David W. Tank - US grants

Project Summary: Plasticity of Neural Integrator Dynamics

The oculomotor neural integrator converts brief input signals for rapid eye movements into sustained patterns of neural activity that maintain tension in eye muscles to hold the eye at a fixed angular position. The leading candidate mechanism for the production of this sustained activity is re-excitation of neurons through recurrent feedback loops, a mechanism that requires precise tuning of the amount of positive feedback for proper operation. Normally, visual signals produce the appropriate amount of tuning by changing the properties of the sustained activity in the neural integrator. Experimentally, the plasticity will be artificially controlled by a training paradigm consisting of a visual pattern rotating with an angular velocity dynamically controlled in real time by eye position. Optimal training protocols will be established and changes in the properties of neurons in the neural integrator will be quantitatively measured. These data will be used to incorporate learning rules into theoretical recurrent neural network models of the neural integrator. The conversion of a transient input into a sustained neural output is a form of short term memory that is widely observed in the nervous system. Thus better understanding of the role tuning mechanisms contribute to neural integrator function should have broader significance in neurobiology.

[unreadable] DESCRIPTION (provided by applicant): The long-range goal of this research is to identify the cellular and circuit mechanisms responsible for persistent neural activity: a sustained change in sodium action potential firing related to short-term memory. Our collaborative research program combines experimental and theoretical studies of the oculomotor integrator, where persistent neural activity is related to a short-term memory of the current eye position. The experimental preparation is the goldfish, which is particularly advantageous for a cellular and computational analysis of mechanisms. [unreadable] Persistent neural activity in awake goldfish will be measured and perturbed by intracellular recording to test hypothetical cellular mechanisms of persistent activity. The intrinsic and synaptic conductances of integrator neurons will be studied in vitro, and a numerical model will be constructed from the results. Synaptic connectivity will be determined by intracellular fills in vivo and dual recording in vitro, and incorporated into a network of conductance based model neurons. The effects of pharmacological reagents on behavior and neural activity will be compared with model predictions. The properties of correlated neural activity will be measured with microelectrode recordings and compared with network models. Finally, the physiological properties of integrator neuron dendrites will be studied in vivo using two photon laser scanning microscopy. [unreadable] There are several reasons why the proposed research should have broad significance for neuroscience. Firstly, the concept of a neural integrator is a very general idea in motor control and many other neural integrators have been proposed. Secondly, transient inputs or commands cause sustained changes in neural firing in many brain areas. The leading theoretical models of this persistent neural activity are recurrent networks in which the sustained activity is produced by net positive feedback, the same mechanism studied in our network models of the oculomotor integrator. Many of the hypotheses in this proposal are generic to recurrent networks; hence the results of testing them may shed light on the function of other brain areas showing persistent neural activity. Persistent neural activity has consistently been observed in brain areas important in short-term memory, a central component of many cognitive abilities. Some mental disorders, such as schizophrenia, may involve deficits in short-term memory. [unreadable] [unreadable]

[unreadable] DESCRIPTION (provided by applicant): This proposal is for a training program in Quantitative and Computational Neuroscience (QCN) at Princeton University (R90 undergraduate and non-NRSA predoctoral; T90 NRSA predoctoral). The way neuroscience research is carried out is rapidly changing and becoming much more dependent on, and engaged with, the physical, mathematical and information sciences. New technologies are providing data of unprecedented complexity and scale. fMRI and MEG map activated regions of the human brain with increasing resolution and temporal precision, while multi-electrode recording and optical imaging using voltage and calcium sensors provide detailed information on the spatial patterns of electrochemical activities in neural circuits and single neurons. Increasingly, the questions addressed with these technologies are systems level questions that concern the interactions of many components in networks. How sensory and motor information is represented across the activity of a population of neurons, how working memory and decisions are implemented in neural circuits, and how interacting biochemical pathways in a single synapse can coordinate plasticity and growth are all examples of contemporary network questions in neuroscience. As the focus of neuroscience has evolved to encompass more systems-level functions involving the interplay among large assemblies of interacting elements, the need for more sophisticated mathematical and computational tools has become more acute, both to quantitatively analyze data and to define and test theoretical models. Our training program will address these changes and challenges by providing undergraduate and pre-doctoral instruction in a combined curriculum of formal theoretical techniques and computational methods on the one hand and hands-on inquiry-based project labs and laboratory rotations on the other. Our emphasis is on the interplay of theory and experiment in neuroscience research and how sophisticated analysis techniques can be used to exploit the most advanced instrumentation, in attacking important neuroscience questions. This program will be a cornerstone of Princeton's new Neurosciences Institute emphasizing neural coding and dynamics, and it will bring together faculty from Psychology, Biology, Physics, Chemistry, Engineering and other disciplines to provide a directed curriculum with cutting- edge technology for empowering future neuroscientists with quantitative methods. [unreadable] [unreadable] [unreadable]

