Jeff W. Lichtman - US grants

Several lines of evidence suggest that the number and distribution of axonal contacts on postsynaptic cells are regulated by competitive interactions between axons during development. The aim of this work is to better understand the developmental strategies that regulate this competition. The studies will utilize new techniques that allow for visualization of individual terminals in living preparations under the light microscope. The normally occurring competitive reduction in the number of terminals that innervate a muscle fiber (synapse elimination) will be followed by viewing terminals of one axon that have been made visible by activity dependent tracer uptake. Preliminary experiments indicate that it is possible (a) to activate an individual identified motor axon and its motor unit in the transversus abdominis muscle of the garter snake by extracellular stimulation, (b) To identify neurally activated nerve terminals in the light microscope using uptake of fluorescein-dextran or a peroxidase enzyme, and (c) to see peroxidase filled processes in vivo by the enzyme mediated conversion of L-DOPA into melanin. Our objective is to use these techniques in order to observe the competitive process which results in the 'capture' of an endplate by one axon. Among the questions this project aims to answer are: (1) Does axonal competition proceed by means of physical contact among terminals or does competition occur at a distance? (2) What is the relationship between the elimination and proliferation of synapses which occur concurrently during development? (3) Does synapse elimination play a role in creating qualitative specificity (e.g., matching of types of motor axon and fiber). Answers to these questions are fundamental to understanding the basis of appropriate connectivity between nerve cells and their targets. The transversus abdominis muscle of the garter snake is an advantageous preparation since it is only one fiber in thickness, enabling excellent visability of all the neuromuscular contacts. Moreover, it contains several types of innervating axons and muscle fibers which are arranged in a stereotyped repeating pattern.

How the intricate pattern of connections between nerve cells and their targets is established is a fundamental and largely unanswered question in neurobiology. One feature of this pattern, however, which has begun to be understood: the number and distribution of an axon's contacts with postsynaptic cells. This quantitative feature of neural connectivity is regulated by a competitive process during development known as synapse elimination. I propose to investigate the mechanisms underlying synapse elimination by developing techniques that allow for light microscopic visualization of individual axonal terminals in living preparations. I plan to follow the normally occurring reduction in the number of terminals by activity dependent enzyme uptake. Preliminary experiments indicate that it is possible to identify neurally activated nerve terminals using uptake of a peroxidase enzyme and the intensification of its reaction produce in vitro. Furthermore, I have found that peroxidase-filled processes can be viewed in living preparations by using a novel histochemical assay for the enzyme: the transformation of L-DOPA into melanin. My objectives are: (1) to combine these two techniques in order to visually identify peroxidase-filled terminals in living preparations, (2) to study the competition between axonal terminals in a unique and potentially important preparation: the transversus abdominis muscle of the garter snake, and (3) to apply these techniques to a study of the pattern of innervation on adult and developing autonomic neurons. The overall aim of this work is to better understand the developmental strategies that regulate the number and distribution of axonal contacts on postsynaptic cells.

DESCRIPTION: This work is directed at understanding the process whereby neurons sever their connections with some of the target cells they make contact with in development. Experiments indicate that the loss of connections is the consequence of a protracted competition between the synapses of different neurons vying to remain connected to the same target cell. In addition it is likely that the activity of each axon plays a role in destabilizing the connections of its competitors. Because neural activity is instrumental in the process leading to elimination of synaptic connections, the mechanisms underlying this loss may be an important part of the process whereby experience may alters the brain in a permanent way as occurs in development and in the formation of memories in adults. This proposal focuses on two simple and accessible synaptic regions that undergo the competitive loss of neuronal input--the neuromuscular junction and synapses on parasympathetic neurons. As previous work has shown that the target cell may be an intermediary in the competition between inputs, many of these studies attempt to provide a better understanding of how and why the target cell is changed during and after synaptic loss. To get a more detailed picture of the minute by minute behavior of competing axons, nerve terminals labeled in living animals will be followed over long periods as synapse loss is occurring. To see if nerve terminal activity mediates synaptic competition through the release of neurotransmitter, experiments that attempt to mimic competition with localized release of neurotransmitter in a culture dish are proposed. Lastly to see whether the mechanisms underlying the loss of synapses in muscle that has already been described is the same as the process that occurs in parasympathetic ganglia, experiments which study changes in the structure and function of soon-to-be eliminated synapses in ganglia are proposed. These results will be useful in the attainment of a full understanding of this key developmental process. Because learning disorders and memory impairments are common but at present almost entirely without rational treatment, the kind of basic information this proposal aims to provide concerning how synapses change is likely to be useful.

