Letters: Population stochastic dynamics for synaptic depression

  • Authors:

  • Wentao Huang;Licheng Jiao;Jianhua Jia

  • Affiliations:

  • Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Institute of Intelligent Information Processing, Xidian University, Xi'an 710071, PR China;Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Institute of Intelligent Information Processing, Xidian University, Xi'an 710071, PR China;Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Institute of Intelligent Information Processing, Xidian University, Xi'an 710071, PR China

  • Venue:
  • Neurocomputing
  • Year:
  • 2008

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Abstract

Synaptic transmission between neocortical neurons often shows activity-dependent synaptic depression. Moreover, it is revealed recently that the synaptic depression has a more active role in information processing. The population density approach is a viable method to describe the large populations of neurons and has generated considerable interest recently. In this paper, we use the population stochastic dynamics to analyze the population of neurons with synaptic depression in the stochastic environment. We have derived an evolution equation of the membrane potential density function with synaptic depression, and obtain several formulas for analytic computing the response of instantaneous fire rate. Through a technical analysis, we arrive at several significant conclusions, which show that the background inputs and the spatial distribution of synapses and the spatial-temporal relation of inputs play an important role in information processing.