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从静息态脑磁图重建的神经电活动传统频段中的健康衰老变化。

Healthy aging changes in conventional frequency bands of neuroelectric brain activity reconstructed from resting-state MEG.

作者信息

Ustinin Mikhail, Boyko Anna, Rykunov Stanislav

机构信息

Keldysh Institute of Applied Mathematics, Russian Academy of Sciences, Moscow, 125047, Russia.

出版信息

Geroscience. 2025 Jan 17. doi: 10.1007/s11357-025-01522-y.

Abstract

Age-related dependencies of electric and spectral powers in conventional frequency bands were studied by the newly proposed method of detailed spectral analysis. The magnetic encephalograms (MEG) and magnetic resonance images (MRI) of the head were obtained from the open archive Cam-CAN. The spatial distributions of elementary spectral components (MEG-based functional tomograms) were reconstructed from MEG for 501 subjects (248 males and 253 females, ages 18-88 years, mean age 54.8 ±18.4). Physiological noise was eliminated by joint analysis of MEG-based functional tomogram and magnetic resonance image for each subject. Spectral and electric powers were calculated in six conventional frequency bands (1-4 Hz - delta; 4-8 Hz - theta; 8-13 Hz - alpha; 13-21 Hz - beta-1; 21-30 Hz - beta-2; 30-48 Hz - gamma), and age-related changes were examined. It was found that the spectral power of the delta band is significantly decreasing (p-value 0.002) and beta-1 and gamma are significantly increasing (p-values 0.001, 0.003). Electric power in the delta band is significantly decreasing (p-value 0.033), while electric power in the beta-1 band is significantly increasing (p-value 0.001). Also, the summary electric power of theta, alpha, beta-1, beta-2, and gamma bands is significantly increasing (p-value 0.024). Results represent general time dependence of the aging brain's electrical sources. The proposed method of joint MEG and MRI analysis can be used for a detailed study of sources location and connectivity.

摘要

采用新提出的详细频谱分析方法,研究了传统频段中电功率和频谱功率与年龄的相关性。头部的脑磁图(MEG)和磁共振图像(MRI)取自开放数据库Cam-CAN。从501名受试者(248名男性和253名女性,年龄18 - 88岁,平均年龄54.8±18.4岁)的MEG重建了基本频谱成分的空间分布(基于MEG的功能断层图)。通过对每个受试者的基于MEG的功能断层图和磁共振图像进行联合分析,消除了生理噪声。在六个传统频段(1 - 4 Hz - δ;4 - 8 Hz - θ;8 - 13 Hz - α;13 - 21 Hz - β-1;21 - 30 Hz - β-2;30 - 48 Hz - γ)中计算了频谱功率和电功率,并研究了与年龄相关的变化。结果发现,δ频段的频谱功率显著下降(p值0.002),β-1和γ频段显著增加(p值分别为0.001和0.003)。δ频段的电功率显著下降(p值0.033),而β-1频段的电功率显著增加(p值0.001)。此外,θ、α、β-1、β-2和γ频段的总电功率显著增加(p值0.024)。研究结果代表了衰老大脑电信号源的一般时间依赖性。所提出的MEG与MRI联合分析方法可用于详细研究信号源的位置和连接性。

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