Chen Bo, Sun Weigang, Yan Chuankui
Department of Mathematics, School of Science, Hangzhou Dianzi University, Hangzhou, 310018 People's Republic of China.
College of Mathematics and Physics, Wenzhou University, Wenzhou, 325024 People's Republic of China.
Cogn Neurodyn. 2024 Aug;18(4):2003-2013. doi: 10.1007/s11571-023-10063-z. Epub 2024 Feb 6.
The role of network metrics in exploring brain networks of mental illness is crucial. This study focuses on quantifying a node controllability index (CA-scores) and developing a novel framework for studying the dysfunction of attention deficit hyperactivity disorder (ADHD) brains. By analyzing fMRI data from 143 healthy controls and 102 ADHD patients, the controllability metric reveals distinct differences in nodes (brain regions) and subsystems (functional modules). There are significantly atypical CA-scores in the Rolandic operculum, superior medial orbitofrontal cortex, insula, posterior cingulate gyrus, supramarginal gyrus, angular gyrus, precuneus, heschl gyrus, and superior temporal gyrus of ADHD patients. A comparison with measures of connection strength, eigenvector centrality, and topology entropy suggests that the controllability index may be more effective in identifying abnormal regions in ADHD brains. Furthermore, our controllability index could be extended to investigate functional networks associated with other psychiatric disorders.
The online version contains supplementary material available at 10.1007/s11571-023-10063-z.
网络指标在探索精神疾病脑网络中的作用至关重要。本研究着重于量化节点可控性指数（CA分数），并开发一种用于研究注意力缺陷多动障碍（ADHD）大脑功能障碍的新框架。通过分析143名健康对照者和102名ADHD患者的功能磁共振成像（fMRI）数据，可控性指标揭示了节点（脑区）和子系统（功能模块）的明显差异。ADHD患者的中央前回盖、眶额内侧上皮质、脑岛、后扣带回、缘上回、角回、楔前叶、颞横回和颞上回存在显著异常的CA分数。与连接强度、特征向量中心性和拓扑熵测量值的比较表明，可控性指数在识别ADHD大脑中的异常区域可能更有效。此外，我们的可控性指数可扩展用于研究与其他精神疾病相关的功能网络。
在线版本包含可在10.1007/s11571-023-10063-z获取的补充材料。
