Resting-state Electroencephalography Microstates Correlate with Pain Intensity in Patients with Complex Regional Pain Syndrome.

Clinical EEG and neuroscience Pub Date : 2024-01-01 Epub Date: 2023-10-16 DOI:10.1177/15500594231204174
Michihiro Osumi, Masahiko Sumitani, Katsuyuki Iwatsuki, Minoru Hoshiyama, Ryota Imai, Shu Morioka, Hitoshi Hirata
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Abstract

Objective: Severe pain and other symptoms in complex regional pain syndrome (CRPS), such as allodynia and hyperalgesia, are associated with abnormal resting-state brain network activity. No studies to date have examined resting-state brain networks in CRPS patients using electroencephalography (EEG), which can clarify the temporal dynamics of brain networks. Methods: We conducted microstate analysis using resting-state EEG signals to prospectively reveal direct correlations with pain intensity in CRPS patients (n = 17). Five microstate topographies were fitted back to individual CRPS patients' EEG data, and temporal microstate measures were subsequently calculated. Results: Our results revealed five distinct microstates, termed microstates A to E, from resting EEG data in patients with CRPS. Microstates C, D and E were significantly correlated with pain intensity before pain treatment. Particularly, microstates D and E were significantly improved together with pain alleviation after pain treatment. As microstates D and E in the present study have previously been related to attentional networks and the default mode network, improvement in these networks might be related to pain relief in CRPS patients. Conclusions: The functional alterations of these brain networks affected the pain intensity of CRPS patients. Therefore, EEG microstate analyses may be used to identify surrogate markers for pain intensity.

复杂区域疼痛综合征患者静息状态脑电图微观状态与疼痛强度的相关性。
目的:复杂区域疼痛综合征(CRPS)的严重疼痛和其他症状,如异常性疼痛和痛觉过敏,与静息状态脑网络活动异常有关。迄今为止,没有任何研究使用脑电图(EEG)检查CRPS患者的静息状态脑网络,这可以阐明脑网络的时间动力学。方法:我们使用静息状态脑电图信号进行微观状态分析,前瞻性地揭示CRPS患者(n = 17) 。将五个微观状态拓扑图拟合回单个CRPS患者的脑电图数据,随后计算时间微观状态测量值。结果:我们的研究结果揭示了CRPS患者静息脑电图数据中五种不同的微观状态,称为微观状态A至E。显微状态C、D和E与疼痛治疗前的疼痛强度显著相关。特别是,在疼痛治疗后,微状态D和E与疼痛缓解一起显著改善。由于本研究中的微观状态D和E以前与注意力网络和默认模式网络有关,这些网络的改善可能与CRPS患者的疼痛缓解有关。结论:这些脑网络的功能改变影响CRPS患者的疼痛强度。因此,脑电图微观状态分析可用于识别疼痛强度的替代标记。
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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