Bio-Information College, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China.
Neural Plast. 2022 Sep 26;2022:4714763. doi: 10.1155/2022/4714763. eCollection 2022.
Attention deficit hyperactivity disorder (ADHD) is a common mental disorder in children, which is related to inattention and hyperactivity. These symptoms are associated with abnormal interactions of brain networks. We used resting-state functional magnetic resonance imaging (rs-fMRI) based on the graph theory to explore the topology property changes of brain networks between an ADHD group and a normal group. The more refined AAL_1024 atlas was used to construct the functional networks with high nodal resolution, for detecting more subtle changes in brain regions and differences among groups. We compared altered topology properties of brain network between the groups from multilevel, mainly including modularity at mesolevel. Specifically, we analyzed the similarities and differences of module compositions between the two groups. The results found that the ADHD group showed stronger economic small-world network property, while the clustering coefficient was significantly lower than the normal group; the frontal and occipital lobes showed smaller node degree and global efficiency between disease statuses. The modularity results also showed that the module number of the ADHD group decreased, and the ADHD group had short-range overconnectivity within module and long-range underconnectivity between modules. Moreover, modules containing long-range connections between the frontal and occipital lobes disappeared, indicating that there was lack of top-down control information between the executive control region and the visual processing region in the ADHD group. Our results suggested that these abnormal regions were related to executive control and attention deficit of ADHD patients. These findings helped to better understand how brain function correlates with the ADHD symptoms and complement the fewer modularity elaboration of ADHD research.
注意缺陷多动障碍（ADHD）是儿童常见的精神障碍，与注意力不集中和多动有关。这些症状与大脑网络的异常相互作用有关。我们使用基于图论的静息态功能磁共振成像（rs-fMRI）来探索 ADHD 组和正常组之间大脑网络的拓扑性质变化。使用更精细的 AAL_1024 图谱来构建具有高节点分辨率的功能网络，以检测大脑区域的更细微变化和组间差异。我们从多层次比较了两组之间大脑网络拓扑性质的改变，主要包括中尺度的模块性。具体来说，我们分析了两组之间模块组成的相似性和差异性。结果发现，ADHD 组表现出更强的经济小世界网络特性，而聚类系数明显低于正常组；额叶和枕叶在疾病状态下的节点度和全局效率较小。模块化结果还表明，ADHD 组的模块数量减少，模块内的短程过度连接和模块间的长程连接不足。此外，包含额叶和枕叶之间长程连接的模块消失了，这表明 ADHD 组的执行控制区域和视觉处理区域之间缺乏自上而下的控制信息。我们的研究结果表明，这些异常区域与 ADHD 患者的执行控制和注意力缺陷有关。这些发现有助于更好地理解大脑功能与 ADHD 症状的相关性，并补充 ADHD 研究中较少的模块细化。
