Analytical solution for dynamic of neuronal populations

Wentao Huang, Licheng Jiao, Shiping Ma, Yuelei Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The population density approach is a viable method to describe the large populations of neurons and has generated considerable interest recently. The evolution in time of the population density is determined by a partial differential equation. Now, the discussion of most researchers is based on the population density function. In this paper, we propose a new function to characterize the population of excitatory and inhibitory spiking neurons and derive a novel evolution equation which is a nonhomogeneous parabolic type equation. Moreover, we study the stationary solution and give the firing rate of the stationary states. Then we solve for the time dependent solution using the Fourier transform, which can be used to analyze the various behavior of cerebra.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages19-24
Number of pages6
StatePublished - Dec 1 2005
Event15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005 - Warsaw, Poland
Duration: Sep 11 2005Sep 15 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3696 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005
CountryPoland
CityWarsaw
Period9/11/059/15/05

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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