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年龄相关的非周期性神经活动差异是否解释了静息 EEG 阿尔法的差异?

Do age-related differences in aperiodic neural activity explain differences in resting EEG alpha?

机构信息

Lifespan Human Neurophysiology Group, School of Biomedicine, The University of Adelaide, Adelaide, Australia; Hopwood Centre for Neurobiology, Lifelong Health Theme, South Australian Health and Medical Research Institute, Adelaide, Australia.

Lifespan Human Neurophysiology Group, School of Biomedicine, The University of Adelaide, Adelaide, Australia; Discipline of Physiology, School of Biomedicine, The University of Adelaide, Adelaide, Australia; Hopwood Centre for Neurobiology, Lifelong Health Theme, South Australian Health and Medical Research Institute, Adelaide, Australia.

出版信息

Neurobiol Aging. 2023 Jan;121:78-87. doi: 10.1016/j.neurobiolaging.2022.09.003. Epub 2022 Sep 14.

Abstract

Alpha-band oscillatory activity in human electroencephalography (EEG) becomes slower and lower in amplitude with advanced age. However, the influence of aperiodic activity on these measures has received little consideration. We investigated whether age-related differences in aperiodic activity explains differences in resting EEG peak alpha frequency and power. We assessed aperiodic activity in 85 younger and 92 older adults by fitting the 1/f-like background activity evident in EEG power spectra using the spectral parameterization ("specparam") algorithm. Across the scalp, the aperiodic exponent and offset were smaller in older compared to younger participants, reflecting a flatter 1/f-like slope and a downward broadband shift in power spectra with age. After correcting for aperiodic activity, peak alpha frequency remained slower in older adults; however, peak alpha power no longer differed statistically between age groups. The large sample size utilized in this study, as well as the depth of analysis, provides further evidence that the aperiodic component of the resting EEG signal is altered with aging and should be considered when investigating neural oscillatory activity.

摘要

人类脑电图(EEG)中的 alpha 波段活动随着年龄的增长而变慢和幅度降低。然而,周期性活动对这些测量的影响很少被考虑。我们研究了周期性活动是否会解释静息 EEG 峰值 alpha 频率和功率的年龄相关差异。我们通过使用频谱参数化(“specparam”)算法拟合 EEG 频谱中明显的 1/f 样背景活动来评估 85 名年轻参与者和 92 名年长参与者的周期性活动。在整个头皮上,与年轻参与者相比,年长参与者的周期性指数和偏移量较小,反映出 1/f 样斜率更平坦,频谱中的宽带功率随年龄向下移动。在纠正周期性活动后,峰值 alpha 频率在老年人中仍然较慢;然而,峰值 alpha 功率在年龄组之间不再存在统计学差异。本研究中使用的大样本量以及分析的深度进一步证明,静息 EEG 信号的周期性成分随年龄而改变,在研究神经振荡活动时应予以考虑。

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