Bagdasarov Armen, Roberts Kenneth, Bréchet Lucie, Brunet Denis, Michel Christoph M, Gaffrey Michael S
Department of Psychology & Neuroscience, Duke University, Reuben-Cooke Building, 417 Chapel Drive, Durham, NC 27708, USA.
Duke Institute for Brain Sciences, Duke University, 308 Research Drive, Durham, NC, USA.
Dev Cogn Neurosci. 2022 Oct;57:101134. doi: 10.1016/j.dcn.2022.101134. Epub 2022 Jul 12.
The ultrafast spatiotemporal dynamics of large-scale neural networks can be examined using resting-state electroencephalography (EEG) microstates, representing transient periods of synchronized neural activity that evolve dynamically over time. In adults, four canonical microstates have been shown to explain most topographic variance in resting-state EEG. Their temporal structures are age-, sex- and state-dependent, and are susceptible to pathological brain states. However, no studies have assessed the spatial and temporal properties of EEG microstates exclusively during early childhood, a critical period of rapid brain development. Here we sought to investigate EEG microstates recorded with high-density EEG in a large sample of 103, 4-8-year-old children. Using data-driven k-means cluster analysis, we show that the four canonical microstates reported in adult populations already exist in early childhood. Using multiple linear regressions, we demonstrate that the temporal dynamics of two microstates are associated with age and sex. Source localization suggests that attention- and cognitive control-related networks govern the topographies of the age- and sex-dependent microstates. These novel findings provide unique insights into functional brain development in children captured with EEG microstates.
大规模神经网络的超快时空动力学可以通过静息态脑电图(EEG)微状态来研究,EEG微状态代表了随时间动态演变的同步神经活动的瞬态期。在成年人中,已发现四种典型微状态可解释静息态EEG中的大部分地形差异。它们的时间结构取决于年龄、性别和状态,并且易受病理性脑状态的影响。然而,尚无研究专门评估幼儿期(大脑快速发育的关键时期)EEG微状态的时空特性。在此,我们试图对103名4至8岁儿童的大样本进行高密度EEG记录,以研究EEG微状态。使用数据驱动的k均值聚类分析,我们发现成年人群中报告的四种典型微状态在幼儿期就已存在。通过多元线性回归,我们证明了两种微状态的时间动态与年龄和性别相关。源定位表明,与注意力和认知控制相关的网络支配着与年龄和性别相关的微状态的地形。这些新发现为通过EEG微状态捕捉到的儿童功能性脑发育提供了独特的见解。