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网络成分分析揭示了结构连通性的发育轨迹以及自闭症谱系障碍中的特定改变。

Network component analysis reveals developmental trajectories of structural connectivity and specific alterations in autism spectrum disorder.

作者信息

Ball Gareth, Beare Richard, Seal Marc L

机构信息

Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia.

Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia.

出版信息

Hum Brain Mapp. 2017 Aug;38(8):4169-4184. doi: 10.1002/hbm.23656. Epub 2017 May 31.

Abstract

The structural organization of the brain can be characterized as a hierarchical ensemble of segregated modules linked by densely interconnected hub regions that facilitate distributed functional interactions. Disturbances to this network may be an important marker of abnormal development. Recently, several neurodevelopmental disorders, including autism spectrum disorder (ASD), have been framed as disorders of connectivity but the full nature and timing of these disturbances remain unclear. In this study, we use non-negative matrix factorization, a data-driven, multivariate approach, to model the structural network architecture of the brain as a set of superposed subnetworks, or network components. In an openly available dataset of 196 subjects scanned between 5 and 85 years we identify a set of robust and reliable subnetworks that develop in tandem with age and reflect both anatomically local and long-range, network hub connections. In a second experiment, we compare network components in a cohort of 51 high-functioning ASD adolescents to a group of age-matched controls. We identify a specific subnetwork representing an increase in local connection strength in the cingulate cortex in ASD (t = 3.44, P < 0.001). This work highlights possible long-term implications of alterations to the developmental trajectories of specific cortical subnetworks. Hum Brain Mapp 38:4169-4184, 2017. © 2017 Wiley Periodicals, Inc.

摘要

大脑的结构组织可被描述为一个分层的集合,由密集互连的枢纽区域连接的分离模块组成,这些枢纽区域促进了分布式功能相互作用。对该网络的干扰可能是异常发育的一个重要标志。最近,包括自闭症谱系障碍(ASD)在内的几种神经发育障碍被视为连接性障碍,但这些干扰的全部性质和时间仍不清楚。在本研究中,我们使用非负矩阵分解,一种数据驱动的多变量方法,将大脑的结构网络架构建模为一组叠加的子网或网络组件。在一个公开可用的包含196名年龄在5至85岁之间受试者的扫描数据集里,我们识别出一组与年龄同步发展且反映解剖学局部和长程网络枢纽连接的强大且可靠的子网。在第二个实验中,我们将51名高功能ASD青少年队列中的网络组件与一组年龄匹配的对照组进行比较。我们识别出一个特定子网,它代表了ASD患者扣带回皮质局部连接强度的增加(t = 3.44,P < 0.001)。这项工作突出了特定皮质子网发育轨迹改变可能产生的长期影响。《人类大脑图谱》38:4169 - 4184,2017年。© 2017威利期刊公司。

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