Suprathreshold stochastic resonance in neural systems tuned by correlations

Durrant, Simon and Kang, Y. and Stocks, N. and Feng, J. (2011) Suprathreshold stochastic resonance in neural systems tuned by correlations. Physical Review E, 84 (1). ISSN 1539-3755

Documents
Suprathreshold stochastic resonance in neural systems tuned by correlations
[img]
[Download]
Request a copy
[img] PDF
Suprathreshold_stochastic_resonance_in_neural_processing_tuned_by_correlation_(Durrant_2011).pdf - Whole Document
Restricted to Repository staff only

404kB

Full text URL: http://pre.aps.org/abstract/PRE/v84/i1/e011923

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:Article
Additional Information: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.
Keywords:SSR, neuronal firing, Suprathreshold stochastic resonance
Subjects:C Biological Sciences > C800 Psychology
C Biological Sciences > C850 Cognitive Psychology
C Biological Sciences > C860 Neuropsychology
Divisions:College of Social Science > School of Psychology
ID Code:4717
Deposited By: Alison Wilson
Deposited On:10 Oct 2011 21:38
Last Modified:13 Mar 2013 09:02

Repository Staff Only: item control page