Michael E. Hasselmo, D.Phil. - US grants

A combination of electrophysiological experiments and computational modeling has led to the hypothesis that acetylcholine may set the appropriate dynamics for learning in the cortex, while removal of cholinergic modulation may set the appropriate dynamics for recall. In this application, we propose to test this hypothesis using the techniques of brain slice physiology. Predictions have been generated using simplified representations of cortical structures as systems of differential equations. In these simulations, feedback regulation of cortical cholinergic modulation allows cortical regions to set their own state of learning or recall dependent upon the familiarity of the incoming information. The memory function of the network is evaluated using a performance measure based on normalized dot products. This leads to predictions about the parameters of cholinergic modulation which give the most effective memory function. Biophysical network simulations will be used to further analyze the validity of these predictions. Experimental data about the relative amplitude of cholinergic effects on cortical parameters will be compared with computational predictions. Experimental work will determine the relative amplitude and dose response curves for cholinergic suppression of neuronal adaptation and afterhyperpolarization currents, the cholinergic suppression of inhibitory synaptic transmission, the cholinergic enhancement of synaptic modification, and the cholinergic suppression of synaptic transmission within the hippocampal formation. In addition, the possibility that GABAergic innervation arising from the basal forebrain selectively suppresses synaptic transmission in a manner similar to acetylcholine will be tested experimentally. Understanding the feedback regulation of cortical cholinergic innervation may shed light on the basis for degeneration of this cholinergic innervation in Alzheimer's disease. In addition, this work will increase understanding of the general role of neuromodulators in cortical function, since other neuromodulators influence many of the same physiological parameters. This may suggest new strategies for the use of drugs in the treatment of psychiatric disorders, since many of these drugs have a strong influence on neuromodulatory systems.

Michael E. Hasselmo PROJECT SUMMARY Computer modeling techniques are required to understand how neurochemicals with subtle and broadly distributed effects alter brain function. In the proposed research, computer models of the olfactory system (the brain system for odor perception) will be used to aid in understanding the action of the neurochemicals acetylcholine and norepinephrine on the function of cells can affect the processing of odor memories. OBJECTIVES Research will focus on the following central questions: 1. How do the combined effects of noradrenaline and acetylcholine in the olfactory system affect the capacity of memory? Computer simulations will be used to model two components of the olfactory system: the olfactory bulb and olfactory cortex. Models will be used to analyze how modulation of inhibitory effects by acetylcholine and norepinephrine in the olfactory bulb and cortex increases the number of odor memories that can be stored by allowing them to be coded by separate populations of cells. 2. How does regulation of noradrenaline and acetylcholine in the olfactory system affect behavior in an odor learning task? Computer models will be used to analyze recent behavioral experiments in this laboratory testing how rats respond to odor pairs which share components (odor A with odor B, odor A with odor C) versus how they respond to odor pairs that do not share components (odor A with odor B, odor C with odor D). The model will generate predictions about how the response to odor pairs with shared components should differ depending on whether the response to odor pairs is based on the familiarity of the odor pair, or on whether the odor pair has been paired with a reward. 3. Does acetylcholine more strongly suppress spread of activity at synapses that have been recently increased in strength? Computer models show that storage of odor memories in the olfactory system appears to function more effectively when acetylcholine suppresses the spread of activity at recently strengthened synapses. This prevents recently stored memories from interfering with storage of new memories. In slices of olfactory cortex, we will test whether drugs that activate acetylcholine receptors more strongly suppress spread of activity at synapses which were recently strengthened by repetitive stimulation. 4. Computer models will be used to analyze the effect of acetylcholine and norepinephrine on fast and slow oscillations of activity in the olfactory system. The interaction of oscillations in the olfactory bulb and olfactory cortex will be analyzed, with an emphasis on feedback connections from the olfactory cortex back to the olfactory bulb.

