dorsal/arxiv
View SchemaMarkov analysis of stochastic resonance in a periodically driven integrate-fire neuron
| Authors | Hans E. Plesser, Theo Geisel |
|---|---|
| Categories | |
| ArXiv ID | physics/9810019 |
| URL | https://arxiv.org/abs/physics/9810019 |
| DOI | 10.1103/PhysRevE.59.7008 |
| Journal | Phys Rev E 59:7008-7017 (1999) |
Abstract
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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"abstract": "We model the dynamics of the leaky integrate-fire neuron under periodic\nstimulation as a Markov process with respect to the stimulus phase. This avoids\nthe unrealistic assumption of a stimulus reset after each spike made in earlier\nwork and thus solves the long-standing reset problem. The neuron exhibits\nstochastic resonance, both with respect to input noise intensity and stimulus\nfrequency. The latter resonance arises by matching the stimulus frequency to\nthe refractory time of the neuron. The Markov approach can be generalized to\nother periodically driven stochastic processes containing a reset mechanism.",
"arxiv_id": "physics/9810019",
"authors": [
"Hans E. Plesser",
"Theo Geisel"
],
"categories": [
"physics.bio-ph",
"q-bio"
],
"doi": "10.1103/PhysRevE.59.7008",
"journal_ref": "Phys Rev E 59:7008-7017 (1999)",
"title": "Markov analysis of stochastic resonance in a periodically driven integrate-fire neuron",
"url": "https://arxiv.org/abs/physics/9810019"
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