DESCRIPTION (provided by applicant): This proposal is for a training program in Quantitative and Computational Neuroscience (QCN) at Princeton University (R90 undergraduate and non-NRSA predoctoral;T90 NRSA predoctoral). The way neuroscience research is carried out is rapidly changing and becoming much more dependent on, and engaged with, the physical, mathematical and information sciences. New technologies are providing data of unprecedented complexity and scale. fMRI and MEG map activated regions of the human brain with increasing resolution and temporal precision, while multi-electrode recording and optical imaging using voltage and calcium sensors provide detailed information on the spatial patterns of electrochemical activities in neural circuits and single neurons. Increasingly, the questions addressed with these technologies are systems level questions that concern the interactions of many components in networks. How sensory and motor information is represented across the activity of a population of neurons, how working memory and decisions are implemented in neural circuits, and how interacting biochemical pathways in a single synapse can coordinate plasticity and growth are all examples of contemporary network questions in neuroscience. As the focus of neuroscience has evolved to encompass more systems-level functions involving the interplay among large assemblies of interacting elements, the need for more sophisticated mathematical and computational tools has become more acute, both to quantitatively analyze data and to define and test theoretical models. Our training program will address these changes and challenges by providing undergraduate and pre-doctoral instruction in a combined curriculum of formal theoretical techniques and computational methods on the one hand and hands-on inquiry-based project labs and laboratory rotations on the other. Our emphasis is on the interplay of theory and experiment in neuroscience research and how sophisticated analysis techniques can be used to exploit the most advanced instrumentation, in attacking important neuroscience questions. This program will be a cornerstone of Princeton's new Neurosciences Institute emphasizing neural coding and dynamics, and it will bring together faculty from Psychology, Biology, Physics, Chemistry, Engineering and other disciplines to provide a directed curriculum with cutting- edge technology for empowering future neuroscientists with quantitative methods.

[unreadable] DESCRIPTION (provided by applicant): Humans and other animals possess neural integrators, brain modules specialized for performing the mathematical operation of integrating a time-varying signal. This computation is important for certain behaviors such as motor control, navigation, and decision making. Transient stimuli to neural integrators produce sustained changes in rate of action potential discharge that persist for up to tens of seconds. Our past research suggests that this persistent neural activity, a correlate of the integrator's memory, is supported by both cellular and circuit mechanisms acting in concert. Our long-range goal is to understand the exact nature of these mechanisms through a collaborative research program combining experimental and theoretical studies of the goldfish oculomotor integrator. To more precisely localize the integrator, intracellular electrodes will be used in vivo to precisely stimulate and inhibit single neurons while extracellular recording methods are used to monitor the effects on other neurons in the circuit. The possibility that vestibular nuclei are part of the integrator will be tested using local pharmacological inactivation. Serial section electron microscopy, and paired recording in a novel in vitro preparation, will be used to improve our understanding of the synaptic connectivity of integrator neurons. Specific hypothesized cellular mechanisms of persistence will be tested using two-photon calcium imaging of dendrites. This information will be used to construct improved hybrid models of the integrator, incorporating dendritic biophysics as well as realistic synaptic connectivity. The role of the cerebellum in a recently discovered form of integrator plasticity will be tested by extracellular recording methods. Models of integrator plasticity based on synaptic learning rules will be developed. The proposed research should have broad significance for neuroscience. Persistent neural activity has been observed in many brain areas, not just in neural integrators, and therefore its mechanisms are of very general interest. Integration can be regarded as the simplest form of working memory, the ability to store information and actively manipulate it. Therefore, understanding how neurons integrate could shed light on how working memory is implemented by the brain. Many of the hypotheses in this proposal are generic to hypothesized circuit and cellular mechanisms of persistence in other brain areas; hence the results of testing them may be relevant to persistent neural activity in general. Health Relatedness: Persistent neural activity has consistently been observed in brain areas important in working memory, a central component of many cognitive abilities. Some mental disorders, such as schizophrenia, may involve deficits in working memory and neural integrators. [unreadable] [unreadable] [unreadable]

