001), suggesting a certain degree of Ca++‐independency of spontaneous release.

Although spontaneous neurotransmission has been widely studied, it is most often considered as a simpler proxy for the evoked release. While relative little is known, some recent studies have suggested that spontaneous release may be involved in the maturation and stability of synaptic networks (McKinney, Capogna et al. 1999), inhibition of local dendritic protein synthesis (Sutton, Wall et al. 2004) and even regulations on synaptic composition of glutamate receptors (Barria and

Malinow 2005; Sutton, Ito et al. 2006). Moreover, recent studies suggest that the frequency of spontaneous release can be regulated not only by activity but also by activity‐dependent epigenetic states of cells (Murthy, Schikorski et al. 2001; Nelson, 7

Kavalali et al. 2006; Nelson, Kavalali et al. 2008). Therefore, rather than a mere random noise in the synaptic release process, spontaneous release is likely to play a bigger functional role on synaptic transmission in also an activity‐dependent manner.

Dissociable evoked and spontaneous release

Up to date, whether evoked and spontaneous releases are tightly coupled or can be independently regulated remains unclear. If they can be independently regulated, what are the respective biological functions these processes serve?

Understanding these issues is essential for getting the whole picture of the biological roles of presynaptic vesicular release.

The probabilities for spontaneous and evoked release have been shown to be correlated at single synaptic sites, which are further correlated with the vesicle pool size. These correlations suggest that evoked and spontaneous release are originated from the same vesicle pool and being modulated by the physical constraint of the total vesicle number (Prange and Murphy 1999).

However, regulations on these two modes of release have also been shown to be uncoupled and dissociable under some circumstances. For example, knockout of synaptotagmin, the putative Ca++ sensor for membrane fusion, results in a great decrease of evoked release but unchanged or even enhanced spontaneous release rates (Broadie, Bellen et al. 1994; Littleton, Stern et al. 1994). Moreover, genetically

knocking‐down VAMP2 (vesicle associated membrane protein‐2, or synaptobrevin) expression completely blocks evoked transmission while leaving some residual activity of spontaneous release (Deitcher, Ueda et al. 1998; Schoch, Deak et al. 2001).

Similarly, enzymatic disruption of VAMP‐2 expression by tetanus toxin (TetTX) application also causes a differential blockade in evoked release and spontaneous release (Capogna, McKinney et al. 1997; Hua, Raciborska et al. 1998; Harms and

Craig 2005; Ehlers, Heine et al. 2007). Interestingly, recent studies suggest that evoked release and spontaneous release are possibly originated from two separated presynaptic vesicle pools and may even be detected by distinct pools of postsynaptic

NMDARs (Sara, Virmani et al. 2005; Atasoy, Ertunc et al. 2008) (Figure 2). Therefore, it is possible that spontaneous release can be independently regulated, in parallel with evoked release, to play its unique biological roles.

Activity-dependent synaptic modifications

Upon synaptic inputs, synapses can be modified in an activity‐dependent manner. Various forms of activity‐dependent modifications are triggered depending on the specific pattern of activity inputs. Activity is able to modify not only the synaptic strength (e.g., Hebbian plasticity), but may also modify the properties of synaptic plasticity per se (i.e., metaplasticity). These two forms of plasticity are described in detail below.

Activity‐dependent synaptic modifications reflect changes of synaptic states through simultaneously influencing clusters of synaptic molecules (Thiagarajan,

Piedras‐Renteria et al. 2002; Ehlers 2003; Thiagarajan, Lindskog et al. 2005; Abraham

2008). Nevertheless, postsynaptic transmitter receptors have been recognized as the key factor under modulation, given their essential roles in synaptic transmission. At excitatory synapses, glutamate receptors (GluR) are crucial for activity‐dependent synaptic modifications. Different types of GluRs have been shown to play specific roles in the process of modulating synaptic strength leading to synaptic plasticity.

For example while synaptic AMPA‐type receptors (AMPARs) are essential for plasticity expression, synaptic NMDARs are required for plasticity induction,.

Therefore, activity inputs may potentially modulate either synaptic efficacy or the threshold for synaptic plasticity through modifying specific GluR subgroups and resulting in differential physiological outcomes. The multiple‐layers of modulation may be crucial for maximizing synaptic capacity for sustained information strorage.

Hebbian plasticity: modifications on synaptic strength

Neuronal activity can generate persistent changes of synaptic efficacy, such as long‐term potentiation (LTP) and long‐term depression (LTD). Although LTP and

LTD are experimental phenomena, these long lasting modifications of synaptic efficacy demonstrate the potential synaptic/cellular mechanisms that the brain can utilize to modify neuronal network. Rather than reflecting the specific outcomes in

response to activity or inactivity, the bidirectional modifications are induced by activity with specific spatial/temporal patterns. Various forms of LTP and LTD are identified based on the unique combination of the induction and the expression at different populations of synapses. The most extensively studied forms of synaptic plasticity are NMDAR‐dependent LTP and LTD on CA1 hippocampal neurons.

LTP

NMDAR‐dependent LTP requires synaptic activation of NMDARs driven by simultaneous presynaptic glutamate release and postsynaptic depolarization, which then leads to an acute and prolonged enhancement of synaptic strength by facilitating AMPA‐type receptors (AMPARs) surface insertions (Bliss and

Collingridge 1993; Malenka and Nicoll 1999; Malenka and Bear 2004; Matsuzaki,

Honkura et al. 2004). Several experimental protocols have been reported to reliably induce LTP. For instance, high frequency stimulation, theta‐burst stimulation, pair protocols (Bliss and Collingridge 1993; Malenka and Nicoll 1999; Lisman 2003) and chemical LTP protocols (Lu, Man et al. 2001; Park, Penick et al. 2004; Park, Salgado et al. 2006) have been widely used to induce enhanced AMPAR‐mediated synaptic currents and corresponding spine growth. Recently, a set of new paradigms that pairs focal two‐photon glutamate uncaging with either postsynaptic depolarization or low Mg++ condition have been shown to also reliably induce not only potentiated

AMPAR‐mediated synaptic currents but also structural enlargements of spines

(Matsuzaki, Honkura et al. 2004; Harvey and Svoboda 2007; Tanaka, Horiike et al.

2008).

Regarding LTP expression, a major mechanism involves the recruitment of

AMPARs into the plasma membrane at synapses via activity‐dependent changes in

AMPAR trafficking. While many molecules have been implicated in LTP induction,

Calcium/calmodulin‐dependent protein kinase II (CaMKII) and AMPAR subunit

GluR1 are considered to play particularly important roles as mediators to enhance synaptic efficacy. Consensus has been gradually reached that Ca++ influx through activated synaptic NMDARs activates CaMKII and leads to a Myosin 5b‐mediated surface insertion of Ca++‐permeable AMPARs (GluR1 homomers) from intracellular recycling endosomes (Lu, Man et al. 2001; Yasuda, Barth et al. 2003; Malenka and

Bear 2004; Park, Penick et al. 2004; Boehm, Kang et al. 2006; Park, Salgado et al. 2006;

Wang, Edwards et al. 2008). Phosphorylation on multiple residues of GluR1 has been documented to be critical for the synaptic targeting of AMPARs (Barria, Muller et al. 1997; Benke, Luthi et al. 1998; Derkach, Barria et al. 1999). Interestingly, the enhanced synaptic efficacy is usually accompanied with structural changes of synapses, including spine growth, reorganization of PSD proteins and even new synapse formation (Matsuzaki, Honkura et al. 2004; Park, Salgado et al. 2006;

Sharma, Fong et al. 2006; Steiner, Higley et al. 2008; Tanaka, Horiike et al. 2008). The regulations on molecular dynamics and molecular composition at synapses, which account for a sustained expression of LTP, needs to be further dissected. 12

LTD

As to NMDAR‐dependent LTD in hippocampal CA1 neurons, a moderate

NMDAR activation upon low frequency stimulation (1Hz for 900 sec, LFS) leads to a prolonged decrease on synaptic efficacy. In addition to LFS, global application of

NMDA also has been shown to induce LTD (Lee, Kameyama et al. 1998). The moderate NMDAR activation allows Ca++ entry with specific magnitudes and dynamics to activate a unique molecular repertoire for LTD induction. Different from activated CaMKII observed under LTP induction, calcineurin (protein phosphotase 1, PP1) activation is known to be required for LTD to occur (Mulkey,

Herron et al. 1993; Kirkwood and Bear 1994; Mulkey, Endo et al. 1994). Also, while the occurrence of dephosphorylated protein kinase C (PKC) correlates with LTD

(Thiels, Kanterewicz et al. 2000; Hrabetova and Sacktor 2001), dephosphorylation on protein kinase A (PKA) is required and sufficient for LTD induction (Kameyama,

Lee et al. 1998; Lee, Kameyama et al. 1998; van Dam, Ruiter et al. 2002).

Likewise, the expression of LTD relies on activity‐dependent changes on synaptic AMPARs, especially regulations on receptor trafficking (Malenka and Bear

2004; Kessels and Malinow 2009). Through posttranslational modifications (e.g., dephosphorylation on S818, S831, S845 and T840), AMPARs are rapidly internalized in response to LTD‐inducing stimuli via a dynamin‐ and clathrin‐dependent mechanism (Lee, Kameyama et al. 1998; Ehlers 2000; Lee, Barbarosie et al. 2000;

Malenka 2003; Brown, Tran et al. 2005; Delgado, Coba et al. 2007). The structural 13

changes associated with LTD induction have also been reported, suggesting the removal of not only AMPARs but presumably also membranes and other molecules from postsynaptic membranes (Zhou, Homma et al. 2004; Horne and DellʹAcqua

2007; Wang, Yang et al. 2007).

Metaplasticity: modifications on Hebbian plasticity

In contrast to Hebbian plasticity, some activity‐dependent synaptic modifications, so‐called metaplasticity, are executed in a way that does not affect synaptic efficacy per se (e.g., number of synaptic AMPARs) but rather modifies synapses on the inducibility of subsequent plasticity induction. Essentially, metaplasticity is defined as a change in the physiological or biochemical state of neurons and synapses that alters the ability of synapses to generate subsequent synaptic plasticity (Montgomery and Madison 2004; Abraham 2008).

Metaplasticity has been considered as mechanisms that not only ensure a proper working range for synaptic plasticity to occur but also allowing for prior experience to modulate current plasticity induction. With the presence of metaplasticity, synaptic plasticity can be tightly regulated while dynamically modulated to provide finer tuning on synaptic states responding to neuronal activity. The essential role of tunable mataplastic synaptic states has been proposed as essential mechanisms for the prolongation of memory retention (Fusi, Drew et al.

2005; Fusi and Abbott 2007; Abraham 2008).

Induction of metaplasticity

While the induction and expression phases are tightly coupled temporally in

Hebbain plasticity, such temporal coupling is loosened in metaplasticity. Essentially, metaplasticity is induced by anything that modifies synaptic states (i.e., priming activity) while the expression of metaplasticity requires the occurrence of synaptic plasticity (Figure 3). The standard paradigm for studying metaplasticity is to have an episode of priming activity at one point and then a subsequent plasticity‐ inducing event, such as low‐frequency stimulation (LFS), high‐frequency stimulation (HFS) or learning that evokes synaptic plasticity such as LTP or LTD.

The interval between the priming activity and the subsequent plasticity‐inducing stimuli is flexible and can be ranging from minutes to days. Up to date, the priming cues are usually manipulations on neuronal activity using electrical stimulation or pharmacological treatments.

For metaplasticitic mechanisms that have been documented, mGluR‐ dependent metaplasticity and NMDAR‐dependent metaplasticity are two relatively well‐understood forms of metaplasticity, as described below.

LTP-facilitation

Facilitation on both the induction and persistence of subsequent LTP in CA1 region has been reported through activation of type 1 metabotropic glutamate receptors (mGluR1). The increased induction is not input‐specific but rather a cell‐

wide phenomenon, suggesting metaplastic changes of synaptic states across synapses in individual neurons. The LTP facilitation effects are at least partially mediated by a long‐term down‐regulation of the Ca++‐activated K+ current that underlies the slow afterhyperpolarazation (sAHP) (Ireland, Guevremont et al. 2004).

Moreover, local protein synthesis is facilitated under mGluR1 activation, which may provide newly synthesized protein as reservoir for enhancing the persistence of subsequently generated LTP (Huber, Kayser et al. 2000).

LTP-inhibition and LTD-facilitation

In contrast to the facilitatory effects of mGluR on LTP, activation of

NMDARs has been suggested to be involved in metaplastic changes that inhibit LTP induction and facilitate LTD induction. The increased LTP and LTD threshold occurs only at the primed synapses and usually sustains for about an hour. One potential mechanism involved is the modified synaptic threshold contributed by the depression of NMDAR currents (LTDNMDAR) and the subsequent reduction of Ca++ entry (Perez‐Otano and Ehlers 2005; Lau and Zukin 2007; Sobczyk and Svoboda

2007). LTDNMDAR may reflect a combination of regulations on synaptic NMDARs, including posttranslational modifications (Sobczyk and Svoboda 2007), physical removal of receptors from synaptic regions (Fong, Rao et al. 2002; Groc, Heine et al.

2004; Montgomery, Selcher et al. 2005) and changes on NMDAR subunit composition (Bellone and Nicoll 2007).

Recently, an increasing number of studies suggest that the number and subtype composition of synaptic NMDARs are dynamically regulated by activity

(Rao and Craig 1997; Chen, Cooper et al. 2000; Barria and Malinow 2002; Perez‐

Otano and Ehlers 2005; Bellone and Nicoll 2007; Kopp, Longordo et al. 2007; Jung,

Kim et al. 2008; Yashiro and Philpot 2008), suggesting that NMDAR composition can potentially serve a general molecular substrate for metaplastic regulations

(Carmignoto and Vicini 1992; Kirkwood, Rioult et al. 1996; Philpot, Sekhar et al.

2001).

To explicitly evaluate the suitability of using NMDAR subunit composition as a substrate of metaplasticity, in the following session, I will review the current literature regarding NMDARs in their subunit‐specific channel properties, activity‐ dependent modifications on subunit composition and also potential subunit‐specific influences on synaptic plasticity.

Synaptic NMDA receptors mediate activity-dependent metaplastic regulations

The NMDAR is a glutamate‐gated ionotropic receptor, which is widely expressed in the central nervous system and plays a key role in excitatory synaptic transmission. Synaptic NMDARs are cation channels mediating excitatory synaptic transmission in the brain. The built‐in Mg++‐blockade in the channel pore makes

NMDARs function as molecular coincidence detectors (Mayer, Westbrook et al. 1984;

Nowak, Bregestovski et al. 1984), activated by near simultaneous presynaptic transmitter releases and postsynaptic depolarization. Activation of synaptic

NMDARs then allows calcium influx to initiate Ca++‐dependent synaptic modifications. NMDARs are critical in the induction of synaptic plasticity, including both LTP and LTD (Malenka and Bear 2004), as well as in metaplasticity (Abraham

2008).

Subunit-specific properties of NMDAR

NMDARs are tetramers composed of two obligatory NR1 subunits and two regulatory subunits (NR2A‐D or NR3A‐B). Specific subunit compositions of

NMDARs determine channel physical properties on gating control and kinetics

(Monyer, Burnashev et al. 1994; Chen, Cooper et al. 2000; Prybylowski, Fu et al.

2002). Subunit compositions also influence channel functions through distinct molecular interactions leading to specific trafficking and downstream signaling pathways ( Bayer, De Koninck et al. 2001; van Zundert, Yoshii et al. 2004; Barria and

Malinow 2005; Prybylowski, Chang et al. 2005; Zhang, Zhou et al. 2006; Haghikia,

Mergia et al. 2007; Al‐Hallaq, Conrads et al. 2007; Elias, Elias et al. 2008; Yashiro and

Philpot 2008; Gardoni, Mauceri et al. 2009).

Among six regulatory subtypes of NMDARs, NR2A and NR2B are most extensively studied because of their broad expression in the brain and relatively clear pharmacology (Cull‐Candy and Leszkiewicz 2004; Liu, Wong et al. 2004;

Morishita, Lu et al. 2007). NR2A and NR2B containing NMDARs are present as either di‐heteromers (NR1/NR2A or NR1/NR2B) or tri‐heteromers

(NR1/NR2A/NR2B). In young rats, it has been shown that about 60‐70% of NR2A and 70‐85% of NR2B subunits were associated in NR1/NR2A or NR1/NR2B di‐ heteromeric complexes (Al‐Hallaq, Conrads et al. 2007). Since NR2A and NR2B are two major NR2 subunits expressed postnatally in the forebrain, NR2A and NR2B will be the two main NR2 subunits focused in this thesis work. Literatures regarding subunit‐specific properties will be reviewed in the following sequence: subunit‐ specific gating and kinetics (Table 1), subunit‐specific synaptic location, subunit‐ specific protein interactions.

Gating and kinetics

As single channels, NR1/NR2A and NR1/NR2B di‐heteromers are different in many aspects, including ligand‐binding affinity, open probability and deactivation kinetics (Prybylowski, Fu et al. 2002; Erreger, Dravid et al. 2005). NR1/NR2A channels show a higher open probability (0.67 ± 0.044) and faster deactivation/desensitization kinetics upon glutamate binding (EC50 = 3.3 μm).

Whereas, NR1/NR2B channels have slightly higher ligand binding affinity (EC50 = 2.8

μm) with lower open probability (0.33 ± 0.040) and slower deactivation/desensitization kinetics. Because of these subtype‐specific gating properties, NR1/NR2A and NR1/NR2B NMDARs show different macroscopic

kinetics (Erreger, Dravid et al. 2005; Yashiro and Philpot 2008). Upon glutamate binding, NR1/NR2A channels tend to open and close earlier than NR1/NR2B channels due to their higher open probability and faster deactivation/desensitization, resulting in the faster rise and decay time of NR2A‐mediated currents. On the other hand, NR1/NR2B receptors with slower deactivation/desensitization kinetics close slowly enough to carry about two‐fold more charge for a single synaptic event than

NR1/NR2A channels. Moreover, Ca++ imaging studies suggest that NR2B‐containing

NMDARs carry more Ca++ per unit current than NR2A‐containing NMDARs

(Sobczyk, Scheuss et al. 2005). In summary, NMDARs with different subunit compositions may show specific Ca++ dynamics upon activation, which may lead to subunit‐specific influences on the induction of Ca++‐dependent synaptic modifications.

Synaptic locations

In excitatory neurons, NMDARs distribute heterogeneously throughout the membrane of postsynaptic neurons: from dendritic spines, dendritic shaft to somatic membrane. NMDARs at PSDs are defined as synaptic receptors, while extrasynaptic receptors are those expressed at perisynaptic, dendritic or even somatic membranes.

