Monthly
288 pp. per issue
6 x 9, illustrated
ISSN
0899-7667
E-ISSN
1530-888X
2014 Impact factor:
2.21

Neural Computation

July 2006, Vol. 18, No. 7, Pages 1511-1526
(doi: 10.1162/neco.2006.18.7.1511)
© 2006 Massachusetts Institute of Technology
Optimal Neuronal Tuning for Finite Stimulus Spaces
Article PDF (445.49 KB)
Abstract

The efficiency of neuronal encoding in sensory and motor systems has been proposed as a first principle governing response properties within the central nervous system. We present a continuation of a theoretical study presented by Zhang and Sejnowski, where the influence of neuronal tuning properties on encoding accuracy is analyzed using information theory. When a finite stimulus space is considered, we show that the encoding accuracy improves with narrow tuning for one- and two-dimensional stimuli. For three dimensions and higher, there is an optimal tuning width.