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Connectivity Dynamics of Interictal Epileptiform Activity

机译:嵌入性癫痫型活动的连通动力学

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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.
机译:在记录的脑电图(EEG)中探讨了剧本癫痫型活性的膜状癫痫型活性,例如尖锐的波,尖峰,尖峰波复合物,以衡量不同的功能连通动态,并评估它们如何受到类型的影响癫痫发作。通过采用非线性数据驱动方法而获得的头皮电极之间的相位同步表示连接措施。使用图形理论分析研究了这些嵌入癫痫活动。通过考虑四个主要脑区(前部区域,后部区域,左半球和右半球)的连接数来进行连接图。结果显示了连接图的有趣和不同的网络拓扑。此外,观察到记录的癫痫活动的连接模式与癫痫发作类型之间的关系。通过对尖锐波浪和尖峰活动的连续性模式的差异(ANOVA)分析统计学证实,这与焦点癫痫(尖锐癫痫患者相比)与与之相关联的尖峰波和波动波复合物相反广义癫痫(p值= 0)。这些结果增加了诊断前景,通过基于EEG的连通图来增强疾病类型的识别。

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