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高功能自闭症谱系障碍青年大脑小脑内在功能连接紊乱:基于数据驱动、全脑、高时间分辨率功能磁共振成像研究。

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.

机构信息

1 A.A. Martinos Imaging Center, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts.

2 Alan and Lorraine Bressler Clinical and Research Program for Autism Spectrum Disorder, Massachusetts General Hospital, Boston, Massachusetts.

出版信息

Brain Connect. 2019 Feb;9(1):48-59. doi: 10.1089/brain.2018.0581. Epub 2018 Jul 31.

Abstract

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.

摘要

本研究采用最先进的 fMRI 数据采集和分析技术,研究了高功能自闭症谱系障碍(HF-ASD)年轻成人的静息态功能连接(RsFc)。使用同时多切片采集的高时间分辨率 fMRI 辅助无偏全脑连接组多变量模式分析(MVPA)技术来评估 RsFc。MVPA 揭示了小脑中两个异常连接的簇(脑桥 I/II 和小叶 IX),这与小脑中非运动处理的三重表示概念一致。基于这些簇的全脑种子 RsFc 分析表明,与健康对照组相比,HF-ASD 组小脑与社会、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领域现有的结构、功能和 RsFc 文献一致,扩展了先前报告自闭症神经病理学中小脑异常的文献,并强调了小脑作为 HF-ASD 治疗、诊断、预测和预后发展的潜在靶点。本研究使用全脑、数据驱动分析报告的功能连接异常描述有可能极大地促进自闭症生物标志物、治疗干预靶点和测量治疗反应的神经预测因子的发展。

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