Statistical physics approaches to neuronal network dynamics.

David Cai, Louis Tao
Author Information
  1. David Cai: Department of Mathematics, Shanghai Jiao Tong University, Shanghai, China. cai@cims.nyu.edu

Abstract

We review a statistical physics approach for reduced descriptions of neuronal network dynamics. From a network of all-to-all coupled, excitatory integrate-and-fire neurons, we derive a (2+1)-D advection-diffusion equation for a probability distribution function, which describes neuronal population dynamics. We further show how to derive a (1+1)-D kinetic equation, using a moment closure scheme, without introducing any new parameters to the system. We demonstrate the numerical accuracy of our kinetic theory by comparing its results to Monte Carlo simulations of the full integrate-and-fire neuronal network.

MeSH Term

Animals
Computer Simulation
Humans
Models, Neurological
Monte Carlo Method
Nerve Net
Neural Networks, Computer
Neurons

Word Cloud

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