2024
A spatially constrained independent component analysis jointly informed by structural and functional network connectivity
Fouladivanda M, Iraji A, Wu L, van Erp T, Belger A, Hawamdeh F, Pearlson G, Calhoun V. A spatially constrained independent component analysis jointly informed by structural and functional network connectivity. Network Neuroscience 2024, 1-31. DOI: 10.1162/netn_a_00398.Peer-Reviewed Original ResearchIntrinsic connectivity networksFunctional brain connectivityBrain connectivityStructural connectivityFunctional connectivityIndependent component analysisResting-state functional MRIAnalysis of group differencesBrain functional organizationFunctional network connectivityStructural-functional connectivityNeuroimaging studiesFunctional MRIWhole-brain tractographyGroup differencesRs-fMRIBrain disordersFunctional couplingSchizophreniaStatistical analysis of group differencesSubject levelFunctional organizationConnectivity networksBrainDiffusion-weighted MRIA Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence
Zhang A, Zhang G, Cai B, Wilson T, Stephen J, Calhoun V, Wang Y. A Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence. Network Neuroscience 2024, 8: 791-807. PMID: 39355441, PMCID: PMC11349030, DOI: 10.1162/netn_a_00384.Peer-Reviewed Original ResearchPhiladelphia Neurodevelopmental CohortEmotional circuitryFunctional connectivityBrain's emotional circuitryEmotion identification skillBrain network organizationIndividuals aged 8Emotional processingEmotion perceptionBrain circuitsNeurodevelopmental CohortFMRI dataCognitive developmentIdentification skillsEmotional changesAged 8Adolescent stageAdolescentsNetwork organizationGroup-specific patternsIntermodular connectionsEmotionsCircuit developmentAccurate performanceBrainAssociations of alcohol and tobacco use with psychotic, depressive and developmental disorders revealed via multimodal neuroimaging
Qiu L, Liang C, Kochunov P, Hutchison K, Sui J, Jiang R, Zhi D, Vergara V, Yang X, Zhang D, Fu Z, Bustillo J, Qi S, Calhoun V. Associations of alcohol and tobacco use with psychotic, depressive and developmental disorders revealed via multimodal neuroimaging. Translational Psychiatry 2024, 14: 326. PMID: 39112461, PMCID: PMC11306356, DOI: 10.1038/s41398-024-03035-2.Peer-Reviewed Original ResearchConceptsFronto-limbic networkSalience networkAssociated with cognitionFronto-basal gangliaDevelopmental disordersBrain networksLimbic systemAlcohol useAssociated with alcohol useMultimodal brain networksTobacco useAssociation of alcoholPsychiatric disordersMultimodal neuroimagingDMNBrain featuresCognitionAlcohol/tobacco useDisordersAssociated with tobacco useDepressionSymptomsFunctional abnormalitiesAlcoholBrainCognitive and psychiatric relevance of dynamic functional connectivity states in a large (N > 10,000) children population
Fu Z, Sui J, Iraji A, Liu J, Calhoun V. Cognitive and psychiatric relevance of dynamic functional connectivity states in a large (N > 10,000) children population. Molecular Psychiatry 2024, 1-12. PMID: 39085394, DOI: 10.1038/s41380-024-02683-6.Peer-Reviewed Original ResearchDynamic functional connectivity statesDynamic functional connectivityAdolescent Brain Cognitive DevelopmentCognitive performanceDynamic functional connectivity patternsSensory networksAnalysis of dynamic functional connectivityFunctional connectivity statesDefault-modeNeurological underpinningsAttention problemsPsychiatric relevanceFunctional connectivitySensorimotor networkMediation analysisCognitive developmentChild's brainBrain statesMental healthMental problemsBrain dynamicsSliding-window approachMental behaviorBrainCerebellum4D dynamic spatial brain networks at rest linked to cognition show atypical variability and coupling in schizophrenia
