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Complex self-sustained oscillation patterns in modular excitable networks

机译:复杂的自持续振荡模式,模块化可易激的网络

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We study the relationship between the modularity of scale-free excitable networks and their ability to support self-sustained oscillation patterns. We find that the probability for a network of given degree-distribution exponent to be able to support self-sustained oscillations is strongly affected by its modularity. In addition, both high- and low-modularity networks are more likely to exhibit long-period oscillation patterns than those with intermediate modularity, but the degrees of complexity and correlation in these two cases are different. The long-period oscillations cannot be explained by a minimum-length Winfree loop, but instead arise from the interplay between two or more propagating waves. Finally, we introduce an improved method that can be used to analyze the structure of the self-sustained oscillation sources at different levels of detail and show that the period of the oscillation pattern is statistically correlated with the fraction of modules that are part of the oscillation source.
机译:我们研究了无规模的可激发网络的模块化与其支持自持续振荡模式的能力之间的关系。我们发现,给定程度分布指数网络能够支持自持续振荡的网络的概率受到模块化的强烈影响。另外,高模块化网络均比具有中间模块化的长期振荡模式更有可能表现出长期振荡模式,但这两种情况下的复杂性和相关性不同。长周期振荡无法通过最小长度的WinFree循环解释,而是从两个或更多个传播波之间的相互作用中出现。最后,我们介绍了一种改进的方法,可以用于分析不同水平的细节的自持振荡源的结构,并表明振荡模式的时期与作为振荡的一部分的模块的分数统计相关来源。

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