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Suprathreshold stochastic resonance in neural processing tuned by correlation
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Durrant, Simon, Kang, Yanmei, Stocks, Nigel G. and Feng, Jianfeng (2011) Suprathreshold stochastic resonance in neural processing tuned by correlation. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics), Vol.84 (No.1). Article: 011923. doi:10.1103/PhysRevE.84.011923 ISSN 1539-3755.
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Official URL: http://dx.doi.org/10.1103/PhysRevE.84.011923
Abstract
Suprathreshold stochastic resonance (SSR) is examined in the context of integrate-and-fire neurons, with an emphasis on the role of correlation in the neuronal firing. We employed a model based on a network of spiking neurons which received synaptic inputs modeled by Poisson processes stimulated by a stepped input signal. The smoothed ensemble firing rate provided an output signal, and the mutual information between this signal and the input was calculated for networks with different noise levels and different numbers of neurons. It was found that an SSR effect was present in this context. We then examined a more biophysically plausible scenario where the noise was not controlled directly, but instead was tuned by the correlation between the inputs. The SSR effect remained present in this scenario with nonzero noise providing improved information transmission, and it was found that negative correlation between the inputs was optimal. Finally, an examination of SSR in the context of this model revealed its connection with more traditional stochastic resonance and showed a trade-off between supratheshold and subthreshold components. We discuss these results in the context of existing empirical evidence concerning correlations in neuronal firing.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics Q Science > QP Physiology T Technology > TA Engineering (General). Civil engineering (General) |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering Faculty of Science, Engineering and Medicine > Science > Centre for Scientific Computing |
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Library of Congress Subject Headings (LCSH): | Stochastic processes, Neural circuitry, Neural networks (Neurobiology), Neurons -- Research | ||||
Journal or Publication Title: | Physical Review E (Statistical, Nonlinear, and Soft Matter Physics) | ||||
Publisher: | American Physical Society | ||||
ISSN: | 1539-3755 | ||||
Official Date: | 25 July 2011 | ||||
Dates: |
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Volume: | Vol.84 | ||||
Number: | No.1 | ||||
Number of Pages: | 10 | ||||
Page Range: | Article: 011923 | ||||
DOI: | 10.1103/PhysRevE.84.011923 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Funder: | University of Sussex , Guo jia zi ran ke xue ji jin wei yuan hui (China) [National Natural Science Foundation (China)] (NSFC) | ||||
Grant number: | 11072182 (NSFC) |
Data sourced from Thomson Reuters' Web of Knowledge
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