The proposed research combines modeling and physiology to explore how acetylcholine changes cellular and network dynamics in entorhinal cortex for different aspects of memory function. Physiological data suggests that high acetylcholine levels may set appropriate dynamics for sustained activity in entorhinal cortex, which might allow buffering of novel input patterns across short intervals in delayed match to sample tasks and might enhance formation of memory traces in the hippocampus, whereas low levels of acetylcholine may set appropriate dynamics for consolidation of additional memory traces. Research will focus on two hypotheses: Hypothesis number 1. Higher acetylcholine levels enhance buffering of novel activity patterns in entorhinal cortex, and thereby enhance memory encoding. Testing of this hypothesis includes modeling cholinergic effects on entorhinal non-stellate and stellate neurons to determine cellular mechanisms of sustained activity and network oscillations. These simulations will then be combined in network simulations of the entorhinal cortex focused on replication of network activity in vitro and in vivo. Physiological work will use pharmacological blockade to test the mechanisms for networks dynamics in slice preparations. In addition, experiments will test the effect of cholinergic receptor blockade on responses of entorhinal cortex neurons including sustained delay activity and match enhancement during performance of a delayed nonmatch to sample task in rats. Hypothesis number 2. Low acetylcholine levels in entorhinal cortex and hippocampus allows strong feedback appropriate for forming additional memory traces. Testing of this hypothesis will include analysis of network dynamics in entorhinal cortex underlying initiation and propagation of sharp wave and ripple activity in entorhinal cortex layer V, and studies of the cholinergic modulation of excitatory feedback connections in hippocampal region CA3 and entorhinal cortex. Acetylcholine levels change dramatically during different stages of waking and sleep. Blockade of acetylcholine receptors can cause amnesia and hallucinations. Disorders of this modulation may contribute to memory deficits in Alzheimer's disease, and Lewy Body dementia, disorders of REM sleep in depression, and the breakdown of slow wave sleep in development disorders such as Landau-Kleffner syndrome. Understanding of the cellular effects of acetylcholine involved in these processes could allow targeting of specific receptor effects in the treatment of disorders.

DESCRIPTION (provided by applicant): This competing continuation application focuses on understanding how changes in physiological properties at different phases of each cycle of the theta rhythm play a role in the functional dynamics necessary for memory guided behavior. Physiological experiments will test hypotheses from detailed network simulations of neurons in the hippocampal formation, which guide the movements of a virtual rat in a virtual environment performing memory-guided behavioral tasks. These models replicate electrophysiological recordings from awake behaving animals, including data from current source density analysis, and unit recording data showing phenomena such as theta phase precession and "splitter cells". We will test two specific hypotheses about how memory-guided behavior is enhanced by specific features of theta rhythm: Hypothesis #1. Changes in LTP and synaptic input during theta rhythm provide separate phases of encoding and retrieval in hippocampal circuits. Hypothesis #2. Phasic timing of synaptic input provides the most effective episodic retrieval for memory-guided behavior. Tests of these hypotheses include measuring timing of units relative to theta rhythm during exposure to a novel environment, measuring theta phase reset and spike timing relative to theta rhythm in prefrontal cortex and hippocampus during performance of a delayed match to sample task, testing unit activity relative to theta rhythm during delayed spatial alternation with different path lengths, testing unit activity during random exploration and single sided reward in a linear track, testing time course of modulation of synaptic transmission mediated by activation of interneurons in stratum oriens projecting to stratum lacunosummolecutare (s. I-m), and testing time course of mGluR modulation of transmission in s. I-m. Understanding these mechanisms may assist in development of pharmacological treatments for Alzheimer's disease.

[unreadable] DESCRIPTION (provided by applicant): The proposed research focuses on development of a detailed and realistic model of how neural firing patterns in the hippocampus, entorhinal cortex, prefrontal cortex and ventral tegmental area mediate goal directed behavior in specific behavioral tasks. These projects explore the interaction of goal activation, response selection and episodic memory for guiding behavior. Understanding these processes of motivated behavior should prove important for understanding the drug addiction processes. In particular this work allows modeling of how alterations in glutamatergic, GABAergic cholinergic and dopaminergic processes within numerous interacting regions could influence addictive behavior. The proposed research will further develop existing software that allows a direct interface between a neural simulation and behavior of a virtual rat in a virtual environment, a model simultaneously constrained by requirements about behavioral function and biologically realistic structure. The neural simulation uses dynamics based on extensive physiological data on rhythmic field potentials (EEG) and firing patterns of individual neurons (unit recording). The research proposed here will involve a continuous interaction between three groups: [unreadable] 1. The group in Edinburgh (Robert Cannon and Nigel Goddard) will provide ongoing development of a flexible, graphics based simulation package (CATACOMB), which allows construction of neural simulations for guiding behavior of a virtual rat in a variety of different experimental tasks, including spatial memory tasks and operant tasks. [unreadable] 2. The Hasselmo group will continue development of simulations of how the hippocampus, entorhinal cortex, prefrontal cortex and ventral tegmental area are involved in goal directed movements in behavioral tasks. This work will generate clear experimental predictions about the timing of spikes relative o behavior and relative to theta rhythm EEG based on hypotheses about the physiological interaction. [unreadable] 3. The Eichenbaum group will analyze data from a spatial alternation task to test specific predictions of the simulation about the timing of spikes during behavior. [unreadable] This project will have a synergistic interaction with a separate collaboration between the Hasselmo and Kantak laboratories at B.U., which focuses on modeling operant tasks used in experimental studies of drug self-administration phenomena, in work supported by a supplement to a previous grant from NIDA. [unreadable] [unreadable]

