A neuronal network model of primary visual cortex explains spatial frequency selectivity

Wei Zhu, Michael Shelley, Robert Shapley

Research output: Contribution to journalArticle

Abstract

We address how spatial frequency selectivity arises in Macaque primary visual cortex (V1) by simulating V1 with a large-scale network model consisting of O(104) excitatory and inhibitory integrate-and-fire neurons with realistic synaptic conductances. The new model introduces variability of the widths of subregions in V1 neuron receptive fields. As a consequence different model V1 neurons prefer different spatial frequencies. The model cortex has distributions of spatial frequency selectivity and of preference that resemble experimental findings from the real V1. Two main sources of spatial frequency selectivity in the model are the spatial arrangement of feedforward excitation, and cortical nonlinear suppression, a result of cortical inhibition.

Original languageEnglish (US)
Pages (from-to)271-287
Number of pages17
JournalJournal of Computational Neuroscience
Volume26
Issue number2
DOIs
StatePublished - 2009

Fingerprint

Visual Cortex
Neurons
Macaca

Keywords

  • Cortical excitation
  • Cortical inhibition
  • Feed forward input
  • Large-scale neuronal network
  • Simple/complex cells
  • Spatial frequency selectivity

ASJC Scopus subject areas

  • Cellular and Molecular Neuroscience
  • Cognitive Neuroscience
  • Sensory Systems

Cite this

A neuronal network model of primary visual cortex explains spatial frequency selectivity. / Zhu, Wei; Shelley, Michael; Shapley, Robert.

In: Journal of Computational Neuroscience, Vol. 26, No. 2, 2009, p. 271-287.

Research output: Contribution to journalArticle

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