Synaptic NMDARs are activated by glutamate released from individual miniature events or evoked releases under physiological conditions. On the other hand, extrasynaptic NMDARs can only be activated by glutamate spillover driven by

stronger activity that occurs under either physiological or even pathological situations (Kullmann and Asztely 1998; Huang and Bergles 2004). Since the subcellular localization of NMDARs has been shown to predict activation of specific signaling pathways (Hardingham and Bading 2002; Hardingham, Fukunaga et al.

2002; Li, Chen et al. 2002; Ehlers 2003; Li, Otsu et al. 2003; Ivanov, Pellegrino et al.

2006), it has been speculated that the NMDAR subunit composition may be different between synaptic and extrasynaptic regions.

NR2B‐containing receptors are predominantly expressed early in development, while the expression of NR2A‐containing receptors increases through development (Lau and Zukin 2007; Philpot, Cho et al. 2007). It has been proposed that in adult animals NR2A‐containing NMDARs occupy the central portion of synapses, whereas NR2B‐containing receptors are targeted to either the perisynaptic or extrasynaptic domains (Dalby and Mody 2003). However, recent studies argue against this view that NR2A and NR2B containing NMDARs are physically strictly segregated. Fist, since both synaptic and extrasynaptic NMDARs are sensitive to

NR2B‐selective antagonist, NR2B‐containing NMDARs are likely to appear at both synaptic and extrasynaptic pools (Harris and Pettit 2007; Harney, Jane et al. 2008).

Moreover, dynamic exchange of NMDARs has been observed between synaptic and extrasynaptic regions, suggesting a dynamic composition of NMDAR subtypes

(Groc, Heine et al. 2006; Groc, Choquet et al. 2007; Harney, Jane et al. 2008).

Although the spatial distribution of synaptic versus extrasynaptic NMDAR 21

composition is not yet clear, it is reasonable to speculate that modulations on the spatial location of synaptic versus extrasynaptic NR2A‐ or NR2B containing

NMDARs are likely to modify synaptic plasticity.

Protein interactions

Specific subtype composition of NMDAR initiates differential signal transduction pathways through unique protein‐protein interactions and leads to specific NMDAR‐dependent synaptic modifications.

Compared to the short c‐terminus of NR1 subunit, NR2A and NR2B both have much longer intracellular c‐tails allowing intracellular signaling. For both

NR2A and NR2B, the c‐tails contain PDZ‐binding motifs, which allow interactions with membrane‐associated guanylate kinase (MAGUK) family of synaptic scaffolding proteins. It has been proposed that NR2A are preferentially bound to postsynaptic density protein‐95 (PSD‐95), while NR2B are preferentially bound to synapse‐associated protein 102 (SAP102) (van Zundert, Yoshii et al. 2004). Although a recent study suggested that MAGUK proteins such as PSD‐95 and SAP102 interact with di‐heteromeric NR1/NR2A and NR1/NR2B receptors at comparable levels biochemically (Al‐Hallaq, Conrads et al. 2007), at the functional level SAP102 and

PSD95 are known to preferentially mediate synaptic targeting of NR2B and NR2A, respectively, during synaptogenesis and synapse maturation (Elias, Elias et al. 2008).

Other than MAGUK scaffolding proteins, NR2A and NR2B have also been reported to have other intracellular binding partners. For examples, NR2A has been shown to co‐immunoprecipitate with neuronal nitric oxide (NO) synthase (Al‐

Hallaq, Conrads et al. 2007). Although the interaction may not be direct, the preferential association may suggest a potential role of NR2A in NO‐mediated forms of presynaptic LTP and LTD (Zhang, Zhou et al. 2006; Haghikia, Mergia et al. 2007).

As to NR2B, Calcium/calmodulin‐dependent protein kinase II (CaMKII) has been shown to bind to NR2B with high affinity. Recent studies have suggested mutual regulations between NR2B‐containg receptors and CaMKII activation. Activated

CaMKII binds strongly to NR2B, allowing CaMKII to remain active even after dissociating from Ca++/calmodulin (Bayer, De Koninck et al. 2001). Also, CaMKII activation is required for a subunit‐specific retention of NR2B‐containing NMDARs at synapses for LTP induction (Gardoni, Mauceri et al. 2009). Due to the well‐ documented role of CaMKII in LTP, the preferential interaction between NR2B and

CaMKII may suggest a favorable induction of LTP by NR2B‐containing NMDARs

(Barria and Malinow 2005; Zhou, Takahashi et al. 2007; Yashiro and Philpot 2008).

Activity modifies NMDAR subunit composition

Both in vivo and in vitro, NMDAR subunit compositions have been shown to be regulated by behavioral experience and neuronal activity in a cell‐wide manner

(Carmignoto and Vicini 1992; Monyer, Burnashev et al. 1994; Sheng, Cummings et al.

1994; Rao and Craig 1997; Sans, Petralia et al. 2000; Philpot, Sekhar et al. 2001; Barria and Malinow 2002; Ehlers 2003) (Figure 4).

Developmental switch from NR2B to NR2A

During circuit maturation, alterations in NMDAR function and composition have been well documented (Monyer, Burnashev et al. 1994; Sheng, Cummings et al.

1994) (Cathala, Misra et al. 2000; Philpot, Sekhar et al. 2001; Barria and Malinow 2002;

Bear 2003; Philpot, Espinosa et al. 2003; Barria and Malinow 2005; Bellone and Nicoll

2007; Philpot, Cho et al. 2007; Brothwell, Barber et al. 2008; Henson, Roberts et al.

2008). Among many brain regions expressing these development‐associated changes of NMDAR composition, visual cortex has been extensively studied with the greatest detail due to the clear role of sensory experience on its circuit maturation.

NR2B‐containing NMDARs are expressed early in development, while the expression of NR2A‐containiing receptors increases during development (Monyer,

Burnashev et al. 1994; Sheng, Cummings et al. 1994; Sans, Petralia et al. 2000). These developmental changes are accompanied by accelerated decay kinetics of NMDAR currents and also a decrease in infenprodil sensitivity (Kirson and Yaari 1996).

These changes in NMDAR composition can be bidirectionally modulated by activity. The switch from NR2B to NR2A can be delayed by visual deprivation

(Carmignoto and Vicini 1992; Philpot, Sekhar et al. 2001), while the delayed switch can be reversed by light exposure (Kirkwood, Rioult et al. 1996). It is clear that

sensory inputs are required and sufficient for effective subunit switch in the visual cortex, whereas molecular mechanisms underlying the switch are not yet well understood.

Chronic activity influences NMDAR composition

To recapitulate the influence of sensory experience on NMDAR subunit composition and to understand how external or intrinsic activity modulates

NMDAR composition, many studies have implemented strategies that modify the level of activity inputs or neuronal states chronically, including pharmacological and genetic manipulations (Figure 4). Pharmacological manipulations allow for prolonged alterations of population activity, which mimic the prolonged increases or sustained decreases of activity inputs during sensory experience or sensory derivation, respectively. On the other hand, genetic manipulations that change the intrinsic excitability or biochemical states of cells have also shown to modify

NMDAR composition in a cell‐autonomous manner.

Pharmacological manipulations. In vitro, various channel blockers have been utilized to create chronic alterations of population activity. Elevated population activity caused by applying GABA‐receptor antagonist (e.g., Bicuculline) for days has been shown to increase NR2A expression while downregulating NR2B expression. On the other hand, reversed effects were seen under prolonged hypoactivity created by a sustained suppression of action potentials (application of

tetrodotoxin, TTX) or a constant blockade of NMDARs (application of 2‐amino‐5‐ phosphonopentanoate, AP5) (Ehlers 2003). These in vitro results are consistent with the in vivo observation that activity inputs are crucial for facilitating NR2A expression to influence NMDAR composition in a cell wide manner.

Genetic manipulations. Other than changing population activity, some recent studies have suggested that alterations of intrinsic neuronal excitability or biochemical states by genetic means may also lead to cell‐autonomous changes of

NMDAR composition. For example, by altering the expression level of a potassium channel (i.e., Kv4.2), the NMDAR composition can undergo rapid and bidirectional modifications at CA1 synapses. Neurons exhibiting enhanced Kv4.2 expression show a decrease in relative synaptic NR2B/NR2A ratio, while suppressing Kv4.2 function leads to an increased fraction of synaptic NR2B/NR2A (Jung, Kim et al.

2008). On the other hand, blocking CaMKII activation or NR2B/CaMKII interaction leads to a specific reduction of synaptic NR2B‐containing NMDA receptors without affecting localization of the NR2A subunit, resulting in changes of synaptic

NR2B/NR2A ratio (Zhou, Takahashi et al. 2007; Gardoni, Mauceri et al. 2009).

Therefore, in addition to external activity inputs, the intrinsic states of neurons may also play a critical role in modulating NMDAR composition in a cell‐wide manner.

Spontaneous releases and NMDAR composition

Conventionally, only evoked release is considered as effective activity inputs that have biological functions. Only until recently, a potential role of spontaneous releases on AMPARs expression was reported (Wasling, Hanse et al. 2004; Sutton,

Ito et al. 2006). Although these studies with local blockade of spontaneous releases have only examined its effect on GluR1 expression without investigating its influences on NMDAR composition, a global blockade of spontaneous release has been shown to modulate cell‐wide NMDAR composition (Barria and Malinow 2002).

In cultured hippocampal neurons, NMDARs undergo a spontaneous NR2B to NR2A switch. While AP5 application effectively abrogates the switch, TTX and MK801

(non‐competitive antagonist of the NMDA receptor) do not prevent the recruitment of NR2A‐containing NMDARs into synapses. This observation suggests that, rather than evoked activity or channel opening, the binding of glutamate onto NR1/NR2B receptors alone is required and sufficient to trigger the subunit switch (Barria and

Malinow 2002). More studies are required to understand how spontaneous release is utilized in parallel with evoked release to modulate NMDAR composition.

Animal models with altered NMDAR composition

In addition to manipulating activity, efforts have also been put to mandate modified NMDAR compositions for the investigation of subunit‐specific roles of

NR2A‐ and NR2B‐containing NMDARs. Two genetic models have been generated, including NR2A knockout mice (Ito, Sakimura et al. 1996) and NR2B transgenic mice 27

(Tang, Shimizu et al. 1999). These genetic models bypass the activity‐dependent modulations on NMDAR composition and have been used to probe the potential physiological functions of NR2A‐ and NR2B‐containg receptors (Tang, Shimizu et al.

1999) (Philpot, Weisberg et al. 2001; Philpot, Cho et al. 2007; Zhao and Constantine‐

Paton 2007; Bannerman, Niewoehner et al. 2008).

NR2A knockout mice, which are viable without NR2A‐containing NMDARs expressed in the brain, have been widely used to understand the subunit‐specific contributions on activity‐ and NMDAR‐ dependent synaptic modulations, such as the developmental subunit switch and the induction of synaptic plasticity (Ito,

Sakimura et al. 1996; Philpot, Cho et al. 2007; Zhao and Constantine‐Paton 2007;

Bannerman, Niewoehner et al. 2008). NR2B transgenic mice, which may partially overwrite the developmental subunit switch with overexpressed synaptic NR2B‐ containing NMDARs later in life, have been reported with modified synaptic plasticity, suggesting a special role of NR2B in plasticity induction (Tang, Shimizu et al. 1999; Lee and Silva 2009).

NMDAR composition is modulated in a cell-wide manner

As described above, activity modifies NMDAR composition. Not only external activity but also intrinsic excitability are able to bidirectionally modulate

NR2A/NR2B ratios in individual cells. In general, activity drives a decrease of

NR2B/NR2A ratio by recruiting NR2A‐containing receptors into synapses while

inactivity prevents the NR2A recruitment and blocks the decrease on NR2B/NR2A ratio. Interestingly, sensory experience, chronic activity manipulations and alterations of neuronal excitability all seem to modify NMDAR composition in a cell‐wide manner. It is not yet clear, however, whether NMDAR composition can only be regulated in a cell wide manner or, alternatively, NMDAR composition can be modulated in an input‐specific manner at the single synapse level. Studies with improved spatial resolution (i.e., single‐synapse resolution) are needed to specifically test the latter possibility of local regulations on NMDAR composition at single synapses.

NMDAR composition modifies synaptic plasticity

Given that NMDAR composition not only determines channel properties but also influences the dynamics of Ca++ influx upon receptor activation, NMDAR composition is likely to affect Ca++ dynamics in response to activity inputs. Moreover, the subunits‐specific coupling to unique signaling pathways may further differentiate the physiological outcomes driven by subunit‐specific activation. For example, the strong interaction between NR2B and CaMKII has been well documented and presumably links NR2B activation to the induction of specific plasticity (Barria and Malinow 2005; Zhou, Takahashi et al. 2007; Gardoni, Mauceri et al. 2009).

Many tools have been utilized to test the specific involvements of NR2A and

NR2B in synaptic plasticity. In addition to the genetic models described above, pharmacological approaches have been widely implemented to selectively block either NR2A‐ or NR2B‐containing receptors to acutely modify NMDAR composition

(e.g., NVPAAM077 for NR2A and ifenprodil and Ro 25‐6981 for NR2B). Neurons with modified NMDAR composition are then subjected to specific stimuli to test the corresponding changes on their LTP and LTD induction.

Subunit composition determines the induction threshold of Hebbian plasticity

Although NMDAR composition has been proposed to determine the direction of plasticity, the subunit‐specific roles have been controversial. While

NR2A has been reported as the obligatory subunit for LTP (Liu, Wong et al. 2004;

Massey, Johnson et al. 2004), many studies have however indicated a crucial role of

NR2B in LTP induction (Tang, Shimizu et al. 1999; Barria and Malinow 2005;

Philpot, Cho et al. 2007; Zhou, Takahashi et al. 2007; Jung, Kim et al. 2008). Similarly, both NR2A and NR2B have been implicated in the induction of LTD (NR2B: (Liu,

Wong et al. 2004; Zhao and Constantine‐Paton 2007); NR2A: (Barria and Malinow

2005; Morishita, Lu et al. 2007; Jung, Kim et al. 2008)) (Table 2). To accommodate the controversy, a recent model proposed that rather than relying one or the other subunit solely, the relative level of these two subunits (i.e., NR2A/NR2B) modifies plasticity threshold for LTP and LTD induction (Kopp, Longordo et al. 2006; Kopp,

Longordo et al. 2007; Philpot, Cho et al. 2007; Yashiro and Philpot 2008). Due to the slower decay kinetics of NR2B and the unique interaction between NR2B and

CaMKII, it is likely that NR2B‐containinng NMDARs not only allow enhanced Ca++ influx upon activation but also provide a molecular substrate in proximity for LTP induction (Barria and Malinow 2005; Zhou, Takahashi et al. 2007; Gardoni, Mauceri et al. 2009). With that, the lower NR2A/NR2B ratio predicts a lower threshold for plasticity induction, whereas a higher NR2A/NR2B ratio raises plasticity threshold

(Figure 5).

NMDAR composition as a substrate for metaplasticity

Other than developmental metaplasticity in the visual cortex, more studies also suggest the possibility of utilizing NMDAR composition as a general substrate for metaplasticity due to following reasons. First, the subunit composition of

NMDARs can be modulated by neuronal activity in many types of neurons (Philpot,

Sekhar et al. 2001; Barria and Malinow 2002; Yashiro and Philpot 2008). Also, alterations of NMDAR composition have been shown to modify the induction of synaptic plasticity (Tang, Shimizu et al. 1999; Liu, Wong et al. 2004; Barria and

Malinow 2005; Jung, Kim et al. 2008; Gardoni, Mauceri et al. 2009). Moreover, a few recent studies have managed to implement chronic activity alterations with resulting changes in NMDAR composition, and then directly test the corresponding modifications on synaptic plasticity (Barria and Malinow 2005; Jung, Kim et al. 2008;

Gardoni, Mauceri et al. 2009). For example, in cultured hippocampal slices, chronic blockade of spontaneous activity prevents the recruitment of NR2A‐containing receptors and preserves the lower threshold of LTP induction (Barria and Malinow

2005) in individual neurons. The expression level of Kv4.2 modifies cell‐wide

NMDAR composition and leads to corresponding modulations on plasticity induction (Jung, Kim et al. 2008). Further, blocking CaMKII activation or

NR2B/CaMKII interaction leads to a cell‐wide reduction of synaptic NR2B‐ containing NMDARs and compromises LTP induction (Zhou, Takahashi et al. 2007;

Gardoni, Mauceri et al. 2009). While the current data are consistent with the idea that activity modulates NMDAR composition to modify synaptic plasticity, studies with finer spatial or temporal resolution may help to understand the nature of

NMDAR‐composition‐dependent metaplasticity.

Heterogeneity of synaptic NMDAR composition

Afferent‐specific NMDAR composition has been reported in both cortical and hippocampal neurons (Kawakami, Shinohara et al. 2003; Kumar and

Huguenard 2003; Arrigoni and Greene 2004; Wu, Kawakami et al. 2005). In layer 5 cortical neurons, differential NMDAR composition has been found between synapses receiving colossal inputs and intracortocal inputs (Kumar and Huguenard

2003) (Table 3). In hippocampal CA1 neurons, afferent‐specific weight of NR2B‐ cntaining NMDARs has been observed in Shaffer‐collateral pathway and Perforant

pathway inputs (Arrigoni and Greene 2004). Synapses receiving Shaffer‐collateral inputs show higher sensitivity (~70%) to NR2B blocker, ifenprodil, while synapses receiving Perforant inputs are less sensitive to ifenprodil blockade (~35%).

Moreover, left‐right asymmetry of hippocampal synapses has also been observed with differential weights of NMDAR containing NR2B (Kawakami, Shinohara et al.

2003; Wu, Kawakami et al. 2005; Shinohara, Hirase et al. 2008). In the apical dendrite of CA1 neurons, afferents originated from the left‐side CA3 predict a higher fraction of NR2B‐containing receptors while in the basal dendrite the afferents originated from the right‐side CA3 predict a higher weight of NR2B. These data suggest that the regulation of NMDAR subunit composition by prior activity may occur at the sub‐cellular level and may potentially be at individual synapses (Sobczyk, Scheuss et al. 2005).

NMDAR composition as a substrate for metaplasticity: input-specific?

The reported cell‐wide expression of changes in NMDAR composition seems to suggest that NMDAR composition can only be modulated globally but not locally at individual synapse. However, the heterogeneity of NMDAR compositions found in different afferents (Arrigoni and Greene 2004; Sobczyk, Scheuss et al. 2005) may indicate the need of local mechanisms in regulating NMDAR composition (more discussion in the next session). Up to date, no studies conducted were able to implement chronic activity alterations locally with resulting modification of NMDAR

composition, and then directly test the corresponding modifications on synaptic plasticity at single synapses. Again, to understand if NMDAR composition can be utilized for input‐specific regulations on synaptic plasticity, strategies with single synapse resolution for local priming and local plasticity induction are required.

