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非周期性脑电图及背景频谱趋势的神经生理基础。

A neurophysiological basis for aperiodic EEG and the background spectral trend.

作者信息

Brake Niklas, Duc Flavie, Rokos Alexander, Arseneau Francis, Shahiri Shiva, Khadra Anmar, Plourde Gilles

机构信息

Quantiative Life Sciences PhD Program, McGill University, Montreal, Canada.

Department of Physiology, McGill University, Montreal, Canada.

出版信息

Nat Commun. 2024 Feb 19;15(1):1514. doi: 10.1038/s41467-024-45922-8.

Abstract

Electroencephalograms (EEGs) display a mixture of rhythmic and broadband fluctuations, the latter manifesting as an apparent 1/f spectral trend. While network oscillations are known to generate rhythmic EEG, the neural basis of broadband EEG remains unexplained. Here, we use biophysical modelling to show that aperiodic neural activity can generate detectable scalp potentials and shape broadband EEG features, but that these aperiodic signals do not significantly perturb brain rhythm quantification. Further model analysis demonstrated that rhythmic EEG signals are profoundly corrupted by shifts in synapse properties. To examine this scenario, we recorded EEGs of human subjects being administered propofol, a general anesthetic and GABA receptor agonist. Drug administration caused broadband EEG changes that quantitatively matched propofol's known effects on GABA receptors. We used our model to correct for these confounding broadband changes, which revealed that delta power, uniquely, increased within seconds of individuals losing consciousness. Altogether, this work details how EEG signals are shaped by neurophysiological factors other than brain rhythms and elucidates how these signals can undermine traditional EEG interpretation.

摘要

脑电图(EEGs)显示出有节律的波动和宽带波动的混合,后者表现为明显的1/f频谱趋势。虽然已知网络振荡会产生有节律的脑电图,但宽带脑电图的神经基础仍无法解释。在这里,我们使用生物物理模型表明,非周期性神经活动可以产生可检测到的头皮电位并塑造宽带脑电图特征,但这些非周期性信号不会显著干扰脑节律量化。进一步的模型分析表明,有节律的脑电图信号会因突触特性的变化而受到严重破坏。为了研究这种情况,我们记录了接受丙泊酚(一种全身麻醉剂和GABA受体激动剂)的人类受试者的脑电图。药物给药导致宽带脑电图变化,其在数量上与丙泊酚对GABA受体的已知作用相匹配。我们使用我们的模型来校正这些混杂的宽带变化,结果表明,独特的是,在个体失去意识的几秒钟内,δ波功率增加。总之,这项工作详细说明了脑电图信号是如何由脑节律以外的神经生理因素塑造的,并阐明了这些信号如何破坏传统脑电图的解释。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0f65/10876973/221dd0ea67ac/41467_2024_45922_Fig1_HTML.jpg

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