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Article overview
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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 | 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. | Source: | arXiv, q-bio.NC/0401015 | Services: | Forum | Review | PDF | Favorites |
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