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Analytical Solution for Dynamic of Neuronal Populations

  • Wentao Huang
  • Licheng Jiao
  • Shiping Ma
  • Yuelei Xu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3696)

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.

Keywords

Firing Rate Neuronal Population Neural Computation Computational Neuroscience Time Dependent Solution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Wentao Huang
    • 1
    • 2
  • Licheng Jiao
    • 1
  • Shiping Ma
    • 2
  • Yuelei Xu
    • 2
  1. 1.Institute of Intelligent Information Processing and Key Laboratory, of Radar Signal ProcessingXidian UniversityXi’anChina
  2. 2.Signal and Information Processing Laboratory, Avionic Engineering Department, College of EngineeringAir Force Engineering UniversityXi’anChina

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