This program comprises a series of projects concerned with long-term changes associated with neurotransmitter receptors. Neurotransmitter receptors serve a primary function of modulating conductance changes when bound by their specific neurotransmitter. It is, however, also clear that receptors mediate a large number of longer-term changes in the cell that they are located on. These more lasting effects are of critical importance in the regulation of nerve cell function. For example, receptor number, functional characteristics, and distribution are all regulated by synaptic activity through long-term changes. The goal of our program is to learn more about the sorts of long-term changes that receptors undergo themselves and that they induce in the cell machinery around them. Half of the projects (Bridgman, Cohen, Lichtman) focus in on the most accessible and best understood neurotransmitter receptor - the nicotinic acetylcholine receptor at the neuromuscular junction. Two projects (Krause, O'Malley) concern the molecular sequelae of receptor activation. These studies address the second messenger and signal transduction pathways in two important central nervous system receptors (substance P and dopamine receptors). Finally, one project (Daw) will examine the role of postsynaptic receptors in long-term changes in an intact animal by studying the relation of the NMDA receptor to experience inducible changes in synaptic connectivity in the visual system. By recruiting individuals who work on a wide variety of preparations with a wide range of techniques, but have a common interest in the same general problem, we believe we have a unique opportunity to address some fundamental questions about long-term changes associated with neurotransmitter receptors.

bioimaging /biomedical imaging

This program comprises a series of projects concerned with long-term changes associated with neurotransmitter receptors. Neurotransmitter receptors serve a primary function of modulating conductance changes when bound by their specific neurotransmitter. It is, however, also clear that receptors mediate a large number of longer-term changes in the cell that they are located on. These more lasting effects are of critical importance in the regulation of nerve cell function. For example, receptor number, functional characteristics, and distribution are all regulated by synaptic activity through long-term changes. The goal of our program is to learn more about the sorts of long-term changes that receptors undergo themselves and that they induce in the cell machinery around them. Half of the projects (Bridgman, Cohen, Lichtman) focus in on the most accessible and best understood neurotransmitter receptor - the nicotinic acetylcholine receptor at the neuromuscular junction. Two projects (Krause, O'Malley) concern the molecular sequelae of receptor activation. These studies address the second messenger and signal transduction pathways in two important central nervous system receptors (substance P and dopamine receptors). Finally, one project (Daw) will examine the role of postsynaptic receptors in long-term changes in an intact animal by studying the relation of the NMDA receptor to experience inducible changes in synaptic connectivity in the visual system. By recruiting individuals who work on a wide variety of preparations with a wide range of techniques, but have a common interest in the same general problem, we believe we have a unique opportunity to address some fundamental questions about long-term changes associated with neurotransmitter receptors.

This is a proposal from a group of five NIH funded neuroscientists interested in understanding how the structural and functional organization of the brain arises during development and changes with experience. Because these studies examine the nervous system at the level of individual cells and their processes, they are particularly amenable to the techniques of modern optical microscopy. We are requesting funds to purchase a newly available commercial two-photon/confocal microscope system that will permit high-resolution optical images of neural preparations.For each of the proposed projects, we have found that more traditional imaging approaches has limited capabilities. Four of the five proposals center of imaging living nerve cells over time either in intact animals or in explanted neural preparations. The fifth involves thick specimens of literally priceless human tissue. Studies include the time- lapse observation of the development of GFP labeled synaptic circuits in C. elegans, following the development of axonal projects in the vertebrate optic tectum, monitoring synaptic competition at the neuromuscular junction, assaying functional alterations in the developing retina and describing changes in cortical circuitry in aging human brain samples. The range of questions and preparations being used assures that this system will provide valuable new information for many different kinds of neuroscience studies. Our microscope system will be housed in the Bakewell Neuroimaging Laboratory a shared facility immediately adjacent to three of the five main users' laboratories and near the other two investigators' labs. The device will have long-term institutional support from a special endowment to the NeuroImaging laboratory. The device will have long-term institutional support from a special endowment to the NeuroImaging laboratory. The device will be available to other members of the neuroscience community at Washington University as time permits.

The goal of these experiments is to better understand the sequence of steps that generate and remove synapses. The approach will be to use a series of transgenics mice that express various fluorescent proteins in some or all of their axons that project to muscle fibers. By using these mice with previously developed techniques that permit monitoring synapses over time in living animals, we will follow the vents that lead to the localization of synapses to a small synaptic site that contains a high density of neurotransmitter receptors. We will also attempt to understand how and why multiple axons come to converge on a signal site and what mechanisms lead to the withdrawal of all but one axon. Because different axons converging on the same muscle an expressing different colors of fluorescent proteins, we will be able to monitor over time, the competitive interactions between axons with far greater resolution than before. In addition, because we can photoconvert one fluorescently labeled axon at a junction contacted by two inputs and reconstruct in the electron microscope the fine structure of each of the competitors, we can visualize the changes that take place with greater spatial resolution than previously. Lastly, by using these approaches in mice that lack wither the post- synaptic machinery to generate synapses, or the presynaptic machinery to release neurotransmitter, we will be able to study the effects of activity and post-synaptic differentiation factors on the formation and elimination of synapses. Understanding the rules that govern formation and elimination of synapses are likely to be fundamental to understanding the mechanisms by which humans learn and remember.

imaging /visualization /scanning; biomedical facility; digital imaging; confocal scanning microscopy; developmental neurobiology; fluorescent dye /probe; fluorescence microscopy; bioimaging /biomedical imaging;

DESCRIPTION (provided by applicant): This proposal is from three NIH funded investigators interested in understanding how structural and functional organization of the nervous system arises during development and changes with experience. The studies here focus on the development of neuronal connectivity at the level of individual cells, and thus require microscopy techniques with high resolution. We are requesting funds to purchase a state-of-the-art confocal/multiphoton system that will acquire high-resolution images, and which will enable us to image neuronal structures in the living animal over days. Many of the projects in the proposal are collaborative between the three investigators. They include in vivo live imaging studies of the neuromuscular junction in development and disease (Lichtman, Sanes), studies of the development of connectivity between the retinas and its central targets (Sanes, Lichtman, Wong) and formation of synaptic circuitry in the retina (Wong, Sanes). This microscope system will be housed in the newly renovated Bakewell Neurolmaging Laboratory, a shared facility immediately adjacent to the laboratories of the three investigators. Lichtman directs the facility with day to day technical support from an engineer, S. Turney, and an experienced microscopist, D. Oakley who is in charge of the management and upkeep of the instruments and training of new users. The device will have long-term institutional support from an endowment to the Neurolmaging laboratory. It will be available to other members of the Neuroscience community at Washington University, particularly for exploring and developing new optical imaging tools.

