Contrast normalization and a linear model for the directional selectivity of simple cells in cat striate cortex

D. J. Tolhurst, D. J. Heeger

Research output: Contribution to journalArticlepeer-review


Previous tests of the linearity of spatiotemporal summation in cat simple cells have compared the responses to moving sinusoidal gratings and to gratings whose contrast was modulated sinusoidally in time. In particular, since a moving grating can be expressed as a sum of modulated gratings, the response to a moving grating should be predictable (assuming linearity) from the responses to modulated gratings. However, these simple linear predictions have shown varying degrees of failure (e.g. Reid et el., 1987, 1991), depending on the directional selectivity of the neurons (Tolhurst and Dean, 1991). We demonstrate here that the failures of these linear predictions are, in fact, explained by the contrast-normalization model of Heeger (1993). We concentrate on the ratio of the measured to predicted moving grating responses. In the context of the contrast-normalization model, calculating this ratio turns out to be particularly appropriate, since the ratio is independent of the precise details of the linear front-end mechanisms ultimately responsible for directional selectivity. Hence, the contrast-normalization model can be compared quantitatively with this ratio measure, by varying only one free parameter. When account is taken both of the expansive output nonlinearity and of contrast normalization, the directional selectivity of simple cells seems to be dependent only on linear spatiotemporal filtering.

Original languageEnglish (US)
Pages (from-to)19-25
Number of pages7
JournalVisual neuroscience
Issue number1
StatePublished - 1997


  • Contrast normalization
  • Directional selectivity
  • Simple cells
  • Visual cortex

ASJC Scopus subject areas

  • Physiology
  • Sensory Systems


Dive into the research topics of 'Contrast normalization and a linear model for the directional selectivity of simple cells in cat striate cortex'. Together they form a unique fingerprint.

Cite this