The altered network complexity of resting-state functional brain activity in schizophrenia and bipolar disorder patients  

作　　者：Yan Niu Nan Zhang Mengni Zhou Lan Yang Jie Sun Xueting Cheng Yanan Li Lefan Guo Jie Xiang Bin Wang 

机构地区：[1]College of Information and Computer,Taiyuan University of Technology,Taiyuan 030024,Shanxi,China [2]Graduate School of Interdisciplinary Science and Engineering in Health Systems,Okayama University,Okayama,Japan [3]Research Center for Medical Artificial Intelligence,Shenzhen Institute of Advanced Technology,Chinese Academy of Sciences,Shenzhen 518055,Guangzhou,China

出　　处：《Brain Science Advances》2023年第2期78-94,共17页神经科学（英文）

基　　金：This work is granted by the National Natural Science Functional of China(Grant Nos.61873178,62176177);Fundamental Research Program of Shanxi Province(Grant Nos.20210302123112,20210302124550);the Shanxi Provincial Foundation for Returnees(Grant No.2021-039);Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi(Grant No.2021L046).

摘　　要：Schizophrenia(SZ)and bipolar disorder(BD)are two of themost frequent mental disorders.These disorders exhibit similarpsychotic symptoms,making diagnosis challenging and leadingto misdiagnosis.Yet,the network complexity changes drivingspontaneous brain activity in SZ and BD patients are still unknown.Functional entropy(FE)is a novel way of measuring the dispersion(or spread)of functional connectivities inside the brain.The FE wasutilized in this study to examine the network complexity of the resting-state fMRI data of SZ and BD patients at three levels,including global,modules,and nodes.At three levels,the FE of SZand BD patients was considerably lower than that of normal control(NC).At the intra-module level,the FE of SZ was substantially higher than that of BD in the cingulo-opercular network.Moreover,a strong negative association between FE and clinical measureswas discovered in patient groups.Finally,we classified using theFE features and attained an accuracy of 66.7%(BD vs.SZ vs.NC)and an accuracy of 75.0%(SZ vs.BD).These findings proposed that network connectivity’s complexity analyses using FE can provideimportant insights for the diagnosis of mental illness.

关 键 词：functional entropy network complexity SCHIZOPHRENIA bipolar disorder resting-state fMRI 

分 类 号：R749.3[医药卫生—神经病学与精神病学] R749.4[医药卫生—临床医学]