Natural image statistics and neural representation

Citation
Ep. Simoncelli et Ba. Olshausen, Natural image statistics and neural representation, ANN R NEUR, 24, 2001, pp. 1193-1216
Citations number
86
Categorie Soggetti
Neurosciences & Behavoir
Journal title
ANNUAL REVIEW OF NEUROSCIENCE
ISSN journal
0147006X → ACNP
Volume
24
Year of publication
2001
Pages
1193 - 1216
Database
ISI
SICI code
0147-006X(2001)24:<1193:NISANR>2.0.ZU;2-T
Abstract
It has long been assumed that sensory neurons are adapted, through both evo lutionary and developmental processes, to the statistical properties of the signals to which they are exposed. Attneave (1954) and Barlow (1961) propo sed that information theory could provide a link between environmental stat istics and neural responses through the concept of coding efficiency. Recen t developments in statistical modeling, along with powerful computational t ools, have enabled researchers to study more sophisticated statistical mode ls for visual images, to validate these models empirically against large se ts of data, and to begin experimentally testing the efficient coding hypoth esis for both individual neurons and populations of neurons.