Extreme events in locally coupled bursting neurons

Ardhanareeswaran R Sree, Sudharsan S, Senthilvelan M, Dibakar Ghosh
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Abstract

We report a new mechanism through which extreme events with a dragon king-like distribution emerge in a network of locally coupled Hindmarsh-Rose bursting neurons. We establish and substantiate the fact that depending on the choice of initial conditions, the neurons in the network are divided into clusters and whenever these clusters are phase synchronized intermittently, extreme events originate in the collective observable. This mechanism, which we name as intermittent cluster synchronization is proposed as the new precursor for the generation of extreme events in this system. These results are also true for electrical diffusive coupling. The distribution of the local maxima shows long tailed non-Gaussian while the interevent interval follows the Weibull distribution. The goodness of fit are corroborated using probability-probability plot and quantile-quantile plot. These extreme events become rarer and rarer with the increase in the number of different initial conditions.
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局部耦合突发性神经元中的极端事件
我们报告了一种新的机制,通过这种机制,局部耦合的辛德马什-罗斯勃兴神经元网络中出现了类似龙王分布的极端事件。我们建立并证实了这样一个事实:根据初始条件的选择,网络中的神经元会被分成若干个簇,每当这些簇间歇性地进行相位同步时,极端事件就会在集体观测中产生。这种机制被称为间歇性群同步,是该系统中极端事件产生的新前兆。这些结果同样适用于电扩散耦合。局部最大值的分布呈现长尾非高斯分布,而事件间期则遵循威布尔分布。概率-概率图和量子-量子图证实了拟合的良好性。随着不同初始条件数量的增加,这些极端事件变得越来越罕见。
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