Edward Boyden, Principal Investigator - US grants

NIH Roadmap Initiative tag; technology /technique development

This project focuses on the functional implications of low-frequency rhythms in the basal ganglia and neocortex. The collaborative effort involves four groups: Kopell, (Boston University), Moore (Massachusetts Institute of Technology), Graybiel (Massachusetts Institute of Technology) and Boyden (Massachusetts Institute of Technology). The project is the first collaborative research effort of the newly formed Cognitive Rhythms Collaborative (CRC), a group of Boston Area faculty members from Boston University, Massachusetts Institute of Technology, Massachusetts General Hospital Martinos Center for Biomedical Imaging, Brandeis University and Tufts University. The aims of the CRC, which fosters research and training, are to map the spatio-temporal structure of brain dynamics and connect these dynamics to brain function. This is the first project to try to understand from basic electrophysiology the growing literature suggesting that the low frequency brain rhythms are critical for both attention and learning, and that interactions among brain structures such as the basal ganglia and neocortex are central for such functions. The project makes use of the electrophysiology skills of the Graybiel lab, which is focused on the dynamics of the basal ganglia, and those of the Moore lab, focused on the neocortex, to understand the flow of information between the cortex and the basal ganglia during learning and attention. This collaboration is enriched by new molecular biology technology developed by the Boyden group. This technology, in which cells can be activated and inactivated by light, provides powerful new techniques for figuring out circuits by looking at effects of perturbations, even in behaving animals. The experimental work is guided by modeling ideas from the Kopell and Moore labs, and the output of the modeling can be tested almost immediately by the labs for quick feedback and changes. This CRC project exemplifies a new and transformational way of doing science, bridging the boundaries of disciplines and institutes to facilitate cutting edge research at the forefront of interdisciplinary endeavors.

The proposed research will test the novel hypothesis that enhanced blood supply to a local brain region impacts neural processing. A key feature of neural circuits is their flexibility, their ability to respond differently (for example, to a sensory stimulus) depending on context. This flexibility allows organisms in general and humans in particular to perform crucial tasks for survival, such as shifting attention. This flexibility is also crucial to brain health: Failures in normal mechanisms of neural dynamics - in the normal ability to shift sensitivity - have been implicated in diseases ranging from epilepsy to schizophrenia.

In this project the PIs will test the prediction that changes in blood supply to cortical sensory neurons can modulate their responses to sensory inputs. To test this hypothesis, they will integrate four techniques, bringing together expertise from two laboratories: whole animal electrophysiological and imaging studies to define the effect of changes in blood flow on neural activity and electrophysiological and imaging studies in brain slices to begin to investigate the mechanisms underlying this phenomenon. A key feature of the proposed research is development of a novel means of bidirectional blood flow regulation, the viral transfection of light-activated channels into smooth muscle. By constricting or relaxing smooth muscles using directed light, they will expand or contract local cerebral arterioles, regulating blood supply. This method provides an approach independent of the potential confounds of pharmacological intervention.

A second key feature of the proposed research is a summer research initiative for Queens College students at MIT. This program will provide a unique opportunity for Queens College students to experience the MIT environment, systematic training in research proposal development, execution of this plan, training in research ethics, and writing a summary for publication.

DESCRIPTION (provided by applicant): Modulating Cortical and Sub-cortical Brain Circuits in Chronic Facial Pain Chronic pain, especially facial pain is difficult to treat because it is associated with an enormous diversity of nervous system alterations. Characterizations of these changes at the molecular level, using animal models, have yielded insights that largely have not translated to the human, perhaps because the molecular complexity of the changes insures that significant differences will exist when comparing across species. At a neural circuit level, on the other hand, it may be possible to define endophenotypes that correlate with pain state, that may better generalize across species (and across patients) because they are convergently downstream of many different upstream molecular changes, and may causally be associatable with, or predict, pain state. Accordingly, we propose to study rat models of pain by optically silencing, in a temporally-precise manner, candidate brain regions in the pain circuit using novel methods we have developed, and assessing the impact on pain behavior, as well as on the pain circuit using functional magnetic resonance imaging (fMRI). In this way we will parse out the brainwide contribution of a neural circuit to pain endophenotype. By expanding our investigation beyond pain behaviors we will better understand the global behavioral effects of chronic pain and the role(s) of specific CNS regions in modulating these behavioral effects, and hopefully better model chronic pain in humans. PUBLIC HEALTH RELEVANCE: Determining the neural substrates that define the chronic facial pain state is a key step in developing treatments that generalize from basic research to humans, and also that generalize across human patients. By moving beyond the combinatorial complexity of molecular changes, to the understanding of how pain is represented in the brain, as described by optical neural control and functional brain imaging, we will develop new biomarkers for pain that accurately reflect the pain state, thus advancing the state of therapy, diagnosis, and drug discovery.

