Markov analysis of stochastic resonance in a periodically driven integrate-fire neuron

Details Markov analysis of stochastic resonance in a periodically driven integrate-fire neuron Markov analysis of stochastic resonance in a periodically driven integrate-fire neuron

1998-10-12

arxiv.org/abs/physics/9810019v1

Phys Rev E 59:7008-7017 (1999)

Physics

Biological Physics

23 pages, 10 figures

Scientific paper

10.1103/PhysRevE.59.7008

We model the dynamics of the leaky integrate-fire neuron under periodic stimulation as a Markov process with respect to the stimulus phase. This avoids the unrealistic assumption of a stimulus reset after each spike made in earlier work and thus solves the long-standing reset problem. The neuron exhibits stochastic resonance, both with respect to input noise intensity and stimulus frequency. The latter resonance arises by matching the stimulus frequency to the refractory time of the neuron. The Markov approach can be generalized to other periodically driven stochastic processes containing a reset mechanism.

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