Effects of spiketimedependent plasticity on the stochastic resonance of smallworld neuronal networks
Abstract
The phenomenon of stochastic resonance in NewmanWatts smallworld neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spiketimedependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient for the transmission of weak external signal in smallworld neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via finetuning of the average coupling strength of the adaptive network. Furthermore, the smallworld topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noiseinduced transmission of weak periodic signal peaks.
 Authors:
 School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)
 Publication Date:
 OSTI Identifier:
 22351010
 Resource Type:
 Journal Article
 Resource Relation:
 Journal Name: Chaos (Woodbury, N. Y.); Journal Volume: 24; Journal Issue: 3; Other Information: (c) 2014 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
 Country of Publication:
 United States
 Language:
 English
 Subject:
 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; COUPLING; NERVE CELLS; NEURAL NETWORKS; NOISE; PERIODICITY; PLASTICITY; RESONANCE; SIGNALS; STOCHASTIC PROCESSES; TIME DEPENDENCE; TOPOLOGY
Citation Formats
Yu, Haitao, Guo, Xinmeng, Wang, Jiang, Email: jiangwang@tju.edu.cn, Deng, Bin, and Wei, Xile. Effects of spiketimedependent plasticity on the stochastic resonance of smallworld neuronal networks. United States: N. p., 2014.
Web. doi:10.1063/1.4893773.
Yu, Haitao, Guo, Xinmeng, Wang, Jiang, Email: jiangwang@tju.edu.cn, Deng, Bin, & Wei, Xile. Effects of spiketimedependent plasticity on the stochastic resonance of smallworld neuronal networks. United States. doi:10.1063/1.4893773.
Yu, Haitao, Guo, Xinmeng, Wang, Jiang, Email: jiangwang@tju.edu.cn, Deng, Bin, and Wei, Xile. Mon .
"Effects of spiketimedependent plasticity on the stochastic resonance of smallworld neuronal networks". United States.
doi:10.1063/1.4893773.
@article{osti_22351010,
title = {Effects of spiketimedependent plasticity on the stochastic resonance of smallworld neuronal networks},
author = {Yu, Haitao and Guo, Xinmeng and Wang, Jiang, Email: jiangwang@tju.edu.cn and Deng, Bin and Wei, Xile},
abstractNote = {The phenomenon of stochastic resonance in NewmanWatts smallworld neuronal networks is investigated when the strength of synaptic connections between neurons is adaptively adjusted by spiketimedependent plasticity (STDP). It is shown that irrespective of the synaptic connectivity is fixed or adaptive, the phenomenon of stochastic resonance occurs. The efficiency of network stochastic resonance can be largely enhanced by STDP in the coupling process. Particularly, the resonance for adaptive coupling can reach a much larger value than that for fixed one when the noise intensity is small or intermediate. STDP with dominant depression and small temporal window ratio is more efficient for the transmission of weak external signal in smallworld neuronal networks. In addition, we demonstrate that the effect of stochastic resonance can be further improved via finetuning of the average coupling strength of the adaptive network. Furthermore, the smallworld topology can significantly affect stochastic resonance of excitable neuronal networks. It is found that there exists an optimal probability of adding links by which the noiseinduced transmission of weak periodic signal peaks.},
doi = {10.1063/1.4893773},
journal = {Chaos (Woodbury, N. Y.)},
number = 3,
volume = 24,
place = {United States},
year = {Mon Sep 01 00:00:00 EDT 2014},
month = {Mon Sep 01 00:00:00 EDT 2014}
}

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