An introductory review of information theory in the context of computational neuroscience

被引:23
作者
McDonnell, Mark D. [2 ]
Ikeda, Shiro [1 ]
Manton, Jonathan H. [3 ]
机构
[1] Inst Stat Math, Tokyo 1908562, Japan
[2] Univ S Australia, Inst Telecommun Res, Mawson Lakes, SA 5095, Australia
[3] Univ Melbourne, Melbourne, Vic 3010, Australia
基金
澳大利亚研究理事会;
关键词
Information theory; Neuroscience; Neural coding; Channel capacity; DIRECTED INFORMATION; GRANGER CAUSALITY; CAPACITY; COMMUNICATION; CHANNEL; FREQUENCY; BRAIN; FLOW;
D O I
10.1007/s00422-011-0451-9
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
This article introduces several fundamental concepts in information theory from the perspective of their origins in engineering. Understanding such concepts is important in neuroscience for two reasons. Simply applying formulae from information theory without understanding the assumptions behind their definitions can lead to erroneous results and conclusions. Furthermore, this century will see a convergence of information theory and neuroscience; information theory will expand its foundations to incorporate more comprehensively biological processes thereby helping reveal how neuronal networks achieve their remarkable information processing abilities.
引用
收藏
页码:55 / 70
页数:16
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