Spike count distributions, factorizability, and contextual effects in area V1

Odelia Schwartz, Javier R. Movellan, Thomas Wachtler, Thomas A. Albright, Terrence J. Sejnowski

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Neural models of contextual integration typically incorporate a mean firing rate representation. We examine representation of the full spike count distribution, and its usefulness in explaining contextual integration of color stimuli in primary visual cortex. Specifically, we demonstrate that a factorizable model conditioned on the number of spikes can account for both the onset and sustained portions of the response. We also consider a simplified factorizable model that parametrizes the mean of a Gaussian distribution and incorporates a logistic nonlinearity. The model can account for the sustained response but does not fair as well in accounting for onset nonlinearities. We discuss implications for neural coding.

Original languageEnglish (US)
Pages (from-to)893-900
Number of pages8
JournalNeurocomputing
Volume58-60
DOIs
StatePublished - Jun 1 2004
Externally publishedYes

Keywords

  • Color
  • Contextual
  • Factorizability
  • Integration
  • Spike count distribution
  • V1

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

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