A multimodal vision transformer for interpretable fusion of functional and structural neuroimaging data
Bi Y, Abrol A, Fu Z, Calhoun V. A multimodal vision transformer for interpretable fusion of functional and structural neuroimaging data. Human Brain Mapping 2024, 45: e26783. PMID: 39600159, PMCID: PMC11599617, DOI: 10.1002/hbm.26783.Peer-Reviewed Original ResearchConceptsCross-attention mechanismVision transformerDeep learning modelsBrain disordersCharacteristics of schizophreniaDiagnosis of schizophreniaStructural neuroimaging dataNetwork connectivity matrixData fusion approachAttention mapsMultimodal baselinesFunctional network connectivityFuse informationDeep learningICA algorithmFusion approachGrey matter mapsAI algorithmsFunctional network connectivity matricesLeverage multiple sources of informationGray matter imagesLearning modelsMultiple sources of informationBrain imaging modalitiesNetwork connectivityA Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity During Brain Development
Wang Y, Qiao C, Qu G, Calhoun V, Stephen J, Wilson T, Wang Y. A Deep Dynamic Causal Learning Model to Study Changes in Dynamic Effective Connectivity During Brain Development. IEEE Transactions On Biomedical Engineering 2024, 71: 3390-3401. PMID: 38968024, PMCID: PMC11700232, DOI: 10.1109/tbme.2024.3423803.Peer-Reviewed Original ResearchDynamic effective connectivityEffective connectivityBrain developmentBrain developmental trajectoriesPhiladelphia Neurodevelopmental CohortLearning modelsNeurodevelopmental CohortBrain regionsDevelopmental trajectoriesSpatio-temporal dataInformation processing capabilitiesFuse informationCausal LearnerYoung adults
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