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DESCRIPTION (provided by applicant): The nervous system undergoes disturbing changes with age. To elucidate key mechanisms underlying age-related decline in neural function, we will examine the neuromuscular system, which is very accessible, relatively simple, and the site of clinically significant age-related functional decline. Our initial analysis has led to four sets of results: 1) Neuromuscular junctions (NMJs) undergo many structural and molecular alterations as they age. 2) Preterminal portions of motor axons exhibit regions of abnormal thinning, distension and sprouting. 3) Atrophy and synaptic changes in aged muscles are correlated on a fiber-by-fiber basis. 4) Although NMJs in most muscles are ravaged by age, those in a few are spared. Here, we propose studies designed to explore the relationships among these changes, identify molecular defects that underlie them, and test one way to reverse them. First, we will follow up preliminary observation of a dramatic and specific decline in levels of three known synaptic organizing molecules at aging NMJs -laminins 4 and 2 and agrin. We will correlate changes in the levels and distribution of these proteins with structural alterations, and ask whether targeted null or conditional mutants with decreased levels of these proteins show premature synaptic aging. Second, we will seek transport defects that underlie axonal dystrophy by correlative light and electron microscopy, along with use of new transgenic mice in which mitochondria and synaptic vesicles are labeled. Third, we will determine the relationship between the synaptic abnormalities and sarcopenia, the clinically significant age-related decline in muscle mass and strength. Using transgenic mice in which single motor axons and muscle fibers of specific types are selectively labeled we will assess myogenic and neurogenic determinants of sarcopenia. Fourth, we will follow up our observation that extraocular muscles are spared from age-related neuromuscular decline. This result is intriguing because extraoculars are also spared in the invariably fatal disease, amyotrophic lateral sclerosis (ALS), suggesting parallel mechanisms underlying age-related and neurodegenerative defects. Finally, we will use transgenic rescue techniques to ask whether reintroduction of laminins or agrin attenuates age- related synaptic disorganization. Together, these studies will provide insights into age- related neural defects that may not only provide ways to ameliorate sarcopenia but also be generally applicable to the nervous system PUBLIC HEALTH RELEVANCE: The nervous system undergoes disturbing changes with age. The investigators propose to use the neuromuscular system to elucidate key mechanisms underlying age-related decline in neural function. This system is very accessible, relatively simple, and the site of clinically significant age-related functional decline. First, they will follow up preliminary observation of a dramatic and specific decline in levels of known developmentally important molecules (laminins and agrin) at aging neuromuscular junction (NMJs), the synapses made by motoneurons on muscle fibers. They will correlate changes in the levels and distribution of these proteins with structural alterations, and ask whether mutant mice with decreased levels of these proteins show premature synaptic aging. Second, they will seek defects in the transport of materials along nerve fibers to the NMJ. Third, they will determine the relationship between the synaptic abnormalities and sarcopenia, the clinically significant age-related decline in muscle mass and strength. Fourth, they will explore intriguing similarities in symptoms and muscle-specific susceptibility between neuromuscular changes in aged mice and those in the invariably fatal disease, amyotrophic lateral sclerosis (ALS). Finally, they will ask whether reintroduction of laminins or agrin attenuates age-related synaptic disorganization. Together, these studies will provide insights into age-related neural defects that may not only provide ways to ameliorate sarcopenia but also be generally applicable to the nervous system.

DESCRIPTION (provided by applicant): The organization of the human brain relies upon precise connectivity among hundreds of billions of neurons. The vast majority of these connections are established during nervous system development, when neurons find and connect to appropriate targets. To date, detailed studies of neuronal circuit development and maturation have been hampered due to technical limitations that prevent the clear visualization of many interacting neurons. New "Brainbow" transgenic mice, however, use random expression of multiple fluorescent proteins to allow for the clear identification of multiple individual components within complex neuronal circuits. These new tools greatly enhance one's ability to study neuronal connectivity and its development by allowing one to extract previously inaccessible information about specific neural circuits. Using confocal imaging methods, clear circuit diagrams can be constructed by direct visualization of the axons and dendrites of many interacting neurons throughout the nervous system. However, existing methods of image analysis are not sufficient for large Brainbow datasets, requiring new advancements in current techniques. This research proposal aims to create and utilize computer algorithms for automating the reconstruction of large neuronal datasets, and to generate new Brainbow mouse lines for improved analysis. These new tools will then be used to conduct a thorough investigation into how neuronal circuitry develops in the young cerebellum, and how cerebellar circuitry may form abnormally in an ataxic mouse model of the developmental cerebellar disease known as ataxia telangectasia. These studies will help to provide a better understanding of how neuronal circuits develop and function in the mammalian brain. PUBLIC HEALTH RELEVANCE The goal of this work is to understand how circuits form in the developing brain. There are a great deal of human disorders that arise when neurological development goes awry;a better understanding of brain circuitry can lead to appropriate treatments for disease. This research will develop new tools that will help us to understand the developmental mechanisms that lead to normal and abnormal connectivity within the brain.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The goals of this collaborative project are, first and foremost, to integrate reconstruction data taken at overlapping scales by methods being developed by the Lichtman laboratory at Harvard and by NCMIR using a similar subvolume of cerebral cortex synaptic neuropil to establish continuity of information about the wiring of a specific brain region[unreadable][unreadable][unreadable]with 3D details about presynaptic and postsynaptic microstructures. This will be done by merging information obtained by backscatter electron imaging of thin sections produced using a prototype taping lathe microtome (at Harvard) with subvolumes from serial section electron microscopic (EM) tomography (at NCMIR).

PROJECT SUMMARY (See instructions): The goal of this work is to obtain a full account of all the nerve cells providing input to, and all the nerve cells providing output from, a particular inhibitory neuron (the PV cell) in the cerebral cortex. In addition the location and number of synaptic connections will be delineated. Such a complete map of the connections to and from a neuron has not previously been attempted in the cerebral cortex. In order to do this we will need to use four different newly developed approaches that include both new optical and new electron microscopy strategies. It is my belief that it is likely that subtle changes in neural circuits may underlie abnormalities that are expressed outwardly as mental illness. Until we have methods to trace the connections at the finest level, such abnormalities will be inaccessible to scientific scrutiny. We have chosen as a first test a particularly interesting neuron that is likely to be located at pivotal regulatory point in the controlling neural wiring plasticity during development and perhaps disease. The particular goal will be to look at changes in the pattern of connections during development and in the present of certain gene deletions that are likely to be related to the way these cells function.

DESCRIPTION (provided by applicant): The overall goal of this work is to develop and validate a new suite of technologies that can rapidly and routinely generate circuit diagrams of nervous system tissue, sometimes called connectomes. The small size of neuronal processes and the synapses that connect them require that reconstruction be done at nanometer resolution; the distributed nature of neuronal connectivity requires reconstruction of large volumes, extending over a millimeter or more. Our method meets these two seemingly incompatible challenges by combining novel sectioning, electron microscopic imaging and reconstruction technologies. Together, these advances will allow us to acquire data and map circuits at least 1000-fold faster than has previously been possible. As a first test, we will reconstruct the retinal circuit of a mouse in its entirety. Enough is known about retinal structure and function to make this an appropriate tissue to validate the method. At the same time, this background will allow us to pose and solve important problems about neural circuits that will be directly applicable to the brain. We will then use the method to compare neural circuits in young adult and aged retina, providing insight into the structural basis of age-related neural decline. Finally, we will test the application of this connectomic method to human tissue. The new methods introduced here will transform neuroscience in several ways. First, it will allow elucidation of the structural underpinnings of brain function. It will also provide insight into how neural circuits are refined in early life and altered in old age. Second, applied to the ever increasing number of animal models of human behavioral disorders, it will help researchers delve into pathologies of cognition, behavior, and affect, some of which likely arise from miswiring of neural circuits. Finally, the method can be applied to any biological tissue where three-dimensional reconstruction of multiple large-volume specimens would be informative.

DESCRIPTION (provided by applicant): Broader Impacts: The project develops open-source software and publicly-accessible infrastructure for the neuroscience community to collect, curate, and analyze electron microscopy (EM) connectomes on data-intensive clusters. Public data-intensive clusters, such as our Open Connectome Project, ease the storage management burden for the experimental biologists that collect data. High-throughput imaging is already producing massive data sets that overwhelm the infrastructure and expertise of their labs. Public clusters also facilitate data sharing for secondary data studies, verification and reanalysis of existing results, and multilevel models that integrate and differentiate multiple connectomes collected from different subjects, researchers, and instruments. Data-intensive storage and analysis will transform the scientific process for EM connectome imaging. At present, experimental biologists in the life sciences collect and analyze individual, private data sets usin proprietary analysis tools. In an Open Science approach, EM connectome data are also stored remotely on a data-intensive compute cluster designed specifically for the curation and analysis of massive EM connectome data. An open-source software pipeline automatically builds data products, including spatial databases, annotations, graphs, and graph statistics. Researchers explore multiple connectomes. Innovative analysis techniques are contributed back to the community as open-source software. In the EM Open Connectome, we define frameworks to engage an interdisciplinary community of life scientists, computer scientists, and statisticians in solving two fundamental problems in EM connectomes: (1) image segmentation, annotation, and tracking and (2) graph analysis. Our approach develops the concept of alg-sourcing (algorithmic outsourcing) in which researchers can easily deploy, run, evaluate, and visualize the efficiency and accuracy of algorithms against connectome databases. The EM Open Connectome provides access to data sets and an execution framework so that researchers simply upload a script or program for one of the algorithmic tasks. Then, they get instant feedback and can visualize and analyze results remotely on the data-intensive cluster, e.g., from a laptop in a cafe. Intellectual Merit: The primary project goal is to transform the process of extracting anatomical structure from image data. Currently, this is a manual process in which few researchers explore tens of neurons [6]. The EM Open Connectome will support high-throughput, machine annotation over the largest data sets being collected. Obstacles include the accuracy and performance of computational vision algorithms, the quality of the image data, and access to software that execute these analyses. We will explore computational vision based on multi-scale aggregates with anatomical priors. We will develop image processing techniques that improve data quality prior to computational vision. We will also build a systems engineering framework to run vision algorithms that allows for rapid deployment, testing, and evaluation. The project will also enhance knowledge and understanding of the functional and computational capabilities of the brain through data-intensive analysis. Given the spatially registered machine annotations, the team will construct statistical models for brain-graphs that provide insight into neural computation. All tools and data products are publicly accessible to an Open-Science community of researchers in order to accelerate discovery through collaboration and by engaging scientists across disciplinary boundaries. Education and Outreach: Our education mission promotes data-analysis in the K-12 curriculum consistent with national benchmarks for math and sciences. We will provide online lesson plans and activities using the EM Open Connectome that directly support the materials that teachers are required to teach. We will also develop resources for the Center for Talented Youth pre-collegiate summer program. Outreach in the form of museum exhibits and a booth at the National Science Fair support our education materials and public data sets.

