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28 March 2024
 
  » arxiv » q-bio.NC/0401015

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Switching Time Statistics for Driven Neuron Models: Analytic Expressions versus Numerics
Michael Schindler ; Peter Talkner ; Peter Hänggi ;
Date 10 Dec 2003
Subject Neurons and Cognition; Disordered Systems and Neural Networks; Statistical Mechanics; Adaptation and Self-Organizing Systems | q-bio.NC cond-mat.dis-nn cond-mat.stat-mech nlin.AO
AbstractAnalytical expressions are put forward to investigate the forced spiking activity of abstract neuron models such as the driven leaky integrate-and-fire (LIF) model. The method is valid in a wide parameter regime beyond the restraining limits of weak driving (linear response) and/or weak noise. The novel approximation is based on a discrete state Markovian modeling of the full dynamics with time-dependent rates. The scheme yields very good agreement with numerical Langevin and Fokker-Planck simulations of the full non-stationary dynamics for both, the first-passage time statistics and the interspike interval (residence time) distributions.
Source arXiv, q-bio.NC/0401015
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