Jia Huibin, Yu Dongchuan
Key Laboratory of Child Development and Learning Science of Ministry of Education, Research Center for Learning Science, School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, Jiangsu, China.
Brain Topogr. 2019 Mar;32(2):295-303. doi: 10.1007/s10548-018-0685-0. Epub 2018 Oct 31.
Autism spectrum disorder (ASD) involves aberrant organization and functioning of large-scale brain networks. The aim of this study was to examine whether the resting-state EEG microstate analysis could provide novel insights into the abnormal temporal and spatial properties of intrinsic brain activities in patients with ASD. To achieve this goal, EEG microstate analysis was conducted on the resting-state EEG datasets of 15 patients with ASD and 18 healthy controls from the Healthy Brain Network. The parameters (i.e., duration, occurrence rate, time coverage and topographical configuration) of four classical microstate classes (i.e., class A, B, C and D) were statistically tested between two groups. The results showed that: (1) the occurrence rate and time coverage of microstate class B in ASD group were significantly larger than those in control group; (2) the duration of microstate class A, the duration and time coverage of microstate class C were significantly smaller than those in control group; (3) the map configuration and occurrence rate differed significantly between two groups for microstate class D. These results suggested that EEG microstate analysis could be used to detect the deviant functions of large-scale cortical activities in ASD, and may provide indices that could be used in clinical researches of ASD.
自闭症谱系障碍(ASD)涉及大规模脑网络的异常组织和功能。本研究的目的是检验静息态脑电图微状态分析是否能为ASD患者内在脑活动的异常时空特性提供新的见解。为实现这一目标,对来自健康脑网络的15例ASD患者和18名健康对照的静息态脑电图数据集进行了脑电图微状态分析。对四个经典微状态类别(即A类、B类、C类和D类)的参数(即持续时间、发生率、时间覆盖率和地形配置)在两组之间进行了统计学检验。结果表明:(1)ASD组中微状态B类的发生率和时间覆盖率显著高于对照组;(2)ASD组中微状态A类的持续时间、微状态C类的持续时间和时间覆盖率显著小于对照组;(3)微状态D类在两组之间的图谱配置和发生率存在显著差异。这些结果表明,脑电图微状态分析可用于检测ASD中大规模皮层活动的异常功能,并可能提供可用于ASD临床研究的指标。