The Center of Excellence for Learning in Education, Science, and Technology (CELEST) brings together leading scientists, educators, and technologists from Boston University, Brandeis University, Massachusetts Institute of Technology, and the University of Pennsylvania to study real-time autonomous learning systems by integrating experimental and computational brain science, biologically inspired technology, and classroom innovation. Contributing scientists are drawn from four Boston University Departments and the Center for Adaptive Systems, the Center for Memory and Brain, the Science and Mathematics Education Center, the Hearing Research Center, and the Center for Polymer Studies; the Brandeis University Department of Psychology and the Volen Center for Complex Systems; the MIT Department of Brain and Cognitive Sciences, the Picower Center for Learning and Memory, and the Harvard/MIT Speech and Hearing Bioscience and Technology Program; and the University of Pennsylvania Department of Psychology.
Intellectual Merit and Creative Concepts: CELEST brings together educators, scientists, and technologists to carry out four types of mutually reinforcing and integrated activities: (1) quantitative behavioral and brain modeling of both normal and abnormal learning processes during perception, cognition, emotion, and action; (2) interdisciplinary cognitive and neuroscience experiments to probe these processes and to test model predictions; (3) development of algorithms, based on biological learning models, for incremental fast learning about complex and rapidly changing environments in large-scale engineering and technological applications that are important in many areas of society; and (4) integration of research and education through contributions to educational technology, curriculum development, and early career recruitment of underrepresented communities into scientific practice. These goals are achieved through interactions among eight main Thrusts in:
Learning in visual perception and recognition: laminar cortical dynamics of adaptive behavior;
Learning in audition, speech, and language; learning in cognitive-emotional interactions and planned sequential behaviors;
Learning and episodic memory: encoding and retrieval;
Learning in concept formation and rule discovery;
Learning in attentive recognition and neuromorphic technology;
Educational technology, curriculum development, and outreach; and
Diversity outreach.
Broader Impact: CELEST will foster interdisciplinary collaborations and training across all its units: frequent seminars, workshops, colloquia, conferences, and publications; integration of research and education by translating basic science results into interdisciplinary curriculum development; and web-based and hands-on training for teachers and students, including classroom activities with a national and international impact. CELEST will hereby provide world-class expertise towards advancing key SLC program goals; namely, the psychological and pedagogical aspects of learning, the biological basis of learning, machine learning, learning technologies, and mathematical analyses and modeling of them all.

computer program /software

stimulus /response

DESCRIPTION (provided by applicant): This competing renewal application focuses on the influence of cellular mechanisms on the coding of space by grid cells, head direction cells and conjunctive grid-by-head-direction cells in the rat medial entorhinal cortex. Specific Aim #1: In this aim, the properties of grid cells, conjunctive grid-by-head-direction cells and head direction cells will be analyzed with recordings of multiple single units in medial entorhinal cortex. The dynamical properties of firing will be analyzed for theta cycle skipping and theta phase precession relative to entorhinal theta rhythm oscillations, for the interaction of entorhinal rhythmic activity with hippocampal rhythmic activity in the field potential, and for the effects of local infusions of pharmacological agents. Computational biophysical network models based on recent anatomical data will combine features of oscillatory dynamics and attractor dynamics to address how the neural properties observed in recordings before and during pharmacological manipulations could arise from interactions of intrinsic properties with excitatory and inhibitory synaptic input. Specific Aim #2: In this aim, experiments will analyze specific cellular properties of entorhinal neurons that could contribute to the dynamical properties of grid cell firing. Experiments will include testing the phase of spiking dynamics relative to rhythmic synaptic input to analyze potential cellular mechanisms of grid cell firing properties. Experiments will als address the resonance properties of entorhinal interneurons and the influence of modulatory receptors on entorhinal interneuron firing properties. In vitro intracellular recordings will be compared with in vivo intracellular recordings during local infusions of pharmacological agents to determine how the intracellular properties extend to the intact circuits. Experiments will be guided by multicompartmental biophysical simulations analyzing how intrinsic membrane currents influence the response to synaptic input and how this could lead to the generation of spiking patterns in entorhinal grid cells, head direction cells and conjunctive grid-by-head-direction cells. The results of these experimental and computational studies can elucidate cellular and network mechanisms for generation of grid cells and their spiking relative to field potential oscillations. Investigating these cellular mechanisms may help understanding how events within an episode are encoded into memory. The analysis of effects of modulatory influences will provide insight into the dynamics underlying grid cell firing properties and into how drugs affect memory function. This influence on memory function could be part of the therapeutic effect of drugs used for treatment of anxiety disorders and depression. This analysis of entorhinal mechanisms for memory is also relevant to understanding the memory deficits associated with disorders that reduce the volume of hippocampus and entorhinal cortex, including Alzheimer's disease, depression and schizophrenia.

