Department of Dynamics and Control, Beihang University, Beijing, 100191 China ; School of Mathematics and Computer Science, Fujian Normal University, Fuzhou, 350007 China.
Department of Dynamics and Control, Beihang University, Beijing, 100191 China.
Cogn Neurodyn. 2014 Apr;8(2):143-9. doi: 10.1007/s11571-013-9257-x. Epub 2013 May 28.
The effects of noise on patterns and collective phenomena are studied in a small-world neuronal network with the dynamics of each neuron being described by a two-dimensional Rulkov map neuron. It is shown that for intermediate noise levels, noise-induced ordered patterns emerge spatially, which supports the spatiotemporal coherence resonance. However, the inherent long range couplings of small-world networks can effectively disrupt the internal spatial scale of the media at small fraction of long-range couplings. The temporal order, characterized by the autocorrelation of a firing rate function, can be greatly enhanced by the introduction of small-world connectivity. There exists an optimal fraction of randomly rewired links, where the temporal order and synchronization can be optimized.
研究了噪声对具有二维 Rulkov 映射神经元动力学的小世界神经元网络中模式和集体现象的影响。结果表明，对于中等噪声水平，空间上会出现噪声诱导的有序模式，这支持了时空相干共振。然而，小世界网络的固有长程耦合可以有效地破坏介质的内部空间尺度，其长程耦合的分数很小。通过引入小世界连接，可以大大增强由点火率函数的自相关所表示的时间顺序。存在一个最优的随机重连链路分数，在这个分数下可以优化时间顺序和同步。