Pusuluri K, Fu Z, Miller R, Pearlson G, Kochunov P, Van Erp T, Iraji A, Calhoun V. 4D dynamic spatial brain networks at rest linked to cognition show atypical variability and coupling in schizophrenia. Human Brain Mapping 2024, 45: e26773. PMID: 39045900, PMCID: PMC11267451, DOI: 10.1002/hbm.26773.Peer-Reviewed Original ResearchConceptsBrain networksFunctional magnetic resonance imagingAssociated with cognitive performanceDynamics of functional brain networksAssociated with cognitionFunctional brain networksVoxel-wise changesVolumetric couplingDynamical variablesCognitive performanceTypical controlsSchizophreniaCognitive impairmentNetwork pairsMagnetic resonance imagingPair of networksCognitionAtypical variabilityResonance imagingCouplingNetwork connectivityNetwork growthImpairmentBrainStatic networksA survey of brain functional network extraction methods using fMRI data
Du Y, Fang S, He X, Calhoun V. A survey of brain functional network extraction methods using fMRI data. Trends In Neurosciences 2024, 47: 608-621. PMID: 38906797, DOI: 10.1016/j.tins.2024.05.011.Peer-Reviewed Original ResearchA Trifecta of Deep Learning Models: Assessing Brain Health by Integrating Assessment and Neuroimaging Data
Ajith M, M. Aycock D, B. Tone E, Liu J, B. Misiura M, Ellis R, M. Plis S, Z. King T, M. Dotson V, Calhoun V. A Trifecta of Deep Learning Models: Assessing Brain Health by Integrating Assessment and Neuroimaging Data. Aperture Neuro 2024, 4 DOI: 10.52294/001c.118576.Peer-Reviewed Original ResearchStatic functional network connectivityBrain health indexBrain healthResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingPsychological assessment measuresAssessment dataFunctional network connectivityMental health disordersBrain systemsEvaluating brain healthNeuroimaging dataRs-fMRINeural patternsPhysical well-beingCognitive declineAssessment measuresHealth disordersVariational autoencoderNeuroimagingHealthy brainBrainMagnetic resonance imagingTesting phaseWell-beingSearching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities
Fu Z, Batta I, Wu L, Abrol A, Agcaoglu O, Salman M, Du Y, Iraji A, Shultz S, Sui J, Calhoun V. Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities. NeuroImage 2024, 292: 120617. PMID: 38636639, PMCID: PMC11416721, DOI: 10.1016/j.neuroimage.2024.120617.Peer-Reviewed Original ResearchConceptsFunctional MRIStructural MRIResting-state scanSpatial similarity analysisMental health researchBrain markersDiffusion MRIAge differencesBrain featuresNeuromarkersBrain disordersYoung adult cohortBrain developmentWell-replicatedHuman brainBrainDiffusion MRI dataData-driven analysisDisordersSimilarity analysisAge cohortsGeneralizabilityPopulation-based researchAdult cohortAge-specific adaptationMarkov Spatial Flows in Bold FMRI: A Novel Lens on the Bold Signal Applied To an Imaging Study of Schizophrenia
Miller R, Vergara V, Calhoun V. Markov Spatial Flows in Bold FMRI: A Novel Lens on the Bold Signal Applied To an Imaging Study of Schizophrenia. 2024, 00: 13-16. DOI: 10.1109/ssiai59505.2024.10508684.Peer-Reviewed Original ResearchComplexity Measures of Psychotic Brain Activity In The FMRI Signal
Li Q, Seraji M, Calhoun V, Iraji A. Complexity Measures of Psychotic Brain Activity In The FMRI Signal. 2024, 00: 9-12. DOI: 10.1109/ssiai59505.2024.10508702.Peer-Reviewed Original ResearchBrain activityPsychotic brainBrain regionsFunctional connectivityCharacteristics of psychiatric disordersAtypical brain activityNeural activity patternsFuzzy recurrence plotsPsychiatric disordersFMRI signalsComplexity measuresRecurrence plotsActivity patternsBrainEntropySample entropyFMRIImage analysisNonlinear dynamical systemsRevealing complex functional topology brain network correspondences between humans and marmosets
