刺激诱发的窄带振荡在人脑电图中是可靠的。

Cerebral cortex communications Pub Date : 2022-01-07 eCollection Date: 2022-01-01 DOI:10.1093/texcom/tgab066
Wupadrasta Santosh Kumar, Keerthana Manikandan, Dinavahi V P S Murty, Ranjini Garani Ramesh, Simran Purokayastha, Mahendra Javali, Naren Prahalada Rao, Supratim Ray
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引用次数: 2

摘要

在临床前阿尔茨海默病(AD)患者的脑电图(EEG)记录中,视觉刺激诱导的伽马振荡最近被证明是受损的,这表明伽马可能是一种廉价的阿尔茨海默病诊断的生物标志物,前提是其特征在多个记录中保持一致。先前对年轻受试者进行的脑磁图研究表明,间隔几周到几个月的记录显示出一致的伽马能量。在此,我们评估了40名年龄为50-88岁的受试者在间隔一年的脑电图记录中刺激诱发的慢速(20-35 Hz)和快速(36-66 Hz)振荡的一致性,并测试了伽马功率的大小、时间演变和频谱分布的一致性。伽马在受试者之间具有明显的光谱/时间特征,在不同的记录之间保持一致(平均类内相关性为~0.7)。α (8- 12hz)和稳态视觉诱发电位也是可靠的。我们进一步测试了如何使用EEG特征来识别属于同一或不同受试者的2个记录,并发现了高分类器性能(AUC为~0.89),其中慢伽马和谱剖面的时间演变信息最多。这些结果表明,脑电图伽马振荡在长时间分离的会话中是可靠的,也可以作为受试者识别的潜在工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Stimulus-Induced Narrowband Gamma Oscillations are Test-Retest Reliable in Human EEG.

Visual stimulus-induced gamma oscillations in electroencephalogram (EEG) recordings have been recently shown to be compromised in subjects with preclinical Alzheimer's Disease (AD), suggesting that gamma could be an inexpensive biomarker for AD diagnosis provided its characteristics remain consistent across multiple recordings. Previous magnetoencephalography studies in young subjects have reported consistent gamma power over recordings separated by a few weeks to months. Here, we assessed the consistency of stimulus-induced slow (20-35 Hz) and fast gamma (36-66 Hz) oscillations in subjects (n = 40) (age: 50-88 years) in EEG recordings separated by a year, and tested the consistency in the magnitude of gamma power, its temporal evolution and spectral profile. Gamma had distinct spectral/temporal characteristics across subjects, which remained consistent across recordings (average intraclass correlation of ~0.7). Alpha (8-12 Hz) and steady-state-visually evoked-potentials were also reliable. We further tested how EEG features can be used to identify 2 recordings as belonging to the same versus different subjects and found high classifier performance (AUC of ~0.89), with temporal evolution of slow gamma and spectral profile being most informative. These results suggest that EEG gamma oscillations are reliable across sessions separated over long durations and can also be a potential tool for subject identification.

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