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Tutorials: Nov 13, 2011, Shanghai, China
Main Conference: Nov 14-17, 2011, Shanghai, China
Workshops: Nov 18, 2011, Hangzhou, China
 
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   Final program of ICONIP2011 and book of abstracts are available now.  
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Computational Modeling of Primary Visual Cortex

Lecturer:

David Cai
Institute of Natural Sciences, Shanghai Jiao Tong University, China

Courant Institute of Mathematical Science and the Center for Neural Science, New York University, USA


Objective:

The tutorial will provide a review of our current state of large-scale computational modeling of the dynamics of the primary visual cortex (V1) and cortical information processing within V1.

Content and Benefits:

The primary visual cortex (V1) is one area of the brain where computational modeling has been successfully used to investigate the link between physiological mechanisms and cortical function. Our approach to large-scale computational modeling of V1 is reviewed in this tutorial. We discuss how to gain a deeper theoretical understanding of brain functions with modeling approaches that strike a careful balance between mathematical abstraction and physiological detail. Furthermore, we illustrate the necessity of employment of fast and efficient computational methods in simulation of large-scale neuronal networks in order to achieve a good understanding of network dynamics. We describe the results of our large-scale computational modeling of spatiotemporal cortical dynamics as revealed by real time optical imaging methods. General issues addressed in this tutorial will be useful for computational modeling of various cortical areas of the brain.

Target Audience:

This tutorial aims to provide Ph.D. students, junior scientists, and researchers from other backgrounds with new perspectives in modeling cortical dynamics. It emphasizes the importance of the roles that dynamical systems, stochastic processes and computational methods have played in studying information processing within the brain.

Biographies:

Institute of Natural Sciences, Shanghai Jiao Tong University, China

Courant Institute of Mathematical Science and the Center for Neural Science, New York University, USA



 
         
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