High-Throughput Connectomics

Connectomics is the science of mapping the connectivity between neuronal structures to help us understand how brains work. Using the analogy of astronomy, connectomics researchers wish to build 'telescopes' that will allow scientists to accurately view the brain. However, as in astronomy, the raw data collected by microtomes and electron microscopes, the instruments of connectomics, is too large to store effectively, and must be analyzed at very high computation rates. Our goal is to research, develop, and deploy a software architecture that enables high-throughput analysis of connectomics data at the speed at which it is being acquired. We will develop the first computational infrastructure to support high-throughput connectomics without human intervention. If successful, this system will allow for the first time the mapping of a cortical column of a small mammalian brain (1 cubic millimeter), and hopefully within a few years the mapping of significant sections of a mammalian cortex.

The solution to the big data problem of connectomics is a new high-throughput connectomics software architecture that we call MapRecurse. MapRecurse, named so because it bears some resemblance to the widely used MapReduce framework, will provide a unified way of specifying sequences of computational steps and validation tests to be applied to the collected data. Key to MapRecurse will be the ability to layout data and computation in a structured way that preserves locality. Using it, programmers will be able to apply fast, less accurate segmentation algorithms to low resolutions of the data in order to quickly compute a first version of the output neural network graph. Domain-specific graph theoretical methods will then check for correctness of the graph and identify areas of inconsistencies that are in need of further refinement. MapRecurse will then apply bottom-up, local processing with slower, more accurate segmentation and reconstruction algorithms to higher resolutions of the data, verifying and correcting any errors. The iterations progress recursively and in parallel across multiple cores, giving the approach its name. We believe that MapRecurse and the data structures and algorithms developed here will find applications in other high-throughput applications, such as, in astronomy, biology, social media applications, or economics.

? DESCRIPTION (provided by applicant): We propose to combine whole brain 2-photon imaging of neural activity in behaving larval zebrafish with detailed anatomical and connectivity information extracted from the same animals. The final goal is to generate quantitative models of brain wide neural circuits that explain the dynamic processing of sensory information as well as the generation of motor output by these circuits. Anatomical data will be generated by two complementary technologies: 1) whole brain EM data sets will be prepared from the same fish that were used for calcium imaging. Respective data sets will be registered to each other, functionally relevant neuronal ensembles will then be identified in the EM stacks and connectivity will be analyzed in these sub-networks via sparse reconstruction. 2) EM based connectivity information will be supplemented by trans-synaptic viral tracing technology. These two technologies for identifying synaptic connections have complementary strengths and weaknesses and are thus ideally suited for combination with in-vivo 2-photon calcium imaging studies. The specific power of this approach is that all three techniques, whole brain calcium imaging, viral tracing and EM reconstruction, can be done in the same animal. Functional, anatomical and behavioral data can then be analyzed in the context of the specific stimuli and quantified behavioral output and subsequently synthesized into a theoretical framework. To that end we will start with quantitative models of simple reflex behaviors, like the optomotor and optokinetic reflex, where the transformation of sensory input to motor output is relatively straightforward and well defined. These elementary models will serve as a scaffold that can be refined and complemented by additional data from structure function studies from fish performing in more sophisticated behavioral assays that involve more complex stimuli, different modalities and plastic changes. As such the process of building such a virtual fish will be an iterative, open ended process that requires continuous and bidirectional exchange of information between the theoretical and experimental groups of the research team.

