Wu Yazhen, Sun Zhongkui
School of Mathematics and Statistics, Northwestern Polytechnical University, Xi'an, 710129, China.
Maths and Information Technology School, Yuncheng University, Yuncheng, 044000, China.
Sci Rep. 2024 Mar 4;14(1):5276. doi: 10.1038/s41598-024-55997-4.
This paper employs statistical complexity measure (SCM) to investigate the occurrence of stochastic multiresonance (SMR) induced by noise and time delay in small-world neural networks coupled with FitzHugh-Nagumo (FHN) neurons. Our findings reveal that SCM exhibits four local maxima at four optimal noise levels, providing evidence for the occurrence of quadruple stochastic resonances. When time delay is taken into account in the information transmission, under moderate noise levels, SCM shows several local maxima when with being a positive integer and being the period of subthreshold signal. This indicates the appearance of delay-induced SMR at the multiples of the period of subthreshold signal. Intriguingly, at low noise levels, a strong coherence between time delay and neuronal firing dynamics emerges at , as confirmed by a series of SCM maxima at these time delays. Furthermore, the study demonstrates that by adjusting the degrees and sizes of small-world networks, as well as the coupling strength, it is possible to optimize the strength of delay-induced SMR, thus maximizing the detection capability of subthreshold signal. The research results may provide us with an effective approach for understanding the role of time delay in signal detection and information transmission.
本文采用统计复杂性度量（SCM）来研究在与菲茨休 - 纳古莫（FHN）神经元耦合的小世界神经网络中，由噪声和时间延迟诱导的随机多共振（SMR）的发生情况。我们的研究结果表明，SCM在四个最佳噪声水平处呈现四个局部最大值，为四重随机共振的发生提供了证据。当在信息传输中考虑时间延迟时，在中等噪声水平下，当 （其中 为正整数， 为阈下信号的周期）时，SCM显示出几个局部最大值。这表明在阈下信号周期的倍数处出现了延迟诱导的SMR。有趣的是，在低噪声水平下，在 时，时间延迟与神经元放电动力学之间出现了很强的相关性，这在这些时间延迟处的一系列SCM最大值中得到了证实。此外，该研究表明，通过调整小世界网络的度数和大小以及耦合强度，可以优化延迟诱导的SMR的强度，从而最大化阈下信号的检测能力。研究结果可能为我们理解时间延迟在信号检测和信息传输中的作用提供一种有效方法。