DESCRIPTION (provided by applicant): This proposal is to develop methods and instrumentation for the simultaneous imaging and optical stimulation of activity in large populations of neurons in the awake mouse brain under conditions in which the mouse is free to navigate in a virtual environment, a capability with wide application in systems neuroscience. The enabling technology is an apparatus that facilitates high-resolution optical imaging at cellular resolution while minimizing brain motion. It is based on an upright table mounted two-photon microscope mounted over a spherical treadmill consisting of a large air supported ball. Mice, with implanted cranial windows designed to reduce brain motion, can walk and run on the surface of the ball during imaging while their head remains motionless. Image sequences demonstrate that movement-associated brain motion is limited to ~2-5 um and that this motion is predominantly in the focal plane, with little out-of-plane motion, providing the conditions for an offline Hidden Markov Model based software method for removing residual motion artifacts. Pilot data using a first generation instrument demonstrate that behaviorally correlated calcium transients from large neuronal and astrocytic populations can be routinely imaged at cellular resolution in awake mice, even during walking and running. The proposed research and development program will further validate and optimize the methods used in the first generation instrument, and extend its capabilities by adding real-time motion correction, new chambers and lenses for imaging of deeper brain structures such as the hippocampus, and the incorporation of a visual virtual reality display system controlled by the running behavior of the mouse. An additional thrust will focus on using pulse time-multiplexing and a multi-focal plane optical design to provide simultaneous imaging and two-photon based photo-stimulation using channelrhodopsin. The scientific questions in systems neuroscience that can be addressed using the instrumentation to be developed are some of the most fundamental ones about how the brain works, ranging from determining the number of active, versus silent, neurons during a specific behavior, to the importance of synchrony and correlation in perception, memory, and motor control. The ability to image the activity in entire populations of neurons at cellular resolution in mice navigating in a virtual environment will facilitate mapping the micron-scale spatial architecture and circuit connectivity of place cells in the hippocampus and grid cells in the cortex. This study will develop an imaging method to measure the chemical processes in many individual neurons simultaneously in the brain while it is operating in the awake state. This capability would be valuable in comparing normal and diseased states in the brain. The methods developed will be applicable to the mouse, which is the leading mammalian genetic model system in health research. In addition to measuring chemical processes, the methods will also provide the ability to stimulate a specific population of neurons, which is important both in determining basic mechanisms of brain function and in evaluating new methods for neural prostheses.