? DESCRIPTION (provided by applicant): The goal of this project is to understand how newly born neurons integrate into existing neural circuits and change sensorimotor responses from juvenile to adult. Throughout development, the nervous system undergoes drastic changes in neuron number, neural connectivity, and neurotransmitter properties. From sensory periphery to neuromuscular junctions, circuits expand as new cellular components, differentiated from progenitors, update sensorimotor responses and adapt to changing body plans at each new life stage. A full understanding of the interplay between anatomical, functional, and behavioral changes across development, requires dynamic and structural models of complete neural circuits at different stages. To construct these models, we need to identify and perform physiological analysis of all circuit components. Because circuit function is flexible and heavily modulated by sensory feedback, we need to perform these studies in vivo in behaving animals where key sensorimotor feedback loops are intact. The nematode C. elegans is a particularly suitable model to unravel the interplay between the developing sensorimotor circuits, and the altering behavioral patterns. The genetic accessibility, known adult neural connectivity, and optical transparency of C. elegans provides an exceptional opportunity to fully dissect relationships between overall animal behaviors and the reshaping of neural circuits by the integration and rewiring of new neurons and synapses. Some C. elegans mechanosensory neurons and many motor neurons are born postembryonically, and incorporated the existing circuit during the larval development to the adult sensorimotor circuit. The adult escape response mediated by touch is one of the few behaviors where we know the complete descending pathway, from sensory input to motor output. We found that the C. elegans escape response changes during development. We hypothesize that changes in neural connectivity and integration of sub-motor circuits are required for the compound motor sequence that comprises the adult escape response. To test this hypothesis, we will use: 1) high-throughput serial-section electron microscopy and computer-aided image analysis to precisely map the C. elegans wiring diagram for escape response at each developmental stage, from juvenile larvae to adulthood; 2) quantitative behavioral analysis and optical neurophysiology, to determine the functional contribution of each circuit component to the escape response across development; and 3) optogenetic and genetic perturbation in freely behaving animals, to pinpoint the causative neural connectivities that underlie the execution, transition and developmental changes of the escape motor sequence. Our studies will unravel how neurons integrate into existing circuits with unparalleled resolution, and how new connections shape behavior throughout development. This studies not only are central to our understanding of neural circuit development, and but also has potential biomedical relevance. Cell replacement is viewed as a promising strategy for brain repair, but transplanted neurons often fail to properly integrate into pre-existing circuits. Understanding on how a complete and functioning circuit continuously integrates new components to generate adaptive behavior is critical for advancing an area of basic biology with great translational significance.

A major limitation in connectomics is that there are few tools to transform connectomic images into a minable database. The research aim of this project is to develop a suite of tools that extract essential structural parameters from the brain's physical structure that was imaged at very high (nanometer scale) resolution. The PIs will determine, by using automated methods, the sizes and shapes of neurons, synapses and their connectivity patterns. Using their tools, the PIs will analyze this detailed and varied dataset to find the key patterns within it. It is their belief that such automated methods are a requirement to comprehend the regularities and rules that govern the formation of neural circuits in the cerebral cortex, which to date have only been studied on very small sample spaces. The cerebral cortex remains perhaps the least understood aspect of mammalian biology. No studyof this magnitude of the neuronal phenotype space has ever been conducted: the dataset will contain hundreds of thousands of somata and a billion synapses, allowing the PIs to search for patterns that could only be guessed at with the tools used in prior research. Knowing what overarching organizational principles exist in a cerebral cortical network is crucial for understanding how brains work normally and how they may go awry in disease. Moreover, connectomic studies are beginning in a large number of different laboratories throughout the world focused on a wide range of species and parts of the brain. These tools should have direct applicability to many of these endeavors.

The PIs are a consortium of four laboratories with complementary areas of expertise in computer science (Shavit), systems biology (Alon), image processing (Pfister) and neurobiology (Lichtman). Together they are building a stacked set of methods that extract important parameters from connectomic images. These methods include neuron geometry extraction, network structure, motif detection, and archetypical pattern analysis. These approaches are based on two software platforms:the MapRecurse platform for generating connectome graphs and the Pareto Inference Engine for mining patterns within such graphs. The PIs will test these techniques on an a volume of mammalian cerebral cortex containing tens of thousands of cells and a billion synapses, with the aim of extracting the properties of neural circuits that would be difficult or impossible to obtain any other way. The work in this proposal will have significant impact on neuroscience. It speaks directly to the central goals of the White House BRAIN Initiative. It will provide neuroscientists with anumber of powerful and novel tools to understand the cells and circuits that underlie brain function. It should also be influential in developing approaches in machine learning and neuromorphic computing.

A companion project is being funded by the US-Israel Binational Science Foundation (BSF).

Project Summary - A realistic multiscale circuit model of the larval zebrafish brain The working group of the BRAIN initiative (BRAIN 2025, a Scientific Vision) identified ?the analysis of circuits of interacting neurons as being particularly rich in opportunity, with potential for revolutionary advances?. They further pointed out that ?truly understanding a circuit requires identifying and characterizing the component cells, defining their synaptic connections with one another, observing their dynamic patterns of activity as their circuit functions in vivo during behavior, and perturbing these patterns to test their significance. It also requires an understanding of the algorithms that govern information processing within a circuit and between interacting circuits in the brain as a whole?. We propose to generate a realistic multiscale circuit model of the larval zebrafish brain ? the multiscale virtual fish (MVF), which is well aligned with the BRAIN initiative's guidelines. The model will be based on algorithms inferred from behavioral assays and it will span spatial ranges across three levels: from the nanoscale at the synaptic level, to the microscale describing local circuits, to the macroscale brain-wide activity patterns distributed across many regions. The model will be constrained and validated by optogenetic interrogation and sparse connectomics of identified circuit elements 1? ,2?. The ultimate purpose is to explain and simulate the quantitative and qualitative nature of behavioral outputs in response to sensory inputs across various timescales, and to explore how these findings might integrate with parallel work in two other important behavioral model systems, ? the ?Drosophila larva and the rat. Our prior U01 project achieved the first instantiation of this model, whereby we successfully dissected the optomotor response (OMR)1? ?, where a larval zebrafish will turn and swim to match the direction of a whole-field visual stimulus ?3?5.? We will build on this model by achieving three further aims: First, we will expand the OMR project with four additional ethologically relevant behaviors: phototaxis, rheotaxis, escape, and hunting. We will extract the precise algorithms underlying each behavior and develop a version of the circuit model to understand their neural implementation. Second, we will further refine the model to account for multimodal integration and decision making, events that naturally happen when conflicting stimuli driving different behaviors are presented simultaneously. For example, a fish might be driven to execute a left turn by whole field motion moving to the left (OMR), while simultaneously being induced to turn right by increased brightness on its right side (phototaxis). Third, we will examine how internal brain states, such as hunger or stress, influence and modulate the specific behaviors (Aim 1) or behavioral interactions (Aim 2). Implementation of neurochemical modulation into the framework of the MVF will be achieved through simulation of highly conserved neuromodulatory neurotransmitter systems such as serotonin, acetylcholine, epinephrine and dopamine. To uncover generalizable principles of circuit design and function, we will compare our findings with those from two other model systems, the fruit fly larva and the rat. This will serve to elucidate the rules, motifs and algorithms of neural circuit function that transcend the potential idiosyncrasies of any given model.

