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

1989/01/01 by Hans E. Plesser, Jane Close Conoley, Theo Geisel +3 · 2 citations
Biochemistry, Genetics and Molecular Biology · Neuroscience · Physics and Astronomy · Psychology · #Diffusion and Search Dynamics #Educational and Psychological Assessments #Neural dynamics and brain function #physics.bio-ph #q-bio #stochastic dynamics and bifurcation

paper · pdf · doi:10.1103/physreve.59.7008

published as Phys Rev E 59:7008-7017 (1999) · 23 pages, 10 figures

arxiv created 1998/10/12 · openalex publication_date 1999/06/01 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28

Abstract

We model the dynamics of the leaky integrate-and-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 papers 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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