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探索帕金森病脑电图模式的复杂性。

Exploring the complexity of EEG patterns in Parkinson's disease.

作者信息

Nucci Lorenzo, Miraglia Francesca, Pappalettera Chiara, Rossini Paolo Maria, Vecchio Fabrizio

机构信息

Brain Connectivity Laboratory, Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele Roma, Rome, 00166, Italy.

Department of Theoretical and Applied Sciences, eCampus University, Novedrate, Como, Italy.

出版信息

Geroscience. 2025 Feb;47(1):837-849. doi: 10.1007/s11357-024-01277-y. Epub 2024 Jul 13.

Abstract

Parkinson's disease (PD) is a progressive neurodegenerative disorder primarily associated with motor dysfunctions. By the time of definitive diagnosis, about 60% of dopaminergic neurons have already been lost; moreover, even if dopaminergic drugs are highly effective in symptoms control, they only help maintaining a near-healthy condition when started as soon as possible. Therefore, interest in identifying early biomarkers of PD has grown in recent years, especially using neurophysiological techniques such as electroencephalography (EEG). This study aims to investigate brain complexity differences in PD patients compared to healthy controls, focusing on the beta band using approximate entropy (ApEn) analysis of resting-state EEG recordings. Sixty participants were recruited, including 25 PD patients and 35 healthy elderly subjects, matched for age and gender. EEG were recorded for each participant and ApEn values were computed in the beta 1 (13-20 Hz) and beta 2 (20-30 Hz) frequency bands for each EEG-channel and for ROIs. PD patients showed statistically lower ApEn values compared to controls in both beta 1 and beta 2 bands. Regarding electrodes analysis, beta 1 band alterations were found in frontocentral areas, while beta 2 band alterations were observed in centroparietal and frontocentral areas. Considering ROIs, statistically lower ApEn values for PD patients has been reported in central and parietal ROIs in the beta 2 band. Complexity reduction in these areas may underlie beta oscillatory activity dysfunction, reflecting impaired cortical mechanisms associated with motor dysfunction in PD. The results suggest that ApEn analysis of resting EEG activity may serve as a potential tool for early PD detection. Further studies are necessary to validate this approach in PD diagnosis and rehabilitation planning.

摘要

帕金森病(PD)是一种主要与运动功能障碍相关的进行性神经退行性疾病。在明确诊断时,约60%的多巴胺能神经元已经丧失;此外,即使多巴胺能药物在症状控制方面非常有效,但只有尽早开始使用才能帮助维持接近健康的状态。因此,近年来人们对识别帕金森病的早期生物标志物越来越感兴趣,尤其是使用脑电图(EEG)等神经生理学技术。本研究旨在调查帕金森病患者与健康对照者在大脑复杂性方面的差异,重点是使用静息态脑电图记录的近似熵(ApEn)分析β频段。招募了60名参与者,包括25名帕金森病患者和35名健康老年受试者,他们在年龄和性别上相匹配。记录了每位参与者的脑电图,并计算了每个脑电图通道和感兴趣区域(ROI)在β1(13 - 20Hz)和β2(20 - 30Hz)频段的ApEn值。与对照组相比,帕金森病患者在β1和β2频段的ApEn值在统计学上均较低。关于电极分析,在额中央区域发现了β1频段的改变,而在中央顶叶和额中央区域观察到了β2频段的改变。考虑感兴趣区域,在β2频段,帕金森病患者在中央和顶叶感兴趣区域的ApEn值在统计学上较低。这些区域的复杂性降低可能是β振荡活动功能障碍的基础,反映了与帕金森病运动功能障碍相关皮质机制受损。结果表明,静息脑电图活动的ApEn分析可能作为帕金森病早期检测的潜在工具。需要进一步的研究来验证这种方法在帕金森病诊断和康复计划中的应用。

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