This grant supports the Collaborative Rhythms Collaborative (CRC), a group of scientists in the Boston area who have begun to work together to advance our understanding of the brain dynamics underlying cognitive functions such as attention, sensation, motor planning, and memory. There is a growing consensus that dynamics are central to understanding how the brain works, but major gaps exist in what we know and in how we seek to understand more. The CRC has focused on the dynamical regime most strongly associated with cognition, rhythmic activity in the frequency range 1 - 200 Hz. Its central aims are to characterize the physiological origins and functions of such rhythms and to understand how pathologies in rhythmic dynamics are related to symptoms and mechanisms of neurological disease. Mathematical modeling, cutting-edge statistical techniques, and their implementation as computer algorithms will be critical to carrying out its scientific program. The grant will support the CRC, concentrating on the application of the mathematical sciences to the investigation of brain dynamics and the potential for new mathematical, statistical and computational techniques driven by challenging scientific problems. This will include support of a technology core that will create new hardware/software platforms to support such techniques. The CRC will also provide mentoring and teaching to a large community of students and post-doctoral fellows.

The Cognitive Rhythms Collaborative, involving multiple institutions in the Boston area, offers a unique chance to develop a network of researchers from the mathematical, biological, and cognitive sciences to explore fascinating questions in the area of neuroscience. This is a different mechanism of interaction than is traditionally seen and has the potential to transform the way such interdisciplinary problems are addressed. The CRC seeks to provide new ways of doing science by fostering broader and deeper collaboration in addressing scientific questions. This work will involve tight collaborations among scientists with a multitude of backgrounds, and will emphasize the role of mathematics in the investigation of neuroscience questions. The CRC will also train a cohort of postdoctoral fellows in a way that will lead to a deep understanding of the intellectual context of their work. The technology core of the project will produce both hardware and software that will be available within and beyond the CRC, and enable computations that are now almost impossible.

This grant application is for a second renewal of our group?s key NIH grant that supports development of optogenetic tools -- microbial opsins that enable safe, temporally precise, and high-magnitude control of neural activity in neurons in awake behaving mammals and other species of importance in neuroscience. Since our grant was first awarded in 2010, it has supported the development of optogenetic tools such as Arch (the first optogenetic neural silencer to result in ~100% optogenetic silencing of neural activity in awake behaving mice), ArchT (a 3x more light-sensitive relative of Arch), Chronos (an ultrafast optogenetic activator, used in contexts where speed is essential), Chrimson (the most redshifted optogenetic activator, useful for activation of large volumes of brain tissue as well as avoiding behavioral artifacts in Drosophila), Jaws (the most redshifted optogenetic silencer), SoCoChR (which enables single-cell, single-spike resolution optogenetics) and ChromeQ (a potassium- and sodium-selective optogenetic activator), resulting in 50 peer reviewed papers, and resulting in wide distribution of next-generation optogenetic tools throughout neuroscience. To date, we have primarily used genomic search to discover novel opsins, mining public and private databases to identify new candidates. Having screened through a large number of genomic resources to identify these molecules, however, one concern is that there are diminishing returns, and that some goals will not be met purely through genomic search, or even structure-guided site-directed mutagenesis. Directed evolution, which sifts through a large number of mutants of a parent gene to identify versions improved towards some goal, offers hope, but has not been applied to optogenetic tools due to the difficulty of performing directed evolution in mammalian cells (essential, since optogenetic tools that express well in cells commonly used in directed evolution, such as E. coli, do not express well in mammalian cells, and evolving optogenetic tools in such cells would likely de- optimize them for expression in mammalian cells), and the difficulty of performing multidimensional directed evolution (essential, because we need to optimize optogenetic tools towards multiple goals ? for example, localization, spectrum, and magnitude ? and optimizing too much along one axis will de-optimize the tool along other axes). We here propose to develop a directed evolution approach for optogenetic tool engineering (Aim 1), and apply it to several longstanding open needs in optogenetics: the creation of redshifted and blue spectrum-trimmed optogenetic activators, Aim 2; the creation of multiphoton-optimized silencers, Aim 3; and the optimization (by developing and applying automated patch clamp technology) of kinetics and ion selectivity, aiming to improve optogenetic tool kinetics for the aforementioned optogenetic tools as well as potassium conductances of light-gated potassium channels (Aim 4). We aim to deliver to the neuroscience community a powerful toolbox of optogenetic controllers of widespread utility, and to disseminate them freely throughout the research world.

