Wang Shan, Sun Zhe, Martinez-Tejada Laura Alejandra, Yoshimura Natsue
Department of Information and Communications Engineering, School of Engineering, Tokyo Institute of Technology, Yokohama, Japan.
Graduate School of Medicine, Juntendo University, Tokyo, Japan.
Front Neurosci. 2024 Oct 4;18:1440222. doi: 10.3389/fnins.2024.1440222. eCollection 2024.
Autism spectrum disorder (ASD) is a series of neurodevelopmental disorders that may affect a patient's social, behavioral, and communication abilities. As a typical mental illness, ASD is not a single disorder. ASD is often divided into subtypes, such as autism, Asperger's, and pervasive developmental disorder-not otherwise specified (PDD-NOS). Studying the differences among brain networks of the subtypes has great significance for the diagnosis and treatment of ASD. To date, many studies have analyzed the brain activity of ASD as a single mental disorder, whereas few have focused on its subtypes. To address this problem, we explored whether indices derived from functional and structural magnetic resonance imaging (MRI) data exhibited significant dissimilarities between subtypes. Utilizing a brain pattern feature extraction method from fMRI based on tensor decomposition, amplitude of low-frequency fluctuation and its fractional values of fMRI, and gray matter volume derived from MRI, impairments of function in the subcortical network and default mode network of autism were found to lead to major differences from the other two subtypes. Our results provide a systematic comparison of the three common ASD subtypes, which may provide evidence for the discrimination between ASD subtypes.
自闭症谱系障碍(ASD)是一系列可能影响患者社交、行为和沟通能力的神经发育障碍。作为一种典型的精神疾病,ASD并非单一疾病。ASD通常分为多种亚型,如自闭症、阿斯伯格综合征以及未特定的广泛性发育障碍(PDD-NOS)。研究这些亚型脑网络之间的差异对ASD的诊断和治疗具有重要意义。迄今为止,许多研究将ASD作为一种单一精神疾病来分析其大脑活动,而很少有研究关注其亚型。为解决这一问题,我们探究了从功能和结构磁共振成像(MRI)数据得出的指标在各亚型之间是否存在显著差异。利用基于张量分解的功能磁共振成像(fMRI)脑模式特征提取方法、fMRI低频波动幅度及其分数值,以及从MRI得出的灰质体积,发现自闭症患者皮质下网络和默认模式网络的功能损伤导致其与其他两种亚型存在重大差异。我们的结果对三种常见的ASD亚型进行了系统比较,这可能为区分ASD亚型提供依据。