While it has not been tested directly, synapse‐specific NMDAR compositions may predict synapse‐specific plasticity threshold (Wu, Kawakami et al. 2005) and suggest the presence of input‐specific metaplasticity. However, due to the limited spatial resolution of manipulations utilized, little has been known about the causes and physiology behind the synapse‐specific NMDAR composition

Local activity manipulations

In order to create systems for sustained activity manipulations at single synapses I utilized in my thesis work, here I review some current strategies that have been used for local activity manipulations. Most of these strategies were implemented to study the spatial expression of activity‐dependent modulations on synaptic AMPARs (Harms, Tovar et al. 2005; Ehlers, Heine et al. 2007; Hou, Zhang et al. 2008; Ibata, Sun et al. 2008).

Acute and local activity manipulations

Traditionally, regulations on synaptic GluR composition have been generally considered as a cell‐wide phenomenon. This conclusion was reached based mostly on manipulations that change the global activity level of all synaptic inputs for a 34

given neuron (Rao and Craig 1997; Turrigiano, Leslie et al. 1998; Burrone, OʹByrne et al. 2002; Thiagarajan, Piedras‐Renteria et al. 2002; Ehlers 2003; Thiagarajan, Lindskog et al. 2005; Thiagarajan, Lindskog et al. 2007; Jung, Kim et al. 2008). The lack of spatial resolution for individual synapses poses a difficulty to distinguish a real cell‐ wide effect from individually responding synapses.

Recently, a few attempts of local activity manipulations were made by pharmacological means (Figure 6A). Local perfusion of activity blockers inactivates synaptic transmission in spatially confined regions ranging from 10‐20 μm (Sutton,

Wall et al. 2004; Sutton and Schuman 2005; Branco, Staras et al. 2008; Ibata, Sun et al.

2008) (Figure 6A). Local perfusion is suitable for comparing contributions of activity inputs from different subcellular compartments (e.g., somatic input versus dendritic inputs) and has been mainly used to determine local homeostasis (Branco, Staras et al. 2008) and the induction mechanism of synaptic AMPARs scaling (Sutton, Wall et al. 2004; Sutton and Schuman 2005; Ibata, Sun et al. 2008). While drug perfusion can be relatively local, it does not provide information with single‐synapse resolution.

Sustained local activity manipulation at individual synapses

Genetically modified presynaptic boutons have also been implemented to chronically inactivate synaptic release at individual synapses (Figure 6B).

Suppression of presynaptic release at individual synapses can be achieved via genetically introducing inward‐rectified potassium channel (Kir2.1) or TetTX into

boutons (Harms, Tovar et al. 2005; Ehlers, Heine et al. 2007; Hou, Zhang et al. 2008).

Expression of Kir2.1 and TetTX affects presynaptic release through different mechanisms. Over‐expressed Kir2.1 channels allow constant inward potassium currents to clamp membrane potential at a slightly hyperpolarized state (Yang, Sun et al. 2000; Burrone, OʹByrne et al. 2002; Yu, Power et al. 2004; Hou, Zhang et al.

2008). Presynaptic boutons kept at the hyperpolarized potential are quieter with less evoked transmitter releases compared to control boutons. Although boutons expressing Kir2.1 show compromised evoked releases, the level of spontaneous releases in these boutons is still preserved. One potential caveat of using the Kir2.1‐ based inactivation is that the suppressed releases may be restored automatically in

2~3 days because of endogenous compensatory mechanisms, suggesting a restricted time window of an effective inactivation (Hou, Zhang et al. 2008).

On the other hand, expression of TetTX not only completely blocks evoked neurotransmitter release but also produces an over 90% blockade on spontaneous release through the proteolytic activity of the toxin against VAMP2 (Capogna,

McKinney et al. 1997; Humeau, Doussau et al. 2000; Schoch, Deak et al. 2001; Harms and Craig 2005). Different from Kir2.1‐based inactivation, TetTX constantly digests

VAMP2 and provides a sustained blockade of synaptic transmission for days or even weeks (Harms and Craig 2005; Ehlers, Heine et al. 2007; Nakashiba, Young et al.

2008).

Local activity manipulation and NMDAR composition

Up to date, both local drug perfusion and synapse‐specific inactivation have been mainly used to study the spatial expression of activity‐dependent modulations on synaptic AMPARs but not NMDARs. Given the crucial role of synaptic NMDARs on the induction of synaptic plasticity, it is critical to understand if synaptic

NMDARs can be locally modulated by activity and serve as a general mechanism for input‐specific metaplasticity.

Experimental rationales and specific aims

The goal of my thesis work is to determine how synaptic states are primed by synaptic inputs at single synapses. I hypothesized that spontaneous release can modulate synaptic states and lead to input‐specific metaplastic regulations by tuning postsynaptic NMDAR composition.

As I discussed above in detail, synapses serve as minimal computation units allowing information to be processed and integrated through time. However, little is known about whether and how activity cues can constantly modulate receptor composition and synaptic states, thus allowing prior experience to modify subsequent plasticity induction at the level of a single synapse.

Moreover, while NMDAR is known for playing crucial roles in synaptic plasticity at excitatory synapses in the mammalian central nervous system, its relatively constant synaptic expression level and well‐documented cell‐wide 37

modulations have given an impression that synaptic NMDARs may not be locally modulated by activity to serve as a general mechanism for input‐specific metaplasticity. Elucidating these synapse‐specific mechanisms is the goal of the two

Specific Aims described below.

AIM#1: To determine if activity inputs modify synaptic states at single synapses

Allowing plasticity induction to be modified is essential to ensure a proper working range for plasticity to occur and likely to offer another layer of capacity for information storage (Montgomery and Madison 2004; Fusi, Drew et al. 2005; Fusi and Abbott 2007; Abraham 2008). However, little is known about whether activity cues can constantly modulate receptor composition and synaptic states homosynaptically at single synapses. To test if the tonic level of synaptic inputs determines the synaptic state by altering synaptic molecular composition at individual synapses, I developed systems allowing sustained alterations of individual synaptic inputs. By implementing a history of inactivity at single synapses (silenced synapses), I demonstrated that individual synaptic inputs control synaptic states homosynaptically while allowing heterosynaptic integration among spatial compartments along dendrites.

AIM#2: To determine if NMDAR composition serves as a substrate for input-specific metaplasticity

The experimental results in AIM#1 suggested an activity‐dependent modulation of synaptic states at single synapses, including changes of synaptic

NMDARs. Given the crucial role of NMDARs involved in plasticity induction, my experiments in AIM#2 were directed at understanding how NMDARs are modulated at single synapses and what are the physiological consequences resulting from these input‐specific modulations on NMDARs.

Using immunocytochemistry, I found that not only the number but also the subunit composition of NMDARs was modified at individual silenced synapses. In collaboration with Ryohei Yasuda, I performed whole‐cell patch recording in conjunction with two‐photon glutamate uncaging to measure NMDAR‐mediated synaptic current at single synapses. I verified the enhanced NMDAR‐mediated responses and increased NR2B weights at single silenced synapses as seen in immunostaining. Furthermore, taking advantage of two‐photon glutamate uncaging system again, I managed to trigger sustained synaptic plasticity at single synapses to probe the threshold for long‐term potentiation of AMPAR‐currents and long‐term spine enlargement at both silenced and control synapses. I discovered that the silenced synapses acquired lower thresholds in both LTP paradigms. Interestingly, since these input‐specific modulations on NMDAR were not sensitive to chronic blockade of evoked release (i.e., chronic TTX application), it is likely that the

synaptic NMDARs were modified by spontaneous release at individual synapses. In summary, I report here a novel form of regulation on synaptic plasticity in which spontaneous glutamate release modifies synaptic NMDAR subunit composition, resulting in the tuning of plasticity threshold.

Table 1. The subunit‐specific properties of NR2A and NR2B subunits

NR1/NR2A NR1/NR2B

References:

Open (Chen, Luo et al. 1999) High Low probability (Erreger, Dravid et al. 2005)

Deactivation Fast Slow (Erreger, Dravid et al. 2005)

Peak amplitude High Low (Erreger, Dravid et al. 2005)

(Monyer, Burnashev et al. 1994) Rise time Fast Slow (Vicini, Wang et al. 1998; Chen) (Luo et al. 1999) (Monyer, Burnashev et al. 1994) (Vicini, Wang et al. 1998;) Decay time Fast Slow (Chen, Luo et al. 1999; ) (Prybylowski, Fu et al. 2002)

Charge transfer Low High (Erreger, Dravid et al. 2005)

Ca++/EPSC Low High (Sobczyk, Scheuss et al. 2005)

CaMKII (Strack and Colbran 1998) Weak Strong binding (Mayadevi, Praseeda et al. 2002)

In addition to the references listed, the table is adapted from (Yashiro and Philpot 2008).

Table 2. NMDAR subunit compositions modify the induction of LTP and LTD

NR2A > NR2B NR2B > NR2A

References:

LTP (2B‐TG*1) (Tang, Shimizu et al. 1999)

LTP LTD (Liu, Wong et al. 2004)

LTP LTD (Massey, Johnson et al. 2004)

LTD LTP (Barria and Malinow 2005)

LTP LTP (Berberich, Punnakkal et al. 2005)

Plasticity LTP LTP (Zhao, Toyoda et al. 2005)

Not LTD (Morishita, Lu et al. 2007)

LTP (2A‐KO*2) (Philpot, Cho et al. 2007) (Lower threshold)

LTD (2A‐KO) (Zhao and Constantine‐Paton 2007)

Impaired LTP (Zhou, Takahashi et al. 2007)

LTD LTP (Jung, Kim et al. 2008)

*1NR2B transgenic mice (Tang, Shimizu et al. 1999) *2NR2A knockout mice (Ito, Sakimura et al. 1996) In addition to the references listed, the table is adapted from (Yashiro and Philpot 2008)

Table 3. Afferent‐specific NMDAR composition

Afferent/synapse‐specific NMDAR composition Higher weight of All afferents References: NR2B‐NMDAR

Neocortical Intra‐cortical (Kumar and Intra‐cortical layer 5 neuron Collossal Huguenard 2003)

Input from left CA3 Apical: Input from left CA3 Input from right CA3 (Kawakami, Shinohara Hippocampal et al. 2003) CA1 neuron (Wu, Kawakami et al. Input from right CA3 Basal: Input from right CA3 2005) Input from left CA3

Hippocampal (Arrigoni and Greene Schaffer‐collateral Perforant Schaffer‐collateral CA1 neuron 2004)

Hippocampal Smaller spines contain a higher fraction of NR2B‐ (Sobczyk, Scheuss et CA1 neuron containing NMDARs al. 2005)

Figure 1. Vesicular recycling and SNAREs at presynaptic boutons

(A) Synaptic vesicles are constantly recycled in presynaptic boutons. In each cycle of vesicle release, individual synaptic vesicles undergo a sequence of events, including vesicle priming/docking, vesicle fusion and endocytosis, to be shuttled between the reserve pool (RP) and the readily releasable pool (RRP) at the active zone (AZ).

(B) Vesicle docking is facilitated by the SNARE complex, which includes VAMP2 (green), SNAP25 (blue) and syntaxin (red). The SNARE complex functions as a zipper to bring synaptic vesicle and plasma membrane in proximity and leads to efficient membrane fusion. The SNARE assembly is facilitated by a rise of intracellular calcium (Ca++) concentration to allow effective synaptic release.

Figure 1. Vesicular recycling and SNAREs at presynaptic boutons

Figure 2. The origin of synaptic vesicles for evoked and spontaneous release

(A) One reserve pool of vesicles supplies both evoked and spontaneous release. Traditionally, the occurrence of spontaneous release is thought to reflect the random fusion of synaptic vesicles onto plasma membrane, while evoked release is a mode of synchronous release triggered by a raise of intracellular Ca++ upon activity. Therefore, it has been considered that synaptic release, including both evoked release and spontaneous release, is supplied by only one reserved pool (RP) of synaptic vesicles.

(B) Two different pools of vesicles are utilized for evoked release and spontaneous release. Recently, some evidence suggests the possibility of utilizing different pools of vesicles for specific modes of synapse release. While vesicles for evoked release are originated from RP, vesicles for spontaneous release are cycled through a physically segregated route and originated from spontaneous recycling pool (SRP).

Figure 2. The origin of synaptic vesicles for evoked and spontaneous release

Figure 3. Metaplasticity

Metaplasticity is considered as mechanisms allowing prior experience to modulate current plasticity induction. While priming activity may not be sufficient to alter the synaptic strength per se, priming activity modifies synaptic states to influence the induction and expression of synaptic plasticity occurring later on.

As shown in the schematic, a prior exposure of priming activity leads to specific changes on synaptic contents of Ca++‐permeable GluRs (e.g., NMDARs) and results in corresponding modifications on the recruitment/removal of synaptic AMPARs in response to plasticity inducing stimuli (HFS, high frequency stimulation; LFS, low frequency stimulation). While the induction and expression phases are tightly coupled temporally in Hebbain plasticity, such temporal coupling is loosened in metaplasticity and can potentially be minutes to days apart.

Figure 3. Metaplasticity

Figure 4. Activity‐dependent regulations on NMDAR subunit composition

NMDAR subunit composition has been shown to be regulated by activity in a cell‐ wide manner. Neurons subjected to activity inputs predict NR2A‐dominant synaptic NMDAR composition, whereas inactivity favors NR2B‐dominant synaptic NMDAR composition. Moreover, in addition to the external activity level, the NMDAR composition is also modulated by the intrinsic state of individual neurons. Changes on the intrinsic activity (e.g., Kv4.2 expression) or biochemical states (e.g., CAMKII inactivation) can also induce cell‐wide alterations on subunit composition in a cell autonomous manner.

Up to date, all manipulations employed to modify the cell‐wide NMDAR composition are implemented globally without single‐synapse resolution. Thus, manipulations with improved spatial resolution may help to gain insights on synapse‐specific regulation of NR2A‐ and NR2B‐containing NMDARs.

Figure 4. Activity‐dependent regulations on NMDAR subunit composition

Figure 5. NMDAR subunit composition modifies synaptic plasticity

Prevailing model suggests that rather than either subunits, the relative level of NR2A and NR2B (NR2A/NR2B) modifies plasticity threshold for LTP and LTD induction. While a higher NR2A/NR2B ratio (i.e., NR2A>NR2B, black trace) predicts a higher threshold for both LTP and LTD, a lower NR2A/NR2B ratio (i.e., NR2A

Due to the cell‐wide expression of NMDAR subunit composition previously documented, it has been assumed that synaptic plasticity threshold is also modulated in a cell‐wide manner. However, it has not been tested directly whether NMDAR composition can modify synaptic plasticity in an input‐specific manner

Figure 5. NMDAR subunit composition modifies synaptic plasticity

Figure 6. Activity manipulations with distinct spatial resolution

Different strategies have been implicated on neuronal cultures to manipulate activity in specific spatial scales.

(A) Pharmacological treatments provide chronic activity manipulations in either global or local fashion. Global application of channel blockers has been widely used to chronically control neuronal activity. For example, activity‐dependent regulations of NMDAR composition are mainly characterized by global application of channel blockers, such as TTX, Bicuculline or AP5. On the other hand, local drug application can improve spatial resolution to 10‐20 μm physical range, covering tens of synaptic connections. Local drug perfusion is suitable for addressing issues such as region– specific roles of dendrites and soma. In most of cases, pharmacological manipulations provide no single‐synapse resolution.

(B) Contrary to pharmacological methods, genetic strategies allow manipulations of activity at single synapses. As shown in the schematic, introducing molecules that affect synaptic release in a subpopulation of neurons can lead to individual modified synaptic inputs on a given postsynaptic neuron. This single‐synapse‐based manipulation is critical for understanding synaptic physiology in an input‐specific manner.

Figure 6. Activity manipulations with distinct spatial resolution

Chapter 2. Materials and methods

In this chapter I will first introduce the experimental approaches that allow chronic synaptic inactivation to occur at single synapses. Then, I will describe in detail all materials used and methods developed for experiments described in chapters 3 and 4. Primary hippocampal neuronal cultures were constantly supplied by Marguerita Klein and Irina Lebedeva. All experiments utilizing two‐photon microscopy systems were done in the laboratory of Ryohei Yasuda (Duke University,

Durham, NC).

General strategy

Synaptic inactivation and single synapse resolution

To examine synapse‐specific effects of synaptic activity inputs, manipulations on synaptic inputs were aimed to chronically control synaptic transmission at the scale of individual synapses. Better spatial resolution was gained by using dissociated hippocampal primary cultures, which are usually single‐layer neuronal networks with adjustable neuronal or even synaptic density in a spatially confined region. Taking advantage of randomized synapse formation among cultured neurons, manipulations of axonal release on a subpopulation of neurons can be translated into a certain fraction of modified inputs in individual postsynaptic unmodified neurons. Therefore, single‐synapse resolution was achieved at individual postsynaptic neurons by visualizing a small fraction of 56

synapses receiving modified inputs that are spatially intermingled with a majority of unaffected neighboring synapses.

Identify excitatory synapses

To focus the effects of synaptic inactivation on only excitatory synapses, two strategies were applied to identify excitatory synapses in individual neurons. First, neuronal cultures that underwent random synaptic inactivation were subjected to immunocytochemistry (IC) against vesicular glutamate transporter (vGlut), which labels glutamatergic boutons. On the other hand, neuronal cultures that underwent synaptic inactivation were subjected to transfection with pCNV5‐mCherry to randomly label postsynaptic neurons. Visualized dendritic spines from cherry‐filled neurons were used as an indication of excitatory synapses. On average, individual neurons contained only a small fraction (1%~3%) of modified synapses under our preparation (Figure 7).

Materials and methods

For all experiments described in Chapter 3, 4 and 5, data were acquired from two to five independent experiments. Unless otherwise indicated, N values correspond to the number of neurons analyzed and n values represent the number of spine (or pair of spines).

DNA constructs, antibodies and reagents

Chemical-based inactivation

VAMP2‐GFP was amplified from VAMP2‐IRES‐Kir2.1 (a gift from Venkatesh

Murthy Harvard, Cambridge, MA) by PCR. Amplified VAMP2‐GFP was subcloned into the SpeI site of the pC4M‐Fv2E vector (Ariad Pharmaceuticals, regulated himodimerization kit) to generate the 2FKBP‐VAMP2‐GFP construct.

Tetanus toxin-based inactivation

Synaptophysin(Sph)‐EGFP was kindly provided by George Augustine (Duke

University, Durham, NC). Tetanus toxin light chain (TetTxLC) cDNA was a gift from Joseph Gogos (Columbia University, New York, NY). These two cDNAs were cloned in frame before and after the internal ribosome entry site (IRES) of pIRES‐

EGFP (Clontech). Synaptophysin‐EGFP‐IRES‐TetTxLC (SphGFP‐IRES‐TetTX) was incorporated into a lentiviral expression vector to generate a high titer virus.

