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

Wei Zhu, Michael Shelley, Robert Shapley

Research output: Contribution to journalArticlepeer-review


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
Issue number2
StatePublished - 2009


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

ASJC Scopus subject areas

  • Sensory Systems
  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience


Dive into the research topics of 'A neuronal network model of primary visual cortex explains spatial frequency selectivity'. Together they form a unique fingerprint.

Cite this