癫痫样活动间期的连通性动力学

H. Rajaei, M. Cabrerizo, Panuwat Janwattanapong, Alberto Pinzon-Ardila, S. Gonzalez-Arias, A. Barreto, M. Adjouadi
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引用次数: 6

摘要

在记录的脑电图(EEG)中探索了间期癫痫样活动的模式,如尖波、尖峰、尖峰波复合体和多尖峰波复合体,以衡量不同的功能连接动态,并评估它们如何受到癫痫发作类型的影响。连接度量由头皮电极间的相位同步表示,该相位同步是采用非线性数据驱动方法获得的。利用图论分析对这些间歇癫痫活动进行了研究。通过考虑大脑四个主要区域(前区、后区、左半球和右半球)的连接数量来比较连接图。结果揭示了连接图的有趣和不同的网络拓扑。此外,还观察了记录的癫痫活动的连接模式与癫痫发作类型之间的关系。这一关系通过方差分析(ANOVA)得到了统计学上的证实,表明局灶性癫痫中观察到的尖波和尖峰活动的连接模式与与全局性癫痫相关的尖峰波和多尖峰波复合物之间存在显著差异(p值= 0)。这些结果增加了诊断的前景,并增强了通过基于脑电图的连接图对疾病类型的识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Connectivity Dynamics of Interictal Epileptiform Activity
Patterns of interictal epileptiform activities, such as sharp waves, spikes, spike-wave complexes and polyspike-wave complexes are explored in the recorded electroencephalograms (EEG) to gauge the different functional connectivity dynamics and to assess how they could be affected by the type of a seizure. Connectivity measures were represented by the phase synchronization among scalp electrodes that were obtained by adopting a nonlinear data-driven method. These interictal epileptic activities were investigated using a graph theory analysis. The connectivity maps were compared by considering the number of connections in four main brain regions (anterior region, posterior region, left hemisphere and right hemisphere). Results revealed interesting and different network topology for the connectivity maps. Besides, a relationship between the connectivity patterns of the recorded epileptic activities and the types of seizures was observed. This relationship was statistically confirmed by analysis of variance (ANOVA) that denoted a significant difference among connectivity patterns of sharp waves and spike activities, which were seen in focal epilepsy, in contrast to the spike-wave and polyspike-wave complexes that were associated with generalized epilepsy (P-value = 0). These results augment the prospects for diagnosis and enhance the recognition of the disease type via EEG-based connectivity maps.
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