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迷走神经刺激周期改变耐药性癫痫患者的脑电图连接:基于图论指标的研究。

Vagal nerve stimulation cycles alter EEG connectivity in drug-resistant epileptic patients: A study with graph theory metrics.

机构信息

Neurorehabilitation Department, IRCCS Istituti Clinici Scientifici Salvatore Maugeri di Milano, 20138 Milan, Italy.

Università Campus-Biomedico di Roma, Neurology and Neurophysiology Unit, Italy.

出版信息

Clin Neurophysiol. 2022 Oct;142:59-67. doi: 10.1016/j.clinph.2022.07.503. Epub 2022 Aug 5.

Abstract

OBJECTIVE

Vagal Nerve Stimulation (VNS) is an effective treatment for Drug-Resistant (DR) epilepsy. Albeit the corroborated effectiveness of VNS, little is known about how VNS works. We aim to leverage quantitative Electroencephalography (qEEG) to study how the brain responds to VNS cycles.

METHODS

Eighteen subjects with DR epilepsy were enrolled in our study. 64-channel EEG was recorded during VNS stimulation. Periods of stimulation (VNS), preceding (preVNS) and following stimulation (postVNS) were identified via an electrode placed on the stimulator. We used qEEG analysis to assess changes in spectral and network activity that characterize these conditions. Graph theory metrics were used to calculate differences in network connectivity.

RESULTS

No differences were found in spectral activity between preVNS, VNS, and postVNS. Graph theory showed consistent changes in network organization expressed by Small World Index (SWI), Betweenness Centrality (BtwC), and Global Efficiency (gE). These changes were most significant in the slow EEG bands.

CONCLUSIONS

In DR epilepsy, VNS has a significant effect on brain network activity, as assessed by EEG connectivity, acting on widespread network distribution rather than band-power.

SIGNIFICANCE

Our findings support the hypothesis that VNS acts on epilepsy by influencing diffuse network connectivity in the brain.

摘要

目的

迷走神经刺激(VNS)是治疗耐药性(DR)癫痫的有效方法。尽管 VNS 的疗效得到了证实,但对于其作用机制知之甚少。我们旨在利用定量脑电图(qEEG)研究大脑对 VNS 周期的反应。

方法

本研究纳入了 18 例 DR 癫痫患者。在 VNS 刺激期间记录了 64 通道 EEG。通过放置在刺激器上的电极识别刺激期(VNS)、刺激前(preVNS)和刺激后(postVNS)。我们使用 qEEG 分析来评估这些条件下的频谱和网络活动变化。使用图论指标来计算网络连接性的差异。

结果

preVNS、VNS 和 postVNS 之间的频谱活动没有差异。图论显示,小世界指数(SWI)、介数中心性(BtwC)和全局效率(gE)等网络组织的一致变化。这些变化在慢 EEG 波段最为明显。

结论

在 DR 癫痫中,VNS 通过影响大脑的广泛网络分布而非频带功率,对脑电图连接性评估的大脑网络活动有显著影响。

意义

我们的发现支持 VNS 通过影响大脑的弥散网络连接来治疗癫痫的假说。

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