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纤维肌痛中的适应性和代偿性神经特征:静息态和刺激诱发脑电图振荡分析

Adaptive and Compensatory Neural Signatures in Fibromyalgia: An Analysis of Resting-State and Stimulus-Evoked EEG Oscillations.

作者信息

Camargo Lucas, Pacheco-Barrios Kevin, Marques Lucas M, Caumo Wolnei, Fregni Felipe

机构信息

Neuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA.

Unidad de Investigación para la Generación y Síntesis de Evidencias en Salud, Universidad San Ignacio de Loyola, Lima 15024, Peru.

出版信息

Biomedicines. 2024 Jun 27;12(7):1428. doi: 10.3390/biomedicines12071428.

Abstract

This study aimed to investigate clinical and physiological predictors of brain oscillatory activity in patients with fibromyalgia (FM), assessing resting-state power, event-related desynchronization (ERD), and event-related synchronization (ERS) during tasks. We performed a cross-sectional analysis, including clinical and neurophysiological data from 78 subjects with FM. Multivariate regression models were built to explore predictors of electroencephalography bands. Our findings show a negative correlation between beta oscillations and pain intensity; fibromyalgia duration is positively associated with increased oscillatory power at low frequencies and in the beta band; ERS oscillations in the theta and alpha bands seem to be correlated with better symptoms of FM; fatigue has a signature in the alpha band-a positive relationship in resting-state and a negative relationship in ERS oscillations. Specific neural signatures lead to potential clusters of neural adaptation, in which beta oscillatory activity in the resting state represents a more adaptive activity when pain levels are low and stimulus-evoked oscillations at lower frequencies are likely brain compensatory mechanisms. These neurophysiological changes may help to understand the impact of long-term chronic pain in the central nervous system and the descending inhibitory system in fibromyalgia subjects.

摘要

本研究旨在调查纤维肌痛(FM)患者脑振荡活动的临床和生理预测因素,评估静息态功率、任务期间的事件相关去同步化(ERD)和事件相关同步化(ERS)。我们进行了一项横断面分析,纳入了78名FM患者的临床和神经生理学数据。构建了多变量回归模型以探索脑电图频段的预测因素。我们的研究结果显示,β振荡与疼痛强度之间呈负相关;纤维肌痛病程与低频和β频段振荡功率增加呈正相关;θ和α频段的ERS振荡似乎与FM的较好症状相关;疲劳在α频段有特征——静息态呈正相关,ERS振荡呈负相关。特定的神经特征导致潜在的神经适应簇,其中静息态β振荡活动在疼痛水平较低时代表一种更具适应性的活动,而较低频率的刺激诱发振荡可能是大脑的补偿机制。这些神经生理学变化可能有助于理解长期慢性疼痛对纤维肌痛患者中枢神经系统和下行抑制系统的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9692/11274211/3d6743fc42ea/biomedicines-12-01428-g001.jpg

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