Kang Jiannan, Xie Hongxiang, Mao Wenqin, Wu Juanmei, Li Xiaoli, Geng Xinling
Child Rehabilitation Division, Ningbo Rehabilitation Hospital, Ningbo 315040, China.
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China.
Bioengineering (Basel). 2023 Sep 1;10(9):1030. doi: 10.3390/bioengineering10091030.
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interaction and communication, and repetitive or stereotyped behaviors. Previous studies have reported altered brain connectivity in ASD children compared to typically developing children. In this study, we investigated the diversity of connectivity patterns between children with ASD and typically developing children using phase lag entropy (PLE), a measure of the variability of phase differences between two time series. We also developed a novel wavelet-based PLE method for the calculation of PLE at specific scales. Our findings indicated that the diversity of connectivity in ASD children was higher than that in typically developing children at Delta and Alpha frequency bands, both within brain regions and across hemispheric brain regions. These findings provide insight into the underlying neural mechanisms of ASD and suggest that PLE may be a useful tool for investigating brain connectivity in ASD.
自闭症谱系障碍(ASD)是一种神经发育障碍,其特征是社交互动和沟通存在缺陷,以及重复或刻板行为。先前的研究报告称,与正常发育的儿童相比,ASD儿童的大脑连接性发生了改变。在本研究中,我们使用相位滞后熵(PLE)(一种衡量两个时间序列之间相位差变异性的指标)研究了ASD儿童与正常发育儿童之间连接模式的多样性。我们还开发了一种基于小波的新型PLE方法,用于在特定尺度上计算PLE。我们的研究结果表明,在Delta和Alpha频段,无论是在脑区内部还是跨半球脑区,ASD儿童的连接多样性均高于正常发育儿童。这些发现为ASD的潜在神经机制提供了见解,并表明PLE可能是研究ASD大脑连接性的有用工具。