Description (provided by applicant): This application addresses broad Challenge Area 06: Enabling Technologies. The specific Challenge Topic is 06-NS-103: Breakthrough Technologies in Neuroscience. Virtual reality (VR) is a technology that allows a user to interact with a computer- simulated environment. The environment can represent a simulation of the real world or an imaginary world that can be modified in real time to provide a novel probe of cognition. Widely used in human behavior and neuro-imaging experiments, we now propose to bring this technology to bear on diverse areas in the study of neural circuits at cellular resolution in rodents. We will develop VR instrumentation and software that can work in a synergistic way with both in vivo two photon laser scanning microscopy and in vivo whole cell patch recording to provide new capabilities in systems neuroscience. The technology revolves around the use of head-restrained rodents walking and running on the surface of a levitated sphere. We have recently demonstrated that this spherical treadmill can be used with two-photon laser scanning microscopy to provide measurements of calcium transients at cellular resolution from populations (~100) of cortical neurons in awake, mobile, mice. To add visual VR capability, a toroidal screen that spans the rodent visual field surrounds the ball. This screen displays a projected computer generated image that has been geometrically transformed to provide a realistic image of the virtual environment from the mouse's perspective. Sensors that detect the motion of the ball produced by movements of the subject provide a control signal to a computer for both turning and forward motion within the environment. Recently completed pilot experiments using this apparatus demonstrate that mice, in an instrumental conditioning paradigm, learn to navigate in virtual arenas and mazes for water rewards. Single unit recordings demonstrate place cells in the virtual environments. Furthermore, the system provides the capability to apply in vivo whole cell intracellular recording methods during navigation and the first intracellular recordings of place cells are demonstrated. By combining VR with two-photon imaging, the capability for monitoring populations of hippocampal pyramidal cells during navigation is also demonstrated. Based on these results, a team of investigators working in diverse areas of neuroscience will work together to expand the development of VR systems for rodents as a new breakthrough technology. First, we will develop improved displays, spherical treadmills, motion sensors, and visual VR software based on experience with the first generation system. This will improve the performance of the existing visual VR system in general and also allow it to be easily adopted by the wider neuroscience community. VR environments for the characterization of place cells and grid cells will be constructed and the characteristics of these cells will be compared to that observed in real environments. Second, we will develop a spherical treadmill and associated instrumentation for head restrained rat VR, a species widely used in studies of navigation and, more recently, executive control. Third, we will develop instrumentation for adding new sensory modalities and feedback capabilities. VR-controlled olfactory and auditory stimuli will be developed. For studies of the role of the cerebellum in motor control, a computer-controlled resistance treadmill will be developed that provides proprioceptive feedback in real-time. In all cases, the VR instrumentation will be optimized for use with in vivo two-photon laser scanning microscopy and whole cell intracellular patch recording. When completed, the suite of new instrumentation will provide the systems neuroscience community with new capabilities for cellular analysis of circuits in awake behaving rodents. This study will develop virtual reality systems for use in neuroscience research. The system will enable the measure of electrical and chemical processes in one or many individual neurons in the brain while the subject is navigating in a virtual environment. This capability would be valuable in comparing normal and diseased states in the brain. The methods developed will be applicable to the mouse, which is the leading mammalian genetic model in health research. It will also be developed for the rat, a species widely used in behavioral studies.

DESCRIPTION (provided by applicant): The medial entorhinal cortex (MEC) contributes to navigation and episodic memory, essential cognitive functions degraded in many degenerative and psychiatric disorders. A key to MEC function was provided by the discovery of grid cells, which fire on the vertices of a set of hexagonal lattices tessellating space. The grid cell system has been hypothesized to perform path integration during navigation and to be a map of the spatial environment. Because of the striking regularity of their firing fields, grid cells have generated widespread theoretical interest, and numerous models have been proposed to explain how grids are formed, how they are organized in microcircuits, and how they might use idiothetic (self motion) information to path integrate. The grid cell system therefore offers the opportunity to study a cognitively meaningful neural computation at a mechanistic level. Here we leverage recent technical advances, including virtual reality methods for rodents previously developed in our lab, to examine the intracellular, microcircuit, and integrative properties of gri cells in three aims: 1.) Current grid cell models can reproduce hexagonal lattice firing patterns but they predict different intracellular membrane potential time courses that reflect different underlying cellular or network mechanisms. To test these predictions, in Aim 1, we will take advantage of head-fixed navigation enabled by our virtual reality system to make intracellular recordings from grid cells during behavior. Statistical analysis will be performed on the membrane voltage time series to examine if characteristic features such as ramps and theta oscillations are present and if they correlate with the location of the firing fields. For example,we will examine if theta oscillation amplitude is larger in firing fields, and if theta frequency increases with mouse velocity, as predicted by theta interference models of grid cells. 2.) Grid cells are not identical, but have different scales and phase shifts that may reflect distinct functional modules. Consistent with this idea, converging evidence points to the existence of anatomically defined clusters of cells in MEC. To delineate the link between functional modules and anatomical clusters, in Aim 2 we will use cellular-resolution two-photon calcium imaging during virtual navigation to provide the first measurements of spatial organization, at the microcircuit scale, of identified grid cells in MEC. In particular, we will map the relationship between grid cell properties (spatial scale and phase) and cytochrome oxidase rich patches, and determine whether there are sharp breaks in spatial scale along the dorsoventral axis. 3.) Grid cells are thought to perform path integration, an idea that dominates the current thinking about the functional role of the MEC. In Aim 3 we will use virtual reality to control all sensory cues providing information about position in order to rigorously test the path integration hypothesis. Together, these aims should advance our understanding of the single-cell, microcircuit, and computational properties of grid cells.