1053233
Boyden

Tools that enable the perturbation of specific cellular processes in a temporally-precise manner are critical in the field of neuroscience for determining when and how such processes contribute to neural computations, behaviors, and pathologies. Without such tools, mechanistic understandings of how neurons and neural networks function are sometimes tentative, limiting not only basic science but also clinical progress, as the core mechanisms that contribute to normal function and disease states, and that might enable potential therapies, can remain obscure. To open up the ability to test the causal role of defined neurons in emergent brain functions, the PI has recently pioneered a set of molecular tools that, when genetically expressed in specific neuron classes within the brain, enable those neurons to be electrically activated and silenced in response to specific colors of light. These molecules are opsins, light-driven membrane proteins from nature that, when illuminated, transport charge from one side of the cellular membrane to the other. Since neurons are electrically excitable cells, expression of these genes in neurons and illumination of the resultant transgenic neurons can effect their electrical activation or silencing. Over the last few years, this lab at MIT has distributed these "optogenetic" reagents to ~300 research labs around the world, enabling these groups to study the causal role of specific cell types in brain functions. Despite their broad impact, these tools are chiefly useful for analyzing neural circuits at the level of seeing how specific cells causally affect behavior and neural dynamics; they do not enable detailed analysis of the contribution of computational processes within neurons, mediated by specific ion channels and receptors, to neural network operation. Accordingly, the PI proposes to engineer a new generation of molecular reagents and hardware to enable the study of the causal roles of receptors and ion channels in neural computations and behaviors.

DESCRIPTION (provided by applicant): Ion channels and neurotransmitter receptors are amongst the most important molecules in the nervous system. They support the high-speed physiological processes that enable neurons to function, they are implicated in many neurological and psychiatric disorders, and they present an incredibly important set of drug targets for treating these diseases. In order to enable a better understanding of how specific ion channels and receptors contribute to behaviors and pathologies, we propose to engineer a toolbox of fully genetically encoded reagents that, when expressed in specific neurons in the brain, enable specific ion channels and ionotropic neurotransmitter receptors to be driven or blocked in a temporally precise fashion, using pulses of light. We anticipate that these tools will find widespread use in both basic and clinical neuroscience, and in other fields of biology, for revealing the roles that specific ion channels and receptors (or changes in their activity levels) play in neural computations, behaviors, and disease states, and for revealing more specific drug targets.

