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Anastasio, Thomas J.
Associate Professor, Molecular and Integrative Physiology, Biophysics and Computational Biology, Bioengineering, Computer Science
B.S., McGill University
Ph.D., University of Texas
Research Areas
Modeling neural systems that produce simple behaviors
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.
Anastasio, T.J. (2001) "A pattern-correlation model of vestibulo-ocular reflex habituaion," Neural Networks 14:1-22.
Anastasio, T.J. (2001) "Input minimization: A model of cerebellar learning without climbing fiber error signals," NeuroReport 12:3825-3831.
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.
Patton, P.E. and Anastasio, T.J. (2003) "Modeling cross-modal enhancement and modality-specific suppression in multisensory neurons," Neural Computation 15:783-810.
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.
Anastasio, T. J.; Gad, Y. P., Sparse cerebellar innervation can morph the dynamics of a model oculomotor neural integrator. Journal of Computational Neuroscience 2007, 22, (3), 239-254.
Raginsky, M.; Anastasio, T. J., Cooperation in self-organizing map networks enhances information transmission in the presence of input background activity. Biological Cybernetics 2008, 98, (3), 195-211.
Additional Information
Collaborative Projects:
Professor Joseph Malpeli - Analyzing saccadic eye movements and modeling information processing in the superior colliculus
Related Research (By Area):
Computational Neuroscience
Neuroengineering
Sensory and Motor Systems
Contact information:
