Switching Time Statistics for Driven Neuron Models: Analytic Expressions versus Numerics

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dc.creatorSchindler, Michael
dc.creatorTalkner, Peter
dc.creatorHänggi, Peter
dc.date2004-01-10
dc.date2006-01-09
dc.date.accessioned2026-07-07T06:36:23Z
dc.date.available2026-07-07T06:36:23Z
dc.descriptionAnalytical 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.
dc.description4 pages, 4 figures, RevTeX4 used, final version
dc.identifierhttps://arxiv.org/abs/q-bio/0401015
dc.identifierhttp://arxiv.org/abs/q-bio/0401015
dc.identifierPhys. Rev. Lett 93 (2004) 048102
dc.identifierdoi:10.1103/PhysRevLett.93.048102
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/100064
dc.subjectNeurons and Cognition
dc.subjectDisordered Systems and Neural Networks
dc.subjectStatistical Mechanics
dc.subjectAdaptation and Self-Organizing Systems
dc.titleSwitching Time Statistics for Driven Neuron Models: Analytic Expressions versus Numerics
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