Emergent patterns in interacting neuronal sub-populations

被引:7
|
作者
Kamal, Neeraj Kumar [1 ]
Sinha, Sudeshna [2 ]
机构
[1] Inst Math Sci, Madras 600113, Tamil Nadu, India
[2] IISER, Sas Nagar, Punjab, India
关键词
Complex networks; Synchronization; SYNCHRONIZATION;
D O I
10.1016/j.cnsns.2014.09.012
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We investigate an ensemble of coupled model neurons, consisting of groups of varying sizes and intrinsic dynamics, ranging from periodic to chaotic, where the inter-group coupling interaction is effectively like a dynamic signal from a different sub-population. We observe that the minority group can significantly influence the majority group. For instance, when a small chaotic group is coupled to a large periodic group, the chaotic group de-synchronizes. However, counter-intuitively, when a small periodic group couples strongly to a large chaotic group, it leads to complete synchronization in the majority chaotic population, which also spikes at the frequency of the small periodic group. It then appears that the small group of periodic neurons can act like a pacemaker for the whole network. Further, we report the existence of varied clustering patterns, ranging from sets of synchronized clusters to anti-phase clusters, governed by the interplay of the relative sizes and dynamics of the sub-populations. So these results have relevance in understanding how a group can influence the synchrony of another group of dynamically different elements, reminiscent of even-trelated synchronization/de-synchronization in complex networks. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:314 / 320
页数:7
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