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癫痫亚型的默认模式的时变特征分析。

Temporal variability profiling of the default mode across epilepsy subtypes.

机构信息

The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.

MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, China.

出版信息

Epilepsia. 2021 Jan;62(1):61-73. doi: 10.1111/epi.16759. Epub 2020 Nov 25.

Abstract

OBJECTIVE

Epilepsies are a group of neurological disorders sharing certain core features, but also demonstrate remarkable pathogenic and symptomatic heterogeneities. Various subtypes of epilepsy have been identified with abnormal shift in the brain default mode network (DMN). This study aims to evaluate the fine details of shared and distinct alterations in the DMN among epileptic subtypes.

METHODS

We collected resting-state functional magnetic resonance imaging (MRI) data from a large epilepsy sample (n = 371) at a single center, including temporal lobe epilepsy (TLE), frontal lobe epilepsy (FLE), and genetic generalized epilepsy with generalized tonic-clonic seizures (GGE-GTCS), as well as healthy controls (HC, n = 150). We analyzed temporal dynamics profiling of the DMN, including edge-wise and node-wise temporal variabilities, and recurrent dynamic states of functional connectivity, to identify abnormalities common to epilepsies as well as those specific to each subtype.

RESULTS

The analyses revealed that hypervariable edges within the specific DMN subsystem were shared by all subtypes (all P  < .005), and deficits in node-wise temporal variability were prominent in TLE (all t ≤ 2.51, P  < .05) and FLE (all t ≤ -2.65, P  < .05) but relatively weak in GGE-GTCS. Moreover, dynamic states were generally less stable in patients than controls (all P's < .001).

SIGNIFICANCE

Collectively, these findings demonstrated general DMN abnormalities common to different epilepsies as well as distinct dysfunctions to subtypes, and provided insights into understanding the relationship of pathophysiological mechanisms and brain connectivity.

摘要

目的

癫痫是一组具有某些核心特征的神经障碍,但也表现出明显的发病机制和症状异质性。各种类型的癫痫已经被确定与大脑默认模式网络(DMN)的异常转移有关。本研究旨在评估癫痫亚型之间 DMN 共享和独特改变的细微差别。

方法

我们在一个单一中心收集了来自大型癫痫样本(n=371)的静息状态功能磁共振成像(MRI)数据,包括颞叶癫痫(TLE)、额叶癫痫(FLE)和具有全身性强直阵挛发作的遗传性全面性癫痫(GGE-GTCS),以及健康对照组(HC,n=150)。我们分析了 DMN 的时间动态特征,包括边缘和节点的时间变异性,以及功能连接的反复动态状态,以确定癫痫共有的异常以及每个亚型特有的异常。

结果

分析表明,所有亚型共有的特定 DMN 子系统中的高变边缘(均 P <.005),以及节点层面时间变异性的缺陷在 TLE(均 t ≤ 2.51,P <.05)和 FLE(均 t ≤ -2.65,P <.05)中更为明显,但在 GGE-GTCS 中相对较弱。此外,患者的动态状态通常不如对照组稳定(均 P's<.001)。

意义

总的来说,这些发现表明不同癫痫之间存在一般的 DMN 异常以及对亚型的独特功能障碍,并为理解病理生理机制和大脑连接之间的关系提供了深入了解。

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