Natural image statistics and neural representation

E. P. Simoncelli, B. A. Olshausen

Research output: Contribution to journalReview articlepeer-review


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) and 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.

Original languageEnglish (US)
Pages (from-to)1193-1216
Number of pages24
JournalAnnual Review of Neuroscience
StatePublished - 2001


  • Efficient coding
  • Independence
  • Redundancy reduction
  • Visual cortex

ASJC Scopus subject areas

  • General Neuroscience


Dive into the research topics of 'Natural image statistics and neural representation'. Together they form a unique fingerprint.

Cite this