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首页> 外文期刊>Neurological Research: An Interdisciplinary Quarterly Journal >Multiplex temporal measures reflecting neural underpinnings of brain functional connectivity under cognitive load in Autism Spectrum Disorder
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Multiplex temporal measures reflecting neural underpinnings of brain functional connectivity under cognitive load in Autism Spectrum Disorder

机译:自闭症谱紊乱认知载荷下反映脑功能连通性的神经内衬的多路复用时间测量

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Methods: Thirty individuals with ASD (11-18years) and thirty Typically Developing (TD) individuals (11-16years) were recruited to perform the mental task. The participants were instructed to flip the shown geometric images mentally and mark their response on a scale. The task-related multivariate EEG activations were analyzed using multiplex temporal Visibility Graphs (VGs) to compute local and global brain network functional connectivity dynamics. Results: With cognitive load (0-back to the 2-back task), the behavioral performance (d' index and Reaction Time) has reduced in ASD. The brain network has become more segregated and less integrated, reflecting more involvement of intra-regions over inter-regions in ASD. The frequent rerouting in hubs measured by Eigenvector Centrality (EC) indicated the progression of brain trajectory towards ASD. Overall, the neural mechanisms involving hyperactive response in frontal regions, frequent rewiring, and strengthened brain connectivity as a result of learning-induced performance reflected the adaptation to cognitive demands in ASD. Discussion: The correlation between complex graph measures and behavioral domain further reflected that neural metrics could predict the behavioral performance of the individuals in the task. In the future, modeling functional connectivity-based markers have the potential to reflect the brain trajectory alterations, which can detect ASD even before the behavioral manifestations become apparent.
机译:方法:招募有三十个具有ASD(11-18年)和三十个通常发展(TD)个人(11-16年)的人,以执行精神任务。参与者被指示心理上翻转所示的几何图像并将其响应标记在规模上。使用多路复用时间可见性图(VGS)分析任务相关的多变量EEG激活,以计算本地和全局大脑功能连接动态。结果:具有认知负载(0-返回2后任务),ASD中的行为性能(D'指数和反应时间)降低。大脑网络变得更加隔离,较少集成,反映了内部区域在ASD间区域上的更多参与。由特征传染媒介中心(EC)测量的集线器频繁重新路由表明脑轨迹的进展朝向ASD。总体而言,由于学习诱导的性能而频繁地重新加速和加强脑连接的神经机制,反映了对ASD中的认知需求的适应性。讨论:复杂图形测量与行为域之间的相关性进一步反映了神经指标可以预测任务中的个人的行为性能。在未来,模型功能连接基标记具有反映脑轨迹改变的可能性,即使在行为表现明显之前也可以检测到ASD。

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