Properties of artificial networks evolved to contend with natural spectra.

Published

Journal Article

Understanding why spectra that are physically the same appear different in different contexts (color contrast), whereas spectra that are physically different appear similar (color constancy) presents a major challenge in vision research. Here, we show that the responses of biologically inspired neural networks evolved on the basis of accumulated experience with spectral stimuli automatically generate contrast and constancy. The results imply that these phenomena are signatures of a strategy that biological vision uses to circumvent the inverse optics problem as it pertains to light spectra, and that double-opponent neurons in early-level vision evolve to serve this purpose. This strategy provides a way of understanding the peculiar relationship between the objective world and subjective color experience, as well as rationalizing the relevant visual circuitry without invoking feature detection or image representation.

Full Text

Duke Authors

Cited Authors

  • Morgenstern, Y; Rostami, M; Purves, D

Published Date

  • July 14, 2014

Published In

Volume / Issue

  • 111 Suppl 3 /

Start / End Page

  • 10868 - 10872

PubMed ID

  • 25024184

Pubmed Central ID

  • 25024184

Electronic International Standard Serial Number (EISSN)

  • 1091-6490

International Standard Serial Number (ISSN)

  • 0027-8424

Digital Object Identifier (DOI)

  • 10.1073/pnas.1402669111

Language

  • eng