Gauss-diffusion processes for modeling the dynamics of a couple of interacting neurons

Math Biosci Eng. 2014 Apr;11(2):189-201. doi: 10.3934/mbe.2014.11.189.

Abstract

With the aim to describe the interaction between a couple of neurons a stochastic model is proposed and formalized. In such a model, maintaining statements of the Leaky Integrate-and-Fire framework, we include a random component in the synaptic current, whose role is to modify the equilibrium point of the membrane potential of one of the two neurons and when a spike of the other one occurs it is turned on. The initial and after spike reset positions do not allow to identify the inter-spike intervals with the corresponding first passage times. However, we are able to apply some well-known results for the first passage time problem for the Ornstein-Uhlenbeck process in order to obtain (i) an approximation of the probability density function of the inter-spike intervals in one-way-type interaction and (ii) an approximation of the tail of the probability density function of the inter-spike intervals in the mutual interaction. Such an approximation is admissible for small instantaneous firing rates of both neurons.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Action Potentials / physiology*
  • Humans
  • Models, Neurological*
  • Neurons / physiology*
  • Normal Distribution
  • Stochastic Processes
  • Synaptic Membranes / physiology*