Alterations in white matter network dynamics in patients with schizophrenia and bipolar disorder. Issue 13 (13th May 2022)

• Record Type: Journal Article
• Authors: Wang, Bin; Zhang, Shanshan; Yu, Xuexue; Niu, Yan; Niu, Jinliang; Li, Dandan; Zhang, Shan; Xiang, Jie; Yan, Ting; Yang, Jiajia; Wu, Jinglong; Liu, Miaomiao
• Is Part Of: Human brain mapping. Volume 43:Issue 13(2022)
• Page Start: 3909
• Page End: 3922
• Publication Date: 2022-05-13
• Subjects: classification -- control strategy -- controllability -- supercontroller -- synchronizability -- tradeoff; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.25892
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: Emerging evidence suggests white matter network abnormalities in patients with schizophrenia (SZ) and bipolar disorder (BD), but the alterations in dynamics of the white matter network in patients with SZ and BD are largely unknown. The white matter network of patients with SZ ( n = 45) and BD ( n = 47) and that of healthy controls (HC, n = 105) were constructed. We used dynamics network control theory to quantify the dynamics metrics of the network, including controllability and synchronizability, to measure the ability to transfer between different states. Experiments show that the patients with SZ and BD showed decreasing modal controllability and synchronizability and increasing average controllability. The correlations between the average controllability and synchronizability of patients were broken, especially for those with SZ. The patients also showed alterations in brain regions with supercontroller roles and their distribution in the cognitive system. Finally, we were able to accurately discriminate and predict patients with SZ and BD. Our findings provide novel dynamic metrics evidence that patients with SZ and BD are characterized by a selective disruption of brain network controllability, potentially leading to reduced brain state transfer capacity, and offer new guidance for the clinical diagnosis of mental illness. Abstract : We used dynamics network control theory to quantify the dynamics metrics of the network, including controllability and synchronizability of healthy controls, patients with schizophrenia and bipolar disorder. Our findings provide novel dynamic metrics evidence that patients with schizophrenia and bipolar disorder are characterized by a selective disruption of brain network controllability, potentially leading to reduced brain state transfer capacity, and offer new guidance for the clinical diagnosis of mental illness.