The proposed program, based in the Center for Theoretical Neuroscience in the Department of Neuroscience, will provide training for predoctoral students in their third through fifth year in the interdisciplinary field of theoretical neuroscience. Trainees will receive dual training in the quantitative methods developed in disciplines such as physics, mathematics, engineering, and computer science and in the experimental approaches developed within biology and neuroscience. Most importantly, they will learn how to apply analytic techniques and modeling approaches to studies of brain function. After completing the program, trainees will be able to bridge the gap between theory and experiment and, lead the way in identifying unifying themes and new principles linking behavior to underlying synaptic, cellular and circuit mechanisms. This will be achieved through a training program that combines rigorous courses in analytic and computational methods with work in the relevant neuroscience laboratories. Trainees include students who work primarily with the theoretical faculty but will have extensive interactions with experimental colleagues as well as with students working in laboratories with dual theory-experimental faculty mentoring. The Center for Theoretical Neuroscience will provide the focal point for the proposed program. The Theory Center consists of a faculty of five full-time and one visiting member, with an additional full-time faculty member to start in the next year or two. Faculty members of Columbia's Program in Neurobiology and Behavior will augment this core group. The Center for Theoretical Neuroscience, with its highly interactive environment and extensive ties to experimental laboratories, provides a unique environment for crossdisciplinary training in theoretical neuroscience. The training program will accept graduate students from the graduate Program in Neurobiology and Behavior and the Integrated Program in Cellular, Molecular and Biophysical Studies at Columbia and augment their knowledge as needed to provide them with a rich education in both quantitative and laboratory methods in neuroscience. The training program is designed to develop a new breed of researcher skilled at applying powerful analytic and computational approaches to complex neurobiological systems.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Institutional National Research Service Award (T32)
Project #
1T32NS064929-01
Application #
7632381
Study Section
Special Emphasis Panel (ZNS1-SRB-P (47))
Program Officer
Korn, Stephen J
Project Start
2009-07-01
Project End
2014-06-30
Budget Start
2009-07-01
Budget End
2010-06-30
Support Year
1
Fiscal Year
2009
Total Cost
$174,920
Indirect Cost
Name
Columbia University (N.Y.)
Department
Neurosciences
Type
Schools of Medicine
DUNS #
621889815
City
New York
State
NY
Country
United States
Zip Code
10032
Russo, Abigail A; Bittner, Sean R; Perkins, Sean M et al. (2018) Motor Cortex Embeds Muscle-like Commands in an Untangled Population Response. Neuron 97:953-966.e8
DePasquale, Brian; Cueva, Christopher J; Rajan, Kanaka et al. (2018) full-FORCE: A target-based method for training recurrent networks. PLoS One 13:e0191527
Schaffer, Evan S; Stettler, Dan D; Kato, Daniel et al. (2018) Odor Perception on the Two Sides of the Brain: Consistency Despite Randomness. Neuron 98:736-742.e3
Zhang, Wujie; Falkner, Annegret L; Krishna, B Suresh et al. (2017) Coupling between One-Dimensional Networks Reconciles Conflicting Dynamics in LIP and Reveals Its Recurrent Circuitry. Neuron 93:221-234
Hattori, Daisuke; Aso, Yoshinori; Swartz, Kurtis J et al. (2017) Representations of Novelty and Familiarity in a Mushroom Body Compartment. Cell 169:956-969.e17
International Brain Laboratory. Electronic address: churchland@cshl.edu; International Brain Laboratory (2017) An International Laboratory for Systems and Computational Neuroscience. Neuron 96:1213-1218
Eichler, Katharina; Li, Feng; Litwin-Kumar, Ashok et al. (2017) The complete connectome of a learning and memory centre in an insect brain. Nature 548:175-182
Caron, Sophie; Abbott, Larry F (2017) Neuroscience: Intelligence in the Honeybee Mushroom Body. Curr Biol 27:R220-R223
Lindsay, Grace W; Rigotti, Mattia; Warden, Melissa R et al. (2017) Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex. J Neurosci 37:11021-11036
Kuchibhotla, Kishore V; Gill, Jonathan V; Lindsay, Grace W et al. (2017) Parallel processing by cortical inhibition enables context-dependent behavior. Nat Neurosci 20:62-71

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