Loren Frank - US grants

DESCRIPTION (provided by applicant): The hippocampal formation is essential for the storage of certain types of memories, including memories for facts and events in humans and memories for space in rodents. Understanding the role of the hippocampus in learning is a complex problem, in part because the hippocampus is not a single region but is instead made of up several areas, including the entorhinal cortex (EC), dentate gyrus (DG), CA3, CA1 and the subiculum, each of which may play a unique role in this process. In addition, learning is itself a complex phenomenon involving multiple behavioral and cognitive components. The challenge, then, is to go beyond the shorthand of discussing the hippocampus and learning and instead begin to examine the role of each area within the hippocampal circuit in the learning and representation of complex tasks. For spatial tasks we must recognize that there are multiple components to learning, including learning about the specific spatial locations as well as learning about the structure of the cognitive task. Learning about space and learning about task could occur in the same regions, or could occur at very different sites in the circuit. One of our major goals is to explore the neural bases of both spatial and task-related learning. We will use behavioral, electrophysiological and advanced analytical techniques to identify the nature of spatial and task-related neural activity and plasticity across the hippocampal circuit. The Specific Aims of this proposal are 1) To test the hypothesis that during learning, plasticity in the hippocampal formation changes the place and theta related responses of hippocampal neurons, 2) To test the hypothesis that each region within the hippocampal formation shows a distinct pattern of neural dynamics associated with the formation of new spatial representations, 3) To test the hypothesis that each region within the hippocampal formation shows a distinct pattern of neural dynamics associated with the encoding of task related information. Our overarching hypothesis is that the formation of new representations in the hippocampus is an incremental process, where representations are quickly established in the input and output regions and then elaborated as a result of processing within the circuit. This work will go beyond previous studies to examine the neural dynamics that underlie learning about new places and new tasks. Understanding how the hippocampus participates in learning may help us develop new strategies for treating people with mental impairments related to hippocampal dysfunction, including individuals suffering from schizophrenia as well as children and adults with learning impairments. The study of plasticity in the hippocampal circuit may also help us understand disorders related to abnormal plasticity such as epilepsy.

DESCRIPTION (provided by applicant): While great advances have been made in understanding the mechanisms of learning in the single synapse or cell, a large gap remains between this understanding and our knowledge of learning at the behavioral level. We know that the activity of large-scale neuronal circuits gives rise to behavior, yet we have little knowledge of what changes in those circuits during learning or how sensory feedback drives these changes. The biggest impediment to answering these questions is the inability to quantitatively measure large-scale circuit properties (e.g. connectivity between brain areas) or to precisely manipulate the activity patterns across these circuits. Optogenetics offers the potential to bridge this gap by allowing the direct control of neural activation in targeted cell types on the millisecond timescale. The development of these tools is progressing most rapidly in mouse, due to the relative ease of genetic manipulations in that species. In contrast, behavioral and circuit-level studies of learning are most practical and have been most successful in "non-genetic" species. Within our team, we have expertise in studying both the behavioral and neural bases of learning in rat, songbird, and nonhuman primate. We propose to develop the optogenetic tools and experimental techniques required to study the circuit-level mechanisms of learning in these species and to apply these to two specific scientific aims: Aim 1: Determine the functional connectivity of learning-related circuitry and how it is altered by experience. It is widely presumed that learning relies on the ability of instructive signals to drive functional modifications of connectivity in the circuits that underlie behavior. However, the tools for measuring functional connectivity in vivo have been limited. We will overcome this limitation using temporally and/or spatially precise optical activation of neurons within a circuit. Functional connectivity will be measured by recording optical-stimulation-triggered changes in activity in downstream neurons. We will assess how functional connectivity is dynamically altered by learning and by factors that may contribute crucially to learning. Connectivity changes will serve as a mechanistic index of the nature and sites of the plasticity that give rise to behavioral change. Aim 2: Test the causal contributions of patterned activity to learning in vivo. Prior research has generated specific and testable hypotheses about how and where patterned activity drives learning. Yet support for these hypotheses has derived primarily from correlative observations of activity during learning rather than causal tests of the proposed mechanisms. We will use optogenetics to causally test the contributions of patterned activity to learning. We will test the sufficiency of instructive signals by imposing precisely controlled patterns of activity at defined loci in a circuit and test their necessity by eliminating the putative signals for learning. PROJECT NARRATIVE This project is aimed at revolutionizing the study of the mechanisms of learning within large neural circuits in the brain by directly measuring large-scale properties of these circuits and precisely manipulating circuit activity. To accomplish this, we will make use of, and continue to develop, advanced new techniques that permit the control of specific population of neurons using optical stimulation (light). The knowledge and tools that we gain from these studies are likely to find broad application in the search for treatments of neurological disorders.