DESCRIPTION (provided by applicant): We propose to combine technologies for in vivo imaging with automated rat behavioral training systems. This will create a transformative technology platform that will enable the first cellular resolution imaging of neural activity durin complex cognitive tasks. Cellular-resolution functional imaging using genetically encoded calcium sensors enables recording the neural activity of the entire neuronal population within a field of view. Each functionally characterized neuron can be precisely pinpointed in space and recorded over multiple weeks. Achieving such high-resolution imaging during complex cognitive tasks will provide an unprecedentedly comprehensive and detailed view of neural circuit dynamics involved in higher cognition. Rats are the simplest vertebrate species that have been trained to perform behaviors that demand executive function, exemplified by a task requiring the ability to rapidly select and implement goal-directed sensorimotor rules. To characterize the neural circuitry underlying executive function and other higher cognitive abilities, we will develo a system for cellular resolution imaging in awake behaving rats. This will require methods to stabilize brain movements during imaging. In Aim 1 we describe a new method for brain stabilization, inspired by kinematic mounts used to precisely align optical components. The new device will be deployed so that trained rats will voluntarily and repeatedly activate the brain stabilization device over hundreds of trials within each session. The device will be integrated into a semi-automated training facility, which will be used to train rats on complex tasks such as rapid rule-switching. In Aim 2 we will augment the training system with a custom automated two-photon microscope. We will develop implantable optics that minimize brain motion while allowing a clear optical path to the cortical surface. Together with the training system, these devices will be used to record calcium dependent fluorescence transients in neurons from the rat frontal cortex while rats perform cognitive tasks.

? DESCRIPTION (provided by applicant): Working memory, the ability to temporarily hold multiple pieces of information for mental manipulation, is central to virtually all cognitive abiliies. Working memory has been closely associated with multiple kinds of neural activity dynamics, such as persistent neural activity, activity ramps, and activity sequences. The neural circuit mechanisms of these dynamics remain unclear. This proposal will apply advanced technologies such as virtual reality, automated monitoring of behavior, in vivo microscopy, ontogenetic, and neural circuit reconstruction to solve fundamental problems in the understanding of working memory. The accumulation of evidence over time scales of seconds, a type of working memory critical for decision-making, will be used as a test bed for studying working memory. The proposal will build upon a rodent evidence-accumulation paradigm that allows quantitative, temporally precise parameterization of working memory and decision-making. The paradigm will be implemented with head-fixed rodents behaving in a virtual reality system (Aim 1), providing mechanical stability that enables the use of two-photon calcium imaging to observe neural activity related to working memory in the neocortex, basal ganglia, and cerebellum (Aim 3). Brain activity will also be perturbed using ontogenetic to probe the roles of brain regions and specific cell types in the formation and stabilization of memory (Aim 2). Finally, we will develop methods for probing the roles of cell types and connectivity in working memory through correlative serial electron microscopy and light microscopy as well as imaging of population responses to ontogenetic stimulation of single cells or groups of cells (Aim 4). This three-year project will produce a catalog of the types of neural circuit dynamics that are related to working memory across many brain regions. In subsequent years, this catalog will be mechanistically investigated by the anatomical and physiological methods developed in Aim 4. The long-term goal of this project is to arrive at a complete, brain-wide understanding of the cellular and circut mechanisms of activity dynamics related to working memory. The understanding is expected to take the form of a new generation of models containing cognitive variables distributed across brain regions, as well as models that explicitly represent neural circuit dynamics. This achievement will be a crucial step towards a mechanistic understanding of the neural basis of cognition.

