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自闭症谱系障碍中与后默认模式网络相关的非典型网络去激活。

Atypical Inter-Network Deactivation Associated With the Posterior Default-Mode Network in Autism Spectrum Disorder.

机构信息

Research Unit of Logopedics, the Faculty of Humanities, University of Oulu, Oulu, Finland.

Research Unit of Medical Imaging, Physics and Technology, the Faculty of Medicine, University of Oulu, Oulu, Finland.

出版信息

Autism Res. 2021 Feb;14(2):248-264. doi: 10.1002/aur.2433. Epub 2020 Nov 18.

Abstract

Previous studies have suggested that atypical deactivation of functional brain networks contributes to the complex cognitive and behavioral profile associated with autism spectrum disorder (ASD). However, these studies have not considered the temporal dynamics of deactivation mechanisms between the networks. In this study, we examined (a) mutual deactivation and (b) mutual activation-deactivation (i.e., anticorrelated) time-lag patterns between resting-state networks (RSNs) in young adults with ASD (n = 20) and controls (n = 20) by applying the recently defined dynamic lag analysis (DLA) method, which measures time-lag variations peak-by-peak between the networks. In order to achieve temporally accurate lag patterns, the brain imaging data was acquired with a fast functional magnetic resonance imaging (fMRI) sequence (TR = 100 ms). Group-level independent component analysis was used to identify 16 RSNs for the DLA. We found altered mutual deactivation timings in ASD in (a) three of the deactivated and (b) two of the transiently anticorrelated (activated-deactivated) RSN pairs, which survived the strict threshold for significance of surrogate data. Of the significant RSN pairs, 80% included the posterior default-mode network (DMN). We propose that temporally altered deactivation mechanisms, including timings and directionality, between the posterior DMN and RSNs mediating processing of socially relevant information may contribute to the ASD phenotype. LAY SUMMARY: To understand autistic traits on a neural level, we examined temporal fluctuations in information flow between brain regions in young adults with autism spectrum disorder (ASD) and controls. We used a fast neuroimaging procedure to investigate deactivation mechanisms between brain regions. We found that timings and directionality of communication between certain brain regions were temporally altered in ASD, suggesting atypical deactivation mechanisms associated with the posterior default-mode network.

摘要

先前的研究表明,功能脑网络的非典型失活与自闭症谱系障碍(ASD)相关的复杂认知和行为特征有关。然而,这些研究并未考虑网络间失活机制的时间动态。在这项研究中,我们通过应用最近定义的动态滞后分析(DLA)方法,检查了 ASD(n=20)和对照组(n=20)年轻人静息态网络(RSN)之间的(a)相互失活和(b)相互激活-失活(即,负相关)的时间滞后模式,该方法测量了网络之间的峰峰时间滞后变化。为了实现时间上准确的滞后模式,大脑成像数据是使用快速功能磁共振成像(fMRI)序列(TR=100ms)采集的。组水平独立成分分析用于为 DLA 识别 16 个 RSN。我们发现,在 ASD 中,相互失活的时间发生了改变,包括(a)三个失活的 RSN 对和(b)两个暂态负相关(激活-失活)的 RSN 对,这些改变在替代数据的严格显著水平上幸存下来。在显著的 RSN 对中,80%包括后默认模式网络(DMN)。我们提出,在后 DMN 和介导与社会相关信息处理的 RSN 之间,失活机制的时间变化,包括时间和方向,可能有助于 ASD 表型。

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