(Transzyme, Durham, NC). Viral titers ranged from 0.1 – 1.0 x 109 particles/ml.

Primary neuronal culture, transfection and viral infection

Hippocampal neuron cultures were prepared from E18 rat embryos and maintained for 19‐22 days in vitro (DIV) as described (Ehlers, Heine et al. 2007).

Hippocampal neurons were introduced with constructs expressing modified

VAMP2 (2FKBP‐VAMP2GFP) or engineered tetanus neurotoxin (SphGFP‐IRES‐

TetTX) through transfection (Lipofectamine™ 2000, Invitrogen, CA) or infection at

DIV11‐14. Modified VAMP2 was introduced into cells and allowed for two days of expression before the induction of dimerization. Synaptic inactivation was measured

30 minutes after drug application using FM loading assays. As to TetTX, 7‐10 days expression of toxin was allowed before measuring the suppression on synaptic release. For experiments that utilized TetTX, immunocytochemistry and electrophysiology assays were conducted at DIV19‐21.

Immunocytochemistry and antibodies

For immunostaining against NMDAR subunits, hippocampal primary cultures were fixed with 4% paraformaldehyde/4% sucrose and permeabilized with ‐

20°C methanol and 0.1% Triton X‐100 in PBS. Blocking was performed on fixed neurons with 5% BSA/10% goat‐serum for 8 hours at 4°C. Fixed neurons were then incubated with mouse anti‐NR1 (Affinity BioReagents, #OMA1‐04010), rabbit anti‐

NR2A (Millipore, #07‐632) or mouse anti‐NR2B (BD Bioscience, #610416) for 8 hours at 4°C. After washing with PBS, cells were incubated with Alexa 647‐conjugated secondary antibodies (Molecular Probes) for 1 hour at room temperature. Cells were then washed with PBS again and mounted onto glass slides with 5‐10 μl of mounting solution (Electron Microscopy Science #17985‐10).

For GluR1 surface staining, the primary antibody, GluR1‐N antibody (rabbit anti‐GluR1 N‐terminal antibody, (Ehlers 2000)), was applied on live hippocampal neurons for 20 minutes at room temperature before standard fixation and staining

protocol applied. For NR2B surface staining (Ab‐NR2B‐N, a gift from F Anne

Stephenson, University of London, London, UK), cultures were first fixed with 4% paraformaldehyde/4% sucrose. Without permeabilization, fixed cells were then incubated with Ab‐NR2B‐N (1.6x10‐3μg/μl) for 20 minutes at room temperature before following the standard staining protocol.

For immunostaining against proteins other than NMDAR subunits, including VAMP2 (synaptic system #104 211), PSD95 (upstate #05‐427), Homer‐1

(synaptic system #160 003), NLG‐1 (synaptic system #129 111), CaMKII‐a (Zymed

#13‐7300) and CaMKII‐b (Zymed #13‐9800), cells were fixed with 4% paraformaldehyde/4% sucrose but permeabilized with only Triton X‐100 in PBS. The rest of staining procedures were similar to the protocol described above.

Chemical-based inactivation

2FKBP‐VAMP2GFP was introduced into hippocampal neuronal cultures using lipofectamine‐2000 based transfection at DIV11‐14. Homodimerization between 2FKBP‐VAMP2‐GFP molecules was induced through application of cell‐ permeable dimerizer (AP20187, 200nM/DMSO, Ariad Pharmaceuticals, regulated homodimerization kit) (Karpova, Tervo et al. 2005). AP20187 is a synthetic molecule that can simultaneously bind to two FKBP (FK506 binding protein) motifs intra or inter molecules. For synaptic inactivation, 2μl of AP20187 (200μM) was added into

the culture medium. Synaptic inactivation was determined by measuring FM uptake on green boutons 30 minutes after dimerizer application.

FM loading assay

To verify blockades of synaptic release, the effectiveness of presynaptic recycling was monitored by FM uptake assays. Synaptic boutons with active vesicular recycling express massive exocytosis and endocytosis upon stimulation, which allows for uptaking amphiphilic FM dyes from the bath medium. On the other hand, boutons with compromised vesicular release would show impaired FM loading.

High potassium‐loading method was utilized here to induce FM loading.

Cultures transfected or infected with inactivating constructs/viruses (i.e., VAMP2‐

GFP‐IRES‐Kir2.1, 2FKBP‐VAMP2GFP and SphGFP‐IRES‐TetTX) were washed with

E4 solution (119mM NaCl, 2.5mM KCl, 2MgSO4, 2mM CaCl2, 25mM HEPES, 30mM glucose, pH=7.4). After wash, cultures were immersed under high potassium solution containing 10 μM FM4‐64 (78.5mM NaCl, 50mM KCl, 2mM MgSO4, 2mM

CaCl2, 10mM HEPES, 10mM glucose, pH=7.4, plus 10uM CNQX, 50uM APV and

1uM TTX) for 60 sec. at room temperature. Samples were then washed with E4 solution for live‐imaging acquisition. (Gaffield and Betz 2006)

Image analysis and quantification

For fixed samples, images were acquired using Ultraview spinning‐disc confocal microscope and analyzed using Metamorph (Universal Imaging

Corporation). Z‐series images were taken for individual neurons of interest and maximal‐projections along Z‐axis were acquired for further quantification. To measure synaptic contents of the protein of interest, circular regions with a diameter of 0.7 μm were selected based on the center of individual spine heads. In individual neurons, regions were first chosen blindly through all synapses and then classified into synapses with GFP + and GFP‐ boutons based on the VAMP2‐GFP or the synaptophysinGFP channel. Unless otherwise indicated, the GFP+ and GFP‐ boutons were corresponding to modified/silenced synapses (S) and neighboring active synapses (A) respectively (Figure 8).

To calculate the normalized synaptic content of the protein of interest, two A and S regions were then each transferred to maximal projections of the target channel (i.e., staining of synaptic molecules), allowing for measuring the integrated intensity of individual regions. For each neuron, 25‐30 more regions from background were randomly picked to measure the background intensity. This background intensity was then subtracted from the measured synaptic signal of individual staining to quantify synaptic contents of individual proteins. Synaptic contents measured from silenced synapses were normalized to the mean synaptic content of active synapses (S/ A , 200~500 active synapses per neuron) within each 62

neuron. Each S/ A value describes how one silence synapse was different from the average active synapse in terms of the fold of changes of specific synaptic content.

Two-photon microscopy

Two‐photon laser‐scanning microscopy and two‐photon glutamate uncaging were performed on the system powered by a Ti:sapphire pulsed laser MaiTai

(Spectra‐Physics, Fremont, CA). The laser was tuned to 920 nm for imaging (spine visualization), and tuned to 720 nm for glutamate uncaging. The intensity of each laser beam was independently controlled with electro‐optical modulators (350‐80 LA;

Conoptics, Danbury, CT). Beams were combined using a dichroic mirror (790SP;

Chroma Technology, Brattleboro, VT) and went through the same set of scan mirrors and a 60x, 0.9 numerical aperture objective (Olympus, Melville, NY).

Fluorescence was detected by summing epifluorescence and transfluorescence signals, as described previously (Mainen, Malinow et al. 1999). All two‐photon based experiments were performed at room temperature in ACSF containing the following (in mM): 2.0 MgCl2, 2.0 CaCl2, 0.001 TTX and 2.0 4‐methoxy‐7‐ nitroindolinyl (MNI)‐caged‐L‐glutamate except for the spine enlargement assays (0

MgCl2 was applied). ACSF was constantly bubbled with 95% O2 and 5% CO2 through experiments. Imaged and stimulated spines were located on secondary and tertiary apical dendrites within 150 μm from the soma.

Two-photon uncaging and uEPSC recording

Voltage‐clamp whole‐cell recordings (Vhold = ‐65 mV) from hippocampal neurons were made with pipettes (4‐6 MΩ containing Cs‐based internal solution (in mM): 135 CsMeSO3, 10 HEPES, 10 Na‐phosphocreatine, 4 MgCl2, 4 Na2‐ATP, 0.4

Na‐GTP, 3 ascorbate). MNI‐caged‐L‐glutamate and TTX were from Tocris Cookson

(Ballwin, MO). Recordings were made using a Multiclamp 700B amplifier, filtered at

2 kHz for voltage‐clamp recordings.

Local uncaging stimulation was delivered on the tip of spine heads (~0.5 μm from the center of the spine head in the direction away from the dendritic shaft) and

2‐photon‐uncaging induced excitatory currents (uEPSCs) were recorded from the soma. Different power of uncaging laser (5‐12 mW) was delivered to the tip of spine heads to induce uEPSCs. As the uncaging power increased, uEPSCs also increased in a near‐linear fashion, suggesting that the power used in our experiment (5mW) is within the proper linear range without saturating all synaptic receptors (Figure 9A). uEPSCs elicited from individual synapses were measured and compared to miniature‐release‐induced‐excitatory‐postsynaptic‐currents (mEPSCs) in individual recordings (Figure 9B). For all events recorded, no significant differences were detected between the average uEPSC (black, 5 spines) and the average mEPSC (grey,

7 events) on peak amplitude, rise time and decay kinetics (peak amplitude: uEPSC =

7.8±0.8pA, mEPSC = 8.9±1.5pA, p = 0.56; Rise time: uEPSC = 2.9±0.4ms, mEPSC =

2.8±0.4ms, p = 0.85; τW: uEPSC = 7.1±2.1, mEPSC = 4.3±1.7, p=0.32), suggesting that 64

individual pulses of uncaging stimulation are comparable to individual quantal releases. Thus, uEPSCs mimic miniature events in our system.

uEPSCs recorded at different holding potentials correspond to currents mediated by different glutamate receptors (i.e., uEPSC‐70 mV = AMPAR‐uEPSC and uEPSC+40 mV = AMPAR‐uEPSC + NMDAR‐uEPSC). NMDAR‐uEPSC was measured from uEPSC+40mV at 40ms after the peak of uEPSC‐70 mV (Figure 9) (Sobczyk,

Scheuss et al. 2005; Beique, Lin et al. 2006; Sobczyk and Svoboda 2007; Zito, Scheuss et al. 2009).

In all the experiments, hippocampal neurons were infected with lentivirus expressing sphGFP‐IRES‐TetTX at DIV11‐21 and then transfected with pCMV5‐ mCherry for two more days. At DIV 19‐21, mCherry‐filled cells were picked and subjected to voltage‐clamp patch for uEPSC recording.

To minimize the differential effect on dendritic filtering, in individual experiments, two nearby but well‐separated spines with comparable size and similar morphology were chosen as a pair of interest, composed of one silenced synapse (S) and one spontaneously active neighboring synapse (A), and stimulated by local glutamate uncaging for uEPSC recordings. To estimate the fraction of NR2B‐ containing receptors at individual synapses, uEPSC recordings were done under the application of 3μM of NR2B selective blocker ifenprodil (Tocris) (Bellone and Nicoll

2007; Morishita, Lu et al. 2007).

Two-photon uncaging and plasticity induction

To probe plasticity threshold at synapses, pairs of spines, one target spine (A or S) and one non‐stimulated neighboring spine (NS), were chosen based on criteria described above. AMPAR‐uEPSCs were measured before and after uncaging stimulation to induce LTP or at a subthreshold stimulation strength (LTP protocol: postsynaptic depolarization (0 mV) paired with 30 uncaging pulses (4ms duration) at 0.5 Hz; subthreshold protocol: postsynaptic depolarization (0 mV) paired with 20 uncaging pulses (1ms duration) at 0.5 Hz)(Matsuzaki, Honkura et al. 2004; Harvey and Svoboda 2007). For individual experiments, AMPAR‐uEPSCs were recorded at two time points before plasticity induction and then recorded once every 5 minutes after the stimulation protocol until the patch was lost. Only cells held more than 20 minutes after the uncaging stimulation protocol were included in our data analysis.

Two-photon uncaging and spine enlargement

As described above, pairs of spines (A+NS or S+NS) were chosen and subjected to uncaging stimulation for plasticity induction. Instead of uEPSCs, the spine volume indicated by mCherry fluorescent intensity was measure before and after uncaging stimulation. For individual experiments, Z stacks were acquired 2 times before plasticity induction and then acquired once every 5 minutes after the uncaging protocol for 30 minutes. Individual z‐series were then collapsed into maximal projections and used to quantify the integrated fluorescent intensity of

individual spines. The changes of spine volume upon uncaging stimulation were described by the fractional change in fluorescent light intensity ([F‐F0]/F0). In ACSF containing 0 Mg++, different uncaging protocols were applied to induce spine enlargement (LTP protocol: 30 uncaging pulses (4ms duration) at 0.5 Hz in 0 Mg++ medium; subthreshold protocol: 20 uncaging pulses (1ms duration) at 0.5 Hz in 0

Mg++ medium and 10 uncaging pulses (1ms duration) at 0.5 Hz in 0 Mg++ medium)(Harvey and Svoboda 2007; Tanaka, Horiike et al. 2008; Zito, Scheuss et al.

2009).

Figure 7. Identify excitatory synapses

Excitatory synapses were identified by vGlut‐staining or postsynaptic cell‐fill.

(A) Glutamatergic presynaptic terminals were identified by vGlut immunocytochemistry (vGlut‐IC, as shown in blue pseudocolor in the left middle and bottom panel). Among labeled glutamatergic terminals, a small fraction of boutons were green silenced boutons (arrowheads). Thus, in individual neurons, excitatory synapses can be characterized as either active (vGlut+, GFP‐) or silenced (vGlut+, GFP‐) synapses, allowing for intracellular comparison between synapses with specific identity.

(B) On the other hand, mCherry expression (cherry‐filled, as shown in blue pseudocolor in the right middle and bottom panel) was used to visualize dendritic spines postsynaptically. Excitatory synaptic connections identified were classified into SphGFP+ (empty arrowhead) and SphGFP‐ groups, which correspond to modified and unmodified synaptic connections, respectively. Therefore, synaptic contents of the protein of interest (as shown in red pseudocolor) can be quantified at both modified and unmodified synapses.

For both strategies, representative pictures were shown in the bottom panels. Scale bar is 5μm.

Figure 7. Identify excitatory synapses

Figure 8. Normalized synaptic content

Normalized synaptic contents (S/ A ) were measured to quantify synapse‐specific effects of modified synaptic inputs. Each S/ A value describes how one silence synapse was different from the average active synapse in terms of fold of changes of specific synaptic content.

For each protein of interest, the synaptic contents were measured from both silenced (arrowhead) and active synapses as total integrated intensity in individual neurons. Then, the absolute synaptic contents (S’ and A’) were acquired by subtracting out the background intensity (B) from the raw integrated intensity (S and A) measured at individual synapses. Each value of normalized synaptic content was acquired by dividing individual S’ to the A (the mean content of all active synapses), indicating the difference between a silenced synapse and its active neighboring synapses.

Figure 8. Normalized synaptic content

Figure 9. Two‐photon glutamate uncaging

Synaptic currents were recorded by whole cell voltage clamp in conjunction with focal two‐photon glutamate uncaging. Pulses of uncaging laser were delivered to the tip of spine heads to elicit uncaging‐induced excitatory postsynaptic currents (uEPSCs) at two holding potentials, ‐70 mV and +40 mV. uEPSCs (black arrowhead) were measured and compared to miniature‐release‐induced‐excitatory‐ postsynaptic‐currents (mEPSCs, grey arrowhead) in individual recordings at ‐70 mV. No significant difference was detected between uEPSCs (n=5) and mEPSCs (grey, 7 events) on peak amplitude (uEPSC: 7.8±0.8ρA, mEPSC: 8.9±1.5ρA, p=0.56), rise time (uEPSC: 2.9±0.4ms, mEPSC: 2.8±0.4ms, p=0.85) and decay kinetics (τW, uEPSC: 4.3±1.7, mEPSC: 7.1±2.1, p=0.32), suggesting that individual pulses of uncaging stimulation were comparable to individual quantal releases and that uEPSCs mimicked miniature events in our system.

Figure 9. Two‐photon glutamate uncaging

Chapter 3. Activity inputs modify synaptic states at

single synapses

As computational units, individual synapses constantly receive, process and integrate information through time. Allowing prior activity to modulate synaptic states is known to be essential for proper plasticity induction and complex information storage to reflect the perspective of experience (Montgomery and

Madison 2004; Fusi, Drew et al. 2005; Fusi and Abbott 2007; Abraham 2008).

However, little is known about how prior inactivity can modify synaptic states at single synapses.

Here, I utilized two VAMP‐2 based strategies to suppress presynaptic release from individual modified boutons to drive prolonged synaptic inactivation. I reported that sustained synaptic inactivation with differential effectiveness was sufficient to correspondingly modify postsynaptic NMDARs. By implementing a history of inactivity at single synapses (silenced synapses), I discovered changes of molecular composition at single silenced synapses, while no significant alterations on spine morphology were observed. Further, I demonstrated that individual synaptic inputs not only modify synaptic states homosynaptically but also allow heterosynaptic integration along dendrites, suggesting potential implications of using the synaptic inactivation systems to quantitatively study information integration in specific spatial domains. 74

Activity manipulation at single synapses

Two scenarios of strategies were applied to generate VAMP2‐based synaptic inactivation, including a chemical‐mediated acute suppression (2FKBP‐VAMP2‐GFP) and a neurotoxin‐mediated inactivation (SynaptophysinGFP‐GFP‐IRES‐tetanus toxin). For both strategies, the suppression of synaptic release was engineered to simultaneously label the affected presynaptic boutons. 2FKBP‐VAMP2‐GFP or

SynaptophysinGFP‐GFP‐IRES‐tetanus toxin (SphGFP‐IRES‐TetTX) was introduced into a subpopulation of neurons at 11‐14 days in vitro (DIV) for 2‐7 days. In individual neurons, excitatory synapses indicated by presynaptic vGlut signal or postsynaptic cherry‐filled spines were classified into two groups, including synapses receiving modified/silenced input and synapses receiving unmodified inputs. In most of cases, individual neurons contained the majority of synapses receiving spontaneously active inputs (A) while containing only a small fraction (1%~3%) of modified synapses (S).

Chemical inactivation: 2FKBP-VAMP2

The first strategy used to disrupt VAMP2‐based vesicular fusion to plasma membrane was taking advantage of a published work: “Molecules for Inactivation of Synaptic Transmission (MISTs)” (Karpova, Tervo et al. 2005). As described in the

Chapter 2, modified VAMP2 was engineered to generate the 2FKBP‐VAMP2‐GFP construct. Neurons expressing 2FKBP‐VAMP2‐GFP for two days tested for

effectiveness of inactivetion. The inactivation was induced by adding synthesized cell‐permeable dimerizers (AP20187), which dimerize FKBP motifs intermolecularlly to crosslink individual 2FKBP‐VAMP2‐GFP molecules. Synaptic inactivation was achieved by crosslinking 2FKBP‐VAMP2‐GFP on individual vesicles at presynaptic boutons upon dimerizer application (Figure 10A).

