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Neuron Neuroview Neuron NeuroView Designing Tools for Assumption-Proof Brain Mapping Adam H. Marblestone1 and Edward S. Boyden1,* 1Synthetic Neurobiology Group, Massachusetts Institute of Technology, Cambridge, MA 02139, USA *Correspondence: [email protected] http://dx.doi.org/10.1016/j.neuron.2014.09.004 Can we develop technologies to systematically map classical mechanisms throughout the brain, while retain- ing the flexibility to investigate new mechanisms as they are discovered? We discuss principles of scalable, flexible technologies that could yield comprehensive maps of brain function. There has been much recent excitement connectomics, similar questions are be- of genes can have profound effects on about the potential for tools that might ing directed at the synapse. Direct electri- neural function. Beyond static transcrip- enable scalable mapping of brain circuits cal connections (mediated by proteins tomic snapshots, some evidence sug- at the anatomical level (i.e., connectom- that make up gap junctions) can form gests that cells can change their type ics), the molecular level (e.g., transcrip- local networks among interneurons with over time, perhaps calling into question tomics, proteomics), and the activity level similar gene expression profiles (Brown the notion of cell type itself. In addition (i.e., dynomics). However, new funda- and Hestrin, 2009), among other kinds to dynamic changes in gene splicing as mental mechanisms of neural function of circuits. Direct electrical interactions a mechanism for transcriptomic variation, are being discovered all the time. This between adjacent neurons—so-called neurons in adult animals can alter which raises a question that sits at the junc- ‘‘ephaptic coupling’’—has been sug- neurotransmitters they use for signaling tion between ‘‘big neuroscience’’ projects gested to entrain the spiking of cortical in response to environmental cues (Birren and discovery-oriented research: how neurons to extracellular electric fields and Marder, 2013). Beyond even cells and should one design brain mapping tech- (Buzsa´ ki et al., 2012) and may play other their interconnections, it has been sug- nologies that can scalably acquire knowl- roles in exciting or inhibiting neurons of gested that new tools to probe the extra- edge about classical mechanisms that specific geometry. cellular matrix, which is implicated in the we know are important, while taking in Classical neurotransmitters are of formation and preservation of memories, stride the continual uncovering of new course of great importance in neural may be important for a full understanding mechanisms? communication. But new kinds of trans- of synaptic plasticity (Tsien, 2013). mitters, such as peptides, are routinely Tools that cannot take into account new New Mechanisms and the Need for being discovered. Retrograde signaling mechanisms are essentially making the Mapping Them by diffusible messengers—from postsyn- assumption that those new mechanisms There is no universal agreement as aptic to presynaptic neurons—is now are not contributing to a significant de- to what data sets are needed for a full un- well established, such as for the case of gree. Certainly, this may be the case for derstanding of the brain. Currently, there cannabinoids (Younts and Castillo, 2014). many well-defined problems, e.g., under- are efforts to understand the brain as a Nitric oxide (NO) functions as a diffusible standing a few seconds of neural network made of neurons (e.g., in sys- gaseous messenger that can pass through dynamics might not require detailed un- tems neuroscience), as well as efforts to cell membranes and can induce, in a derstandings of how that neural activity understand neurons as networks of mole- temporally precise fashion, synaptic plas- regulates downstream gene expression cules (e.g., in molecular neuroscience). ticity (Hardingham et al., 2013). Indicators over timescales of hours to days. But, Efforts to build bridges between these for gases and other hard-to-tag molecules when developing new mechanism map- levels of abstraction in the brain are might be needed to understand how these ping tools, it is useful to at least consider much desired. nonclassical transmitters contribute to whether they can easily be extended to Dynomics and connectomics focus neural circuit functions. include new mechanisms. largely on mapping the spiking activity of Another mapping effort is the quest to neural populations and the synaptic con- enumerate the kinds of building blocks Tools for Assumption-free Brain nectivity of neural networks, respectively. of the brain. One of the early flagship pro- Mapping Yet, many other mechanisms of electrical jects of the BRAIN initiative is to assemble The timing is right to elucidate design and chemical computation