Project 1 - A comprehensive atlas of the larval zebrafish brain - Abstract Anatomical information about the brain, such as the identity of brain regions, the molecular and morphological makeup of individual neurons and their connectivity arrangements, are all critical information for formulating hypotheses of neural circuit function. While much anatomical data concerning the zebrafish brain are being generated by the community, the field lacks a central repository which is capable of ingesting, integrating and quantitatively describing these data. To meet this need, we propose to generate a multilayered, multimodal, and multiscale atlas of the larval zebrafish brain. This project will provide the necessary infrastructure to import data from all the team members as well as the international community, integrate these data into a common reference brain, and make it publicly available and easily accessible online. This Atlas will exist at 3 levels of resolution: 1) The macro-scale, where we will define and describe the known anatomical regions of the brain, and provide new tools for regional annotation and 3D visualization. 2) The micro-scale will aggregate diverse datasets describing individual neurons in the brain. These will include: molecular makeup (through transgenic and antigenic stains - neurotransmitter, neuropeptide, neuromodulator, gene expression, etc), functional properties (through calcium and perhaps voltage imaging), morphology (through single cell imaging/tracing, and EM reconstructions) and connectivity (through functional connectivity, viral tracing, patch clamp recordings and nano-scale EM data). Finally, 3) The nano-scale, which will aggregate whole-brain serial EM volumes from multiple individual larvae. It will provide the infrastructure for collaborative nano-scale annotations, such as identified synaptic connections and high-resolution morphology. Collectively, this Atlas will be a foundational resource for zebrafish neuroscientists, and will be an invaluable tool for creating and constraining biologically plausible neural circuit models, including the Multiscale Virtual Fish.

EM Core - Abstract While the neural circuits that underlie behavior are of interest to all of the investigators on this grant (and a substantial part of the entire neuroscience community), there have been very few technical approaches that actually provide this kind of information across all levels at which circuits function, including the level of synaptic connections. This electron microscopy core is explicitly designed to provide the ?wiring diagrams? of neural circuits in an efficient way. Much of our effort over the past 5 years has been to transform serial electron microscopy of large volumes (such as the fish nervous system) from a heroic to a more mundane enterprise. This transformation required innovations in hardware and software to abbreviate all the time-consuming steps in the connectomic pipeline. In particular we: 1) automated ultra-thin sectioning (using a tape-based approach), 2) automated image acquisition (using a custom multibeam serial electron microscope), 3) automated stitching and registration of the image data on high performance computing clusters, 4) automated segmentation of neurons and synapses on a GPU cluster, and 5) semi-automated proofreading and rendering of the neural circuits with custom software. Because of these developments, we can routinely collect tens of thousands of sections losslessly at 30 nm thickness and acquire images of them at lateral resolutions of 4 x 4 nanometers. This voxel size (480 nm3? ?) provides enough detail for human or machine vision methods to trace out the finest aspects of neural connectivity. Obtaining this information about neural circuits is relevant inasmuch as it provides insight into circuit function. Hence the tremendous benefit of doing electron microscopy on functionally imaged samples - a main goal of this proposal. Acquiring these circuits is also relevant if neuronal connectivity can be associated with cells of particular types, hence the significant benefit of doing analysis of cell types that have been defined in the fish atlas associated with this proposal. Finally, these circuit diagrams provide ground truth for testing and refining computational theories of brain function, another important prong of this proposal. Because of the speed of the EM Core approaches, we have the ability to acquire datasets of many different fish that each have been used in particular experimental or live-cell imaging contexts. The overarching goal being to provide synaptic level structural information for all research questions where such detailed data can enhance our comprehension of the way fish behavior is instantiated in its nervous system.