Partial suppression of synaptic release

Taking advantage of FM loading assays, the efficiency of inactivation was determined. While the expression of 2FKBP‐VAMP2GFP seemed to slightly affect synaptic recycling even under basal condition (77.6±5% of active boutons, see Table

4), dimerizer application acutely and significantly suppressed synaptic recycling in tens of minutes (37.8±4% of active boutons at 30 minutes after application of dimerizer, p<<0.05, Figure 10B and Table 4).

Slight increases of postsynaptic NMDAR contents

To test whether the partial suppression driven by 2FKBP‐VAP2GFP was sufficient to modify postsynaptic NMDARs, a sustained inactivation was implemented by repeatedly administration of dimerizer for three days (DIV14‐17).

Interestingly, a preferential accumulation of NR1 was observed at individual modified synapses, suggesting that partially silenced synapses likely acquire increased numbers of functional NMDARs (S/ A : NR1= 1.46±0.12, n=31, N=10).

TetTX-mediated synaptic inactivation

In addition to overexpressing modified VAMP2 at presynaptic terminals, an alternative way of inactivating synaptic release was implemented by genetically introducing tetanus toxin (TetTX) into individual boutons.

TetTX is a well‐known neurotoxin that specifically cleaves VAMP2. It has been widely documented that global application of TetTX blocks synaptic release

(Capogna, McKinney et al. 1997; Harms and Craig 2005; Ehlers, Heine et al. 2007).

TetTX is composed of one heavy chain and one light chain. While the heavy chain is essential for targeting the toxin to axon terminals, the light chain functions as protease to digest VAMP2 (Figure 11A). Taking advantage of its proteolytic activity, the TetTX light chain was engineered in a fashion of generating the

SynaptophysinGFP‐IRES‐TetTX (SphGFP‐IRES‐TetTX) construct, which not only prevents presynaptic vesicles fusion but also allows visualization of the modified presynaptic terminals. The effectiveness of TetTX from SphGFP‐IRES‐TetTX was then determined through VAMP2 immunostaing and FM loading assays.

Sufficient expression of TetTX from SphGFP‐IRES‐TetTX was verified by performing immunocytochemistry of VAMP2, the substrate of TetTX. On the other hand, the effective blockade of presynaptic release was confirmed using FM loading assays.

Reduced VAMP2 staining

Since VAMP2 is the specific substrate of TetTX, VAMP2 staining was utilized to indicate the sufficient expression of TetTX at individual synaptic boutons.

Hippocampal cultures transfected with SphGFP‐IRES‐TetTX or infected with a lentivirus expressing SphGFP‐IRES‐TetTX at 11‐14 DIV were allowed for 2‐7 days of expression before subjected to vGlut and VAMP2 stainings. vGlut staining indicated all excitatory presynaptic terminals while only a small fraction of excitatory terminals was SphGFP positive, indicating the expression of SphGFP‐IRES‐TetTX.

Unlike most of excitatory boutons showing strong VAMP2 staining, SphGFP positive boutons contained much reduced VAMP2 staining (26±3%, n=91, N=20,

Figure 11B). The reduced signal of VAMP2 staining at boutons expressing SphGFP‐

IRES‐TetTX suggests that the expression of TetTX was sufficient to cleave VAMP2 presynaptically.

Impaired FM uptake

FM loading assay was then performed to determine if reduced VAMP2 expression led to a functional blockade of presynaptic release. High potassium protocol was utilized for FM4‐64 loading to monitor the efficient vesicular recycling at control and modified boutons. While the FM loading was quite efficient at control boutons (84.7±5% are active), the majority of boutons expressing SphGFP‐IRES‐

TetTX showed complete blockade on FM uptake (only 8.9±3% are active). The high effectiveness of the functional blockade (91.1±3% are inactive) among synapses 78

expressing SphGFP‐IRES‐TetTX suggests that TetTX expression was sufficient to effectively digest presynaptic VMAP2 and lead to a relatively uniformed blockade on presynaptic release (Figure 11C and Table 4).

Increase in postsynaptic NMDAR contents

To examine synapse‐specific effects of inactivity on synaptic NMDAR composition, postsynaptic NMDAR contents were measured after a 7 days of synaptic inactivation driven by the expression of SphGFP‐IRES‐TetTX (DIV11‐17). A preferential accumulation of NR1 was observed at individual modified synapses

(normalized synaptic content of NR1: S/ A = 1.9±0.08, n=506, N=40), suggesting an activity‐dependent modification on synaptic NMDARs at single modified synapses.

More effective synaptic inactivation by the TetTX-based system

Although both strategies seemed to modify presynaptic release, the utilization of SphGFP‐IRES‐TetTX provided a much more powerful system with more efficient suppression on presynaptic release (Table 4) and stronger modification on postsynaptic NMDARs (2FKBP‐VAP2GFP: 1.46±0.12; SphGFP‐IRES‐

TetTX: 1.9±0.08). Moreover, while the expression of SphGFP‐IRES‐TetTX did not affect the general health of the transfected/infected cultures, chronic application of dimerizer seemed to cause some cell death and affect the general health of neuronal cultures. It is also worth mentioning that the utilization of 2FKBP‐VAMP2GFP and

SphGFP‐IRES‐TetTX may have differential effects on dissociating spontaneous from

evoked release. While 2FKBP‐VAMP2GFP may or may not affect spontaneous release due to its heterogeneous degree of crosslinking vesicles from bouton to bouton, presynaptic terminals expressing SphGFP‐IRES‐TetTX may show differential blockade on the evoked and spontaneous synaptic release (Capogna,

McKinney et al. 1997; Humeau, Doussau et al. 2000; Harms, Tovar et al. 2005; Ehlers,

Heine et al. 2007).

In order to maximize the potential effects to be observed by single synapse inactivation, in the following studies, experiments were carried out utilizing

SphGFP‐IRES‐TetTX.

Synaptic connections are maintained under the TetTX- mediated suppression of synaptic release

Prevailing models of neural circuit plasticity suggest that active synapses preferentially contribute to excitatory networks while inactive synapses are ultimately subjected to depression or elimination. Here we test whether suppression of effective synaptic release affects spine morphology or synapse stability.

To avoid the influence of synaptic release in the process of synapse formation, synaptic inactivation was initiated only after synapse formation was complete, by introducing SphGFP‐IRES‐TetTX into the system at DIV12. Postsynaptic dendritic spines of postsynaptic neurons were visualized through subsequent mCherry

transfection. The expression of TetTX was targeted using a lentivirus expressing

SphGFP‐IRES‐TetTX to a small subpopulation of cultured hippocampal neurons to inactivate only a small fraction of synaptic inputs in individual neurons and then subjected to a subsequent mCherry transfection. Under this preparation, individual mCherry‐filled neurons obtained the majority of spines with no labeled presynaptic counterparts, while a small fraction of spines were apposed to SphGFP‐expressing green boutons (Figure 12A).

Dendritic protrusions of mCherry expressing neurons were visualized using spinning‐disc confocal microscope. Width (W) and length (L) of visualized protrusions/spine heads were measured to classify protrusions into four categories (I:

W>1.5um, W/L=0.8~1.2; II: W>1.5um, 0.3

W<1.5, 0.3

Modified synaptic states at silenced synapses

Activity‐dependent remodeling of PSD is well documented with global changes in the molecular composition of PSD proteins. These changes have been reported as bidirectional, reversible and involved multiple classes of PSD proteins

(Ehlers 2003). In order to determine the synapse‐specific effects of inputs on synaptic properties, a screen was performed to probe the postsynaptic molecular composition

at silenced and active synapses. Three categories of molecules were quantified and compared between silenced and active synapses, including glutamate receptors, scaffold protein and CaMKII.

As described in the methods section, normalized synaptic contents (S/ A ) were measured for AMPARs (GluR1 and GluR2), NMDAR (NR1), PSD95,

Neuroligin and CaMKII (α and β isoforms). Interestingly, despite unmodified PSD‐

95 content (1.0±0.05), silenced synapses contained less surface GluR1 (0.7±0.05), while acquiring more NR1 (1.9±0.08), Homer‐1 (1.5±0.14), Neuroligin‐1 (2.1±0.33) and both isoforms of CaMKII (CaMKII‐α: 1.4±0.12; CaMKII‐β: 1.9±0.22) (Table 5).

These differential changes on individual GluRs and scaffold proteins ruled out non‐ specific scaling effects on all molecules and instead suggested specific modifications at single synapses upon suppressed presynaptic release. Moreover, the correlated increase of synaptic NR1, Neuroligin, and CaMKII content at individual inactivated synapses may suggest specific modulations on synapses with a favorable state for the induction of Ca++ dependent synaptic modifications (Barria and Malinow 2005;

Zhou, Takahashi et al. 2007; Kim, Jung et al. 2008)(also more discussion in chapter 4 and 5).

Homosynaptic modification at silenced synapses

In the process of quantifying the modified molecular composition at silenced synapses, I noticed that the changes of protein contents were observed at almost

every single silenced synapse. This observation suggested that single synapses could possibly serve as a minimal computation unit to sense input and modulate the gain individually. To understand the spatial confinement of individual inactivation events, normalized synaptic contents of NR1were surveyed in groups of synapses, which individually was composed of one silenced synapse and 4 franking active synapses on each side. By quantifying the synaptic content of NMDARs in a ~10 synapses wide region, the homosynaptic effect of NR1 accumulation was confirmed.

While a suppressed input was sufficient to accumulate NR1postsynaptically (S:

1.84±0.14), the change of NR1 content is spatially confined at the single silenced synapses (AP1: 1.10±0.14, AP2: 1.13±0.14, AP3: 1.23±0.13, AP4: 1.13±.05; AD1: 1.04±0.13,

AD2: 0.84±0.13, AD3: 1.05±0.14, AD4: 0.92±0.02; n=21groups) (Figure 13). The homosynaptic changes suggest stringent regulations on synaptic NMDARs, which may play crucial roles in preserving input‐specific information.

Heterosynaptic modulations driven by silenced synapses

Although the homosynaptic modulation of NMADR contents was observed at single silenced synapses, whether input‐specific expression can be spatially integrated and drive interplays among synapses is still unknown. To determine if the effect of synaptic inputs can be spatially integrated along dendrites, analysis was done to probe the spatial summation of synaptic NR1 contents among multiple inactivation events. From 51 dendrites with differential fraction of silenced synapses,

the inactivation fraction was plotted against the mean of normalized synaptic NR1 content from the active synapses. If spatial summation among silencing events was present, a higher fraction of silenced synapses would predict a heterosynaptic increase of NR1 content at active synapses. This prediction was consistent with the result observed. Increased fraction of suppressed input was correlated with the increase of NR1 content expressed not just homosynaptically but also appeared at active synapses (r=0.53; 51 dendrites with inactivation fraction ranging form 0.017 to

0.33) (Figure 14). The spatial summation among local events suggests that signal may undergo spatial integration along dendrite, which may lead to heterosynaptic crosstalk among synapses.

Summary and discussion

As suggested by the normal spine morphology of silenced synapses observed, synaptic connections were maintained under TetTX‐based synaptic inactivation. Therefore, without dramatically changing connectivity, this system can be potentially utilized to probe afferent‐specific function in individual neurons

(Nakashiba, Young et al. 2008). Also, the quantitative nature of controlling the inactive fraction in individual neurons suggests a possible implication of titrating the threshold of local versus global scaling (Harms and Craig 2005; Hou, Zhang et al.

2008; Ibata, Sun et al. 2008). Interestingly, by screening the synaptic content of multiple synaptic molecules, I found that synapses acquired increased NR1,

Neuroligin and CaMKII in response to suppressed presynaptic release. These activity‐dependent modulations on molecular ensembles may reflect an active tuning on synaptic state, which may in turn influence the induction of synaptic plasticity.

Moreover, the homosynaptic expression of increased NR1 accumulation at single silenced synapses can be heterosynaptically integrated to modify the synaptic state of adjacent active synapses.

Table 4. Different efficiency of synaptic inactivation

Active boutons Inactive boutons (GFP+ / FM+) (GFP+ / FM–)

2FKBP‐VAMP‐GFP*1 77.6 ± 5 % 22.4 ± 5 %

2FKBP‐VAMP2‐GFP + dimerizer *2 37.8 ± 4 % 62.3 ± 5 %

SynaptophysinGFP *3 84.7 ± 5 % 15.3 ± 5 %

SynaptophysinGFP‐IRES‐TetTX *4 8.9 ± 3 % 91.1 ± 3 %

*1 Data form 2 independent experiments (483 GFP+ boutons) *2 Data form 2 independent experiments (641 GFP+ boutons) *3 Data form 1 experiment (339 GFP+ boutons) *4 Data form 1 experiment (306 GFP+ boutons)

Table 5. Modified synaptic molecular composition at silenced synapses

Normalized synaptic content (S/ A )#1, #2

NMDAR NR1 1.9 ± 0.08 ↑

GluR1 (surface) 0.7 ± 0.05 ↓ AMPAR GluR2 (total) 1.1 ± 0.05 ─

CaMKII‐α 1.4 ± 0.12 ↑ CaMKII CaMKII‐β 1.9 ± 0.22 ↑

PSD‐95 1.0 ± 0.05 ─

Homer‐1 1.5 ± 0.14 ↑

Neuroligin‐1 2.1 ± 0.33 ↑

#1 Data represent means+‐SEM of normalized synaptic content of synaptic molecules. #2 S/ A of individual synaptic proteins were calculated by combining 2‐5 independent experiments. The (N,n) values for individual molecules are listed as following: NMDAR=(40,506); GluR1=(33,207); GluR2=(13,236); CaMKII‐α=(29,258) CaMKII‐β=(27,353); PSD95=(26,260); Homer‐1=(15,122); Neuroligin=(11,87).

Figure 10. Chemical inactivation partially blocks presynaptic vesicular recycling

(A) As shown in the schematic, application of the dimerizer interferes with presynaptic vesicular recycling by cross‐linking synaptic vesicles carrying over‐ expressed FKBP‐VAMP2GFP.

(B) Application of the dimerizer for 30 minutes partially blocked FM4‐64 uptake in the boutons expressing FKBP‐VAMP2GFP (arrowheads). The drug‐induced cross‐ linking of presynaptic vesicles not only reduced the overall intensity of FM signal in the boutons but also increased the fraction of FM‐negative boutons (inactive boutons from22.4±5% to 62.3±5%). Scale bar is 5μm.

Figure 10. Chemical inactivation partially blocks presynaptic vesicular recycling

Figure 11. TetTX‐based synaptic inactivation

(A) TetTX specifically targets and digests VAMP2 to block efficient membrane fusion between synaptic vesicles and the plasma membrane. The boutons expressing TetTX were indicated by the expression of synaptophysinGFP.

(B) The expression of TetTX from SphGFP‐IRES‐TetTX was sufficient to digest presynaptic VAMP2. Among the glutamatergic presynaptic boutons labeled by vGlut staining, SphGFP‐IRES‐TetTX expressing boutons (empty arrowhead) showed reduced VAMP2 signal (down to 26±3% compared to control synapses). Scale bar is 5μm.

(C) The reduction of presynapticVAMP2 content was sufficient to suppress presynaptic vesicle release. While the boutons expressing synaptophysinGFP only (white arrowheads) were able to uptake FM4‐64 efficiently, FM uptake was blocked at SphGFP‐IRES‐TetTX boutons (empty arrowheads). Scale bar is 5μm.

Figure 11. TetTX‐based synaptic inactivation

Figure 12. Silenced synapses show similar spine morphology as active synapses

(A) The spine morphology was visualized by postsynaptic expression of pCMV5‐ mCherry. The synaptic connections with green presynaptic boutons presumably released little if any glutamate due to the co‐expression of TetTX (silenced synapses, S, arrowheads). Meanwhile, silenced synapses had neighboring synapses receiving inputs from uninfected neurons, which were spontaneously active (A). Scale bar is 50 μm in the left panel and 5μm in the right panel.

(B) To describe the spine morphology of active and silenced synapses, the width of head (W) and the length (L) of individual protrusions were measured. In individual neurons, all protrusions were classified into four categories based on their W and L. (I: W>1.5μm, W/L=0.8~1.2; II: W>1.5μm, 0.32μm were considered as filopodia and removed form the data set). From 14 neurons and 3694 spines measured, silenced and active synapses showed similar distributions in their spine morphology (I: A=0.18±0.03, S=0.22±0.03; II: A=0.36±0.03, S=0.41±0.02; III: A=0.34±0.01, S=0.28±0.03; IV: A=0.11±0.03, S=0.08±0.02; p>0.05 for I, II and IV). The result suggests that the suppressed presynaptic inputs did not alter the general spine morphology.

Figure 12. Silenced synapses show similar spine morphology as active synapses

Figure 13. The spatial profile of NR1 accumulation

The spatial profile of individual inactivation events was characterized by surveying the NR1accumulation in a ~10‐synapses wide spatial region centered by a silenced synapse (4 synapses toward the proximal end and 4 synapses toward the distal end). The analysis was done under two constrains. First, only neurons containing less than 3% of inactivated inputs were chosen. Second, only dendritic regions (between 2 branch points) with a single silenced synapse were analyzed. Surprisingly, the normalized synaptic content of NR1 along the chosen dendrites suggested a homosynaptic increase of NR1 accumulation only at silenced synapses. (AP1: 1.10±0.14, AP2: 1.13±0.14, AP3: 1.23±0.13, AP4: 1.13±.05; AD1: 1.04±0.13, AD2: 0.84±0.13, AD3: 1.05±0.14, AD4: 0.92±0.02; n=23 groups from 10 neurons).

Figure 13. The spatial profile of NR1 accumulation

Figure 14. Spatial integration among inactivation events

The spatial summation among inactivation events was analyzed to determine whether signal could be spatially integrated. While each inactivation event is homosynaptically expressed, the presence of spatial summation would predict a heterosynaptic increase of NR1 content at active synapses flanked by silenced synapses. The analysis was done under two constraints. First, only neurons containing less than 3% of inactivated inputs were chosen. Second, dendritic regions (between 2 branch points) containing different fractions of silenced synapses were collectively analyzed. The spatial summation was characterized by correlating the NR1accumulation at active synapses to the inactivation fraction of individual dendrites. Interestingly, a positive correlation (r=0.53 from 51 dendrites) was observed between inactivation fraction and NR1 accumulation at active synapses. The heterosynaptic accumulation of NR1 at active synapses suggests signal integration along the dendrite and also potential cross‐talks among synapses.

Figure 14. Spatial integration among inactivation events

Chapter 4. Input-specific gain control

Taking advantage of TetTX‐based strategy that offered an effective and sustained suppression on synaptic release at single synapses, we asked how prior synaptic activity modulates synaptic plasticity induction at single synapses.

