Neuron firing in driven nonlinear integrate-and-fire models
Copyright policy )Neuron firing in driven nonlinear integrate-and-fire models
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.
- Augsburg College United States
- Universität Augsburg Germany
time dependent rates, Neurons, waiting time density, Refractory Period, Electrophysiological, Markov processes, ddc:530, Models, Neurological, Neural Conduction, Action Potentials, interspike interval density, Electric Capacitance, Markov Chains, driven nonlinear neuron models, Electrophysiology, Langevin equation, Neural biology, Nonlinear Dynamics, Animals, Humans, Computer Simulation, refractory periods, Applications of Brownian motions and diffusion theory (population genetics, absorption problems, etc.), Algorithms
time dependent rates, Neurons, waiting time density, Refractory Period, Electrophysiological, Markov processes, ddc:530, Models, Neurological, Neural Conduction, Action Potentials, interspike interval density, Electric Capacitance, Markov Chains, driven nonlinear neuron models, Electrophysiology, Langevin equation, Neural biology, Nonlinear Dynamics, Animals, Humans, Computer Simulation, refractory periods, Applications of Brownian motions and diffusion theory (population genetics, absorption problems, etc.), Algorithms
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