DESCRIPTION (provided by applicant): General anesthesia is a reversible, drug-induced behavioral state comprised of unconsciousness, amnesia, analgesia and immobility with stability and control of vital physiological systems. This fundamental tool of modern medicine is crucial for allowing thousands of patients daily to safely undergo most surgical and many non-surgical procedures. Today this state is induced and maintained by administering multiple drugs that act at multiple sites in the brain and central nervous system. Emergence from general anesthesia is a passive process whereby anesthetic drugs are merely discontinued at the end of surgery and no drugs are administered to actively reverse their effects. Allowing multiple drugs to act at multiple sites without specific mechanisms to terminate their effects most likely explains a significant component of anesthesia-related morbidity; drug side effects (nausea, hypotension, respiratory depression, hypothermia) are due to actions at sites other than their intended targets whereas persistent effects (delirium, cognitive dysfunction) are due to actions at intended targets for periods longer than desired. Hence, general anesthesia, as presently produced, is highly non-specific and inefficient. Despite the central role of anesthesiology in modern healthcare, research in this field is overly focused on deciphering the anesthetic and toxic mechanisms of current drugs with little to no attention being paid to developing new approaches. The paradigm-shifting question whose answer will revolutionize anesthesiology is not, how do current anesthetics work?, but rather, how should the state of general anesthesia be designed? We hypothesize that the answer is by developing strategies to control directly the brain's natural inhibitory pathways and arousal centers. We propose to redesign general anesthesia by combining optogenetic, electrical and pharmacological manipulations in rodent models to create this behavioral state through precisely timed control of the brain's natural inhibitory pathways and its arousal centers. If successful this research will provide a new fundamental understanding of brain arousal control, and eventually, new anesthesiology practices including: neurophysiologically-designed approaches to creating general anesthesia; reduction in morbidity; improved brain function monitoring; safer anesthesia care by non-anesthesiologists; and possibly novel therapies for arousal disorders such as depression, insomnia, pain and coma.

DESCRIPTION (provided by applicant): The cells of the brain exhibit a diversity of expressed genes, morphologies, and electrophysiological properties, and have come to be grouped into cell types that are distinguished by one or more of these characteristics. However, there is no one-to-one correspondence between cell type-defining expressed genes, morphological characteristics, and electrophysiological properties and no unified taxonomy of brain cells. Furthermore, cells routinely change their expressed genes, morphologies, and electrophysiological properties, as a result of development, plasticity, or disease, raising the question of how to categorize cell types as they change their states as a result of experience. Accordingly, we propose to develop a powerful, easy-to-use tool that enables the integrative phenotyping of cells of the brain - namely, a robot that can acquire simultaneously the gene expression patterns, morphologies, and electrophysiological properties of single cells in brain tissue, in an automated fashion. Recently, two of our labs developed a prototype autopatching robot that enables automated whole-cell patch clamp recording of neurons in living mouse brain, significantly increasing the efficiency of this highly challenging task. In a multidisciplinary tea, we propose to augment this robot, coupling it to transcriptional and morphological analysis strategies, yielding a platform for the comprehensive characterization of single cells in intact tissues. We will develop variants of the robot and its algorithms to enable it to patch in brain slices, including in an image guided fashion (Aim 1), to extract transcriptomic information (Aim 2), and to perform morphological fills (Aim 3) and gene delivery to cells (Aim 5). We will also create massively parallel autopatching robots (Aim 4). We will autopatch hundreds to thousands of single cells from different cortical regions of mice (Aim 6), in vivo as well as in slices, both broadly surveying cells, as well as targeting specific fluorescently labeled neural populations. We will create visualization software to help with analysis of the integrated cell profiles that emerge, aiming to estimate the dimensionality of cell type space, characterize cell- to-cell heterogeneity, and discover optimal cell type markers for molecular targeting. Our goal is to create a powerful, easy-to-use toolbox that makes fundamentally new kinds of science possible, converting the critical tasks of categorizing cell types, and characterizing cell states, into routne, simple tasks. As our goal is to develop a toolbox which will have very broad applicability, we are focusing our innovation not only on power, but ease of use, aiming to enable fields across biology to characterize normal and diseased organ states at the single cell level. We will distribute all tools, methods, and datasets as freely as possible, and teach others to use these technologies. As many diseases affect different cells to different extents, we will seek to commercialize our work to enable diagnostic or therapeutic tools that directly improve human health.