and communi- a list of neuron types. Tools for mapping principles for neurotechnologies that cation are routinely being discovered. For glial circuits, of course, might easily com- work backward from the fundamental dynomics, mapping the timing of discrete plement those for mapping circuits of properties of the brain and are equal to action potentials may reflect only part of neurons. For neurons, mapping tran- the challenge of mapping their mecha- the neural code, and full maps that reflect scriptomes has been proposed to pro- nisms, rather than working forward the analog electrical signals being discov- vide a basis for classifying cell types. from known technology building blocks. ered in many cell types may require new But whether genes are ‘‘on’’ or ‘‘off’’ is In particular, we want to design tech- recording or imaging technologies. For perhaps not enough: alternative splicing nologies so that they can take new Neuron 83, September 17, 2014 ª2014 Elsevier Inc. 1239 Neuron NeuroView mechanisms in stride, minimizing the reli- to systematically map molecular mecha- Tightening the Loop between ance on assumptions that may later be nisms will probably require new kinds of Discovery and Mapping shown to be false. observable tags and imaging systems. How can one design assumption-resis- One key difficulty with brain mapping is tant, scalable, brain mapping technolo- that vastly different spatial and temporal Integrated Tools gies that can be extended to new mecha- scales often have to be simultaneously An ideal technology would be able to map nisms as they are found? It is important to considered. The brain is organized with many kinds of variables (anatomical, mo- work backward from the properties of the nanoscale precision, yet neural circuits lecular, physiological) in the same brain. brain that need to be mapped and then to can span vast regions, even tens of centi- Surprising organizational features of the design the technology to meet that need. meters or larger. Individual signaling connectivity of circuits are often apparent But this approach can be limiting if it events can last milliseconds, yet learning only after looking at many neurons within cannot take into stride undiscovered or development or disease progression a single instantiation of a circuit and their mechanisms. One strategy is to bring can take years. Thus, neuroscience is a topology of connectivity. Within a circuit, forth new models of collaboration that kind of ‘‘mesoscale biology,’’ to borrow self-organization via plasticity mecha- connect people from different back- a term from physics. nisms occurs to ensure network operation grounds so that technologies are de- For the case of neural activity, it will within the evolutionarily selected bounds signed ideally without excluding potential likely be important to map neural activity of behavior, but two neurons in two mechanisms that might to be considered not only at the single-neuron level, but different brains would not experience in the future. It also requires systematic potentially with neural subcompartment any such interaction. Such mechanisms thinking in design. For example, attempt- resolution. Observing the propagation of of homeostasis could prove to yield ing to make roadmaps of all possible di- neural activity through parts of neurons, important organizing principles of neural rections before picking a path has in our e.g., in the dendritic tree, may be required circuitry. experience helped narrow focus on paths to understand how neurons integrate in- Correlations between multiple variables that obey physical laws and can, poten- puts toward their neural code outputs. can of course be seen even at the popula- tially, match the complexity of the brain. Despite the need for such spatial resolu- tion level. Gene expression and projection In this ‘‘architecting’’ strategy, we actively tion, however, it is also clear that neurons patterns are linked variables for neurons recruit experts on different potential tech- in widely distributed circuits are operating in the cerebral cortex (for example, Soren- nology building blocks, bringing them in close coordination, and thus tech- sen et al., 2013). Technologies that only together to consider not just the quantita- nologies for brain activity mapping reflect connectomic or only gene expres- tive evaluation of potential paths, but new must span these large spatial scales. sion patterns, and not both, would miss creative ideas or intuitions that might help The temporal precision required is also such linkages. Studies linking cell shape generate an integrative technology. demanding, one millisecond or even bet- and gene expression pattern have also re- For example, we recently completed ter, which makes the recording of behav- vealed rich interdependencies,
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