Modeling cortex network: a spatio-temporal population approach

Authors:
Wentao Huang;Licheng Jiao;Maoguo Gong;Chuang Guo
Affiliations:
Institute of Intelligent Information Processing, and Key Laboratory of Radar Signal Processing, Xidian University, Xi'an, Shaanxi, China;Institute of Intelligent Information Processing, and Key Laboratory of Radar Signal Processing, Xidian University, Xi'an, Shaanxi, China;Institute of Intelligent Information Processing, and Key Laboratory of Radar Signal Processing, Xidian University, Xi'an, Shaanxi, China;College of Engineering, Air Force Engineering University, Xi'an, Shaanxi, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Year:
2005

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Abstract

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.