Disrupted Cerebrocerebellar Intrinsic Functional Connectivity in Young Adults with High-Functioning Autism Spectrum Disorder: A Data-Driven, Whole-Brain, High-Temporal Resolution Functional Magnetic Resonance Imaging Study
Disrupted Cerebrocerebellar Intrinsic Functional Connectivity in Young Adults with High-Functioning Autism Spectrum Disorder: A Data-Driven, Whole-Brain, High-Temporal Resolution Functional Magnetic Resonance Imaging Study
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DOI：
10.1089/brain.2018.0581
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发表时间：
2019-02-01
影响因子：
3.4
通讯作者：
Joshi, Gagan
中科院分区：
文献类型：
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作者：
Anteraper, Sheeba Arnold;Guell, Xavier;Joshi, Gagan
本研究使用最先进的功能磁共振数据采集和分析技术，研究了患有高功能自闭症谱系障碍(HF-ASD)的年轻人的静息状态功能连接性(RsFc)。高时间分辨率功能磁共振成像使用同步多层切片采集辅助无偏全脑连接组范围的多变量模式分析(MVPA)技术评估RsFc。MVPA显示了小脑中两个异常连接的簇(CRU I/II和小叶IX)，这与小脑中非运动加工的三重表示的概念一致。由这些簇提供信息的基于全脑种子的RsFc分析显示，与健康对照组相比，HF-ASD组的小脑与社交、情感和语言脑区之间的连接明显不足。我们报告的结果与自闭症现有的结构、功能和RsFc文献一致，扩展了先前关于自闭症神经病理中小脑异常的文献，并强调小脑作为治疗、诊断、预测和预后发展的潜在靶点。本研究报告的使用全脑、数据驱动的分析对功能连接异常的描述有可能极大地推动ASD生物标记物、治疗干预目标和用于衡量治疗反应的神经预测因子的开发。
This study examines the resting-state functional-connectivity (RsFc) in young adults with high-functioning autism spectrum disorder (HF-ASD) using state-of-the-art fMRI data acquisition and analysis techniques. High temporal resolution fMRI using simultaneous multi-slice acquisition aided unbiased whole-brain connectome-wide multivariate pattern analysis (MVPA) techniques for assessing RsFc. MVPA revealed two clusters (Crus I/II and lobule IX) of abnormal connectivity in the cerebellum that are consistent with the notion of a triple representation of nonmotor processing in the cerebellum. Whole-brain seed-based RsFc analyses informed by these clusters showed significant under connectivity between the cerebellar and social, emotional, and language brain regions in the HF-ASD group compared to healthy controls. The results we report are coherent with existing structural, functional, and RsFc literature in autism, extend previous literature reporting cerebellar abnormalities in the neuropathology of autism, and highlight the cerebellum as a potential target for therapeutic, diagnostic, predictive, and prognostic developments in HF-ASD. The description of functional connectivity abnormalities reported in this study using whole-brain, data-driven analyses has the potential to crucially advance the development of ASD biomarkers, targets for therapeutic interventions, and neural predictors for measuring treatment response.