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个性化功能网络图谱在自闭症谱系障碍和注意缺陷多动障碍中的应用。

Personalized functional network mapping for autism spectrum disorder and attention-deficit/hyperactivity disorder.

机构信息

College of Electrical Engineering, Sichuan University, Chengdu, China.

State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China.

出版信息

Transl Psychiatry. 2024 Feb 12;14(1):92. doi: 10.1038/s41398-024-02797-z.

Abstract

Autism spectrum disorder (ASD) and Attention-deficit/hyperactivity disorder (ADHD) are two typical neurodevelopmental disorders that have a long-term impact on physical and mental health. ASD is usually comorbid with ADHD and thus shares highly overlapping clinical symptoms. Delineating the shared and distinct neurophysiological profiles is important to uncover the neurobiological mechanisms to guide better therapy. In this study, we aimed to establish the behaviors, functional connectome, and network properties differences between ASD, ADHD-Combined, and ADHD-Inattentive using resting-state functional magnetic resonance imaging. We used the non-negative matrix fraction method to define personalized large-scale functional networks for each participant. The individual large-scale functional network connectivity (FNC) and graph-theory-based complex network analyses were executed and identified shared and disorder-specific differences in FNCs and network attributes. In addition, edge-wise functional connectivity analysis revealed abnormal edge co-fluctuation amplitude and number of transitions among different groups. Taken together, our study revealed disorder-specific and -shared regional and edge-wise functional connectivity and network differences for ASD and ADHD using an individual-level functional network mapping approach, which provides new evidence for the brain functional abnormalities in ASD and ADHD and facilitates understanding the neurobiological basis for both disorders.

摘要

自闭症谱系障碍(ASD)和注意缺陷多动障碍(ADHD)是两种典型的神经发育障碍,对身心健康有长期影响。ASD 通常与 ADHD 共病,因此具有高度重叠的临床症状。区分共同和独特的神经生理特征对于揭示神经生物学机制以指导更好的治疗至关重要。在这项研究中,我们旨在使用静息态功能磁共振成像来建立 ASD、ADHD-混合型和 ADHD-注意力不集中型之间的行为、功能连接组和网络特性差异。我们使用非负矩阵分解方法为每个参与者定义个性化的大规模功能网络。执行个体的大规模功能网络连接(FNC)和基于图论的复杂网络分析,并确定 FNC 和网络属性中的共享和特定于疾病的差异。此外,边缘功能连接分析揭示了不同组之间异常的边缘共同波动幅度和转换数量。总之,我们的研究使用个体水平的功能网络映射方法,揭示了 ASD 和 ADHD 的特定和共享的区域和边缘功能连接和网络差异,为 ASD 和 ADHD 的大脑功能异常提供了新的证据,并有助于理解这两种疾病的神经生物学基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2709/10861462/bb82e35376ca/41398_2024_2797_Fig1_HTML.jpg

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