ABSTRACT
This INSPIRE award is partially funded by the Biophotonics (7236)and Biomedical Engineering (5345) programs in the CBET Division in the Directorate for Engineering; the Robust Intelligence (7495) program in the Division of Information and Intelligent Systems in the Directorate for Computer and Information Science and Engineering; and the the Organization (7712) program in the Division of Integrative Organismal Systems in the Directorate for Biology and the Instrumentation and Instrument Development (1108) program in the Division of Biological Infrastructure, also in the Directorate for Biology. Emerging Frontiers (7275) money was provided for the Organization and Instrumentation and Instrument Development programs by the Directorate for Biology.


The ability to optically image real-time physiological processes in living systems is of central importance for understanding how biological systems compute and function. In order to enable the imaging of deep, arbitrary-scale tissues, the PI proposes to address one of the fundamental limitations in live tissue imaging: the scattering of light by live tissues. Much work has been devoted to adaptive optics using conventional off-the-shelf spatial light modulators, interferometers, cameras, and other hardware. Here the PI proposes to create new technologies for adaptive optics based instead upon nanotechnology, which can help correct optical imaging for the scattering properties of living tissues. The project goal is nothing less than that of making real-time physiological processes visible throughout live tissues and organs, important for understanding how biological computations occur. The impact will be large for any field where understanding complex 3-D systems is key - for the study of live organs such as heart and brain, for the immune system, for the study of metabolism, for the study of development and aging, and for cancer biology.
They will distribute all tools as freely as possible, and pursue distribution mechanisms to maximize the availability of tools, at cost whenever possible. The proposed innovations will also benefit the field of optogenetic control of complex systems. These innovations will also greatly help with teaching of biology and medicine at all levels of education, since the ability to visualize things is powerful in education; we will incorporate these tools into teaching both at MIT and elsewhere, engaging scientists-in-training, as well as the public. Through both direct impact of tool usage, as well as via teaching, they anticipate that these proposed technologies will result in a more scientifically literate workforce. they also anticipate commercial impact, in the creation of new methods of diagnostics and medicine. The ability to hunt down better disease mechanisms, or mechanisms of disease treatment, may accelerate the development of new drugs and therapies. Some of the technologies here proposed could also lead to new companies, or new products, thus contributing to economic development, as well as helping with dissemination of the tools.

DESCRIPTION (provided by applicant): One of the great challenges in neuroscience is to understand how the neurons of the brain work together as a circuit to compute behaviors, and how such circuit functions are changed in brain disorder states. There is a great need for technologies that enable the neural activity of large numbers of individual cells to be measured in the brain of a mammal such as a mouse - ideally throughout the entire brain, since we do not precisely know the exact set of cells involved with any behavior or brain disorder. We here propose two radical departures from the past, using computational and theoretical analyses to design new neural recording devices, and augmenting these technologies with supplementary tools to enable the bridging of dynamic and anatomical pictures of the brain. As we validate these technologies, we will examine whole-brain neural dynamics and anatomical phenotypes in autism and schizophrenia mouse models, performing whole-brain activity mapping to characterize the altered computations associated with psychiatric illness. Such maps may fundamentally open up new frontiers in thinking about how distributed brain circuits are changed in mental illness, paving the way to new treatment strategies.

DESCRIPTION (provided by applicant): General anesthesia is a reversible, drug-induced behavioral state comprised of unconsciousness, amnesia, analgesia and immobility with stability and control of vital physiological systems. This fundamental tool of modern medicine is crucial for allowing thousands of patients daily to safely undergo most surgical and many non-surgical procedures. Today this state is induced and maintained by administering multiple drugs that act at multiple sites in the brain and central nervous system. Emergence from general anesthesia is a passive process whereby anesthetic drugs are merely discontinued at the end of surgery and no drugs are administered to actively reverse their effects. Allowing multiple drugs to act at multiple sites without specific mechanisms to terminate their effects most likely explains a significant component of anesthesia-related morbidity; drug side effects (nausea, hypotension, respiratory depression, hypothermia) are due to actions at sites other than their intended targets whereas persistent effects (delirium, cognitive dysfunction) are due to actions at intended targets for periods longer than desired. Hence, general anesthesia, as presently produced, is highly non-specific and inefficient. Despite the central role of anesthesiology in modern healthcare, research in this field is overly focused on deciphering the anesthetic and toxic mechanisms of current drugs with little to no attention being paid to developing new approaches. The paradigm-shifting question whose answer will revolutionize anesthesiology is not, how do current anesthetics work?, but rather, how should the state of general anesthesia be designed? We hypothesize that the answer is by developing strategies to control directly the brain's natural inhibitory pathways and arousal centers. We propose to redesign general anesthesia by combining optogenetic, electrical and pharmacological manipulations in rodent models to create this behavioral state through precisely timed control of the brain's natural inhibitory pathways and its arousal centers. If successful this research will provide a new fundamental understanding of brain arousal control, and eventually, new anesthesiology practices including: neurophysiologically-designed approaches to creating general anesthesia; reduction in morbidity; improved brain function monitoring; safer anesthesia care by non-anesthesiologists; and possibly novel therapies for arousal disorders such as depression, insomnia, pain and coma.

