Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, H3A2B4, Montreal, Canada.
Center for the Developing Brain, Child Mind Institute, 10022, New York, NY, USA.
Nat Commun. 2019 Mar 4;10(1):1022. doi: 10.1038/s41467-019-08944-1.
One paradox of autism is the co-occurrence of deficits in sensory and higher-order socio-cognitive processing. Here, we examined whether these phenotypical patterns may relate to an overarching system-level imbalance-specifically a disruption in macroscale hierarchy affecting integration and segregation of unimodal and transmodal networks. Combining connectome gradient and stepwise connectivity analysis based on task-free functional magnetic resonance imaging (fMRI), we demonstrated atypical connectivity transitions between sensory and higher-order default mode regions in a large cohort of individuals with autism relative to typically-developing controls. Further analyses indicated that reduced differentiation related to perturbed stepwise connectivity from sensory towards transmodal areas, as well as atypical long-range rich-club connectivity. Supervised pattern learning revealed that hierarchical features predicted deficits in social cognition and low-level behavioral symptoms, but not communication-related symptoms. Our findings provide new evidence for imbalances in network hierarchy in autism, which offers a parsimonious reference frame to consolidate its diverse features.
自闭症的一个悖论是感觉和更高阶社会认知加工缺陷的同时发生。在这里，我们研究了这些表型模式是否可能与一个总体的系统水平失衡有关——具体来说，是一个影响单模态和跨模态网络的整合和分离的宏观层次结构的破坏。我们结合基于无任务功能磁共振成像 (fMRI) 的连接梯度和逐步连接分析，在一个大型自闭症个体队列中，与典型发育对照组相比，我们证明了感觉和更高阶默认模式区域之间的连接过渡异常。进一步的分析表明，与从感觉到跨模态区域的逐步连接中受到干扰相关的分化减少，以及异常的长程富俱乐部连接。有监督的模式学习表明，层次特征预测了社会认知和低水平行为症状的缺陷，但不能预测与交流相关的症状。我们的发现为自闭症中的网络层次结构失衡提供了新的证据，为整合其多种特征提供了一个简洁的参考框架。
