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题名: Time Delay and Long-Range Connection Induced Synchronization Transitions in Newman-Watts Small-World Neuronal Networks
作者: Qian, Y
刊名: PLOS ONE
出版日期: 2014
卷号: 9, 期号:5, 页码:e96415
关键词: COMPLEX NETWORKS ;  OSCILLATIONS ;  SYNAPSES ;  MODEL
学科分类: Physics
DOI: 10.1371/journal.pone.0096415
通讯作者: Qian, Y (reprint author), Baoji Univ Arts & Sci, Nonlinear Res Inst, Baoji, Peoples R China.
部门归属: [Qian, Yu] Baoji Univ Arts & Sci, Nonlinear Res Inst, Baoji, Peoples R China
英文摘要: The synchronization transitions in Newman-Watts small-world neuronal networks (SWNNs) induced by time delay tau and long-range connection (LRC) probability P have been investigated by synchronization parameter and space-time plots. Four distinct parameter regions, that is, asynchronous region, transition region, synchronous region, and oscillatory region have been discovered at certain LRC probability P = 1: 0 as time delay is increased. Interestingly, desynchronization is observed in oscillatory region. More importantly, we consider the spatiotemporal patterns obtained in delayed Newman-Watts SWNNs are the competition results between long-range drivings (LRDs) and neighboring interactions. In addition, for moderate time delay, the synchronization of neuronal network can be enhanced remarkably by increasing LRC probability. Furthermore, lag synchronization has been found between weak synchronization and complete synchronization as LRC probability P is a little less than 1.0. Finally, the two necessary conditions, moderate time delay and large numbers of LRCs, are exposed explicitly for synchronization in delayed Newman-Watts SWNNs.
资助者: National Natural Science Foundation of China [11105003]; Natural Science Foundation of the Education Bureau of Shaanxi Province of China [2013JK0619]
收录类别: SCI
原文出处: 查看原文
语种: 英语
WOS记录号: WOS:000338213300033
Citation statistics: 
内容类型: 期刊论文
URI标识: http://ir.itp.ac.cn/handle/311006/15764
Appears in Collections:理论物理所2014年知识产出 _期刊论文

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Recommended Citation:
Qian, Y. Time Delay and Long-Range Connection Induced Synchronization Transitions in Newman-Watts Small-World Neuronal Networks[J]. PLOS ONE,2014,9(5):e96415.
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