文献类型：期刊文献

英文题名：Noise and Synchronization Analysis of the Cold-Receptor Neuronal Network Model

作者：Du, Ying[1];Wang, Rubin[1];Qu, Jingyi[2]

机构：[1]E China Univ Sci & Technol, Sch Sci, Inst Cognit Neurodynam, Shanghai 200237, Peoples R China;[2]Civil Aviat Univ China, Sch Informat Sci & Technol, Tianjin 300300, Peoples R China

年份：2014

卷号：2014

外文期刊名：DISCRETE DYNAMICS IN NATURE AND SOCIETY

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000338062700001)】；

基金：This work was supported by the National Natural Science Foundation of China (Grant nos. 11002055, 11232005, and U1204106) and the Special Fund of Civil Aviation University of China nos. 2012QD09X and ZXH2012C004.

语种：英文

摘要：This paper analyzes the dynamics of the cold receptor neural network model. First, it examines noise effects on neuronal stimulus in the model. From ISI plots, it is shown that there are considerable differences between purely deterministic simulations and noisy ones. The ISI-distance is used to measure the noise effects on spike trains quantitatively. It is found that spike trains observed in neural models can be more strongly affected by noise for different temperatures in some aspects; meanwhile, spike train has greater variability with the noise intensity increasing. The synchronization of neuronal network with different connectivity patterns is also studied. It is shown that chaotic and high period patterns are more difficult to get complete synchronization than the situation in single spike and low period patterns. The neuronal network will exhibit various patterns of firing synchronization by varying some key parameters such as the coupling strength. Different types of firing synchronization are diagnosed by a correlation coefficient and the ISI-distance method. The simulations show that the synchronization status of neurons is related to the network connectivity patterns.