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在非快速眼动睡眠和清醒期间,叶的网络变化

I Rigoni¹, B J Vorderwülbecke², M Carboni¹

¹EEG and Epilepsy Unit, University Hospital and Faculty of Medicine of Geneva, University of Geneva, Switzerland.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology

|February 9, 2024

概括

叶 (TLE) 改变了大脑网络,特别是在清醒期间. 这些网络变化,在清醒时更容易检测到,可能表明一种病态的大脑状态.

科学领域:

神经科学是一个神经科学.
的研究研究.
大脑网络分析脑网络分析

背景情况:

叶 (TLE) 是一种常见的神经疾病.
了解TLE对大脑功能的影响,尤其是在睡眠和清醒等不同警觉状态期间,至关重要.
脑电图 (EEG) 提供了关于大脑活动和网络动态的宝贵见解.

研究的目的:

研究睡眠和清醒对TLE患者大脑网络改变的影响.
为了在不同警觉状态下比较TLE患者和健康对照者 (HC) 之间的大脑网络特征.
探索网络变化与睡眠和清醒期间发作的关系.

主要方法:

从23名TLE患者和HC在NREM睡眠阶段2 (N2) 和清醒期间收集了高密度EEG数据.
对EEG信号的来源重建发现了72个大脑区域的活性.
网络集成和分离 (全球效率,平均集群系数) 被计算并比较了各组和各州.

主要成果:

与对照组相比,TLE患者的全球网络集成程度 (delta GE,delta avgCC,theta avgCC) 高于对照组,独立于警状态.
在清醒状态下,TLE患者与对照组相比,以及与他们自己的N2状态相比,显示出更高的theta全局效率 (GE).
在TLE中,网络变化在清醒期间更明显,并且与清醒期间的发作比例相关.

结论:

在TLE中,大脑网络的变化在清醒期间更为突出和可检测,特别是在较低的频率 (delta,theta) 中.
观察到的网络集成和分离的增加表明TLE.的病态"小世界"大脑网络配置.
这些发现强调了在评估TLE中大脑网络功能障碍时考虑警觉状态的重要性.

关键词:

大脑网络大脑网络这是一个EEGEEGEEGEEGEEGEEGEEG.功能连接性的功能连接性.NREM 睡眠第二阶段时间叶发作时间叶.

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