DESCRIPTION (provided by applicant): Storing memories for the experiences of daily life requires the hippocampus. These memories shape our personalities and decisions, and are central to our identity. Given the importance of memory, it is perhaps not surprising that hippocampal dysfunction is associated with numerous psychiatric disorders, including post- traumatic stress disorder, depression and schizophrenia. A deep understanding of hippocampal function and dysfunction has great potential to contribute to the development of new and more effective treatments for these disorders. Somehow the hippocampus stores complex patterns of inputs corresponding to experiences and does so quickly enough to keep up with the continual flow of events. While this basic phenomenon is well established, it mechanism remain somewhat mysterious. We lack a clear picture of how the hippocampus interacts with the neocortex to store long lasting memories and how these memories are used to guide behavior. We have discovered that new learning, whether it is related to exploring a new place or learning a new task in a familiar place, leads to a massive and selective increase in coordinated activity during waking behavior, and in particular during network events known as sharp-wave ripples (SWRs). These SWRs frequently activate entire sequences of hippocampal neurons associated with specific behaviors and have therefore been termed replay events. In parallel, we have developed new techniques that allow us to detect and interrupt these correlated patterns of neural activity in real-time. In collaboration with Dr. Karl Deisseroth we have also combined optogenetic manipulations of targeted circuits with large scale, multielectrode recording, allowing us to perturb genetically targeted hippocampal circuits and record the results in awake, behaving animals. We will use these techniques to test our central hypothesis that awake replay of past experience during SWRs is necessary for the formation and retrieval of memories in hippocampal - neocortical circuits In particular, our aims are 1) To test the hypothesis that neural activity during awake SWRs is necessary for hippocampally-dependent memory formation and retrieval, 2) To test the hypothesis that awake replay events reactivate memory traces in the cortex and 3) To test the hypothesis that the influence of the hippocampus on the cortex is greatest during behavioral states associated with awake replay. Together these aims will provide 1) a determination of the causal role of awake SWRs in learning and hippocampal memory processing and 2) a new understanding of the propagation of mnemonic activity from the hippocampus to target structures. These findings have the potential to link elements of memory formation and retrieval to specific patterns of hippocampal neural activity and to thereby point the way toward therapies where these patterns are manipulated to relieve the symptoms of disorders associated with hippocampal dysfunction.

DESCRIPTION (provided by applicant): The ability to use experience to guide behavior (to learn) is one of the most remarkable abilities of the brain. Our goal is to understand how activity and plasticity in neural circuits underlie both learning and the ability to use learned information to make decisions. We have examined how information processing in the hippocampus changes as animals behavior changes. We found that that there is a smooth transition from greater CA3 to greater EC drive of hippocampal output area CA1 as animals move more quickly. Changes as function of moment speed are rapid and are most pronounced in new environments. The level of coordinated spiking activity in CA1 reflects that transition: cell pairs are highly correlated at low speeds and become progressively less correlated as animals move more quickly. These results suggest that behavior drives a dynamic balance between correlated activity representing stored associations and more independent sensory representations in the hippocampus. This dynamic balance is well suited to support the mnemonic functions of the hippocampal circuit, including the formation of reliable memories during exploration of new places. The goal of this grant is to investigate the mechanism that drives this dynamic balance. Currently available results suggest that cholinergic modulation from the medial septum and the ventral diagonal band of Broca (MS/DB) is central to regulating hippocampal circuits, so we will use multielectrode recording and targeted optogenetic manipulations in awake, behaving animals to determine the role of cholinergic inputs to the hippocampus in regulating moment-by-moment changes in hippocampal information processing. Our Specific Aims are: 1) Test the hypothesis that modulation of MS/DB input populations is sufficient to control the dynamic balance of information processing in the hippocampus and 2) Test the hypothesis that dynamic levels of MS/DB cholinergic neuron activity are important for rapid learning. The experiments carried out to accomplish these aims have the potential to provide a fundamental new understanding of the regulation of the many functions of the hippocampal circuit.

? DESCRIPTION (provided by applicant): The brain is a massively interconnected network of specialized circuits. Even primary sensory areas, once thought to support relatively simple, feed-forward processing, are now known to be parts of complex feedback circuits. All brain functions depend on millisecond timescale interactions across these brain networks, but current approaches cannot measure or manipulate these interactions with sufficient resolution to resolve them. We need the capacity to measure and manipulate the activity large ensembles of neurons distributed across anatomically or functionally connected circuits. That technology does not yet exist, a lack that motivates our efforts to develop a new system for large scale, multisite recording and manipulation that takes integrates biocompatible polymer electrodes, new headstage amplifiers, a new Ethernet-based data transmission system and open source, real-time cross-platform software. This system will support recordings and manipulations across thousands of channels in awake, behaving animals as well as closed loop feedback for the next generation of experiments. Our Specific Aims are 1) To develop new high-density, double-sided polymer recording/manipulation probes, 2) To develop new high-density headstage chips, integrated electrode- headstage assemblies and surgical techniques for implanting them, and 3) To develop a low-cost, powerful data acquisition system with open-source software and real-time capabilities. We have assembled a unique team of scientists and engineers with expertise spanning polymer electrode technology, integrated electronics, real-time systems, large-scale recording, and commercial experience. Our combined expertise will allow us to create and provide to the neuroscience community an integrated system that will allow for large scale, distributed measurements and manipulation of neural activity across many sites in awake, behaving animals.

