Modeling cortex network: A spatio-temporal population approach

Wentao Huang, Licheng Jiao, Maoguo Gong, Chuang Guo

Research output: Contribution to journalConference articlepeer-review


The cerebral cortex is composed of a large number of neurons. More and more evidences indicate the information is coded via a population approach in cerebrum, and is associated with the spatio-temporal pattern of spiking of neurons. In this paper, we present a novel model that represents the collective activity of neurons with spatio-temporal evolution. We get a density evolution equation of neuronal populations in phase space, which utilize the single neuron dynamics (integrate-and-fire neuron model). Both in theory analysis and applications, our method shows more predominance than direct simulation the large populations of neurons via single neuron.

Original languageEnglish (US)
Pages (from-to)369-374
Number of pages6
JournalLecture Notes in Computer Science
Issue numberI
StatePublished - 2005
EventSecond International Symposium on Neural Networks: Advances in Neural Networks - ISNN 2005 - Chongqing, China
Duration: May 30 2005Jun 1 2005

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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