CELEST seeks to understand the fundamental processes that underlie human learning by studying dynamic interactions within and among brain regions. Interdisciplinary research teams study how the brain learns to (1) plan: to make decisions for appropriate actions based on assessment of risks and potential rewards in a given situation, (2) explore: to perform planned actions to move about familiar and unfamiliar environments, (3) communicate: to use noisy and incomplete sensory information to interact effectively with other agents and objects in the world, and (4) remember: to encode and guide retrieval of information to achieve goals. CELEST is a multi-faceted collaboration that focuses the efforts of scientific and educational teams led by 15 senior scientists at four Boston-area universities. CELEST combines undergraduate and graduate training in interdisciplinary research that combines experimental cognitive neuroscience with quantitative behavioral and brain modeling of normal and abnormal learning during perception, cognition, emotion, and action.

Broader impacts: CELEST transfers the results of basic research on learning to undergraduate and graduate courses. This is achieved through its ongoing development of course materials for the new undergraduate neuroscience major at Boston University, and through electronic dissemination on the CELEST web site. Outreach to the undergraduate neuroscience community also occurs by means of a one-day CELEST workshop and related workbook about the cognitive basis of successful learning strategies. A number of CELEST programs are targeted at increasing opportunities for groups underrepresented in science to participate in its innovative curriculum and research initiatives. These include graduate fellowships, summer internships for faculty from minority-serving institutions, a ten-week summer program for undergraduates from underrepresented groups to work in CELEST faculty labs, and a week-long summer workshop to introduce undergraduates to the interplay of modeling and experimental techniques in cognitive neuroscience. Center added value: By bringing together distinct scientific communities that traditionally employ different practices and techniques, CELEST interdisciplinary science is changing the way we understand how the brain learns, and how different parts of the brain interact with each other during learning. Through collaboration with industrial partners, including the development and transfer of large-scale neuromorphic engineering and technological algorithms to industry and government laboratories, CELEST facilitates research for practical applications that cannot be supported by conventional single-investigator grants. CELEST faculty, postdocs, and students are playing increasingly important roles in communicating with non-specialists through many activities including blogs, workshops, and presentations to secondary school audiences. The integration of CELEST research and education is accomplished through the development of innovative curriculum materials based upon mathematical and computational models of mind and brain. through electronic and personal presentations to a variety of audiences, and through sponsorship of scientific conferences and workshops.

This project will develop a shared computational model to identify unified mechanisms for interactions of the prefrontal cortex (PFC) and medial temporal lobe cortex (MTL) in the performance of a behavioral task requiring cued responses based on context. The specific aims focus on modeling the properties of timing of neural spiking activity in PFC and MTL during performance of related behavioral tasks in rodents in Project 4-5, and on the properties of neural spiking in monkeys in Project 3 and the magnitude of functional magnetic resonance imaging (fMRI) activity in humans in Projects 1-2. In addition, the specific aims will address the effect of the damage to different cortical regions on behavioral performance and measures of neural activity. Based on previous models from this lab, network models of integrate-and-fire neurons or biophysical compartmental simulations representing subregions of the PFC and MTL will be used to generate predictions about experimental data that will guide data analysis, and comparison with the data will determine whether features of the shared model are retained or restructured to account for the data. Modeling predictions will address relative timing of unit activity between regions and timing relative to network oscillations in Projects 4-5, and experimental outcomes will guide selection of neural mechanisms for representation of context, such as oscillatory interference or the temporal context model. Models will generate predictions about the relative timing of unit activity in monkeys in Project 3, and the magnitude of fMRI activity and patterns of preferential viewing in humans in Projects 1 and 2 before and after the transition to context-based responding, and during inferences to cues presented in novel quadrants. The outcomes of these comparisons to data will guide extension of the model to address human and monkey PFC-MTL interactions in relation to rodents.

