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 complexit...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.展开更多
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)+1 种基金the Shanxi Provincial Foundation for Returnees(Grant No.2021-039)Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi(Grant No.2021L046).
文摘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.
