Switching Time Statistics for Driven Neuron Models: Analytic Expressions versus Numerics
Neurons and Cognition
2007-05-23 v2 Disordered Systems and Neural Networks
Statistical Mechanics
Adaptation and Self-Organizing Systems
Abstract
Analytical 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.
Cite
@article{arxiv.q-bio/0401015,
title = {Switching Time Statistics for Driven Neuron Models: Analytic Expressions versus Numerics},
author = {Michael Schindler and Peter Talkner and Peter Hänggi},
journal= {arXiv preprint arXiv:q-bio/0401015},
year = {2007}
}
Comments
4 pages, 4 figures, RevTeX4 used, final version