Linking neurons to behavior in multisensory perception: A computational review

作     者：Ma, Wei Ji Pouget, Alexandre 

作者机构：Univ Rochester Dept Brain & Cognit Sci Rochester NY 14627 USA 

出 版 物：《BRAIN RESEARCH》 (脑研究)

年 卷 期：2008年第1242卷

页      面：4-12页

核心收录：

学科分类：1002[医学-临床医学] 1001[医学-基础医学(可授医学、理学学位)] 10[医学] 

主　　题：Multisensory integration Cue combination Computational modeling Population coding Neural variability Superadditivity Segregation 

摘      要：A large body of psychophysical. and physiological findings has characterized how information is integrated across multiple senses. This work has focused on two major issues: how do we integrate information, and when do we integrate, i.e., how do we decide if two signals come from the same source or different sources. Recent studies suggest that humans and animals use Bayesian strategies to solve both problems. With regard to how to integrate, computational studies have also started to shed light on the neural basis of this Bayes-optimal computation, suggesting that, if neuronal variability is Poisson-like, a simple linear combination of population activity is all that is required for optimality. We review both sets of developments, which together lay out a path towards a complete neural theory of multisensory perception. (c) 2008 Elsevier B.V. All rights reserved.