DESCRIPTION (provided by applicant): A fundamental goal of neuroscience is to understand the cellular and network mechanisms of neural circuit dynamics that give rise to cognition and behavior. Such a mechanistic picture would significantly enhance our ability to understand and potentially address the cellular and circuit dysfunctions that underlie psychiatric and neurologica disorders, including schizophrenia, epilepsy, and autism. To achieve this understanding, new tools are needed that can measure and perturb neural activity, at cellular and subcellular resolution, in a wide range of neural populations during behavior. Work in this renewal proposal addresses this need by enhancing the capabilities of a powerful set of optical and behavioral instrumentation and methods, developed in the PI's laboratory during the past funding period, for head-restrained mice navigating in virtual reality. When implemented, our proposed aims will provide several new capabilities. First, it will be possible to not only measure, but also experimentally manipulate, specific patterns of neural activity during ongoing behavior by using simultaneous imaging and cellular-resolution optogenetic stimulation in mice navigating in virtual reality (VR). The system will be applied to study synaptic inputs and plasticity underlying place-cell firing patterns in the hippocampus. This capability could also form a general-purpose method for mapping functional connectivity between neurons whose firing properties have been characterized during behavior. Second, it will be possible to apply cellular resolution optical methods in a number of widely studied deep brain regions that are optically inaccessible using current techniques, including medial prefrontal cortex. In addition, our methods will make it possible to image multiple hippocampal areas simultaneously, together spanning the entire hippocampal circuit from input to output. Third, it will be possible to optically measure the dynamics of neuromodulatory inputs within functioning microcircuits, as well as to measure the activity of synaptic inputs to functionally identified neurons during behavior. This will enable direct tests of hypotheses about the contributions these inputs make to cellular and circuit computations. As a first application, we will measure dopaminergic inputs to medial prefrontal cortex at fine spatio-temporal resolution during learning. We will also measure the spatial firing properties of synaptic inputs to hippocampal place cells during virtual navigation. In general, the new capabilities will provide an improved means to discover and characterize the cellular and network mechanisms that underlie neural coding and dynamics.

Project Summary Working memory, the ability to temporarily hold multiple pieces of information in mind for manipulation, is central to virtually all cognitive abilities. R? ecent technical advances have opened an unprecedented opportunity to comprehensively dissect the neural circuit mechanisms of this ability across multiple brain areas. The task to be studied is a common form of decision-making that is based on the gradual accumulation of sensory evidence and thus relies on working memory. ?A team of leading experts propose to investigate the neural basis of this behavior using the latest techniques, including virtual reality, high-throughput automated behavioral training, l? arge-scale cellular-resolution imaging ?in behaving rodents, manipulation of neural activity in specific brain areas and cell types, and a? utomated anatomical reconstruction?. In particular, the researchers will i? dentify key brain regions that are required for this decision task through systematic, temporally specific inactivations via optogenetics technology, across all of dorsal cortex and in key subcortical areas, and use quantitative model-fitting to evaluate the effects. They will use state-of-the-art ?two-photon calcium imaging? methods and electrophysiology to characterize the information flow in many individual neurons within these brain areas during the task. In addition, they will use cutting-edge anatomical reconstructions and new functional connectivity methods, within and across brain regions, to evaluate the interactions of these physiologically characterized neurons. ?The long-term goal of this project is to arrive at a complete, brain-wide understanding of the cellular and circuit mechanisms of activity dynamics related to working memory. ?Finally, they will use sophisticated computational methods to incorporate this new understanding into a realistic circuit model that will support a tightly integrated process of model-guided experimental design, in which the model suggests the most informative experiments and their results are then fed back to improve the model?s fidelity. ?This process is expected to produce? the most accurate and detailed multi-brain-region biophysical circuit model of a cognitive process in existence?. ?In addition, the proposed research will enable researchers to generate and test a variety of hypotheses about the neural basis of evidence accumulation, working memory, and decision-making. Taken together, these achievements will represent a crucial step toward a mechanistic understanding of how the brain works with information.

Project Summary: Core 5, Optical Instrumentation Working memory, the ability to temporarily hold multiple pieces of information in mind for manipulation, is central to virtually all cognitive abilities. This multi-component research project aims to comprehensively dissect the neural circuit mechanisms of this ability across multiple brain areas. Our projects have been designed to take full advantage of new optics-based technologies developed in the BRAIN Initiative. It is imperative that we continue to innovate and upgrade our instrumentation and methods as the cutting edge of the field moves forward. The Optical Instrumentation Core will develop, implement, and support the optical microscopes and other optics-based instrumentation used in our projects to ensure that they represent the best of the new technologies. To do so, we will leverage the technical and engineering expertise in Princeton?s Bezos Center for Neural Circuit Dynamics and recruit additional staff devoted to constructing and maintaining our state-of-the-art instruments. Our projects depend on the latest technology for two- and three-photon calcium imaging at cellular resolution, laser-based optogenetic perturbation systems combined with simultaneous imaging, and novel forms of widefield microscopy. Some of this instrumentation is based on recent innovations in the labs of our PIs. In other cases, we will collaborate with colleagues at other institutions who have developed innovative new methods. Creating an Optical Instrumentation Core will address the problem that much of the technical work required to innovate and maintain these instruments has shifted to students and postdocs, because it has exceeded the capacity of existing staff. This division of labor is a problem for four reasons: (1) lab personnel often do not have sufficient time or expertise to produce the best possible results, (2) the diffusion of responsibility leads people to duplicate one another?s efforts, (3) researchers spend their time on technical work at the expense of doing science, and (4) expertise can be lost as students and postdocs move on. For all these reasons, we propose to standardize this function across projects to improve quality control and efficiency. Centralizing the design, construction, maintenance, and support of these instruments will increase the efficiency and rigor of our microscopy experiments, while freeing lab personnel to focus on designing experiments and collecting data.

Project Summary: Project 2, Neural Coding and Dynamics in Neocortical Regions Working memory, the ability to temporarily hold multiple pieces of information in mind for manipulation, is central to virtually all cognitive abilities. This multi-component research project aims to comprehensively dissect the neural circuit mechanisms of this ability during a working memory and decision task based on accumulation of sensory evidence. Inactivation experiments in another component of the project will identify participating brain areas and their particular roles in such tasks. The goal of this project is to characterize the neural coding and dynamics in the neocortical brain areas found to have a causal role in the behavior. Initial inactivation results suggest that much of neocortex is involved. Thus, the project will produce a broad survey of neocortex using cellular-resolution calcium imaging with the most advanced optical-imaging technology, like the mesoscope. The results of this survey will be a dataset, unprecedented in the field of working memory and decision-making, that will greatly illuminate the nature of each region?s potential contributions and their computations. In parallel, neocortical dynamics will be measured with cell-type specificity, starting with populations of inhibitory neurons. Preliminary data shows choice-specific sequences and cue-locked cells in neocortical pyramidal neurons in six brain regions during an evidence-accumulation task involving navigation in virtual reality, but it is unclear whether these kinds of activity are specific to preliminary experiments or will generalize to diverse evidence-accumulation behaviors. To address this question, researchers will apply two-photon, cellular-resolution calcium imaging during other evidence-accumulation tasks, to explore the dependence on species (rat vs. mouse), behavioral readout (T-maze navigation vs. orienting vs. right/left licking), or sensory modality (towers, light flashes, airpuffs). The survey of neocortical activity at cellular resolution will be done one or a few areas at a time. Finally, the project will use widefield imaging fluorescence macroscopes, including a novel head-mounted version, for simultaneous imaging of all dorsal cortical areas during evidence-accumulation tasks. The maps will identify, for the first time, the simultaneously acquired spatial and temporal structure of region activation across the neocortical surface during an evidence-accumulation task in rodents. Based on the preliminary data, this work, along with the imaging results obtained in another project component, is expected to produce the most detailed information available to date on brain-wide activity, at cellular resolution, during performance of a cognitive task. Ultimately, these results will be used, in conjunction with perturbation and interaction data from other parts of the project, to develop and constrain biophysically realistic models of the neural mechanisms underlying working memory and decision-making across multiple brain areas.