Prevailing models suggest that the subunit composition of NMDARs is tuned by activity in a cell‐wide manner to gate synaptic plasticity induction. Here, we report that subunit‐specific regulation of NMDARs at single synapses mediates a novel form of input‐specific metaplasticity. Prolonged suppression of synaptic releases at single synapses enhances synaptic NMDAR‐mediated currents and increases the number of functional NMDARs containing NR2B. Interestingly, synaptic NMDAR composition is adjusted by spontaneous glutamate release rather than evoked activity. Silenced synapses with more NMDARs containing NR2B may predict a bigger Ca++ influx upon activation to express a lower threshold for long‐term synaptic potentiation.

Enhanced NMDAR currents at single silenced synapses

As described in Chapter 2 and 3, SphGFP‐IRES‐TetTX was utilized to chronically suppress synaptic release at individual synapses while selectively visualizing the inactivated boutons. Using a lentivirus expressing SphGFP‐IRES‐

TetTX, the expression of TetTX was targeted to a small subpopulation of cultured

hippocampal neurons to inactivate only a small fraction of synaptic inputs in individual neurons. Postsynaptic neurons visualized by mCherry expression indicated that the majority of spines had no labeled presynaptic counterparts (active,

A), while a small fraction of spines were apposed to SphGFP‐expressing green boutons (silenced, S). Most of our experiments were performed on DIV21‐22, when neurons were subjected to SphGFP‐IRES‐TetTX infection for 10 days and mCherry transfection for 2 days.

To probe the synaptic receptor composition, synaptic currents were measured from individual synapses by combining whole‐cell voltage clamp recording with focal two‐photon glutamate uncaging. Pulses of local uncaging stimulation were delivered on the tip of spine heads and uncaging‐induced‐ excitatory‐postsynaptic currents (uEPSCs) were recorded from the soma.

To determine if input activity modifies synaptic receptor composition at single synapses, uEPSCs were measured at active and silenced synapses. For individual experiments, two nearby but well separated synapses, one S and one neighboring A, were chosen as a pair of interest. For each pair, average uEPSCs were recorded from 5‐10 times of local uncaging stimulation sequentially delivered on A and S (uEPSC‐A and uEPSC‐S respectively). uEPSCs were recorded at two holding potentials, ‐70 mV (uEPSC‐70mV) and +40 mV (uEPSC+40mV) to probe responses mediated by specific glutamate receptors (AMPARs and NMDARs). uEPSC‐70mV is

solely contributed by AMPARs, while uEPSC+40mV is a mixture of both AMPARs‐ and

NMDARs‐mediated synaptic currents (Figure 15A).

Interestingly, while no significant differences on APMAR‐uEPSC were recorded among synapses (A = 10.93±2.81 pA, S = 11.02±2.28 pA, pA_S = 0.98), silenced synapses contained enhanced NMDAR‐uEPSCs (Figure 15B, A: NMDAR‐ uEPSC = 8.5±1.3 pA, S: NMDAR‐uEPSC = 14.0±1.9 pA; paired‐t‐test, p = 6x10‐6; n=19,

N=16). This observation is consistent with the result described in Chapter 3 showing that more NR1 accumulated at individual silenced synapses.

Moreover, across the pairs recorded, silenced synapses showed a higher

NMDAR‐uEPSC / AMPAR‐uEPSC (NMDAR/AMPAR) ratio compared to its neighboring active synapses, suggesting a receptor‐specific regulation at silenced synapses (Figure 15C, A: NMDAR/AMPAR = 0.73±0.10; S: NMDAR/AMPAR =

1.09±0.13; paired t‐test, p = 0.0006).

Subunit-specific regulation of NMDARs at single silenced synapses

In addition to the increased molecular accumulation and enhanced synaptic response of NMDARs (NR1) at silenced synapses, NMDAR composition was further assayed through immunocytochemistry using antibodies specifically recognizing

NR2A or NR2B. Concurrently, a stronger NR2B but not NR2A staining was observed at silenced synapses (Figure 17A and B), indicating a potential subunit‐

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specific modification upon inactivation at single synapses. Changes of NMDAR subunit composition were quantified by calculating normalized synaptic content

(S/ A ) for NR1, NR2A and NR2B in individual neurons. As shown in the cumulative plot of S/ A (Figure 16C1), NR1 distribution overlapped with the NR2B distribution (Kolmogorov‐Smirnov test: pNR1_NR2B>0.05) while deviating from the

NR2A trace (Kolmogorov‐Smirnov test: pNR1_NR2A<<0.05, pNR2B_NR2A<<0.05).

This result indicated that silenced synapses specifically obtained more NR1 and

NR2B than NR2A subunits. Moreover, frequency counts of NR2A showed that

NR2A distribution peaked around 1 (Figure 16C2‐4, S/ A NR2A ≤1 for 45% of S), suggesting similar NR2A expression levels at active and silenced synapses. Whereas the NR1 and the NR2B distributions both peaked around 2 (Figure 16C2‐4, S/ A NR1

≥1 for 82% of S; S/ A NR2B ≥1 for 83% of S), indicating that silenced synapses acquired a ~2 fold increase in NR1 and NR2B subtypes. Moreover, the consistent increase of the mean of S/ A at multiple silenced inputs calculated in each neuron suggested a synapse‐specific regulation of NMDAR subunits across the population (Figure 16D

NR1: 1.90±0.08 (N=39); NR2A: 1.16±0.04 (N=34); NR2B: 1.88±0.08 (N=35). pNR1_NR2A = 7.2x10‐10; pNR2A_NR2B = 7.5x10‐10; pNR1_NR2B = 0.91).

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Spontaneous glutamate releases regulate NMDAR composition at single synapses

The results described so far indicate that activity modifies synaptic NMDAR composition at single synapses. However, it is not clear whether the modulation of

NMDAR composition resulted from either evoked releases or from spontaneous synaptic releases. To reveal what activity cues were essential for modifying

NMDARs composition at single synapses, I further dissected the differences between active and silenced inputs.

As discussed in Chapter 3, one interesting feature of the TetTX‐based synaptic inactivation is its differential blockade on evoked release and spontaneous release. While active synapses expressed both evoked vesicle releases and spontaneous transmitter releases, TetTX‐expressing boutons expressed no evoked vesicle releases but maintained spontaneous transmitter releases at a reduced level

(<10%) (Capogna, McKinney et al. 1997; Hua, Raciborska et al. 1998; Harms and

Craig 2005). Taking advantage of this unique feature, it was possible to dissociate the contributions of spontaneous release from evoked release and to directly investigate the specific function of each mode of synaptic release. By completely blocking evoked releases with global TTX application (Figure 17A and B), I tested if spontaneous release was sufficient to modify NMDAR composition at single synapses. Interestingly, with chronic TTX application, the differential level of spontaneous release between active and silenced inputs was sufficient to lead to the

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accumulation of NR1 and NR2B at silenced synapses (Figure 17B, S/ A : NR1TTX =

1.90±0.09 (N=24, n=251), pCtrl_TTX = 0.94; NR2BTTX: 1.89±0.08 (N=11, n=124), pCtrl_TTX =

0.97). On the other hand, chronic AP5 application, which blocks glutamate binding to NMDARs, equalized active and silenced inputs and diminished preferential accumulation of NR1 and NR2B at silenced synapses, (Figure 17B, S/ A : NR1AP5 =

1.10±0.06 (N=29, n=216), pCtrl_AP5 = 3.02x10‐10, pTTX_AP5 = 3.02x10‐10; NR2BAP5 =

1.07±0.07 (N=11, n=124), pCtrl_AP5 = 7.78x10‐9, pTTX_AP5 = 9.88x10‐9) suggesting that glutamate binding to NMDARs was essential for this subunit‐specific regulation. As to NR2A, similar synaptic contents were detected at active and silenced synapses under all conditions. (Figure 17B, S/ A : NR2ATTX = 1.18±0.05 (N=14, n=158), pCtrl_TTX =

0.73, NR2AAP5: 1.06±0.07 (N=16, n=106), pCtrl_AP5 = 0.17, pTTX_AP5 = 0.12).

Local synaptic activity reduces NR2B content

To further extend the finding that silenced synapses showed stronger NR1 and NR2B staining (Figure 18), we tested whether silenced synapses acquired more functional NR2B‐containing NMDARs.

Consistent with previous studies (Kirson and Yaari 1996) (Liu, Wong et al.

2004; Sobczyk, Scheuss et al. 2005; Bellone and Nicoll 2007; Morishita, Lu et al. 2007),

NMDAR‐uEPSC was partially sensitive to ifenprodil (3μM) application, presumably due to blockade of NR2B‐containing NMDARs (Figure 18A). We then determined if active and silenced synapses showed differential degree of blockade upon ifenprodil

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application (Figure 18B‐F). In the presence of ifenprodil, other than the fast component mediated by AMPARs, active synapses still contained a slow uEPSC+40mV component (NMDAR‐uEPSC) (Figure 18B). Whereas at silenced synapses, ifenprodil almost completely blocked the slow component of uEPSC+40mV (Figure 18B, the right panel). Comparison of the uEPSCs+40mV responses suggested that active and silenced synapses expressed differential degrees of blockade (Figure 18C‐F). About half (52±13%) of NMDARs at the active synapses were sensitive to ifenprodil while almost all NMDARs were ifenprodil‐sensitive

(92±3%) at silenced synapses (p = 0.03) (Figure 18F). In summary, these results were consistent with our prediction that silenced synapses acquired a higher fraction of functional NMDAR containing NR2B.

Single silenced synapses acquire a lower threshold for potentiation

Considering that silenced synapses acquired more NR2B‐containing

NMDARs, it is likely that the altered NMDAR composition predicts corresponding modulation on synaptic plasticity at silenced synapses. To probe the plasticity threshold at individual synapses, two‐photon glutamate uncaging system was utilized again for generating sustained synaptic plasticity at single synapses. Two paradigms of LTP induction were implemented, including the long‐term potentiation of AMPAR‐uEPSCs and long‐term spine enlargement.

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For the first paradigm, AMPARs‐uEPSCs were measured before and after a

LTP protocol (30 times of uncaging stimulation of 4ms duration at 0.5 Hz paired with postsynaptic depolarization at 0mV). This LTP protocol reliably potentiated

AMPAR‐uEPSCs at stimulated synapses for more than 20 minutes (183±16.7% at 20 minutes post LTP induction, N=n=8) but not at the non‐stimulated neighboring synapses (NS; 109±11.7%)(Figure 19A). Non‐distinguishable degree of potentiation was found at stimulated active and silenced synapses (p>0.05 throughout the recording) in response to the LTP protocol, suggesting both A and S synapses are capable of potentiation upon strong stimulation.

To further determine if silenced synapses acquire a lower threshold for potentiation, a weaker stimulation protocol (20 times of uncaging stimulation of 1ms duration at 0.5 Hz paired with postsynaptic depolarization at 0 mV) was implemented to stimulate synapses (Figure 19B). Interestingly, the weaker protocol failed to potentiate AMPAR‐uEPSCs at active synapses (subthreshold protocol;

N=n=8; 104±9.7% at 20 minutes post stimulation), while induced a sustained potentiation of AMPAR‐uEPSCs at silenced synapses (N=n=8; 207±24% at 20 minutes post stimulation). Again, no potentiation was observed at NS synapses

(109±11.7% at 20 minutes post stimulation). These results suggest that silenced synapses with increased NR2B‐containing NMDARs express a lower threshold for synaptic potentiation.

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To further confirm the finding, we also used spine enlargement, the other hallmark of synaptic potentiation, as the readout to monitor plasticity induction. For each experiment, two nearby but well‐separated spines with comparable size and similar morphology were chosen as a pair of interest, composed of one target spine

(A or S) plus NS) (Figure 20). At stimulated active synapses, prolonged spine enlargement was only observed after the LTP protocol (30 pulses of uncaging stimulation of 4ms duration, at 0.5 Hz, 0 Mg++) but not induced by two weaker subthreshold protocols (20 (1ms) and 10 pulses (1ms))([(F‐F0)/F0]: ALTP = 142±9%,

Asub_20 = 112±9%, Asub_10 = 88±9%). However, at silenced synapses, all three protocols were sufficient to trigger sustained spine enlargements, suggesting that silenced synapses may express lower threshold for potentiation ([(F‐F0)/F0]: SLTP = 162±8%,

Ssub_20 = 143±9%, Ssub_10 = 149±12%). The results showed that silenced synapses acquired a lower threshold to express long‐term AMPAR‐currents potentiation and corresponding structural plasticity. Our findings suggest that prior activity sets synaptic gain in an input‐specific manner by tuning synaptic NMDAR composition at single synapses.

Model

Here, I identified a novel form of input‐specific metaplasticity. The frequency of spontaneous release (FS) serves as the priming activity to modify individual synapses. As the results of my work suggested, a prior exposure of reduced FS modifies the synaptic NMDAR composition by acquiring more NR2B‐containing

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NMDARs at single synapses. Increased number and weight of NR2B‐containing

NMDARs at synapses then lower the LTP threshold in an input‐specific manner.

Moreover, based on the results from Chapter3, it is likely that rather than only modify NMDAR composition, synaptic inputs alter the synaptic states by regulating clusters of synaptic molecules. Therefore, more than the solely increased

NR2B weight at silenced synapses, the modified NMDAR/AMPAR ratios, the accumulation of scaffold and CaMKII may also contribute to the lower LTP threshold at silenced synapses. While further examinations are required, this input‐ specific metaplasticity may be bidirectional and can potentially provide underlying mechanisms for afferent‐specific gain control in vivo.

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Figure 15. Enhanced NMDAR‐uEPSCs from silenced synapses

(A) Synaptic currents were probed at single synapses upon focal two‐photon glutamate uncaging stimulation. Local uncaging (yellow circle) was delivered on the tip of spine heads and uncaging induced excitatory postsynaptic currents (uEPSCs) were recorded from the soma. Two nearby but well‐separated spines (one A and one S; scale bar is 1μm) with comparable size and similar morphology were chosen as a pair of interest for individual uEPSCs recordings. uEPSCs were recorded at both ‐ 70mV and +40mV to measure responses mediated by AMPARs or AMPARs + NMDARs, respectively. Representative traces of uEPSCs recorded from A (uEPSC‐A) and S (uEPSC‐S) at both holding potentials were shown.

(B) Enhanced NMDAR‐mediated uEPSCs at silenced synapses. Upper panel, average uEPSCs‐A (black) and uEPSCs‐S (green) were compared. uEPSCs‐70mV were not significantly different between A and S synapses, suggesting comparable AMPAR‐uEPSCs in both population of synapses (inset, mean±SEM. A: 10.93±2.81 pA, S: 11.02±2.28 pA, paired‐t‐test p=0.98). Thus, the larger average uEPSC+40mV‐S was likely caused by an increase of non‐AMPAR‐mediated response at silenced synapses. NMDAR‐uEPSC components, measured as the uEPSCs+40mV amplitude at 40ms after the uEPSCs‐70mV peak, were significantly enhanced at silenced synapses compared to their active neighboring synapses (A: 8.5±1.3 pA, S: 14.0±1.9 pA; paired‐t‐test p = 6x10‐6). Data from 19 A‐S pairs in 16 neurons.

(C) Higher NMDAR/AMPAR ratio in silenced synapses. The NMDAR/AMPAR ratio was calculated by comparing their respective uEPSC components in individual synapses (A: black; S: green). Ratios from each A‐S pair were linked by a gray line. Across the pairs recorded, silenced synapses showed higher NMDAR/AMPAR ratios than their neighboring active synapses (A: 0.73±0.10; S: 1.09±0.13; paired t‐test, **p = 0.0006).

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Figure 15. Enhanced NMDAR‐uEPSCs from silenced synapses

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Figure 16. Accumulation of NR1 and NR2B at single silenced synapses

(A) Examples of NR1, NR2A and NR2B immunostaining in silenced and active synapses. Hippocampal neurons infected with lentivirus expressing SphGFP‐IRES‐ TetTX and transfected by pCMV5‐mCherry were stained for total synaptic content of NR1, NR2A or NR2B. For each representative staining, two or more silenced synapses (empty arrowheads) were indicated. Compared to neighboring active synapses, silenced synapses showed stronger synaptic staining of NR1 and NR2B, but not NR2A, subunits. Scale bar is 5μm.

(B) Examples of A‐S pairs with NR1, NR2A or NR2B staining. In each pair, the silenced synapse (empty arrowhead) contained more synaptic content of either NR1 or NR2B but not NR2A subunits compared to its active neighbor.

(C) Normalized synaptic content (S/ A ) of individual NMDAR subunits. For NR1, NR2A and NR2B staining, S/ A values were measured at individual silenced synapses in each neuron. As described in Chapter 2, each S/ A value describes how one silenced synapse was different from the average active synapse in terms of the fold of changes of specific synaptic content. By pooling S/ A values across different neurons, the cumulative plot (C1) showed overlapping NR1 and NR2B distributions (Kolmogorov‐Smirnov test: p>0.05), which significantly deviated from the NR2A trace (Kolmogorov‐Smirnov test: pNR1_NR2A<0.05, pNR2B_NR2A<0.05). These results suggest that silenced synapses specifically obtained more NR1 (n=475S, N=39 neurons) and NR2B (n=343S, N=35) than NR2A subunits (n=364S, N=34). Panels C2‐ C4 showed frequency distributions of S/ A values for each subunit. The NR2A distribution peaked around 1 (45% of S/ A NR2A ≤1), suggesting that silenced synapses acquired similar NR2A contents as active synapses. On the other hand, the distributions of NR1 and NR2B peaked around 2 (82% of S/ A NR1 ≥1; 83% of S/A NR2B ≥1), indicating preferential accumulations of NR1 and NR2B subtypes in silenced synapses.

(D) Mean of S/A values for individual NMDAR subunits calculated per neuron. Each circle represented the average S/ A value from one neuron, with the population mean indicated by the empty bars (means±SEM, NR1: 1.90±0.08 (N=39); NR2A: 1.16±0.04 (N=34); NR2B: 1.88±0.08 (N=35). **pNR1_NR2A=7.2x10‐10; **pNR2A_NR2B=7.5x10‐10; pNR1_NR2B=0.91).

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Figure 16. Accumulation of NR1 and NR2B at single silenced synapses

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Figure 17. Spontaneous glutamate release tunes NMDAR composition at single synapses

(A) Schematics represent how specific blockers affected evoked and spontaneous glutamate releases at A and S synapses. Under control condition (Ctrl), active synapses received both evoked and spontaneous releases while silenced synapses received no evoked activity and a reduced level (<10%) of spontaneous releases. TTX application completely blocked population evoked releases and left spontaneous releases as the only difference between A and S synapses. AP5 application diminished differences between active and silenced synapses by blocking NMDAR transmission induced by both evoked and spontaneous releases.

