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

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Abstract

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.

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Notes

  1. Notation: A small-world network topology is applied in this paper. In order to satisfy the statistic characteristics of small-world network topology, the network size should be not too small. Usually, the network size should be larger than 100. Thus, we choose N be 200 in this paper. And for different network size N, we need to modulate value of k to keep the obtained results be preserved.

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Acknowledgements

Xiaojuan Sun thanks for the supports by the National Natural Science Foundation of China (Grant Nos. 11472061, 11772069) and the Fundamental Research Funds for the Central University (No. 2018XKJC02). Matjaž Perc acknowledges support from the Slovenian Research Agency (Grant Nos. P5-0027 and J1-7009).

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Authors and Affiliations

  1. School of Science, Beijing University of Posts and Telecommunications, Beijing, 100876, People’s Republic of China

    Xiaojuan Sun & Zhaofan Liu

  2. Faculty of Natural Sciences and Mathematics, University of Maribor, Koroška cesta 160, 2000, Maribor, Slovenia

    Matjaž Perc

  3. CAMTP–Center for Applied Mathematics and Theoretical Physics, University of Maribor, Mladinska 3, 2000, Maribor, Slovenia

    Matjaž Perc

  4. Complexity Science Hub, Josefstädterstraße 39, 1080, Vienna, Austria

    Matjaž Perc

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  1. Xiaojuan Sun
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Sun, X., Liu, Z. & Perc, M. Effects of coupling strength and network topology on signal detection in small-world neuronal networks. Nonlinear Dyn 96, 2145–2155 (2019). https://doi.org/10.1007/s11071-019-04914-w

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