? DESCRIPTION (provided by applicant): Significant work is ongoing to reveal how different cell types in the brain contribute to behavior and pathology, and how they change in plasticity and disease, empowered by new genetic, optical, and physiological tools. However, the functional activity and dysregulation of neuronal circuits relies critically on the in situ molecular composition of neuronal synapses. Although it is clear that the properties of a given synapse are determined by, amongst other things, the specific types of cells that are thus connected, far less is known about the diversity of synapse types in the brain than cell types, perhaps because this is an intrinsically proteomic problem: a given neuron might make many different kinds of synapse with different targets, and thus transcriptomics (which is prevailing as a method for cell type analysis) may not suffice for synapse typing. High- throughput in situ proteomic tools are needed to characterize synapse molecular composition at the single-cell level in the context of whole brains or brain regions, and thus to connect the currently distant topics of neuronal activity and genetic aberrations associated with disease pathology. Here, we propose a high-risk, high-payoff, and as far as we know entirely novel agenda: to develop tools capable of resolving the molecular proteomic composition of synapse types, testing them in cultured neurons and intact brain tissues. To achieve this transformative goal of establishing a broadly useful tool for in situ synapse proteomics, we will build on our recent breakthrough in developing the DNA-based highly multiplexed, quantitative super-resolution imaging method DNA- PAINT (Points Accumulation for Imaging in Nanoscale Topography). DNA-PAINT exploits the transient binding of short fluorescently labeled DNA-probes for simple and easy-to-implement quantitative, highly multiplexed, super-resolution imaging with sub-10 nm resolution. In this application, we plan to develop and apply DNA-PAINT to enable quantitative, ultra-multiplexed, in situ characterization of neuronal synapse proteins for understanding synaptic types and studying cell type-specific synaptic functions. The outcome of our work will be a broadly useful in situ proteomic tool for quantification of neuronal synapse composition that can be used by diverse neurobiology laboratories to study single cell-level synapse properties in fixed tissues from whole brains or cell culture assays.

How does the brain compute? Understanding this process could lead to many advances in science and technology. The Boyden, Flavell, Barabasi, and Tegmark groups propose to examine how the cells within the brain of a simple animal work together to generate the computations that underlie behavior. The teams will study C. elegans, a small worm with just a few hundred neurons, yet capable of learning and adaptive behavior in complex real-world environments.  The teams will apply new technologies to measure and control the neural circuits of C. elegans, in order to investigate how they works. The project will also generate new mathematical tools to analyze the data that is collected - tools that could help analyze how the brain goes wrong in disorders such as Parkinson's or Alzheimer's. Using the data acquired, the project will reveal how brain circuits compute, which could inspire new algorithms for machine learning and computer information processing. These in turn could have broad impact on economic prosperity as well as in advancing human quality of life.