(B) Representative A‐S pairs (S: empty arrowhead) of NR1, NR2A and NR2B staining under different blocker treatments along with the population summary. Silenced synapses maintained stronger NR1 staining under TTX as under the Ctrl condition (S/ A NR1TTX: 1.90±0.09 (N=24, n=251), p = 0.94), suggesting that the difference in spontaneous releases alone was sufficient to regulate synaptic NR1 content. On the other hand, chronic AP5 application diminished preferential NR1 accumulation at silenced synapses (S/ A : NR1AP5: 1.10±0.06 (N=29, n=216), **pCtrl_AP5 =3.02x10‐10). Similarly, for NR2B, silenced synapses maintained more NR2B content under TTX treatment but not under AP5 treatment. (S/ A : NR2BTTX: 1.89±0.08 (N=11, n=124), pCtrl_TTX = 0.97; NR2BAP5: 1.07±0.07 (N=11, n=124), **pCtrl_AP5=7.78x10‐9, **pTTX_AP5=9.88x10‐9). No difference of NR2A synaptic contents was observed under all drug application. (S/ A : NR2ATTX: 1.18±0.05 (N=14, n=158), pCtrl_TTX = 0.73; NR2AAP5: 1.06±0.07 (N=16, n=106), pCtrl_AP5 =0.17, pTTX_AP5=0.12). These results suggest that synaptic NR1 and NB2B contents are regulated locally by tonic spontaneous releases at individual synapses.

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Figure 17. Spontaneous glutamate release tunes NMDAR composition at single synapses

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Figure 18. Local synaptic activity reduces NR2B content

(A) Schematics show that while NMDARs were activated upon local glutamate uncaging regardless of their subunit composition, only synaptic transmission through NR1/NR2A di‐heteromer receptors was kept intact under NR2B‐specific blocker, ifenprodil. Representative traces showed NMDAR‐uEPSC before (Control) and after bath application of ifenprodil.

(B) Both active and silenced synapses were sensitive to ifenprodil application. uEPSC traces here represented ifenprodil‐resistant synaptic currents recorded under ifenprodil application from one active synapse (left) and one silenced synapse (right). At the active synapse, uEPSC+40mV contained both a faster ifenprodil‐resistant AMPAR‐uEPSC and a slower ifenprodil‐resistant NMDAR component (arrow). In contrast, silenced synapses showed a faster ifenprodil‐resistant AMPAR‐uEPSC with little ifenprodil‐resistant NMDAR component (arrow).

(C) Average uEPSC+40mV traces recorded with (Ifen.) or without ifenprodil (Ctrl) blockade showed that both active and silenced synapses were sensitive to ifenprodil blockade. (ACtrl: grey, n=25 synapses, N= 16 neurons; AIfen.: black, n=16, N=16; SCtrl: green, n=26, N= 16; SIfen.: light green, n=12, N= 12).

(D) Smaller ifenprodil‐resistant NMDAR‐uEPSCs at silenced synapses, shown in the averaged uEPSC+40mV traces. However, both silenced and active synapses had similar uEPSCs‐AMPAR (inset, AIfen.: 8.74±1.86, SIfen.: 9.02±1.15, pA_S=0.90).

(E) Ifenprodil suppressed NMDAR‐uEPSCs in differential degrees at active and silenced synapses. The degree of NMDAR‐uEPSCs suppression was quantified by comparing the amplitude of uEPSCs+40mV at 40ms after the peak of uEPSCs‐70mV, with and without ifenprodil treatment. Although both active and silenced synapses were suppressed by ifenprodil, silenced synapses showed a stronger suppression (ACtrl: 11.9±2.4 pA; AIfen.: 5.6±1.6 pA; SCtrl: 16.4±1.8 pA; SIfen.: 1.5±0.6 pA; t‐test, pA= 0.02, **pS=1.11*10‐6).

(F) Silenced synapses may contain a higher fraction of NR2B‐containing NMDARs due to their higher sensitivity to ifenprodil. Ifenprodil blocked 52±13% of NMDAR‐ uEPSCs in active synapses while blocking 92%±3% of NMDAR‐responses at the silenced population (*p=0.03).

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Figure 18. Local synaptic activity reduces NR2B content

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Figure 19. Subthreshold stimuli potentiated silenced synapses

(A) A schematic illustrates the LTP induction protocol at single synapses by pairing focal glutamate uncaging (orange arrowheads) with postsynaptic depolarization. Representative AMPAR‐uEPSCs traces recorded before (Pre‐stim, black traces) and after (Post‐stim, red traces) LTP protocol showed that LTP was successfully induced at the stimulated synapse but not at the un‐stimulated neighboring synapse (NS, grey trace). Right panel, the potentiation of AMPAR‐uEPSCs sustained for at least 20 minutes (183±16.7% at 20 minutes post LTP induction, N=n=8). Inset shows the non‐ distinguishable degree of potentiation at stimulated active (black) and silenced (green) synapses (p>0.05 throughout the recording.)

(B) A weaker stimulation protocol (subthreshold protocol), which failed to potentiate active synapses (black trace, 104±9.7%, N=n=8), triggered a sustained potentiation at silenced synapses (green trace, 207±24%, N=n=8) but not NS synapses (111±25.8% at 20 minutes post stimulation).

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Figure 19. Subthreshold stimuli potentiated silenced synapses

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Figure 20. Subthreshold stimuli induce structural plasticity at silenced synapses

Subthreshold protocols triggered spine enlargement at silenced synapses. Instead of postsynaptic depolarization, 0 mM Mg++ ACSF was used together with glutamate uncaging to induce structural plasticity at single synapses. Selected spines were subjected to similar uncaging protocols described in Figure 19 (30‐pulses(4ms) LTP protocol; 20‐pulses(1ms) subthreshold protocol; 10‐pulses(1ms) subthreshold protocol), while the fluorescent intensity of spines was measured. Example images illustrated spine morphology before and after trains of uncaging stimulation. Twenty minutes after uncaging stimulation, the LTP protocol reliably triggered a sustained spine enlargement at stimulated active and silenced synapses. Whereas the subthreshold protocols induced prolonged spine enlargement only at silenced but not at active nor NS synapses. (LTP protocol: A=142±9%, S=162±8%, NS=95±6%; subthreshold‐20‐pulses: A=112±9%, S=143±9%, NS=98±6%; subthreshold‐10‐pulses: A=88±9%, S=149±12%, NS10sub: 99±6%; paired‐t‐test, p<0.05; F and F0 were integrated fluorescent mCherry intensity at selected spines before and after uncaging stimulation, respectively.)

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Figure 20. Subthreshold stimuli induce structural plasticity at silenced synapses

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Figure 21. Model of input‐specific metaplasticity

Here, I identified a novel form of input‐specific metaplasticity. I propose that the frequency of spontaneous release (FS) serves as a priming activity to modify synaptic state at individual synapses. Based on my work, a prior exposure of reduced FS modifies the synaptic NMDAR composition by acquiring more NR2B‐containing NMDARs at single synapses. Increased number and weight of NR2B‐containing NMDARs at synapses lower the LTP induction threshold in an input‐specific manner.

While further examinations are required, this input‐specific metaplasticity may be bidirectional and can potentially provide underlying mechanisms for afferent‐ specific gain control in vivo.

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Figure 21. Model of input‐specific metaplasticity

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Chapter 5. Discussions & future directions

In my thesis work, I have developed new tools for sustained synaptic inactivation at singe synapses. I discovered that prolonged suppression of presynaptic release modulates synaptic states by modifying not just homosynaptic but also heterosynaptic molecular composition. Furthermore, in conjunction with immunocytochemistry, two‐photon glutamate uncaging and electrophysiology, I discovered a novel form of input‐specific metaplasticity via a local switch of postsynaptic NMDARs. Surprisingly, the frequency of presynaptic spontaneous release rather than evoked release tunes postsynaptic NMDAR subunit composition to modulate the induction of future synaptic plasticity. In this chapter, I will first discuss potential implications of my work and then propose several future studies that would extend my findings in Chapter 3 and Chapter 4.

Spontaneous glutamate releases and synaptic NMDAR composition

The results from Chapter 4 suggested a novel role of spontaneous release involved in information storage. While spontaneous release has been previously reported to regulate postsynaptic AMPAR scaling (Sutton, Wall et al. 2004; Sutton,

Ito et al. 2006), my thesis work is the first report suggesting that spontaneous release can modify postsynaptic NMDAR composition and plasticity threshold in an input‐ specific manner.

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Couple lines of recent studies have been encouraging to support the idea of utilizing spontaneous release as the cue to trigger input‐specific metaplasticity. First, a potential interesting difference of synaopic GluR composition was found between synapses inactivated by presynaptic Kir2.1 expression and TetTX expression. While only GluR1 was upregulated at the Kir2.1‐synapses, preferential accumulation of

NR1, NR2B but not GluR1 was observed at TetTX‐synapses. This discrepancy on the

GluR composition may reflect the different nature of synaptic inactivation driven by

Kir2.1 and TetTX. Although evoked releases are almost completely blocked in both

Kir2.1‐and TetTX‐expressing boutons, only TetTX‐expressing boutons show compromised spontaneous releases (Capogna, McKinney et al. 1997; Hua,

Raciborska et al. 1998; Burrone, OʹByrne et al. 2002; Harms and Craig 2005; Hou,

Zhang et al. 2008). Therefore, it is possible that evoked release and spontaneous release specifically modulate different postsynaptic GluRs to convey distinct aspects of information. Second, recent studies suggest that evoked releases and spontaneous releases are likely to be originated from two separate presynaptic vesicle pools and may even be detected by distinct pools of postsynaptic NMDARs (Sara, Virmani et al. 2005; Atasoy, Ertunc et al. 2008). These results also support the idea that evoked and spontaneous release may be independently regulated and account for distinct modulations on synaptic properties. Finally, although spontaneous release has not been considered as a tunable component for information storage, recent studies suggest that the frequency of spontaneous release can be regulated not only by 123

activity but also by activity‐dependent epigenetic state of cells (Murthy, Schikorski et al. 2001; Nelson, Kavalali et al. 2006; Nelson, Kavalali et al. 2008). Thus, the rate of spontaneous releases may reflect the activity state of individual neurons and can potentially be considered as an afferent‐specific signature.

In summary, in parallel to the information carried by evoked synaptic transmission, rather than existing as random noise, spontaneous release is likely to play a distinct role in modulating synaptic plasticity in an input‐specific manner.

Modify NMDAR composition at single synapses

While NMDAR subunit composition has been considered as a cell‐wide phenomenon, my results suggest an alternative possibility for input‐specific regulations on NR2A‐ and NR2B containing receptors. This local modulation view resonates with the heterogeneous expression of NR2B‐containing receptors observed across hippocampal CA1 synapses (Sobczyk, Scheuss et al. 2005). Moreover, the input‐specific NMDAR‐composition may represent the in vitro correlate of the afferent‐specific NMDAR composition observed in hippocampal neurons and cortical neurons (Kawakami, Shinohara et al. 2003; Kumar and Huguenard 2003;

Arrigoni and Greene 2004; Wu, Kawakami et al. 2005).

Altered NR2A/NR2B ratios at single silenced synapses

Based on the results from Chapter 4, silenced synapses not only acquired more NMDARs but more NMDARs containing NR2B. 124

To further understand how NMDARs composition was modified by synaptic activity, I was able to estimate the fractions of NR1/NR2A, NR1/NR2B and

NR1/NR2A/NR2B heteromers at both active and silenced synapses based on 3 premises: (1) Silenced synapses and active synapses acquire similar contents of

NR2A in immunostaining assays (Figure 16), suggesting similar numbers of NR2A subunits at active and silenced synapses. (2) Silenced synapses showed stronger surface NR2B staining compared to active synapses (S/ A : 3.1±0.29, n=462, N=34;

Figure 22), suggesting that silenced synapses obtain 3 times more surface NR2B subunits. (3) The ifenprodil‐sensitive fraction is about 90% in silenced synapses and about 60% in active synapses. Based on these premises, I estimated that active synapses acquired 40% of NR1/NR2A, 20% of NR1/NR2A/NR2B and 40% of

NR1/NR2B, which is closed to the prediction of previous studies (Al‐Hallaq,

Conrads et al. 2007). On the other hand, silenced synapses acquired functional

NMDARs in a composition of 10% of NR1/NR2A, 30% of NR1/NR2A/NR2B and 60% of NR1/NR2B.

Based on the estimation, silenced synapses obtain a higher fraction of NR2B‐ containing NMDARs, including NR1/NR2A/NR2B and NR1/NR2B. The changes of

NMDAR composition can be translated into a 3‐fold increase of NR2B/NR2A ratios at silenced synapses.

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Potential local mechanisms underlie input-specific changes on NMDAR composition

The input‐specific changes on NMDAR composition support the idea that the trafficking of NR2A‐ and NR2B‐containing receptors is likely to be locally regulated at individual synapses. While little is known about the mechanisms of local regulations, from the knowledge of activity‐dependent modulations on

NMDAR composition I would like to propose several potential mechanisms that can potentially be locally utilized. Since the NMDAR composition reflects a dynamic balance between receptor insertion and removal, potential local modulations on synaptic targeting, endocytosis and lateral diffusion of receptors may serve as local mechanisms to account for input‐specific NMDAR composition (Figure 23).

Synapse-specific synaptic targeting

The synaptic delivery of NR2A and NR2B has been linked to distinct activity‐dependent mechanisms (Barria and Malinow 2002). Although the molecular mechanisms are not yet clear, it is possible that the synaptic states with unique molecular compositions may selectively capture one subunit over the other. As the result suggested in Chapter 3, single silenced synapses showed modified molecular composition with unchanged PSD‐95 but increased Homer‐1 and Neuroligin‐1 (NL‐

1) content.

While it is possible that NMDAR and NL‐1 are regulated in parallel by synaptic inputs, the co‐occurrence of NR1 and NL‐1 accumulation may suggest

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functional interaction between these two molecules. Although only indirect molecular interaction has been established has been documented between NMDAR and NL‐1 at synapses (Chih, Engelman et al. 2005; Nam and Chen 2005; Varoqueaux,

Aramuni et al. 2006). Moreover, despite the inability to recruit PSD‐95, NL∆C

(deletion of the interacting motif with ß‐neurexin) expression still increased NMDA‐ receptor cluster density at synapses, suggesting that NMDA receptors are primarily recruited to NL‐1–induced synapses independently of PSD‐95 (Chih, Engelman et al.

2005). Thus, it is possible that the synaptic accumulation of NL‐1 recruit NMDAR into synapses.

Subunit-specific endocytosis at single synapses

Since NR2A and NR2B have distinct endocytic motifs in their C‐terminus tails, subunit‐specific rates of endocytosis has been reported. In the basal condition,

NR2B undergoes more robust endocytosis than NR2A presumably because of the differential interaction between their endocytic motifs and AP2 complex (Lavezzari,

McCallum et al. 2004; Kim, Dunah et al. 2005). While NR2A‐containing receptors show slower internalization rates mediated by the interaction between AP2 complex and a dileucine (LL) motif, NR2B‐containing receptors are more robustly endocytosed due to the interaction between YEKL motif and AP2 complex (Cheung and Gurd 2001). Interestingly, upon agonist stimulation, the endocytosis of NR2B has been shown to be modulated by Fyn kinase through phosphorylation on the

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tyrosine 1472 residue (Y1472) within the YEKL motif. The phosphorylated Y1742 then inhibits NR2B binding to AP2 and blocks endocytosis (Prybylowski, Chang et al. 2005).

Therefore, it is reasonable to hypothesize that spontaneous release may modulate the endocytosis of NR2B‐containing receptor though modifying its phosphorylation state on Y1472 residue at individual synapses. The hypothesis can be easily tested through detecting the synaptic phospho‐Y1472 level using phospho‐

Y1427‐specific antibody (Abcam, #ab59205) at active and silenced synapses.

Lateral diffusion

Recent studies have shown that NMDARs not only cycle in and out of synaptic sites, but also move laterally on the plasma membrane (Groc, Heine et al.

2004; Groc, Heine et al. 2006; Groc, Choquet et al. 2007; Groc, Lafourcade et al. 2007).

By using single‐molecule tracking to monitor individual NMDAR molecules, the results suggested that NMDARs exhibit lateral mobility between synaptic and extrasynaptic domains within the plasma membrane. A subunit‐specific surface mobility has been recently documented. While NR2A‐containing NMDARs diffuse laterally more slowly within the synapses (~2x10‐4 μm2/sec), NR2B‐containing receptors diffuse much faster (~500x10‐4 μm2/sec) (Groc, Heine et al. 2006). Thus, it is possible that the differential lateral mobility between NR2A‐ and NR2B‐containing

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receptors may account for the developmental switch (Groc, Heine et al. 2006; Groc,

Choquet et al. 2007).

On the other hand, input‐specific lateral mobility of GluR1 has been reported using the same TetTX‐based system (Ehlers, Heine et al. 2007). While single GluR1 molecule is highly mobile at the silenced synapses, the synaptic activity traps GluR1 molecule at active synapses. Therefore, it is possible that individual inputs also locally modulate the lateral mobility of NR2A and NR2B to retain specific subunit and modify NMDAR composition accordingly in an input‐specific manner.

While little is know about the molecular basis of subunit‐specific rates of lateral diffusion, it is possible that postsynaptic scaffold molecules may have differential binding affinity to NR2A‐ and NR2B‐containing receptors to influence their lateral mobility. As the result showed in Chapter 3, at silenced synapses, the modified composition of scaffold proteins may account for the accumulation of

NR2B‐containing receptors via influencing the lateral mobility of NR2A‐ and NR2B‐ containing receptors. Therefore, it is possible that synaptic input may modify the scaffold composition at single synapses to hamper the free movement of specific subunits at differential degree to account for synapse‐specific NMDAR composition.

Altered plasticity threshold at silenced synapses

Given the subunit‐specific channel properties (Erreger, Dravid et al. 2005), synaptic NMDAR composition has been predicted to influence synaptic plasticity 129

induction. Consistent with this idea, recent studies have suggested that alterations of

NMDAR composition modify the induction of synaptic plasticity (Tang, Shimizu et al. 1999; Liu, Wong et al. 2004; Barria and Malinow 2005; Jung, Kim et al. 2008;

Gardoni, Mauceri et al. 2009). However, while NMDAR composition modulates plasticity, the subunit‐specific roles are still rather controversial (Tang, Shimizu et al.

1999; Liu, Wong et al. 2004; Massey, Johnson et al. 2004; Barria and Malinow 2005;

Morishita, Lu et al. 2007; Philpot, Cho et al. 2007; Zhao and Constantine‐Paton 2007;

Zhou, Takahashi et al. 2007; Jung, Kim et al. 2008). A recent model proposes that the relative level of two subunits (i.e., NR2A/NR2B) modifies plasticity threshold for

LTP and LTD induction (Kopp, Longordo et al. 2006; Kopp, Longordo et al. 2007;

Philpot, Cho et al. 2007; Yashiro and Philpot 2008), which can presumably serve as a substrate of metaplasticity.