This project will foster collaborations between physicists, mathematicians and neuroscientists to generate theoretical frameworks and statistical tools to interpret genomic, anatomical and physiological data on brain function. A community of researchers will be built through development of a seminar series for discussions of problems in which the theoretical approaches of physics, mathematics and statistics can be brought to be bear on specific research questions regarding neural systems. In addition, a set of pilot projects will be funded to foster collaborations between mathematicians, physicists and neuroscientists. Specific pilot projects will use the techniques of theoretical physics to address problems of understanding large scale functional anatomical connectivity, with the objective of identifying constraints on the distance and pattern of inter-areal connectivity in the human brain. Pilot projects will also develop a theoretical framework for understanding neural activity on different time scales during behavior, with the objective of understanding the unifying neural principles underlying human memory behavior over time scales from seconds to minutes to hours. Pilot projects will also develop mathematical and statistical techniques to identify molecular networks underlying specific features of neural function, with the objective of identifying specific network modules in the prefrontal cortex. These pilot projects will provide example interactions that can be expanded to further build a community of interaction of physicists, mathematicians and neuroscientists.

The maturation of scientific fields such as physics required the development of sophisticated theoretical frameworks to account for experimental phenomena at multiple different scales of analysis ranging from particle physics to condensed matter physics to astrophysics. The maturation of neuroscience as a field will require similarly sophisticated theoretical frameworks that effectively account for data at the different levels including the genomic, physiological and behavioral levels. Current theories of single neuron function have not yet been effectively extended to address physiological phenomena at the circuit and population level or the behavioral function of these network dynamics. The pilot projects in this grant will attempt to develop theoretical frameworks for addressing these multiple levels of analysis. The intellectual merit of the proposal will be the application of mathematical and statistical techniques to the interpretation of neuroscience data, including the development of theoretical models to account for existing data and to guide the design of future experiments. The field of neuroscience needs more extensive development of a theoretical framework for understanding the structure and function of neural systems at different levels, including genomic, physiological and behavioral. Successful interactions in the pilot projects could provide a model for further interaction of physicists, mathematicians, and neuroscientists throughout the field. More specifically, these pilot projects will provide a framework for development of new theories for analyzing the connectivity patterns of neural systems, the dynamics of brain function underlying behavior, and the molecular networks underlying these neural properties. The resources provided by this grant will serve to recruit additional mathematicians and physicists to address relevant questions concerning brain function.

This project is being jointly supported by the Physics of Living Systems program in the Division of Physics and the Mathematical Biology program in the Division of Mathematical sciences.

This National Science Foundation Research Traineeship (NRT) award to Boston University will train scientists and engineers in the emerging interdisciplinary field of neurophotonics - the use of light-based tools to study brain function at the cellular scale. Understanding how neural activities and circuits drive human computation, behavior, and psychology is motivated by a critical societal need to address brain diseases that involve disruptions or deterioration of neural circuitry - including Alzheimer's, traumatic brain injury, Parkinson's, cerebral palsy and multiple sclerosis. Recent scientific discoveries and powerful new tools in brain research have inspired broad student interest in career paths focused on understanding brain structure and function, as well as new industrial and academic career opportunities. Neurophotonics is among the most rapidly evolving research frontiers in brain science because it allows researchers to monitor and influence neuron activity and neural circuits at their most fundamental level. A prominent neurophotonic technique is optogenetics, through which communication signals from neurons are precisely monitored, activated, or inhibited using light. This project will support training for eighty (80) PhD students, including twenty (20) funded trainees, across the disciplines of neuroscience, biomedical engineering and photonics.

Trainees will become versed in the biology of neural function and the development of optical instruments, photo-excitable materials, and imaging techniques to sense and affect neural circuits. NRT trainees will graduate having attended a hands-on neurophotonics technology boot camp, participated in multiple laboratory research rotations, completed a four-course core curriculum, conducted challenging doctoral research in a neurophotonics laboratory, and written a neurophotonics-themed dissertation co-mentored by NRT faculty. The traineeship project will emphasize immersive experiential learning activities and peer-to-peer learning, two educational approaches that have been shown to reinforce learning while simultaneously improving outcomes for STEM trainees, especially underrepresented minorities. Interwoven with educational activities will be a professional preparation program that supports trainee career goals, develops communication skills, and builds professional networks. Trainee learning objectives will focus on identifying important research problems in neurophotonics, applying light-based methods to measure and control neural circuits, working on team-oriented projects, and communicating effectively.