The Boyden, Flavell, Barabasi, and Tegmark groups will launch a novel integrative endeavor to reveal how entire nervous systems - from sensory input neurons, to motor output neurons, and including the networks that underlie learning, decision making, and other processes - work together as emergent wholes to generate the computations that underlie behavior. They will utilize C. elegans, with just 302 neurons, yet capable of learning and adaptive behavior in complex real-world environments.  They will optimize and deploy novel technologies, including a new fluorescent voltage indicator for C. elegans, and a method for 3-D visualization of entire nervous systems with molecular information via physical expansion by up to 10,000 fold in volume. They will record neural and behavioral dynamics, imaging the activity of neurons throughout entire brains and even entire nervous systems of freely moving as well as fictively behaving C. elegans engaged in complex decision-making tasks, or forming new memories. They will then use expansion microscopy to map the structure and molecular profiles of entire individual nervous systems. They will analyze the resultant network structures to determine how individual variation in these features connect to details of an individual's behavior, and make mathematical models of the relevant neural circuits capable of predicting how the nervous system would respond in complex contexts. The outcome of their work will yield radical new theories of how nervous systems operate, as well as a diversity of tools for the neuroscience and computational communities.

This project is funded by Integrative Strategies for Understanding Neural and Cognitive Systems (NSF-NCS), a multidisciplinary program jointly supported by the Directorates for Computer and Information Science and Engineering (CISE), Education and Human Resources (EHR), Engineering (ENG), and Social, Behavioral, and Economic Sciences (SBE).

The ability to dynamically image, using fluorescent probes, neural activity and other fast physiological events in living brains has begun to revolutionize neuroscience. The fundamental limitation of optical scattering in living tissue, which limits fast imaging to shallow depths, has attracted much attention from hardware inventors, who have developed a diversity of strategies -- ranging from multiphoton laser-scanning microscopy, to adaptive optics approaches that attempt to invert tissue scattering. However, imaging extended volumes of brain tissue, at rates that keep up with fast events like action potentials, remains a challenge. We here propose to invert the problem, and make the living brain, itself, more transparent. By developing chemicals that safely and efficaciously smooth out refractive index inhomogeneities that scatter light, we will enable observation of high speed neural processes throughout extended volumes, e.g. entire cortical microcircuits (and potentially, across arbitrary scales). In this way, neuroscientists will be able to analyze the neural activity patterns across circuits underlying complex phenomena like emotions, decisions, and actions, and that contribute to disease states. Beyond neuroscience, our technology may broadly improve the observation of high-speed physiological events in the living body, of importance to immunity, development, cancer, and other parts of biology and medicine.

Many questions in biology and neuroscience would benefit greatly from a technology that enabled molecular information (e.g., the identities of specific nucleic acids and proteins) to be imaged throughout preserved 3-D specimens (e.g., brain circuits), with nanoscale precision. Accordingly, we developed a fundamentally new approach, published in Science in 2015: in contrast to earlier methods of magnification in light microscopy, which rely on lenses to optically magnify images of cells and tissues, we physically magnify preserved specimens. By synthesizing a swellable polyelectrolyte gel directly within a specimen, mechanically homogenizing the specimen, then dialyzing in water, we could expand tissues by ~4.5x in linear dimension. This method could separate molecules located within a diffraction-limited volume to distances great enough to be resolved with conventional microscopes, resulting in an effective resolution of ~70 nm. We call this novel method expansion microscopy (ExM). Since then, we have made the technology easier to use, creating a version of ExM which we call proExM (protein retention ExM) that uses commercially available chemicals to directly anchor genetically encoded fluorophores or antibody-borne fluorophores to the swellable gel, and validating its ability to preserve nanoscale features in a variety of tissues (accepted at Nature Biotechnology) and extended ExM to the anchoring and expansion of RNA molecules away from one another for nanoscale RNA visualization, which we call ExFISH (accepted at Nature Methods). There is great pent-up demand for a method of nanoscale imaging for extended 3-D specimens, especially one that requires no specialized equipment; we host visitors weekly in our group at MIT to come and learn and practice ExM, and with the Janelia Research Campus we will run a workshop to teach ExM hands-on in August 2016. Given the potential for ExM to solve many problems in neuroscience, we now propose to increase its power and versatility. Specifically, we will (Aim 1) develop optimized forms of ExM for difficult specimens (such as C. elegans), as well as strategies for single-sample validation (by creating ?physical scalebars? within samples), (Aim 2) invent new chemistries for expanding specimens by 20x or 80x in linear dimension, enabling ~15 nm and ~3 nm effective resolutions respectively, and (Aim 3) extend ExM anchoring chemistries for the visualization of lipids and DNA, as well as combinations of biomolecules (e.g., seeing proteins, DNA, and RNA all at once). Our project will result in tools of great applicability in neuroscience, as well as throughout biology. We propose a fast-paced, 4 year technology development grant that will result in tools that will enable a large number of scientific problems to be analyzed. We will distribute all tools as freely as possible, and teach usage thereof.