ABSTRACT (Lichtman) It is likely that abnormalities in the number or pattern of synaptic connections (?connectopathies?) underlie neurodevelopmental and psychiatric disorders such as autism spectrum disorder and schizophrenia. But finding pathological structural motifs in brain circuitry may require sufficient resolution to analyze each synapse and identify the networks linking thousands of pre- and postsynaptic neurons together. Such high resolution volumetric structural analysis can be achieved with serial section electron microscopy, however this process has been extremely slow and labor intensive preventing the comparison of samples and analysis of volumes containing multiple neurons. To solve these problems we have devised a largely automated computer and technology intensive pipeline to overcome the principal obstacles that have to date prevented discovering structural abnormalities in brain circuits. We propose to use this suite of automated microscopy and analysis tools to reconstruct circuits in insular or prefrontal cerebral cortex from mouse, marmoset and human (cerebral organoids and actual cerebral cortex). The aims are designed to provide synaptic and circuit level information about the effects of molecular perturbations being studied by other members of our Conte team. Each of these perturbations is associated with human neuropsychiatric and neurodevelopmental disorders. In all, 10 experimental brain tissues and their controls will be analyzed. We will take a structural inventory for a full thickness of cerebral cortex determining among other things: the number and types of neurons; the number and types of synapses; the synaptic vesicle numbers per synapse, mitochondrial numbers and densities per synapse; and sizes of active zones, dendritic spine number, density and size. In addition we will itemize the glial cell types, their prevalence, and look for differences is glial cell structure. All of these approaches have been used previously by us. Finally we will reconstruct circuits using a seed cell approach that we have also previously developed. It is our hope that providing this kind of detailed synaptic and connectional information for many abnormal and control tissue will help focus research on the sites of physical abnormality in diseases that to date have little in the way structural underpinnings.

High-resolution analysis of the brain's connectivity, which reveals the actual wiring diagram connecting nerve cells of the brain, provides insights unattainable any other way into the way the healthy brain works and what goes awry in diseases and disorders of the nervous system. The primary challenge of this approach is that at present there are no reliable, robust and powerful computer-based techniques to analyze the extraordinarily large and vastly complicated networks of brain cells to detect connectional motifs in their highly branching and connected structure. Nor are there visualization tools that allow neuroscientists to explore the brain network patterns effectively. This work will analyze large brain networks from electron microscopy datasets in young and old mammalian brain samples. These data sets each contains hundreds of thousands of nerve cells and billions of synapses that interconnect them. The proposal aims to develop new methods and tools to analyze these vast brain networks at the synapse, motif, and network levels. If successful, the project will provide data and analysis tools for the development of new theories of how the brain works.

Recent advances in image acquisition using multi-beam serial-section electron microscopy (sSEM) and automated segmentation methods have enabled data collection for large tissue samples in a variety of animals. These data will be used to curate large-scale datasets with one million labeled synapses with synaptic cleft locations, pre- and postsynaptic polarity predictions, and excitatory and inhibitory type predictions. This has not been accomplished previously given the enormous amount of data. The aim is to discover synaptic motifs by subdividing complex neural networks into quantifiable and meaningful subgraphs. Automatic generation of candidates for motifs will be created by developing an efficient neurite-centric wiring-diagram reconstruction method and subgraph detection algorithm to find common patterns. These data will be used to quantify and compare reconstructed neural networks from different specimens at different spatial and temporal scales and build a visualization platform to assist neuroscientists to analyze these networks as they seek to ask and answer fundamental questions related to neural circuits in the brain.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

The goal of this proposal is to disseminate high resolution large volume serial section electron microscopy data to neuroscientists. Using our electron microscopy facility, we will provide user training on the use of these new technologies and provide access to our specialized facilities so that they may generate permanent ultrathin sections and create data sets amenable for neural circuit analysis or neural and glial cell type analysis. We will make minor improvements in our software to increase the scale and efficiency of user data production to meet the needs of a user community that are inexperienced in these approaches. This project addresses compelling needs of neuroscience researchers who work on the first high priority goal of the BRAIN 2025 report: ?Mapping the Structure and Components of Circuits? by providing them access to tools that are otherwise unavailable or impractical in their current form.

The field of connectomics aims to reconstruct the wiring diagram of neurons and synapses at nanometer resolution to enable new insights into the workings of the brain. Recent advances in image acquisition and machine learning methods have yielded complete reconstructions of neural connectivity of large tissue samples. The investigators have one such dataset from a human brain tissue consisting of two petabytes of raw image data from electron microscopy. In collaboration with Google, they have spent the past two years reconstructing the complete 3D shape of about 50,000 cells, including 18,000 neurons, and identifying about 133 million synapses. This data will enable them to examine the prototypes of various neuron shapes, the correlations between these neuron types and their internal structures, and how they are connected to each other. This will be done in a dataset that is orders of magnitude larger than previous brain samples. These dense brain reconstruction results come with complex spatial and network structures, posing new challenges for scientists who wish to explore and analyze such data. The proposed program will develop a scalable visual analytics system that allows researchers to generate novel data-driven hypotheses from the petabyte-scale connectomics data.

This three-year project aims to build novel visual analytics tools and efficient deep learning methods to advance the field of connectomics. Project deliverables will empower neuroscientists to analyze large brain networks in a one cubic millimeter volume containing tens of thousands of neurons and hundreds of millions of synaptic connections. The project aims to analyze the brain at the neuron level and network level. It will investigate scalable visual analytics methods for the comparison of morphological features and analysis of spatial distributions and proximity of cell organelles. The network-level analysis will be supported, from local synaptic network motifs to larger-scale connectivity patterns of different cortical layers. A tightly integrated targeted proofreading/analysis loop will be developed, using techniques from machine learning for automatic error suggestion and guidance of the proofreading process to obtain high-quality data with minimal user interaction. To support intuitive hypothesis generation based on the data-driven visual analysis, an intuitive domain-specific query framework and investigate methods for automatic user guidance and hypothesis suggestion will be designed. Ultimately, this project will provide data and analysis tools to develop new theories of how the brain works.

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

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.