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.

网络指标在探索精神疾病的大脑网络中的作用至关重要。这项研究的重点是量化节点可控性指数（CA 分数）并开发一个新的框架来研究注意力缺陷多动障碍（ADHD）大脑的功能障碍。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数据，可控性指标揭示了节点（大脑区域）和子系统（功能模块）的明显差异。 ADHD患者的Rolandic盖、内侧眶额皮质上层、岛叶、后扣带回、缘上回、角回、楔前叶、heschl回和颞上回存在显着非典型的CA评分。与连接强度、特征向量中心性和拓扑熵测量值的比较表明，可控性指数可能更有效地识别 ADHD 大脑中的异常区域。此外，我们的可控性指数可以扩展到研究与其他精神疾病相关的功能网络。