Why modify and probe synaptic plasticity at single synapses?

Due to the technical limitations, while plasticity has been always probed at individual inputs, the implementation of modifying NMDAR composition has been global. Selective subunit blockers have been widely utilized to determine the exact roles of NR2A‐ and NR2B‐containing receptors on plasticity induction (Barria and

Malinow 2002; Liu, Wong et al. 2004; Barria and Malinow 2005; Weitlauf, Honse et al.

2005; Morishita, Lu et al. 2007; Zhou, Takahashi et al. 2007; Zhao, Peng et al. 2008).

One caveat of this global pharmacological manipulation is that the drug application

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not only blocks the specific receptor subtype but also reduce the overall excitatory drive on individual neurons. This latter effect can potentially alter the overall neuronal excitability and may result in the changes on NMDAR composition and even plasticity (Rao and Craig 1997; Ehlers 2003; Jung, Kim et al. 2008). Therefore, it would be ideal to locally change NMDAR composition and probe the corresponding modification on the plasticity induction without perturbing the overall excitability level.

Here, I overcame these limitations and implemented a sustained synaptic inactivation system at individual synapses, which resulted in a 3‐fold increase of

NR2B/NR2A ratio, and discovered a corresponding decrease in LTP induction threshold at single silenced synapses. My work identified a novel form of input‐ specific metaplasticity by providing causal evidence that prior experience modulates synaptic plasticity induction via NMDAR switch at single synapses.

How silenced synapses acquire a lower LTP threshold?

One rather surprising finding from my work is that the silenced synapses express a lower LTP threshold compared to their neighboring active synapses.

Stimuli that are subthreshold for eliciting potentiation at active synapses robustly potentiate synaptic strength at silenced synapses. Although the underlying mechanism is not yet clear, the modified molecular composition at silenced synapses is likely to account for the modified plasticity threshold. Based on the results from

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Chapter 3 and 4, at silenced synapses, the accumulation of NR2B‐containing

NMDARs was accompanied with the increased NL‐1 and CaMKII contents and reduced surface GluR1 content. Therefore, in the following discussion, I would like to propose the potential contribution of NR2B‐containing NMDARs, CaMKII and modified NMDAR/AMPAR ratios in modifying the plasticity threshold at silenced synapses.

More NR2B-containing NMDARs

Given the slower deactivation/desensitization kinetics, NR2B‐containing

NMDARs allow about two‐fold more charge and more Ca++ per unit current than

NR2A‐containing NMDARs (Erreger, Dravid et al. 2005; Sobczyk, Scheuss et al.

2005). Therefore, the increased number of NR2B‐containing and increased

NR2B/NR2A ratio at silenced synapses are likely to predict an increase of Ca++ entry upon channel activation and results in a lower threshold for LTP induction.

More CaMKIIs

Moreover, as the results showed in Chapter 3, individual silenced synapses also acquired more CaMKII. While the mechanism of synapse‐specific CaMKII accumulation is unknown, one possible route would be through the strong interaction between NR2B and CaMKII (Bayer, De Koninck et al. 2001; Barria and

Malinow 2005). Moreover, recent studies suggest that the interaction between NR2B and CaMKII increases the synaptic expression of both proteins (Bayer, De Koninck

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et al. 2001; Gardoni, Mauceri et al. 2009). Therefore, the increased NR2B at silenced synapses likely recruits more CaMKII at single synapses. However, one note worthy of mentioning is the potential source of CaMKII. Since only activated CaMKII binds strongly to NR2B, the synapses with suppressed input may not be capable of activating CaMKII locally at those synapses. Therefore, the activated CaMKII likely came from other synapses with spontaneously active inputs. A phenomenon of propagating synaptic accumulation of CaMKII (Rose, Jin et al. 2009) reported recently may provide a potential explanation of the accumulation of CaMKII at silenced synapses.

Therefore, considering that CaMKII has a well‐documented role in the induction of LTP (Barria and Malinow 2005; Zhou, Takahashi et al. 2007; Yashiro and Philpot 2008), the synapse‐specific accumulation of CaMKII may at least partially contribute to lowering the LTP induction threshold at single silenced synapses through facilitating the surface insertion of AMPARs.

Reduced AMPAR/NMDAR ratio

Interestingly, despite the increased number of NMDARs at silenced synapses, the expression of synaptic AMPARs are relative constant or even slightly decreased at individual silenced synapses (results form Chapter 3 and 4; (Harms, Tovar et al.

2005; Ehlers, Heine et al. 2007)).

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The synapse‐specific loss of surface GluR1 is likely due to the activity‐ dependent modifications on GluR1 trafficking. For example, the activity‐dependent modulations on surface GluR1 mobility is likely to at least partially account for the reduced AMPAR accumulation at silenced synapses. Moreover, a recent study suggests that NMDAR composition may influence the surface insertion of GluR1.

While NR1/NR2A facilitate the surface expression of GluR1, NR1/NR2B decreases the surface expression of GluR1. Thus, it is also possible that accumulated NR2B locally facilitate GluR endocytosis and results in the reduced surface AMPARs at single silenced synapses.

As the data reported in Chapter 4, the universal increases of

NMDAR/AMPAR ratios were observed at silenced synapses. Since the increased

NMDAR/AMPAR has been shown to enhance LTP induction (Liu, Pu et al. 2005;

Smith and McMahon 2005; Beique, Lin et al. 2006; Kim, Choi et al. 2009), the increased NMDAR/AMPAR ratios at silenced synapses are also consistent with the lower LTP threshold observed at silenced synapses.

Synaptic state determines plasticity threshold

In summary, rather than one single component, the lower LTP threshold at silenced synapses reflects a combination of modification on many synaptic molecules. Upon stimulation, the stronger Ca++ entry mediated by increased number of NR2B‐contaiining NMDARs is then relayed to the increased number of CaMKII to

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amplify the signal even more and eventually trigger more efficient surface insertion of AMPARs.

Afferent-specific gain control

Rather than only proving that inactivated synapses are meant to be potentiated, my thesis work provides a potential molecular mechanism for afferent‐ specific gain control. Individual afferents carry signature mini frequency reflecting the activity or epigenetic states of the originated brain regions. Afferents with specific mini frequency then set the gain of synapses by tuning the NMDAR subunit composition in an input‐specific manner.

This afferent‐specific gain control may have interesting biological implications. First, rather than using evoked release to carry multiple layers of information, the utilization of spontaneous release provides a spatially and temporarily segregated cue as an afferent‐specific signature. Second, while the real physical range of synaptic gain is unknown and may be relatively small at individual synapses, the effect can certainly be amplified by the synchronous activation of specific afferents. With that, afferent‐specific information not only can be preserved but may also influence neuronal output with specific weight (Alle and

Geiger 2006; Shu, Hasenstaub et al. 2006; Christie and Jahr 2008).

In summary, the model of afferent‐specific gain control is likely to offer another layer of capacity for complex information storage (Montgomery and 135

Madison 2004; Fusi, Drew et al. 2005; Fusi and Abbott 2007; Abraham 2008). At single synapses, afferent‐specific gain control may help keeping synaptic plasticity at proper working range along time. In the meanwhile, afferent‐specific gain control may help to preserve afferent‐specific information in individual neurons.

Implications of single-synapse inactivation systems

My thesis work provides novel tools for effective and sustained synaptic inactivation at individual synapses. With the ability to chronically manipulate individual synaptic inputs, issues regarding long‐term information stroage and processing can be addressed at the scale of single synapses. Moreover, the quantitative nature of the systems provides potential routes to determine the spatial integration of information among individual synaptic inputs. Ultimately, the spatial resolution of our system may help to understand the afferent‐specific properties in vivo.

To gain inducibility and reversibility

The utilization of both inactivation systems may broaden the temporal and spatial range of manipulating synaptic activity for future studies. The chemical inactivation system (i.e., 2FKBP‐VAMP2GFP‐based synaptic inactivation) is capable of acute blockade while providing potential reversibility through application of the reverser (AP1998, Ariad Pharmaceuticals). While the effectiveness of chemical inactivation has shown to be heterogeneous, it may provide a system for tunable 136

suppression by controlling the amount of overexpressed 2FKBP‐VAMP2GFP in individual presynaptic terminals.

On the other hand, while TetTX‐based system enables effective and sustained synaptic inactivation and maximizes the observed effects, the system can potentially be modified to gain inducibility and reversibility. For example, taking advantage of the inducible promoter such as Tet‐on or Tet‐off system, the SphGFP‐

IRES‐TetTX expression can be turned on/off by doxycycline or tetracycline application (Yu, Power et al. 2004; Nakashiba, Young et al. 2008). Also, by introducing the TetTX‐resistant VAMP2 (Q76V and F77W) into the presynaptic terminals expressing TetTX, active presynaptic recycling can be restored (De Haro,

Quetglas et al. 2003). Moreover, in combination with the global application of TetTX, the expression of TetTX‐resistant VAMP2 at small fraction of synaptic inputs may create a complementary system to TetTX‐based synaptic inactivation. With that, the bidirectional modifications on NMDAR composition can be directly tested at relative hyperactive synapses (TetTX‐resistant VAMP2) and neighboring quite synapses.

Determine the induction threshold for synaptic scaling

These single‐synapse‐based systems can be implemented to determine the signal integration among synapses through time. It has been controversial whether the homeostatic scaling of AMPARs can be induced locally or only globally by

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chronic activity alterations (Turrigiano, Leslie et al. 1998; Murthy, Schikorski et al.

2001; Ehlers 2003; Thiagarajan, Lindskog et al. 2005; Thiagarajan, Lindskog et al.

2007; Hou, Zhang et al. 2008; Ibata, Sun et al. 2008). Although the question has been tackled using local drug perfusion and Kir2.1‐based synaptic inactivation system, the debate is still on. While local TTX perfusion suggests that homeostatic scaling of

GluR2 can only be induced globally through somatic inactivation, the possibility of local induction was supported by the finding that individual Kir2.1‐synapses express homosynaptic upregulation of surface GluR1 (Hou, Zhang et al. 2008; Ibata,

Sun et al. 2008). Recently, based on computational modeling (Rabinowitch and

Segev 2006) and the heterogeneous expression of synaptic scaling among synapses

(Thiagarajan, Lindskog et al. 2005), a growing amount of evidence suggests a compelling model that certain local mechanisms may underlie local homeostatic regulations before reaching the threshold to trigger the global expression of synaptic scaling (Rabinowitch and Segev 2006; Thiagarajan, Lindskog et al. 2007; Rabinowitch and Segev 2008). However, the threshold that bridges local and global homeostatic regulations has not yet been identified.

Here, with the capability of titrating the fraction of inactivated synaptic inputs in individual neurons, both VAMP2‐based systems may be utilized to study synaptic input signal integration in different spatial domains. For example, by modifying the transfection/infection efficiency of 2FKBP‐VAMP2GFP and SphGFP‐

IRES‐TetTX in cultured neurons, the correlation between inactivation fraction and 138

synaptic GluR1 expression can be determined. Further, with similar methodology, it would be possible to determine the specific homeostatic regulations at specific spatial compartments (e.g., spines, dendrites, neurons) for understanding signal integration in individual spatial domains.

Test afferent-specific gain control in vivo

A number of predictions can to be further examined to verify the hypothesis of afferent‐specific gain control. First, manipulations on the rate of spontaneous at specific afferents should change its postsynaptic NMDAR compositions. Second, the modified NMDAR composition will predict changes on the threshold for plasticity induction. Third, the afferent‐specific gain will be reflected in the synaptic weights and corresponding influences on driving neuronal out put.

Taking advantage of the known NMDAR composition at Shaffer‐collateral

(SC) pathway and perforant pathway (PP) in hippocampal CA1 neurons (Arrigoni and Greene 2004), the predictions can be directly tested. First, introducing the

SphGFP‐IRES‐TetTX into specific afferents should change its postsynaptic NMDAR compositions. For example, infecting the perforant pathway with a lentivirus expressing SphGFP‐IRES‐TetTX should increase its postsynaptic composition of

NR2B‐containing receptors. Second, introducing the SphGFP‐IRES‐TetTX into specific afferents should modify its plasticity threshold. For example, afterchronic

PP inactivation, the increased weight of NR2B‐containing NMDARs would predict a

139

lower LTP induction threshold. Third, to test if the afferent‐specific gain can influence neuronal out put, a reversion of the sustained inactivation on the Perforant inputs (e.g., 2FKBP‐VAP2GFP system) should increase the weight of Perforant inputs on CA1 neuronal output regardless its distal localization on the dendritic tree

(Figure 24).

Spontaneous release, GluR composition and neurological disorders

Overall, my thesis work show that at single synapses, spontaneous release primes the synapse by modifying its synaptic state with specific GluR and scaffold compositions, which in turn determine the synaptic gain in an input‐specific manner.

Moreover, I also propose that the input‐specific metaplasticity may serve as a potential mechanism for in vivo afferent‐specific gain control.

While more studies are needed to elucidate the physiological roles and underlying molecular mechanisms of the input‐specific metaplasticity and afferent‐ specific gain control, some hints may be gained from documented neurological disorders. For example, abnormal rates of spontaneous release have been documented in MeCP2 KO mice and implicated in the potential pathological function of amyloidβ1‐42 (Nelson, Kavalali et al. 2006; Nimmrich, Grimm et al. 2008;

Zhang, He et al. 2008; Monteggia and Kavalali 2009). Moreover, dysregulation of

NMDAR trafficking has also been reported in Alzheimer’s disease and

140

Schizophrenia (Snyder, Nong et al. 2005; Lau and Zukin 2007). Furthermore, modified AMPAR/NMDAR ratios have been implicated in multiple animal models of neurological diseases, such as Sapap3 knockout mice (a mouse model for

Obsessive‐compulsive disorder, OCD) (Welch, Lu et al. 2007) and Fmr1 knockout mice (a mouse model for fragile X) (Pilpel, Kolleker et al. 2009). Therefore, by providing the first glimpse on this spontaneous release‐dependent modulation on synaptic plasticity, my thesis work may open new avenues for understating the molecular bases underlying the pathology of multiple neurological diseases.

141

Figure 22. Surface accumulation of NR2B

The surface expression of NR2B was quantified by the use of an antibody that specifically recognizes the N‐terminus of NR2B subunit. The antibody was applied on fixed neuronal cultures before triton‐based permeabilization. Representative dendrites showed the preferential accumulation of surface NR2B at silenced synapses (arrowheads). On average, silenced synapses acquired 3‐fold more surface NR2B subunits (S/ A : 3.1±0.3, n=462S, N=34).

142

Figure 22. Surface accumulation of NR2B at silenced synapses

143

Figure 23. Local mechanisms account for NMDAR composition at single synapses

The synapse‐specific accumulation of NR2B‐containing NMDARs can not simply reflect the reduction on synaptic recruiting of NR2A containing receptors but, instead, can potentially be achieved by actively regulating the NR2B‐contaiining receptor on its synaptic targeting (➊), endocytosis (➋) and lateral diffusion (➌) at single synapses. At silenced synapses, it is likely that the NR2B‐containing NMDARs acquire enhanced synaptic targeting and retention but down‐regulated endocytosis compared to NR2A‐containing NMDARs.

144

Figure 23. Local mechanisms account for NMDAR composition at single synapses

145

Figure 24. Afferent‐specific gain control

(A) The afferent‐specific weight of NR2B‐containg NMDARs has been documented in the Shaffer‐collateral pathway (SC) and the Perforant pathway (PP) in CA1 neurons. While the SC inputs are quite sensitive to ifenprodil blockade (~70%), the PP inputs are more resistant to ifenprodil application (~35% is sensitive) (Arrigoni and Greene 2004).

(B) To determine if input‐specific metaplasticity reported here can underlie this afferent‐specific NMDAR composition, two further experiments are proposed here. First, a sustained suppression of spontaneous release at PP inputs should increase the synaptic weight of NR2B‐containing NMDARs. Second, the modified PP synapses should express a corresponding modification on synaptic threshold, presumably acquiring a lower LTP threshold.

146

Figure 24. Afferent‐specific gain control

}

147

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Biography

Ming-Chia Lee

Born on Feb 5th, 1978, Taipei, Taiwan

Education

2003‐2009 Ph.D., Neurobiology, Duke University

2000‐2002 M.S., Zoology, National Taiwan University

1996‐2000 B.S., Zoology, National Taiwan University

Honors

2008 Poster award of Neurobiology Department Retreat: Ready to launch award

2004 Poster award of Neurobiology Department Retreat: Best preliminary result award

2002 Dean’s Award, College of Science, National Taiwan University

2002 Award of Da‐Qui Chei and Song‐Yeng Fong Memorial Science Fair Scholarship for Scientific Poster

1999 Award of Dean of College of Science, National Taiwan University

1999 Presidential Award, National Taiwan University

1999 Award of Da‐Qui Chei and Song‐Yeng Fong Memorial Science Fair Scholarship for Scientific Poster

Publications

Lee MC, Yasuda R, Ehlers MD. (2009) Input‐specific metaplasticity by a local switch in NMDA receptors. In preparation.

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Helton TD, Otsuka T, Lee MC, Mu Y, Ehlers MD. (2008) Pruning and loss of excitatory synapses by the parkin ubiquitin ligase. Proc Natl Acad Sci U S A. 2008 Dec 9;105(49):19492‐7. Epub 2008 Nov 25.

Ehlers MD, Heine M, Groc L, Lee MC, Choquet D. (2007) Diffusional trapping of GluR1 AMPA receptors by input‐specific synaptic activity. Neuron. 2007 May 3;54(3):447‐60.

Wang X, Wu YC, Fadok VA, Lee MC, Gengyo‐Ando K, Cheng LC, Ledwich D, Hsu PK, Chen JY, Chou BK, Henson P, Mitani S, Xue D. (2003), Cell corpse engulfment mediated by C. elegans phosphatidylserine receptor through CED‐5 and CED‐12. Science. 302, 1563‐6

Lee MC and Wu YC. (2002) PSR‐1and cMER potentially act together as receptors to transduce apoptotic signals during the cell‐corpse engulfment in C. elegans. Master thesis. National Taiwan University, Taipei, Taiwan

Wu YC, Cheng TW, Lee MC and Weng NY, (2002), Distinct Rac activation pathways control Caenorhabditis elegans cell migration and axon outgrowth. Dev. Biol. 250, 145‐155.

Chou WH, Lee MC, and Yu HT (2002), Community structure of ground‐dwelling vertebrates sampled with drift‐fence pitfall traps in a subtropical montane forest in central Taiwan, Endemic species research 4, 1‐11

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