Aberrant Intrinsic Brain Activity in Patients with Autism Spectrum Disorder: Insights from EEG Microstates
Aberrant Intrinsic Brain Activity in Patients with Autism Spectrum Disorder: Insights from EEG Microstates
复制标题
自闭症谱系障碍患者异常的内在大脑活动：来自脑电图微观状态的见解
DOI：
10.1007/s10548-018-0685-0
复制
发表时间：
2019-03-01
期刊：
影响因子：
2.7
通讯作者：
Yu, Dongchuan
中科院分区：
文献类型：
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作者：
Jia, Huibin;Yu, Dongchuan
自闭症谱系障碍 (ASD) 涉及大规模大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可以为自闭症谱系障碍患者内在大脑活动的异常时间和空间特性提供新的见解。为了实现这一目标，我们对来自 Healthy Brain Network 的 15 名 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、B、C 和 D 类）的参数（即持续时间、发生率、时间覆盖和地形配置）在两组之间进行了统计测试。结果表明：（1）ASD组B级微状态的发生率和时间覆盖率均显着大于对照组； (2)A级微状态持续时间、C级微状态持续时间和时间覆盖范围均显着小于对照组; (3) D类微状态的图谱配置和发生率在两组之间存在显着差异。这些结果表明脑电图微状态分析可用于检测ASD大规模皮质活动的异常功能，并可为ASD临床研究提供指标。
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.