Altered network recruitment in multiple sclerosis patients during resting state

IF 3 3区医学 Q2 CLINICAL NEUROLOGY

Multiple sclerosis and related disorders Pub Date : 2026-05-01 Epub Date: 2026-03-03 DOI:10.1016/j.msard.2026.107111

Annika Lüttjohann , Saskia Räuber , Melanie Korsen , Alice G. Willison , Saskia Elben , Christina B. Schroeter , Tobias Ruck , Philipp Albrecht , Marc Pawlitzki , Albrecht Stroh , Nico Melzer , Thomas Budde , Sven G. Meuth

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引用次数: 0

Abstract

Background

Electroencephalography (EEG) allows a versatile recording of neuronal activity in neurological disorders. Signal analytical techniques like time-frequency analysis (TFA) can uncover latent information in the EEG of patients. Classically, EEG and TFA analysis relies on predefined frequency bands. Cluster-based permutation statistics provides an unbiased statistical comparison of high dimensional neurophysiological data, stabilizing the measured effect size and increasing the probability of uncovering the main effect present.

Methods

Resting state surface EEG recordings from 51 Multiple Sclerosis (MS) and 51 control patients were analyzed using TFA and compared by cluster-based permutation statistics. We further correlated results with disease characteristics, retinal nerve fiber layer (RNFL) thickness assessed by optical coherence tomography, evoked potentials (EPs), and neuropsychological data.

Results

We detected increased power in the low and high beta frequency bands in MS compared to control patients in a subset of recording sites. Spectral power in the high beta band of resting state EEG recorded at O1 negatively correlated with the RNFL thickness. Furthermore, differences in low and high beta power were dependent on the EP score of MS patients.

Conclusion

Our results suggest a more desynchronized EEG activity in MS patients compared to controls, correlating with clinical markers of disease severity. The findings indicate differential brain network recruitment that may be the result of compensatory mechanisms and the basis for clinical impairment in MS.

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多发性硬化症患者静息状态下网络募集的改变。

背景：脑电图（EEG）允许在神经系统疾病的神经元活动的多功能记录。信号分析技术如时频分析（TFA）可以揭示患者脑电图中的潜在信息。通常，EEG和TFA分析依赖于预定义的频带。基于聚类的排列统计提供了高维神经生理数据的无偏统计比较，稳定了测量的效应大小，增加了发现当前主要效应的概率。方法：采用TFA对51例多发性硬化症（MS）患者和51例对照组的静息状态表脑电图记录进行分析，并采用聚类排列统计进行比较。我们进一步将结果与疾病特征、光学相干断层扫描评估的视网膜神经纤维层（RNFL）厚度、诱发电位（EPs）和神经心理学数据相关联。结果：我们检测到在记录部位的一个子集中，MS患者的低频段和高频段的功率比对照患者增加。O1时静息状态脑电图高β带频谱功率与RNFL厚度呈负相关。此外，低β功率和高β功率的差异取决于MS患者的EP评分。结论：我们的研究结果表明，与对照组相比，MS患者的脑电图活动更加非同步，与疾病严重程度的临床标志物相关。研究结果表明，不同的脑网络招募可能是代偿机制的结果，也是MS临床损伤的基础。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Multiple sclerosis and related disorders CLINICAL NEUROLOGY-

CiteScore

5.80

自引率

20.00%

发文量

814

审稿时长

66 days

期刊介绍： Multiple Sclerosis is an area of ever expanding research and escalating publications. Multiple Sclerosis and Related Disorders is a wide ranging international journal supported by key researchers from all neuroscience domains that focus on MS and associated disease of the central nervous system. The primary aim of this new journal is the rapid publication of high quality original research in the field. Important secondary aims will be timely updates and editorials on important scientific and clinical care advances, controversies in the field, and invited opinion articles from current thought leaders on topical issues. One section of the journal will focus on teaching, written to enhance the practice of community and academic neurologists involved in the care of MS patients. Summaries of key articles written for a lay audience will be provided as an on-line resource. A team of four chief editors is supported by leading section editors who will commission and appraise original and review articles concerning: clinical neurology, neuroimaging, neuropathology, neuroepidemiology, therapeutics, genetics / transcriptomics, experimental models, neuroimmunology, biomarkers, neuropsychology, neurorehabilitation, measurement scales, teaching, neuroethics and lay communication.