Natural image statistics and neural representation

Annu Rev Neurosci. 2001;24:1193-216. doi: 10.1146/annurev.neuro.24.1.1193.

Abstract

It has long been assumed that sensory neurons are adapted, through both evolutionary and developmental processes, to the statistical properties of the signals to which they are exposed. Attneave (1954)Barlow (1961) proposed that information theory could provide a link between environmental statistics and neural responses through the concept of coding efficiency. Recent developments in statistical modeling, along with powerful computational tools, have enabled researchers to study more sophisticated statistical models for visual images, to validate these models empirically against large sets of data, and to begin experimentally testing the efficient coding hypothesis for both individual neurons and populations of neurons.

Publication types

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

MeSH terms

  • Animals
  • Brain Mapping*
  • Environment
  • Humans
  • Image Processing, Computer-Assisted
  • Neurons / physiology*
  • Pattern Recognition, Visual*
  • Visual Cortex / physiology*
  • Visual Perception*