静息态脑电功率谱在轻度认知障碍老年人群中的特征分析
Characterization of Resting-State EEG Power Spectrum in Older Adults with Mild Cognitive Impairment
DOI: 10.12677/ap.2025.159535, PDF,    科研立项经费支持
作者: 蒋璧聪, 张 影, 成 楠, 刘海宁*：承德医学院心理学系，河北 承德；黄 群：承德医学院生物医学工程系，河北 承德；刘 颖：南京医科大学护理学系，南京 江苏
关键词: 脑电；静息态；功率谱；轻度认知障碍；EEG； Resting-State； Power Spectrum； MCI
摘要: 目的：探讨轻度认知障碍(MCI)老年人与认知正常老年人静息态脑电图(EEG)功率谱特征的差异。方法：招募60岁以上老年人54名(MCI组29例，健康对照组25例)，采集闭眼(EC)与睁眼(EO)静息态EEG信号。采用64导联Neuroscan系统记录数据，经预处理后通过Welch方法计算Delta (1~4 Hz)、Theta (4~8 Hz)、Alpha (8~13 Hz)和Beta (13~30 Hz)频段的绝对功率，并绘制功率谱密度(PSD)头皮地形图。结果：睁眼状态下，MCI组Delta (6.71 vs 13.44 μV2/Hz)和Theta功率(1.31 vs 2.37 μV2/Hz)低于对照组；闭眼状态趋势相似但差异减弱；MCI组总功率降低，Alpha/Beta高频段功率下降。PSD地形图显示MCI组低频段(Delta/Theta)前额功率差异不明显，高频段(Alpha/Beta)后部功率减弱，尤其Alpha枕区活动显著消退，整体分布相比HC更为凌乱。结论：MCI患者静息态EEG呈现“慢波化”(低频功率增强、高频功率降低)及空间节律紊乱的特征，可作为早期识别的生物标志物，EEG频谱分析为MCI筛查和干预评估提供了客观依据。
Abstract: Objective: To investigate differences in resting-state electroencephalogram (EEG) power spectral characteristics between older adults with mild cognitive impairment (MCI) and cognitively normal older adults. Methods: 54 older adults aged >60 years (29 in MCI group, 25 in healthy control group) were recruited. EEG signals were collected under eyes-closed (EC) and eyes-open (EO) resting-state conditions. Data were recorded using a 64-channel Neuroscan system. After preprocessing, absolute power in Delta (1~4 Hz), Theta (4~8 Hz), Alpha (8~13 Hz), and Beta (13~30 Hz) frequency bands was calculated via Welch method. Power spectral density (PSD) scalp topographic maps were plotted by MATLAB R2022a. Results: Under EO conditions, Delta (6.71 vs. 13.44 μV2/Hz) and Theta power (1.31 vs. 2.37 μV2/Hz) in MCI group were lower than control group. Similar trends were observed under EC conditions but with weaker differences. Total power decreased in MCI group, with reduced high-frequency band (Alpha/Beta) power. PSD topographic maps showed that insignificant frontal power differences in low-frequency bands (Delta/Theta) for MCI group. Lower posterior power in high-frequency bands (Alpha/Beta) for MCI group, especially significantly decreased Alpha activity in occipital regions. There were more chaotic overall distribution compared to HC group. Conclusion: Resting-state EEG in MCI patients demonstrates “slowing” (increased low-frequency power, decreased high-frequency power) and disordered spatial rhythms, which may serve as biomarkers for early identification, EEG spectral analysis provides an objective basis for MCI screening and intervention evaluation.
文章引用：蒋璧聪, 张影, 黄群, 成楠, 刘颖, 刘海宁 (2025). 静息态脑电功率谱在轻度认知障碍老年人群中的特征分析. 心理学进展, 15(9), 450-458. https://doi.org/10.12677/ap.2025.159535

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