Brain Relatively Inert Network: Taking Adult Attention Deficit Hyperactivity Disorder as an Example - Zhang, Hua; Zeng, Weiming; Deng, Jin; Shi, Yuhu; Zhao, Le; Li, Ying (Frontiers in Neuroscience, 2021)
Resting-state functional magnetic resonance imaging (RS-fMRI) has been increasingly applied in the research of brain cognitive science and psychiatric diseases. However, previous studies only focus on specific activation areas of the brain, and there are few studies on the inactivation areas. This may overlook lots of information that explains the brain's cognitive function. In this paper, we propose a relatively inert network (RIN) and try to explore its important role in understanding the cognitive mechanism of the brain and the study of mental diseases, using adult Attention deficit hyperactivity disorder (ADHD) as an example. Here we utilize methods based on group independent component analysis (GICA) and t-test to identify IRN and calculate its corresponding time-course. Through experiments, it is observed that alteration in the RIN and the corresponding activation network (AN) in adult ADHD patients. And compared with the left brain, the activation changes in the right brain are greater. Further, when the RIN functional connectivity is introduced as a feature to classify adult ADHD patients from healthy controls (HCs), the classification accuracy rate is 7% higher than that of the original functional connectivity feature. After further screening features by using XGBoost, the diagnostic accuracy rate for adult ADHD reached 98%. These findings confirm that the RIN of the brain contains lots of information that probably be neglected. Moreover, this research provides an effective new means of exploring the information integration between brain regions and the diagnosis of mental illness.