DESCRIPTION (provided by applicant): The abilities to learn, remember, evaluate and decide are central to who we are and how we structure our lives. These abilities, and indeed the vast majority of cognitive functions, are thought to depend on specific patterns of brain activity. Each new experience is thought to drive a unique pattern of brain activity in the hippocampus, a brain region critical for storing memories for the events of daily life. Subsequent reactivation of this experience after learning is thought to drive a consolidation process that engrains the patterns in hippocampal and cortical circuits. Similarly, subsequent retrieval is thought to rely on the reinstatement of patterns similar to those present during the original experience. Current evidence points to the replay of sequences of hippocampal neurons during sharp-wave ripple events (SWRs) as a candidate mechanism for both memory consolidation and memory retrieval. To determine whether memory replay drives consolidation and retrieval for the associated memory representations, we will carry out directed manipulations that go beyond interrupting all SWRs to target replay events by their content. Our work will build on our expertise in real-time feedback and recent developments in cluster-less decoding that have allowed us to develop all of the technological elements required for real-time, content-based interruption of hippocampal replay events. This will allow us to assess the role of specific memory replay events in memory processes. Our Specific Aims are: 1) to develop an optimal adaptive statistical framework for real-time decoding and interruption of memory replay, 2) to test the hypothesis that hippocampal replay events drive memory consolidation for the replayed memories, and 3) to test the hypothesis that hippocampal replay events support rule learning and the internal exploration of specific future possibilities. Our real-time approach has the potential to create new causal links between the replay of specific patterns of activity and the ability to consolidation memories and to use past experience to guide future decisions.

? DESCRIPTION (provided by applicant): The brain is a massively interconnected network of specialized circuits. Even primary sensory areas, once thought to support relatively simple, feed-forward processing, are now known to be parts of complex feedback circuits. All brain functions depend on millisecond timescale interactions across these brain networks, but current approaches cannot measure or manipulate these interactions with sufficient resolution to resolve them. We need the capacity to measure and manipulate the activity large ensembles of neurons distributed across anatomically or functionally connected circuits. That technology does not yet exist, a lack that motivates our efforts to develop a new system for large scale, multisite recording and manipulation that takes integrates biocompatible polymer electrodes, new headstage amplifiers, a new Ethernet-based data transmission system and open source, real-time cross-platform software. This system will support recordings and manipulations across thousands of channels in awake, behaving animals as well as closed loop feedback for the next generation of experiments. Our Specific Aims are 1) To develop new high-density, double-sided polymer recording/manipulation probes, 2) To develop new high-density headstage chips, integrated electrode- headstage assemblies and surgical techniques for implanting them, and 3) To develop a low-cost, powerful data acquisition system with open-source software and real-time capabilities. We have assembled a unique team of scientists and engineers with expertise spanning polymer electrode technology, integrated electronics, real-time systems, large-scale recording, and commercial experience. Our combined expertise will allow us to create and provide to the neuroscience community an integrated system that will allow for large scale, distributed measurements and manipulation of neural activity across many sites in awake, behaving animals.

The brain is a massively interconnected network of specialized circuits. Three characteristics of these circuits make them particularly challenging: diversity of time scales, diversity of spatial scales, and heterogeneity. Understanding the brain therefore requires spanning these temporal and spatial scales and providing information about cell-types. We need to be able to record the activity of individual neurons across time to understand activity patterns on a millisecond timescale and how those patterns evolve with experience across hours, days, months and even years. We need to be able to record throughout a cortical region, spanning both different parts of the region as well as all layers, to understand both local and distributed information processing. We also need to be able to combine these dense and distributed recordings with imaging to take advantage of the complementary strengths of electrical and optical measurements. This is hindered by multiple challenges: 1) Current approaches lack the spatial extent (spanning multiple structures) required to examine three-dimensional or distributed networks in detail. 2) Current electrophysiological approaches (which do provide the millisecond resolution) typically lack the necessary lifetime to follow long-term dynamics. 3) Current electrophysiological approaches use rigid electrodes that are ill-suited to use with imaging techniques. The overall objective of this project is to optimize a suite of complementary technologies that can address these challenges for the community and make them ready for common use by the neuroscience community. Our central hypothesis is that our recently developed nanoelectronic thread (NET) devices, which have demonstrated biocompatibility, in vivo function longevity, high quality unit recording and compatibility with optical methods, are a potentially ideal candidate for understanding patterns of brain activity. We plan to develop a selection of NET probes and high-density arrays that are suitable for multiple brain regions in different spices. We will engage expert neuroscientists, allowing us to develop and optimize NETs that work across mouse, rat and marmoset, and to expedite the delivery of resulting technologies to the scientific community. We will pursue the following three specific aims: 1) To optimize NET probes for various brain regions and species.; 2) To optimize NET probes for high-density regional and distributed recordings; and 3) To determine the best devices for each species and brain regions. The approach is innovative, because the technology we will develop and put into common use has the potential to drive innovation throughout the field, enabling new, very high density recording studies and allowing investigators to track large ensembles of neurons in unprecedented details and time duration.

Project Summary No changes from original grant U01NS115588