Kurt A. Thoroughman - US grants

Synaptic inhibition is important for all neuronal networks. Nonetheless, relatively little is known about the learning rules by which inhibitory synaptic strengths are controlled, in development and in adult animals. The goal of this project is to determine whether the inhibitory synapses in the lobster stomatogastric ganglion (STG) show activity-dependent modifications in strength, and whether previously proposed theoretical learning rules capture these modifications. A presynaptic neuron in the STG will be voltage clamped and driven to produce trains of depolarization for extended periods of time. The voltage response of the postsynaptic neuron, held in current clamp, before and after extended presynaptic depolarization will determine the existence and properties of any synaptic modification. The dependence of this modification on postsynaptic voltage and calcium concentration will be investigated. These experiments will motivate development of theoretical synaptic modification rules which will be implemented in biologically realistic model neurons results will also motivate modeling of coincident tuning of synaptic and intrinsic conductances.

[unreadable] DESCRIPTION (provided by applicant): The neural control of movement encompasses several conundrums in computational neuroscience. The fundamental function of cerebellum and primary and premotor cortices remains elusive. We have recently pioneered behavioral experiments of haptic learning that identify the transformation from sensed movements to incremental adaptations. Simulations have predicted neuronal activities necessary to generate these transformations and have suggested surprising plasticity in the neural representation of movement. Permanent motor impairments due to degeneration, strokes, and traumas affect hundreds of thousands of individuals each year, rendering people unable to perform motor behaviors. A quantitative understanding of normal motor adaptation will enhance the ability of rehabilitation to help patients regain normal function. [unreadable] Here we propose serial human and primate experiments of learning novel visuomotor environments. Humans will experience virtual reality environments that alter the dependence of visual feedback on hand position; the transformation complexity will vary across training days. We will identify how people learn visuomotor transformations over sessions and trial-by-trial, enabling neuronal network simulations to predict neuronal activity needed to mimic human adaptation. We will then record in motor cortex, premotor cortex, and cerebellum as monkeys perform the same visuomotor adaptations, to determine how neuronal activities depend on the environment and on trial-by-trial adaptation. The within-session and across-session changes will test the network simulations and will elucidate the particular contribution of each cortical area as inputs of motor plans, adaptive transformations between vision and action, or outputs of generated movements. The proposed collaboration between Dr. Thoroughman, a computational neuroscientist and psychophysicist, and Dr. Moran, a primate neurophysiologist, will enable a rich connection between neural computation, adaptive behavior, and cortical activity. The new collaboration will directly impact the quality and specificity of leading theories of motor control and learning. We aim to formulate basic scientific foundations that will ultimately improve metrics of neurological diagnosis, inform the design of patientspecific therapies and neuro-rehabilitation protocols, and help patients generalize beyond clinical training to improve motor function in their daily lives. [unreadable] [unreadable] [unreadable]

This Integrative Graduate Education and Research Training (IGERT) award supports the establishment of an interdisciplinary graduate training program in Cognitive, Computational, and Systems Neuroscience at Washington University in Saint Louis. Understanding how the brain works under normal circumstances and how it fails are among the most important problems in science. The purpose of this program is to train a new generation of systems-level neuroscientists who will combine experimental and computational approaches from the fields of psychology, neurobiology, and engineering to study brain function in unique ways. Students will participate in a five-course core curriculum that provides a broad base of knowledge in each of the core disciplines, and culminates in a pair of highly integrative and interactive courses that emphasize critical thinking and analysis skills, as well as practical skills for developing interdisciplinary research projects. This program also includes workshops aimed at developing the personal and professional skills that students need to become successful independent investigators and educators, as well as outreach programs aimed at communicating the goals and promise of integrative neuroscience to the general public. This training program will be tightly coupled to a new research focus involving neuro-imaging in nonhuman primates. By building upon existing strengths at Washington University, this research and training initiative will provide critical new insights into how the non-invasive measurements of brain function that are available in humans (e.g. from functional MRI) are related to the underlying activity patterns in neuronal circuits of the brain. IGERT is an NSF-wide program intended to meet the challenges of educating U.S. Ph.D. scientists and engineers with the interdisciplinary background, deep knowledge in a chosen discipline, and the technical, professional, and personal skills needed for the career demands of the future. The program is intended to catalyze a cultural change in graduate education by establishing innovative new models for graduate education and training in a fertile environment for collaborative research that transcends traditional disciplinary boundaries.

[unreadable] DESCRIPTION (provided by applicant): Despite the centrality of motor learning to basic and clinical neuroscience, we know very little about the quantitative role neural systems play in the transformation of senses into adapted control. The experiments presented here will challenge normal human subjects with perturbations of varying strengths, durations, frequency of application, biases, and spatial complexities both within and across movements. The variability of these perturbations will generate a template with which we will identify subtleties in trial-by-trial adaptation. These interrogations, coupled with novel state space analyses, will enable a thorough understanding of the transformation of specific sensory experiences into immediate, incremental adaptations in predictive control, greatly enhancing our quantitative understanding of human motor adaptation. Experience enables us to build internal dynamic models of our movement environment. Investigators of this internal dynamic adaptation have hypothesized two components of learning: the abstraction of an error signal from previous movements and the application of this error to either specify or generalize learning across movement space. Human trial-by-trial adaptation has, to date, suggested that adaptation constantly scales with sensed error and generalizes broadly across movement space. However, preliminary results from the PI have discovered surprising flexibility in both components of learning: sensory feedback can induce adaptation strikingly disproportional to movement error, and environments can induce narrowing of generalization across movement space. Here we propose to identify the necessary sensory experiences to induce these newly established changes in the fundamental computations people execute to transform single movement sense into incremental adaptation. These results will illuminate how the nervous system performs real-timed signal processing to improve motor performance. The resultant models will help the neuroscience and biological modeling community to better connect behavior to its underlying physiological basis. These insights will also be of use to investigate the full repertoire of normal motor control and how control fails in disease states. We aim to formulate the scientific basis of how rehabilitation can optimally help patients generalize beyond clinical training to improve motor function in their daily lives. [unreadable] [unreadable] [unreadable]

DESCRIPTION (provided by applicant): Project Summary The fields of biology, psychology, and biomedical engineering have generated exciting new advances in the study of neural systems underlying behavior. Individually, these disciplines have individually provided novel insights into brain function and provide opportunities for improved understanding of disorders of the nervous system, healthy and disordered development, and communication. However, the rapid advancement of scientific progress has been limited by the boundaries surrounding the disciplines. Moreover, neuroscientists that are firmly grounded in an array of approaches used by biologists, psychologists, and engineers will best advance new research technologies such as non-invasive functional imaging and neural prosthetics. A training model that is thoroughly interdisciplinary is needed. At Washington University, we have developed such a model: The Cognitive, Computational, and Systems Neuroscience (CCSN) Pathway produces rigorously trained independent investigators that will lead a new generation of scientists who study the brain in truly integrated interdisciplinary investigations. CCSN serves students from the PhD programs in Biomedical Engineering, Psychology, and Neuroscience. The core of CCSN is a two-year curriculum that emphasizes interdisciplinarity, collaboration, and project-based instruction. In the first year, students take courses that bring them up to speed on the core concepts and methods in Cognitive Psychology, Biological Neural Computation, and Neural Systems. In the second year, students participate in two unique courses that have been specially designed as the capstone to the CCSN pathway Advanced CCSN and Project Building in CCSN. Advanced CCSN consists of a series of interdisciplinary case studies in cutting-edge brain science topics. Each topic is presented as a module by a faculty team drawn from the three home programs. Modules include team-based projects and peer review as well as primary source readings and classroom lectures and discussions. Project Building in CCSN is a fully student-driven course. In collaboration with the faculty leader, each student designs an independent interdisciplinary research project. The faculty leader helps them to assemble an interdisciplinary faculty advising team, to whom they present their project multiple times throughout the semester. Faculty advising is complemented by peer advising including written peer review, culminating in a research grant-style project proposal. Surrounding the core CCSN curriculum is a rich penumbra of activities. These are designed to provide intellectual training and to build a cohort of scientists with the identification and social skills necessary to conduct research in interdisciplinary teams. Formal coursework is provided in Mathematics and Statistics of Experimental Neuroscience, and by an intensive mini- course preceding Advanced CCSN. Immersive Encounters with distinguished visiting scientists provide high-intensity exposure to cutting-edge research. In collaboration with the Saint Louis Science Center, CCSN trains students to communicate with the public and helps them build programs and presentations to teach children and adults about the brain and mind. In its initial phases, CCSN has produced cohorts of young brain scientists on the fast track to new discoveries. Evaluations from students, faculty, and an outside advisory team indicate the pathway is on track for continued growth. PUBLIC HEALTH RELEVANCE: Project)Narrative) Cutting edge research in brain science is increasingly interdisciplinary, and traditional discipline-based graduate training programs strain to accommodate this development. The Cognitive, Computational &Systems Neuroscience pathway at Washington University represents a unique new model for training 21st century brain scientists. Such training will produce a generation of scientists effectively equipped to produce breakthroughs in neurological disease, mental illness, and neural engineering.

The PIs and Co-PIs of grants supported through the NSF-NIH-BMBF Collaborative Research in Computational Neuroscience (CRCNS) program meet annually. This eighth meeting of CRCNS investigators brings together a broad spectrum of computational neuroscience researchers supported by the program, and includes poster presentations, talks, plenary lectures, and discussions. The meeting is scheduled for June 3-5, 2012 and is hosted by Washington University in Saint Louis.