Noise in integrate-and-fire neurons: from stochastic input to escape rates

Neural Comput. 2000 Feb;12(2):367-84. doi: 10.1162/089976600300015835.

Abstract

We analyze the effect of noise in integrate-and-fire neurons driven by time-dependent input and compare the diffusion approximation for the membrane potential to escape noise. It is shown that for time-dependent subthreshold input, diffusive noise can be replaced by escape noise with a hazard function that has a gaussian dependence on the distance between the (noise-free) membrane voltage and threshold. The approximation is improved if we add to the hazard function a probability current proportional to the derivative of the voltage. Stochastic resonance in response to periodic input occurs in both noise models and exhibits similar characteristics.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Membrane Potentials / physiology
  • Models, Neurological
  • Neural Networks, Computer*
  • Neurons / physiology*
  • Normal Distribution
  • Stochastic Processes*