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Emergent network topology at seizure onset in humans.

机译:人体发作时出现的新兴网络拓扑。

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Epilepsy - the world's most common serious brain disorder - is defined by recurrent unprovoked seizures that result from complex interactions between distributed neural populations. We explore some macroscopic characteristics of emergent ictal networks by considering intracranial recordings from human subjects with intractable epilepsy. For each seizure, we compute a simple measure of linear coupling between all electrode pairs (more than 2400) to define networks of interdependent electrodes during preictal and ictal time intervals. We analyze these networks by applying traditional measures from network analysis and identify statistically significant global and local changes in network topology. We find at seizure onset a diffuse breakdown in global coupling, and local changes indicative of increased throughput of specific cortical and subcortical regions. We conclude that network analysis yields measures to summarize the complicated coupling topology emergent at seizure onset. Using these measures, wecan identify spatially localized brain regions that may facilitate seizures and may be potential targets for focal therapies.
机译:癫痫病是世界上最常见的严重脑部疾病,其定义是由于分布的神经种群之间复杂的相互作用而导致的反复无故发作。通过考虑难治性癫痫的人类受试者的颅内记录,我们探索了紧急的金属网络的一些宏观特征。对于每次癫痫发作,我们计算所有电极对(超过2400个)之间线性耦合的简单度量,以定义在发作前和发作后的时间间隔内相互依赖的电极网络。我们通过应用网络分析中的传统方法来分析这些网络,并确定网络拓扑中具有统计意义的全局和局部变化。我们发现癫痫发作在整体耦合中弥漫性分解,局部变化表明特定皮层和皮层下区域的通量增加。我们得出的结论是,网络分析产生了一些措施,以总结癫痫发作时出现的复杂耦合拓扑。使用这些措施,我们可以确定可能促进癫痫发作并可能成为局灶性治疗目标的空间定位的大脑区域。

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