2024
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 connectivityNeurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm
Jiang Y, Luo C, Wang J, Palaniyappan L, Chang X, Xiang S, Zhang J, Duan M, Huang H, Gaser C, Nemoto K, Miura K, Hashimoto R, Westlye L, Richard G, Fernandez-Cabello S, Parker N, Andreassen O, Kircher T, Nenadić I, Stein F, Thomas-Odenthal F, Teutenberg L, Usemann P, Dannlowski U, Hahn T, Grotegerd D, Meinert S, Lencer R, Tang Y, Zhang T, Li C, Yue W, Zhang Y, Yu X, Zhou E, Lin C, Tsai S, Rodrigue A, Glahn D, Pearlson G, Blangero J, Karuk A, Pomarol-Clotet E, Salvador R, Fuentes-Claramonte P, Garcia-León M, Spalletta G, Piras F, Vecchio D, Banaj N, Cheng J, Liu Z, Yang J, Gonul A, Uslu O, Burhanoglu B, Uyar Demir A, Rootes-Murdy K, Calhoun V, Sim K, Green M, Quidé Y, Chung Y, Kim W, Sponheim S, Demro C, Ramsay I, Iasevoli F, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Park M, Kirschner M, Georgiadis F, Kaiser S, Van Rheenen T, Rossell S, Hughes M, Woods W, Carruthers S, Sumner P, Ringin E, Spaniel F, Skoch A, Tomecek D, Homan P, Homan S, Omlor W, Cecere G, Nguyen D, Preda A, Thomopoulos S, Jahanshad N, Cui L, Yao D, Thompson P, Turner J, van Erp T, Cheng W, Feng J. Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm. Nature Communications 2024, 15: 5996. PMID: 39013848, PMCID: PMC11252381, DOI: 10.1038/s41467-024-50267-3.Peer-Reviewed Original ResearchConceptsGray matter changesDisorder constructsEnlarged striatumPsychiatric conditionsMental disordersSubcortical regionsSchizophreniaBiological foundationsMatter changesBrain imagingStriatumDisordersBiological factorsIndividualsSubtypesHealthy subjectsCross-sectional brain imagingHippocampusTemporal trajectoriesInternational cohortSubgroup 2Subgroup 1SubgroupsFunctionally-Adaptive Gray and White Matter Structural Basis Sets via Dynamic Fusion of Multimodal MRI Data
Duda M, Calhoun V. Functionally-Adaptive Gray and White Matter Structural Basis Sets via Dynamic Fusion of Multimodal MRI Data. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40040008, DOI: 10.1109/embc53108.2024.10782492.Peer-Reviewed Original ResearchParallel Multilink Joint ICA for Multimodal Fusion of Gray Matter and Multiple Resting fMRI Networks
Khalilullah K, Agcaoglu O, Duda M, Calhoun V. Parallel Multilink Joint ICA for Multimodal Fusion of Gray Matter and Multiple Resting fMRI Networks. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40039683, DOI: 10.1109/embc53108.2024.10782528.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingJoint independent component analysisAssociated with Alzheimer's diseaseFalse discovery rateMultimodal fusion approachGray matterAssess group differencesHealthy controlsMultimodal fusionIndependent component analysisFusion approachSensorimotor domainBrain regionsSMRI dataGroup differencesParacentral lobuleBrain functionAD pathologyConnectivity patternsDiscovery rateJoint ICAJoint relationshipAlzheimer's diseaseActivity patternsMagnetic resonance imaging
2023
Network Differential in Gaussian Graphical Models from Multimodal Neuroimaging Data*
Falakshahi H, Rokham H, Miller R, Liu J, Calhoun V. Network Differential in Gaussian Graphical Models from Multimodal Neuroimaging Data*. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2023, 00: 1-6. PMID: 38083176, DOI: 10.1109/embc40787.2023.10340856.Peer-Reviewed Original ResearchConceptsStatic functional network connectivityGaussian graphical modelsBrain disordersBrain graphsModel of schizophreniaMiddle temporal gyrusMechanisms of brain disordersFunctional network connectivityGray matter featuresBrain network analysisTemporal gyrusGroup graphPath-based analysisCerebellar regionsGraph theory approachSchizophreniaMultimodal studiesGraphical modelsNetwork connectivityNetwork differentiationGray matterGraphical metricsControl graphPairwise edgesBrainICA-based Individualized Differential Structure Similarity Networks for Predicting Symptom Scores in Adolescents with Major Depressive Disorder
Li X, Xu M, Jiang R, Li X, Calhoun V, Zhou X, Sui J. ICA-based Individualized Differential Structure Similarity Networks for Predicting Symptom Scores in Adolescents with Major Depressive Disorder. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2023, 00: 1-5. PMID: 38082692, DOI: 10.1109/embc40787.2023.10340456.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentBrainConnectomeDepressive Disorder, MajorGray MatterHumansMagnetic Resonance ImagingConceptsMajor depressive disorderGray matter volumeDepressive disorderWhole-brain structural covariance networksConnectome-based predictive modelingAdolescent MDD patientsComplex mood disorderMeasure individual differencesDefault-mode networkStructural brain alterationsStructural covariance networksHamilton Depression ScaleHamilton Anxiety ScaleSpatially constrained ICAMDD patientsMood disordersBrain alterationsMatter volumeIndividual differencesBrain structuresCovariance networksAnxiety ScaleVisual networkDepression ScaleStructure similarity networkFunctional and Structural Longitudinal Change Patterns in Adolescent Brain
Saha R, Saha D, Fu Z, Silva R, Calhoun V. Functional and Structural Longitudinal Change Patterns in Adolescent Brain. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2023, 00: 1-4. PMID: 38082649, DOI: 10.1109/embc40787.2023.10340079.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingStructural magnetic resonance imagingFunctional network connectivityWhole-brainGray matterBrain functional magnetic resonance imagingMagnetic resonance imagingAdolescent brainFunctional connectivityResonance imagingMultivariate patternsLongitudinal change patternsUnivariate changesAdolescentsLongitudinal changesBrainIncreasing ageFunctional changesComplementary techniquesNetwork connectivity
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply