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U of I

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Thomas J. Anastasio

Associate Professor of Molecular & Integrative Physiology, Biophysics, and Neuroscience

Beckman Institute for Advanced Science and Technology

B.Sc. 1980 McGill University
Ph.D. 1986 University of Texas, Galveston
Postdoc.1988 John Hopkins University


3041 Beckman Institute


Mailing Address:

Department of Molecular & Integrative Physiology
524 Burrill Hall
407 S. Goodwin Ave
Urbana, IL 61801

Sensorimotor Transformations in the Nervous System

Experimental neuroscience has produced a wealth of information concerning the neural substrates of behavior. My main goal is to develop computer models that synthesize and explain these data, and provide insight into how the nervous system works. I'm interested in modeling neural systems that produce relatively simple behaviors, such as the saccadic system, which rapidly reorients gaze. I'm also interested in modeling the cerebellum which, among other functions, produces adaptive changes in saccadic and other eye-movement systems. I use a variety of approaches to modeling -- from linear systems and probability theory to adaptive neural networks. I make my models relevant to nervous system function by using them to simulate real data and derive experimentally testable predictions.

Representative Publications:

Anastasio, T.J., Patton, P.E. and Belkacem-Boussaid, K. (2000) "Using Bayes' rule to model multisensory enhancement in the superior colliculus," Neural Computation 12:997-1019. [Abstract]

Anastasio, T.J. (2001) "Input minimization: A model of cerebellar learning without climbing fiber error signals," NeuroReport 12:3825-3831. [Abstract]

Anastasio, T.J. (2001) "A pattern correlation model of vestibulo-ocular reflex habituation," Neural Netw. 14(1):1-22. [Abstract]

Patton, P.E., Belkacem-Boussaid, K. and Anastasio, T.J. (2002) "Multimodality in the superior colliculus: An information theoretic analysis," Cognitive Brain Research 14:10-19. [Abstract]

Patton, P.E. and Anastasio, T.J. (2003) "Modeling cross-modal enhancement and modality-specific suppression in multisensory neurons," Neural Computation 15:783-810. [Abstract]

Anastasio, T.J. and Patton, P.E. (2003) "A two-stage unsupervised learning algorithm reproduces multisensory enhancement in a neural network model of the corticotectal system," Journal of Neuroscience 23:6713-6727. [Abstract]

View Publications by Thomas J. Anastasio listed on the National Library of Medicine (PubMed)

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