Altered brain functional connectivity in vegetative state and minimally conscious state

Frontiers in Aging Neuroscience

Aging Neuroscience

Shan Wang¹  Jianghong He²  Xueling Chen²  Qiheng He²  Xiaoli Geng²  Yi Yang³  Feng Duan⁴  Yangyang Dai⁴ 

[1] Department of Information and Communications Engineering, School of Engineering, Tokyo Institute of Technology, Yokohama, Kanagawa, Japan;Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China;Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China;Chinese Institute for Brain Research, Beijing, China;Beijing Institute of Brain Disorders, Beijing, China;China National Clinical Research Center for Neurological Diseases, Beijing, China;Tianjin Key Laboratory of Brain Science and Intelligent Rehabilitation, College of Artificial Intelligence, Nankai University, Tianjin, China;

关键词: DoC;    MCS;    VS;    functional connectivity;    network representation;   

DOI  :  10.3389/fnagi.2023.1213904

 received in 2023-04-28, accepted in 2023-06-06,  发布年份 2023

来源: Frontiers

【 摘 要 】

ObjectivesThe pathological mechanism for a disorder of consciousness (DoC) is still not fully understood. Based on traditional behavioral scales, there is a high rate of misdiagnosis for subtypes of DoC. We aimed to explore whether topological characterization may explain the pathological mechanisms of DoC and be effective in diagnosing the subtypes of DoC.MethodsUsing resting-state functional magnetic resonance imaging data, the weighted brain functional networks for normal control subjects and patients with vegetative state (VS) and minimally conscious state (MCS) were constructed. Global and local network characteristics of each group were analyzed. A support vector machine was employed to identify MCS and VS patients.ResultsThe average connection strength was reduced in DoC patients and roughly equivalent in MCS and VS groups. Global efficiency, local efficiency, and clustering coefficients were reduced, and characteristic path length was increased in DoC patients (p < 0.05). For patients of both groups, global network measures were not significantly different (p > 0.05). Nodal efficiency, nodal local efficiency, and nodal clustering coefficient were reduced in frontoparietal brain areas, limbic structures, and occipital and temporal brain areas (p < 0.05). The comparison of nodal centrality suggested that DoC causes reorganization of the network structure on a large scale, especially the thalamus. Lobal network measures emphasized that the differences between the two groups of patients mainly involved frontoparietal brain areas. The accuracy, sensitivity, and specificity of the classifier for identifying MCS and VS patients were 89.83, 78.95, and 95%, respectively.ConclusionThere is an association between altered network structures and clinical symptoms of DoC. With the help of network metrics, it is feasible to differentiate MCS and VS patients.

【 授权许可】

Unknown   
Copyright © 2023 Yang, Dai, He, Wang, Chen, Geng, He and Duan.