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癫痫发作时功能性脑网络中的关联混合。

Assortative mixing in functional brain networks during epileptic seizures.

机构信息

Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Straße 38, 01187 Dresden, Germany.

出版信息

Chaos. 2013 Sep;23(3):033139. doi: 10.1063/1.4821915.

Abstract

We investigate assortativity of functional brain networks before, during, and after one-hundred epileptic seizures with different anatomical onset locations. We construct binary functional networks from multi-channel electroencephalographic data recorded from 60 epilepsy patients; and from time-resolved estimates of the assortativity coefficient, we conclude that positive degree-degree correlations are inherent to seizure dynamics. While seizures evolve, an increasing assortativity indicates a segregation of the underlying functional network into groups of brain regions that are only sparsely interconnected, if at all. Interestingly, assortativity decreases already prior to seizure end. Together with previous observations of characteristic temporal evolutions of global statistical properties and synchronizability of epileptic brain networks, our findings may help to gain deeper insights into the complicated dynamics underlying generation, propagation, and termination of seizures.

摘要

我们研究了 60 名癫痫患者多通道脑电图数据,在 100 次癫痫发作前后,分析了不同解剖起始部位的功能性脑网络的同配性。我们从时间分辨的配分系数估计中得出结论,正度-度相关性是癫痫动力学的固有特征。随着癫痫发作的进展,同配性的增加表明潜在的功能网络逐渐分离成只有稀疏连接的脑区组,如果有的话。有趣的是,同配性在癫痫发作结束前就已经降低了。结合之前对癫痫网络的全局统计特性和同步性的特征时间演化的观察,我们的发现可能有助于深入了解癫痫发作产生、传播和终止背后的复杂动力学。

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