Effects of coupling strength and network topology on signal detection in small-world neuronal networks

被引:1
作者
Xiaojuan Sun
Zhaofan Liu
Matjaž Perc
机构
[1] Beijing University of Posts and Telecommunications,School of Science
[2] University of Maribor,Faculty of Natural Sciences and Mathematics
[3] University of Maribor,CAMTP–Center for Applied Mathematics and Theoretical Physics
[4] Complexity Science Hub,undefined
来源
Nonlinear Dynamics | 2019年 / 96卷
关键词
Neuronal network; Small-world network; Multiple stochastic resonance; Signal detection;
D O I
暂无
中图分类号
学科分类号
摘要
We study the effects of different coupling strengths and network topologies on signal detection in small-world neuronal networks. Research has previously revealed that the ability of detecting subthreshold signals could be significantly enhanced by appropriately fine-tuning the noise intensity. Here we show that the coupling strength and the structure of the underlying network can also lead toward enhanced signal detection. In particular, we show that there are two levels of the coupling strength at which the subthreshold signal can be detected at an appropriate noise intensity and network structure. We also show that the network structure has little impact on signal detection if the coupling is weak. On the other hand, for intermediate coupling strengths, we show that the shorter the average path length, the better the signal detection. Finally, if the coupling is strong, we show that there exists an intermediate average path length at which signal detection becomes optimal.
引用
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页码:2145 / 2155
页数:10
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