arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2009.09830nlin.AO
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多重神经网络相干共振的控制

Control of coherence resonance in multiplex neural networks

M. Masoliver, C. Masoller, A. Zakharova

摘要:

我们研究了两个神经元群体的动力学弱,相互耦合的多环配置。我们用随机FitzHugh-Nagumo(FHN)模型模拟神经元的活动。这两个神经元群体感知不同水平的噪声:一个群体表现出由阈上噪声诱导的尖峰活动(第1层),而另一个群体在没有层间耦合的情况下是沉默的,因为它自己的噪声水平是阈下的(第2层)。我们发现,适当的水平的噪声在第1层,弱层间耦合可以诱导相干共振(CR),反相干共振(ACR)和逆随机共振(ISR)在第2层。我们还发现,少量的随机分布的层间链路是足以引起这些现象在第2层。我们的结果适用于小型和大型神经元群体。

英文摘要:

We study the dynamics of two neuronal populations weakly and mutually coupled in a multiplexed ring configuration. We simulate the neuronal activity with the stochastic FitzHugh-Nagumo (FHN) model. The two neuronal populations perceive different levels of noise: one population exhibits spiking activity induced by supra-threshold noise (layer 1), while the other population is silent in the absence of inter-layer coupling because its own level of noise is sub-threshold (layer 2). We find that, for appropriate levels of noise in layer 1, weak inter-layer coupling can induce coherence resonance (CR), anti-coherence resonance (ACR) and inverse stochastic resonance (ISR) in layer 2. We also find that a small number of randomly distributed inter-layer links are sufficient to induce these phenomena in layer 2. Our results hold for small and large neuronal populations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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