Genetically encoded molecular tools are having impact throughout neuroscience. However, each genetically encoded molecular tool is a feat of protein engineering, requiring extensive effort to design and optimize. One appealing thought is that it might be possible to create a small number of modular protein building blocks, which then could be organized in patterns, and achieve user-programmable functions, by being scaffolded together on strands of RNA. We recently derived from the Pumilio homology domain (PumHD) protein, 4 building blocks, each of which prefers one of the 4 bases of RNA, so that for any RNA of interest in a cell, a chain made out of the 4 building blocks in a defined sequence can be created to bind to that RNA (bringing along any protein payloads that are fused to that chain). We propose to adapt this Pumilio based (or ?Pum? for short) strategy to create RNA-scaffolded molecular tools that address two major classes of problem in neuroscience ? the targeting of gene expression to specific cell types in the mammalian brain, with high specificity, without requiring transgenic animals (Aim 1), and the ability to image multiple independent fluorescent reporters of physiological activity within individual neurons without crosstalk (Aim 2). We will assess, and optimize, these scaffolded molecular tools in mice (Aims 1, 2) and a non-genetic model organism (macaques), aiming to open up new frontiers of neuroscience experimentation (Aim 3). Our grant is a fast- paced, 4-year grant, which brings together experts in neurotechnology development (Boyden), primate systems neuroscience (Desimone), and nucleic acid technology (Adamala). We will share all tools freely with the neuroscience community, in order to broadly accelerate neuroscience progress.

The functional activity and dysregulation of neuronal circuits relies critically on the physiology of neuronal synapses, which are challenging to analyze because they appear in great numbers, and they are difficult to record in vivo, especially in relation to the dynamic neural codes generated by specific neurons. To make things even more complex: synapses are incredibly dynamic in fashions that are dependent on recent history, sensory stimuli, disease state, and other behaviorally relevant contexts. Ideally there would be a technology that would allow for individual investigators to rapidly analyze synapses between neurons exhibiting neural codes in a behavioral context, so that it is possible to understand how information is trans formed at synapses. We here propose to develop a simple, easily deployable toolbox for achieving this, building from several recent discoveries. First, we have found (manuscript in preparation) that it is possible to automatically perform whole cell patch clamp neural recording of cells in the living mouse brain that have been identified via two-photon fluorescence microscopy (e.g., cells of a given type that express a genetically encoded fluorophore). We here propose to invent a multiple-neuron patching version of this ?imagepatching? robot, to enable the simultaneous characterization of the neural codes in multiple neurons, as well as the synaptic connections between them (Aim 1). We will also develop miniaturized and optimized hardware capable of performing imagepatching, neurosurgery, and patch clamp electrode reuse for improved yield and throughput of synaptic assessment. (Aim 2). Also, we have discovered that it is possible to physically expand preserved neural circuits, by embedding them in swellable polymers, and then chemically expanding those polymers, a technology we call expansion microscopy (ExM), which enables nanoscale imaging of 3-D tissues and organisms. We propose to optimize ExM for the analyses of synapses (Aim 3). We here propose a fast-paced, 4-year grant, to create a powerful, easy-to-use toolbox that makes the critical task of in vivo synaptic physiology into a routine, automated procedure. We will distribute all tools and datasets as freely as possible, sharing all algorithms, circuit designs, and assembly instructions, and hosting visitors to learn these technologies ? for which we have an extensive track record.