Optimal neuronal tuning for finite stimulus spaces

Neural Comput. 2006 Jul;18(7):1511-26. doi: 10.1162/neco.2006.18.7.1511.

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.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Action Potentials / physiology
  • Computer Simulation
  • Humans
  • Information Theory*
  • Models, Neurological*
  • Nerve Net / physiology
  • Neurons / physiology*
  • Orientation*