biostudies-literatureJing RNatural Science Foundation of Beijing MunicipalityNational High Technology Research and Development Program of ChinaR&D Program of Beijing Municipal Education CommissionR&D Program of Beijing Municipal Education CommissionR&D Program of Beijing Municipal Education CommissionNational Natural Science Foundation of ChinaBeijing Natural Science Foundation2744-2754https://www.ebi.ac.uk/biostudies/studies/S-EPMC9638404biostudies-literatureUnknown16(6)Patients with major depressive disorder (MDD) display affective and cognitive impairments. Although MDD-associated abnormalities of brain function and structure have been explored in depth, the relationships between MDD and spatio-temporal large-scale functional networks have not been evaluated in large-sample datasets. We employed data from International Big-Data Center for Depression Research (IBCDR), and comparable 543 healthy controls (HC) and 314 first-episode drug-naive (FEDN) MDD patients were included. We used a multivariate pattern classification method to learn informative spatio-temporal functional states. Brain states of each participant were extracted for functional dynamic estimation using an independent component analysis. Then, a multi-kernel pattern classification method wBrain imaging and behaviorAltered spatio-temporal state patterns for functional dynamics estimation in first-episode drug-naive major depression.PMC96384047212141KM202011232008KM2020112320072019YFA070620142140807214299KM202211232018421408182101566Li HYu MHuo YSi JLin XLi PJing RLiu GfalseAltered spatio-temporal state patterns for functional dynamics estimation in first-episode drug-naive major depression.Patients with major depressive disorder (MDD) display affective and cognitive impairments. Although MDD-associated abnormalities of brain function and structure have been explored in depth, the relationships between MDD and spatio-temporal large-scale functional networks have not been evaluated in large-sample datasets. We employed data from International Big-Data Center for Depression Research (IBCDR), and comparable 543 healthy controls (HC) and 314 first-episode drug-naive (FEDN) MDD patients were included. We used a multivariate pattern classification method to learn informative spatio-temporal functional states. Brain states of each participant were extracted for functional dynamic estimation using an independent component analysis. Then, a multi-kernel pattern classification method w2022-01-01T00:00:00Z2022 Dec2025-04-03T21:30:58.864Z2025-04-03T21:30:58.864ZS-EPMC96384043633352210.1007/s11682-022-00739-1