The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The Traineeship Track is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas, through the comprehensive traineeship model that is innovative, evidence-based, and aligned with changing workforce and research needs.

PROJECT SUMMARY/ABSTRACT The hippocampus plays a critical role in the organization of memories. Previous studies on the nature of neural representations in the hippocampus have focused on spatial representations by hippocampal neurons, but many studies in humans and animals indicate a broader role for the hippocampus in memory organization. Representational Similarity Analysis, which has been very successful in revealing the organization of neural representations in other domains, will be employed to explore how hippocampal networks organize memories that are distinguished by temporal context and by specific salient cues and rules; and how multiple memory representations are integrated and stabilized over time. These experiments employ a combination of multi- electrode recording in rats, state-of-the-art calcium imaging in behaving mice, and novel neural population analyses, to generate a new understanding of neural network representations. These studies are of high translational potential because cognition dependent on memory organization is impaired in mental disorders including schizophrenia.

DESCRIPTION (provided by applicant): A recent convergence of findings in humans and animals indicates that our capacity for episodic memory relies on a system of cortical areas and the hippocampus that encode events in the context in which they occur. To understand the information processing mechanisms that underlie episodic memory, we are pursuing a systems analysis that will compare the nature of information processing and identify functional interactions between cortical and hippocampal areas. In this phase of funding we will focus on the lateral entorhinal cortex (LEC), testing the hypothesis that this area is a critical convergenc site for object and context representation: (1) We will distinguish LEC neural activity with regard to object and context processing and examine whether the nature of this processing has a functional topography. (2) We will characterize interactions between the LEC and interconnected cortical and hippocampal areas, testing the hypothesis that functional interactions develop during the course of learning. (3) We will test whether object and context processing in LEC depend on specific inputs from interconnected cortical and hippocampal areas. Our approach combines a behavioral paradigm for associating events and context, multi-site recording that allows us to identify single neuron and ensemble representation and synchronized activity in multiple areas, and multiple methods of reversible inactivation that identify key interactions between areas. The combined information gained from this systems analysis will improve our model of the functional organization of the cortical-hippocampal system and increase our understanding of how episodic memories are stored and retrieved within this system.

PROJECT SUMMARY/ABSTRACT The projects proposed in this new grant address the properties of spatial coding in cortical regions. Representations of spatial location are important for a broad range of cognitive functions, including the planning of goal-directed navigation. This grant proposes specific experiments to test modeling predictions about the existence of egocentric representations of boundaries and coding of running speed relevant to the formation of allocentric spatial representations in cortical structures. Specific Aim #1: Recordings of the neural spiking activity in retrosplenial cortex and entorhinal cortex will test the hypothesis that cortical regions must code the position of environmental boundaries in egocentric coordinates. This prediction arose from models of the formation of allocentric representations of boundaries which require input from an egocentric, view-centered coding of environmental boundaries. Experiments will extend preliminary data from this lab showing egocentric coding of boundaries in retrosplenial cortex. Models show that egocentric boundary cells could be combined with head direction input to code allocentric boundary position, which can drive coding of spatial location. Further experiments will test the influence of environmental boundaries on spiking activity in the entorhinal cortex and retrospenial cortex, including testing the influence of manipulations of the shape of the environment, the insertion of new boundaries and different reward locations, recordings in darkness, and testing coexistence of egocentric coding with allocentric coding by head direction cells. This experimental testing of the predictions from models will provide an important link for building our understanding of the coding of space for cognitive processing. Specific Aim #2: Recordings of neural spiking activity in retrosplenial cortex and entorhinal cortex will test the complementary hypothesis that coding of running speed also plays a role in generation of representations of spatial location, and how the coding of running speed varies over different time courses and may depend on sensory input from boundaries. Experiments will include analysis of the coding of running speed at different spatial scales in entorhinal cortex and retrosplenial cortex ranging from one second to many minutes. The time course will also be analyzed in experiments exploring the change in running speed representations when barrier features are obscured by darkness. This aim also includes whole cell patch recording in slices to analyze the time course of intrinsic spiking activity relevant to the circuit dynamics for coding of speed and location. Finally, optogenetic inactivation of specific populations of neurons in medial septum will test how inputs regulate the coding of spatial location and speed by neurons in the medial entorhinal cortex. These experiments will contribute to our understanding of the dynamics of cortical circuits that underlie the formation of allocentric spatial representations important to many aspects of cortical cognitive processing, including the planning of goal-directed behavior.