2024
Interpretable Cognitive Ability Prediction: A Comprehensive Gated Graph Transformer Framework for Analyzing Functional Brain Networks
Qu G, Orlichenko A, Wang J, Zhang G, Xiao L, Zhang K, Wilson T, Stephen J, Calhoun V, Wang Y. Interpretable Cognitive Ability Prediction: A Comprehensive Gated Graph Transformer Framework for Analyzing Functional Brain Networks. IEEE Transactions On Medical Imaging 2024, 43: 1568-1578. PMID: 38109241, PMCID: PMC11090410, DOI: 10.1109/tmi.2023.3343365.Peer-Reviewed Original ResearchConceptsGraph transformation frameworkBrain imaging datasetsFunctional brain networksPhiladelphia Neurodevelopmental CohortConvolutional deep learningFeature embeddingPropagation weightsGraph embeddingHuman Connectome ProjectAttention mechanismImage datasetsDeep learningGraph transformationFunctional connectivityAnalyze functional brain networksTransformation frameworkDiffusion strategyBrain networksPositional encodingSpatial knowledgePrediction accuracyIndividual cognitive abilitiesEmbeddingNetworkGraphConnectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study
Georgiadis F, Larivière S, Glahn D, Hong L, Kochunov P, Mowry B, Loughland C, Pantelis C, Henskens F, Green M, Cairns M, Michie P, Rasser P, Catts S, Tooney P, Scott R, Schall U, Carr V, Quidé Y, Krug A, Stein F, Nenadić I, Brosch K, Kircher T, Gur R, Gur R, Satterthwaite T, Karuk A, Pomarol- Clotet E, Radua J, Fuentes-Claramonte P, Salvador R, Spalletta G, Voineskos A, Sim K, Crespo-Facorro B, Tordesillas Gutiérrez D, Ehrlich S, Crossley N, Grotegerd D, Repple J, Lencer R, Dannlowski U, Calhoun V, Rootes-Murdy K, Demro C, Ramsay I, Sponheim S, Schmidt A, Borgwardt S, Tomyshev A, Lebedeva I, Höschl C, Spaniel F, Preda A, Nguyen D, Uhlmann A, Stein D, Howells F, Temmingh H, Diaz Zuluaga A, López Jaramillo C, Iasevoli F, Ji E, Homan S, Omlor W, Homan P, Kaiser S, Seifritz E, Misic B, Valk S, Thompson P, van Erp T, Turner J, Bernhardt B, Kirschner M. Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study. Molecular Psychiatry 2024, 29: 1869-1881. PMID: 38336840, PMCID: PMC11371638, DOI: 10.1038/s41380-024-02442-7.Peer-Reviewed Original ResearchConnectivity profilesCortical alterationsCourse of schizophreniaBrain morphological alterationsAssociation of schizophreniaBrain network architectureAnatomical MRI scansTransdiagnostic comparisonsHuman Connectome ProjectDepressive disorderAffective disordersPathophysiological continuityPatient-specific symptomsSchizophreniaFrontal regionsDisease-related alterationsENIGMA studyCortical thinningNormative dataConnectome architectureIndividual symptomsConnectome ProjectDisease stageAlteration patternsHealthy controlsFunctional MRI of the Brainstem for Assessing Its Autonomic Functions: From Imaging Parameters and Analysis to Functional Atlas
Mohamed A, Kwiatek R, Del Fante P, Calhoun V, Lagopoulos J, Shan Z. Functional MRI of the Brainstem for Assessing Its Autonomic Functions: From Imaging Parameters and Analysis to Functional Atlas. Journal Of Magnetic Resonance Imaging 2024, 60: 1880-1891. PMID: 38339792, DOI: 10.1002/jmri.29286.Peer-Reviewed Original ResearchTemporal signal-to-noise-ratioHuman Connectome ProjectTesla MR scannerT1-weighted imagesFunctional atlasFunctional MRIFunctional MRI protocolROI overlapBrainstem atlasAdolescent Brain Cognitive DevelopmentBrainstem regionsBrainstemAutonomic functionImaging protocolFunctional MRI scansMeta-analysisConnectome ProjectImaging parametersMR scannerMRISignal-to-noise-ratioRoot-mean-square (rmsFunctional MRI data
2023
Denoising brain networks using a fixed mathematical phase change in independent component analysis of magnitude‐only fMRI data
Zhang C, Lin Q, Niu Y, Li W, Gong X, Cong F, Wang Y, Calhoun V. Denoising brain networks using a fixed mathematical phase change in independent component analysis of magnitude‐only fMRI data. Human Brain Mapping 2023, 44: 5712-5728. PMID: 37647216, PMCID: PMC10619417, DOI: 10.1002/hbm.26471.Peer-Reviewed Original ResearchConceptsComplex-valued dataComplex-valued fMRI dataBrain networksFMRI dataPhase informationHuman Connectome ProjectMapping frameworkMagnitude mapsExperimental fMRI dataConnectome ProjectPhase mapFMRI datasetsMagnitude dataDenoisingNetworkAmplitude thresholdComponent analysisPhase changePhaseSSP approachSpatial mappingFMRIUniversity of New MexicoThreshold