Resonances and noise in a stochastic Hindmarsh-Rose model of thalamic neurons

Document Type

Article

Publication Date

1-1-2003

Abstract

Thalamic neurons exhibit subthreshold resonance when stimulated with small sine wave signals of varying frequency and stochastic resonance when noise is added to these signals. We study a stochastic Hindmarsh-Rose model using Monte-Carlo simulations to investigate how noise, in conjunction with subthreshold resonance, leads to a preferred frequency in the firing pattern. The resulting stochastic resonance (SR) exhibits a preferred firing frequency that is approximately exponential in its dependence on the noise amplitude. In similar experiments, frequency dependent SR is found in the reliability of detection of alpha-function inputs under noise, which are more realistic inputs for neurons. A mathematical analysis of the equations reveals that the frequency preference arises from the dynamics of the slow variable. Noise can then transfer the resonance over the firing threshold because of the proximity of the fast subsystem to a Hopf bifurcation point. Our results may have implications for the behavior of thalamic neurons in a network, with noise switching the membrane potential between different resonance modes. © 2003 Society for Mathematical Biology. Published by Elsevier Science Ltd. All rights reserved.

Identifier

0038306355 (Scopus)

Publication Title

Bulletin of Mathematical Biology

External Full Text Location

https://doi.org/10.1016/S0092-8240(03)00026-0

ISSN

00928240

PubMed ID

12875337

First Page

641

Last Page

663

Issue

4

Volume

65

Fund Ref

Canadian Institutes of Health Research

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