Neuron firing in driven nonlinear integrate-and-fire models.

Marcin Kostur; Michael Schindler; Peter Talkner; Peter Hänggi

doi:10.1016/j.mbs.2006.08.014

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PubMed · 17011592

Neuron firing in driven nonlinear integrate-and-fire models.

Marcin Kostur·Michael Schindler·Peter Talkner·Peter Hänggi

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Abstract

Statistical properties of neuron firing are studied in the framework of a nonlinear leaky integrate-and-fire model that is driven by a slow periodic subthreshold signal. The firing events are characterized by first passage time densities. The experimentally better accessible interspike interval density generally depends on the sojourn times in a refractory state of the neuron. This aspect is not part of the integrate-and-fire model and must be modelled additionally. For a large class of refractory dynamics, a general expression for the interspike interval density is given and further evaluated for the two cases with an instantaneous resetting (i.e. no refractory state) and a refractory state possessing a deterministic lifetime. First passage time densities and interspike interval densities following from the proposed theory compare favorably with precise numerical simulations.

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Action Potentials Algorithms Animals Computer Simulation Electric Capacitance Electrophysiology Humans Markov Chains Models, Neurological Neural Conduction Neurons Nonlinear Dynamics Refractory Period, Electrophysiological Journal Article Research Support, Non-U.S. Gov't

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Marcin Kostur, Michael Schindler, Peter Talkner, Peter Hänggi. 2006-08-25. Neuron firing in driven nonlinear integrate-and-fire models.. https://doi.org/10.1016/j.mbs.2006.08.014

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