Comparison of Bayesian and empirical ranking approaches to visual perception.

Journal Article (Journal Article)

Much current vision research is predicated on the idea--and a rapidly growing body of evidence--that visual percepts are generated according to the empirical significance of light stimuli rather than their physical characteristics. As a result, an increasing number of investigators have asked how visual perception can be rationalized in these terms. Here, we compare two different theoretical frameworks for predicting what observers actually see in response to visual stimuli: Bayesian decision theory and empirical ranking theory. Deciding which of these approaches has greater merit is likely to determine how the statistical operations that apparently underlie visual perception are eventually understood.

Full Text

Duke Authors

Cited Authors

  • Howe, CQ; Beau Lotto, R; Purves, D

Published Date

  • August 2006

Published In

Volume / Issue

  • 241 / 4

Start / End Page

  • 866 - 875

PubMed ID

  • 16537082

Electronic International Standard Serial Number (EISSN)

  • 1095-8541

International Standard Serial Number (ISSN)

  • 0022-5193

Digital Object Identifier (DOI)

  • 10.1016/j.jtbi.2006.01.017


  • eng