Gong Yubing, Hao Yinghang, Xie Yanhang, Ma Xiaoguang, Yang Chuanlu
School of Physics and Electronic Engineering, Ludong University, Yantai, Shandong 264025, PR China.
Biophys Chem. 2009 Sep;144(1-2):88-93. doi: 10.1016/j.bpc.2009.07.001. Epub 2009 Jul 10.
In this paper, we numerically study how the NGN's deviation q from Gaussian noise (q=1) affects the spike coherence and synchronization of 60 coupled Hodgkin-Huxley (HH) neurons driven by a periodic sinusoidal stimulus on random complex networks. It is found that the effect of the deviation depends on the network randomness p (the fraction of random shortcuts): for larger p (p>0.15), the spiking regularity keeps being improved with increasing q; while, for smaller p (p< 0.15), the spiking regularity can reach the best performance at an optimal intermediate q value, indicating the occurrence of "deviation-optimized spike coherence". The synchronization becomes enhanced with decreasing q, and the enhancing extent for a random HH neuron network is stronger than for a regular one. These behaviors show that the spike coherence and synchronization of the present HH neurons on random networks can be more strongly enhanced by various other types of external noise than by Gaussian noise, whereby the neuron firings may behave more periodically in time and more synchronously in space. Our results provide the constructive roles of the NGN on the spiking activity of the present system of HH neuron networks.
在本文中，我们通过数值模拟研究了非高斯噪声（NGN）与高斯噪声的偏差q（q = 1）如何影响由周期性正弦刺激驱动的随机复杂网络上60个耦合霍奇金 - 赫胥黎（HH）神经元的放电相干性和同步性。研究发现，偏差的影响取决于网络随机性p（随机捷径的比例）：对于较大的p（p> 0.15），随着q的增加，放电规律性持续提高；而对于较小的p（p <0.15），放电规律性在最优的中间q值时可达到最佳性能，表明出现了“偏差优化的放电相干性”。同步性随着q的减小而增强，并且随机HH神经元网络的增强程度比规则网络更强。这些行为表明，与高斯噪声相比，各种其他类型的外部噪声可以更强烈地增强当前随机网络上HH神经元的放电相干性和同步性，从而使神经元放电在时间上可能表现得更具周期性，在空间上更具同步性。我们的结果揭示了非高斯噪声对当前HH神经元网络系统放电活动的建设性作用。
