Wang Chaoyan, Yang Lu, Lin Yanan, Wang Caihong, Tian Peichao
Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Department of Pediatrics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Front Integr Neurosci. 2023 Jan 19;16:922577. doi: 10.3389/fnint.2022.922577. eCollection 2022.
Neurobiological models to explain the vulnerability of autism spectrum disorders (ASDs) are scarce, and previous resting-state functional magnetic resonance imaging (rs-fMRI) studies mostly examined static functional connectivity (FC). Given that FC constantly evolves, it is critical to probe FC dynamic differences in ASD patients.
We characterized recurring phase-locking (PL) states during rest in 45 ASD patients and 47 age- and sex-matched healthy controls (HCs) using Leading Eigenvector Dynamics Analysis (LEiDA) and probed the organization of PL states across different fine grain sizes.
Our results identified five different groups of discrete resting-state functional networks, which can be defined as recurrent PL state overtimes. Specifically, ASD patients showed an increased probability of three PL states, consisting of the visual network (VIS), frontoparietal control network (FPN), default mode network (DMN), and ventral attention network (VAN). Correspondingly, ASD patients also showed a decreased probability of two PL states, consisting of the subcortical network (SUB), somatomotor network (SMN), FPN, and VAN.
Our findings suggested that the temporal reorganization of brain discrete networks was closely linked to sensory to cognitive systems of the brain. Our study provides new insights into the dynamics of brain networks and contributes to a deeper understanding of the neurological mechanisms of ASD.
用于解释自闭症谱系障碍（ASD）易感性的神经生物学模型稀缺，以往的静息态功能磁共振成像（rs-fMRI）研究大多考察的是静态功能连接（FC）。鉴于功能连接处于不断演变中，探究ASD患者的功能连接动态差异至关重要。
我们使用主导特征向量动力学分析（LEiDA）对45名ASD患者以及47名年龄和性别匹配的健康对照（HC）在静息状态下反复出现的锁相（PL）状态进行了特征描述，并探究了不同精细粒度下PL状态的组织情况。
我们的研究结果识别出五组不同的离散静息态功能网络，它们可被定义为反复出现的PL状态随时间的变化情况。具体而言，ASD患者出现三种PL状态的概率增加，这三种状态由视觉网络（VIS）、额顶叶控制网络（FPN）、默认模式网络（DMN）和腹侧注意网络（VAN）组成。相应地，ASD患者出现另外两种PL状态的概率降低，这两种状态由皮层下网络（SUB）、躯体运动网络（SMN）、FPN和VAN组成。
我们的研究结果表明，大脑离散网络的时间重组与大脑的感觉系统到认知系统密切相关。我们的研究为大脑网络动力学提供了新的见解，并有助于更深入地理解ASD的神经机制。
