Modeling Cortex Network: A Spatio-temporal Population Approach

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.