Magnetoencephalography reveals increased slow-to-fast alpha power ratios in patients with chronic pain

脑磁图 阿尔法(金融) 慢性疼痛 医学 心理学 临床心理学 物理疗法 神经科学 脑电图 心理测量学 结构效度
作者
Bart Witjes,Sylvain Baillet,Mathieu Roy,Robert Oostenveld,Frank J. P. M. Huygen,Cecile C. de Vos
出处
期刊:Pain reports [Wolters Kluwer]
卷期号:6 (2): e928-e928 被引量:26
标识
DOI:10.1097/pr9.0000000000000928
摘要

Objective disease markers are a key for diagnosis and personalized interventions. In chronic pain, such markers are still not available, and therapy relies on individual patients' reports. However, several pain studies have reported group-based differences in functional magnetic resonance imaging, electroencephalography, and magnetoencephalography (MEG).We aimed to explore spectral differences in resting-state MEG brain signals between patients with chronic pain and pain-free controls and to characterize the cortical and subcortical regions involved.We estimated power spectral density over 5 minutes of resting-state MEG recordings in patients with chronic pain and controls and derived 7 spectral features at the sensor and source levels: alpha peak frequency, alpha power ratio (power 7-9 Hz divided by power 9-11 Hz), and average power in theta, alpha, beta, low-gamma, and high-gamma bands. We performed nonparametric permutation t tests (false discovery rate corrected) to assess between-group differences in these 7 spectral features.Twenty-one patients with chronic pain and 25 controls were included. No significant group differences were found in alpha peak frequency or average power in any frequency band. The alpha power ratio was significantly higher (P < 0.05) in patients with chronic pain at both the sensor and brain source levels. The brain regions showing significantly higher ratios included the occipital, parietal, temporal and frontal lobe areas, insular and cingulate cortex, and right thalamus.The alpha power ratio is a simple, promising signal marker of chronic pain, affecting an expansive range of cortical and subcortical regions, including known pain-processing areas.
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