Normative Temporal Dynamics of Resting EEG Microstates.

IF 2.3 3区 医学 Q3 CLINICAL NEUROLOGY
Brain Topography Pub Date : 2024-03-01 Epub Date: 2023-09-13 DOI:10.1007/s10548-023-01004-4
Anthony P Zanesco
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引用次数: 0

Abstract

The large-scale electrophysiological events known as electroencephalographic microstates provide an important window into the intrinsic activity of whole-brain neuronal networks. The spontaneous activity of coordinated brain networks, including the ongoing temporal dynamics expressed by microstates, are thought to reflect individuals' neurocognitive functioning, and predict development, disease progression, and psychological differences among varied populations. A comprehensive understanding of human brain function therefore requires characterizing typical and atypical patterns in the temporal dynamics of microstates. But population-level estimates of normative microstate temporal dynamics are still unknown. To address this gap, I conducted a systematic search of the literature and accompanying meta-analysis of the average dynamics of microstates obtained from studies investigating spontaneous brain activity in individuals during periods of eyes-closed and eyes-open rest. Meta-analyses provided estimates of the average temporal dynamics of microstates across 93 studies totaling 6583 unique individual participants drawn from diverse populations. Results quantified the expected range of plausible estimates of average microstate dynamics across study samples, as well as characterized heterogeneity resulting from sampling variability and systematic differences in development, clinical diagnoses, or other study methodological factors. Specifically, microstate dynamics significantly differed for samples with specific developmental differences or clinical diagnoses, relative to healthy, typically developing samples. This research supports the notion that microstates and their dynamics reflect functionally relevant properties of large-scale brain networks, encoding typical and atypical neurocognitive functioning.

Abstract Image

静息脑电图微状态的规范时间动态
被称为脑电微状态的大规模电生理事件为了解全脑神经元网络的内在活动提供了一个重要窗口。协调的大脑网络的自发活动,包括微状态所表达的持续时间动态,被认为可以反映个体的神经认知功能,并预测不同人群的发育、疾病进展和心理差异。因此,要全面了解人类大脑功能,就必须描述微观状态时间动态的典型和非典型模式。但是,对正常微观状态时间动态的人群水平估计仍是未知数。为了填补这一空白,我对文献进行了系统性检索,并对调查闭眼和睁眼休息期间个体自发大脑活动的研究中获得的微状态平均动态进行了相应的荟萃分析。荟萃分析提供了 93 项研究中微状态平均时间动态的估计值,这些研究共涉及 6583 名来自不同人群的个体参与者。研究结果量化了各研究样本中平均微状态动态可信估计值的预期范围,并描述了由抽样变异和发育、临床诊断或其他研究方法因素的系统性差异导致的异质性。具体来说,与健康、发育正常的样本相比,有特定发育差异或临床诊断的样本的微状态动态存在显著差异。这项研究支持这样一种观点,即微观状态及其动态反映了大规模大脑网络的功能相关特性,编码了典型和非典型的神经认知功能。
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来源期刊
Brain Topography
Brain Topography 医学-临床神经学
CiteScore
4.70
自引率
7.40%
发文量
41
审稿时长
3 months
期刊介绍: Brain Topography publishes clinical and basic research on cognitive neuroscience and functional neurophysiology using the full range of imaging techniques including EEG, MEG, fMRI, TMS, diffusion imaging, spectroscopy, intracranial recordings, lesion studies, and related methods. Submissions combining multiple techniques are particularly encouraged, as well as reports of new and innovative methodologies.
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