兴奋性神经群体的非周期信息传输研究

Study of Aperiodic Information Transmission in Ensembles of Excitable Neurons

研究了FitzHugh-Nagumo(FHN)可兴奋性神经元的小世界网络模型中非周期信息传输的问题。此小世界网络模型的每个节点都是一个FHN神经元,每个神经元的输入为具有一定相关时间的高斯非周期信号,而内部噪声为强度相同但相互独立的高斯白噪声。数值结果表明,随着噪声强度的增加,输入输出信号的相关系数出现了非周期随机共振现象。连接度对于非周期信号传输性能影响有限。对于两个不同小世界网络的互相关进行了分析以期提高信息传递率。这些研究结果对于复杂系统信号处理理论具有重要意义。

A small world network of excitable FitzHugh-Nagumo （FHN） neurons for aperiodic signal transmission is studied in this paper, where each node of this small world network is a FHN neuron. Here, FHN neuronal model is driven by a common aperiodic input Gaussian signal with a certain correlated time, and independent internal Gaussian noise with zero mean and the same noise density. We numerically demonstrate that, as the internal noise density increases, the correlation coefficient of input-output signals displays aperiodic stochastic resonance effects. However, the addition of rewiring probability has small effect on the transmission of aperiodic signal through the small world network of FHN neuronal models. Finally, we analyze the correlation between outputs of two different small world networks. We argue that the present results are interesting to the signal processing theories in complex systems.