An egalitarian network model for the emergence of simple and complex cells in visual cortex

Louis Tao, Michael Shelley, David McLaughlin, Robert Shapley

Research output: Contribution to journalArticle

Abstract

We explain how simple and complex cells arise in a large-scale neuronal network model of the primary visual cortex of the macaque. Our model consists of ≈4,000 integrate-and-fire, conductance-based point neurons, representing the cells in a small, 1-mm2 patch of an input layer of the primary visual cortex. In the model the local connections are isotropic and nonspecific, and convergent input from the lateral geniculate nucleus confers cortical cells with orientation and spatial phase preference. The balance between lateral connections and lateral geniculate nucleus drive determines whether individual neurons in this recurrent circuit are simple or complex. The model reproduces qualitatively the experimentally observed distributions of both extracellular and intracellular measures of simple and complex response.

Original languageEnglish (US)
Pages (from-to)366-371
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume101
Issue number1
DOIs
StatePublished - Jan 2004

Keywords

  • Computational models
  • Spatial summation

ASJC Scopus subject areas

  • General

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