论文标题
控制多重神经网络中相干共振的控制
Control of coherence resonance in multiplex neural networks
论文作者
论文摘要
我们研究了两个神经元群体的动力学，并在多重环形构型中相互耦合。我们使用随机Fitzhugh-Nagumo（FHN）模型模拟神经元活性。两个神经元种群感知到不同水平的噪声：一个人群表现出由阈值上噪声引起的尖峰活动（第1层），而在没有层间耦合的情况下，另一个种群是沉默的，因为其自身的噪声水平是亚阈值（第2层）。我们发现，对于第1层中适当的噪声水平，较弱的层间耦合可以引起连贯的共振（CR），抗共振共振（ACR）和第2层中的逆随机共振（ISR）。我们还发现，少数随机分布的室内层链接足以在2层中诱导这些现象。
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.