Li Q, Calhoun V, Iraji A. Revealing complex functional topology brain network correspondences between humans and marmosets. Neuroscience Letters 2024, 822: 137624. PMID: 38218321, DOI: 10.1016/j.neulet.2024.137624.Peer-Reviewed Original ResearchConceptsWhole-brain functional connectivityFunctional brain connectivityDorsal attention networkFunctional connectivity patternsBrain connectivityMarmoset monkey brainBrain networksTopological characteristicsMode networkFunctional connectivityCognitive functionVisual networkNon-human primatesMonkey brainAttention networkConnectivity patternsNeural connectionsBrainFunctional correspondenceConnectome
2023
Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links
Fedorov A, Geenjaar E, Wu L, Sylvain T, DeRamus T, Luck M, Misiura M, Mittapalle G, Hjelm R, Plis S, Calhoun V. Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links. NeuroImage 2023, 285: 120485. PMID: 38110045, PMCID: PMC10872501, DOI: 10.1016/j.neuroimage.2023.120485.Peer-Reviewed Original ResearchConceptsBrain regionsMultimodal neuroimaging dataNeuroimaging dataBrain disordersComplex brain disordersMRI dataNeuroimaging researchGroup inferencesDeep InfoMaxSupervised modelsDiagnostic labelsDisordersBrainState-of-the-art unsupervised methodsAlzheimer's phenotypeNovel self-supervised frameworkSelf-supervised frameworkSelf-supervised methodologyCanonical correlation analysisSelf-supervised representationsState-of-the-artDeep learning approachSingle-modal dataMultimode linksComplex brainsPairing explainable deep learning classification with clustering to uncover effects of schizophrenia upon whole brain functional network connectivity dynamics
Ellis C, Miller R, Calhoun V. Pairing explainable deep learning classification with clustering to uncover effects of schizophrenia upon whole brain functional network connectivity dynamics. Neuroimage Reports 2023, 3: 100186. DOI: 10.1016/j.ynirp.2023.100186.Peer-Reviewed Original ResearchEffect of schizophreniaDynamic functional network connectivityBrain network dynamicsNeuropsychiatric disordersBrain activityFunctional magnetic resonance imagingInteractions of brain regionsFunctional network connectivityNetwork dynamicsBrain regionsSchizophreniaClustering algorithmEffect of SZHealthy controlsLearning classificationBrainMagnetic resonance imagingDeep learning modelsDeep learning classificationDisordersNetwork interactionsMachine learning classificationResonance imagingClustersNovel measuresMultimodal Fusion of Functional and Structural Data to Recognize Longitudinal Change Patterns in the Adolescent Brain
Saha R, Saha D, Fu Z, Silva R, Calhoun V. Multimodal Fusion of Functional and Structural Data to Recognize Longitudinal Change Patterns in the Adolescent Brain. 2023, 00: 1-5. DOI: 10.1109/bhi58575.2023.10313489.Peer-Reviewed Original ResearchFunctional network connectivityAdolescent brainPotential gender-related differencesBilateral sensorimotor cortexStructural magnetic resonance imagingMagnetic resonance imagingBrain functional connectivityGender-related differencesSensorimotor cortexLongitudinal change patternsGrey matter dataResonance imagingJoint independent component analysisLongitudinal changesFunctional connectivityBrain developmentBrain functionEntire brainBrain connectivityBrain connectionsBrain analysisBrainSensorimotor domainModalitiesSMRI dataAddressing Global Environmental Challenges to Mental Health Using Population Neuroscience
Schumann G, Andreassen O, Banaschewski T, Calhoun V, Clinton N, Desrivieres S, Brandlistuen R, Feng J, Hese S, Hitchen E, Hoffmann P, Jia T, Jirsa V, Marquand A, Nees F, Nöthen M, Novarino G, Polemiti E, Ralser M, Rapp M, Schepanski K, Schikowski T, Slater M, Sommer P, Stahl B, Thompson P, Twardziok S, van der Meer D, Walter H, Westlye L, Heinz A, Lett T, Vaidya N, Serin E, Neidhart M, Jentsch M, Eils R, Taron U, Schütz T, Banks J, Meyer-Lindenberg A, Tost H, Holz N, Schwarz E, Stringaris A, Christmann N, Jansone K, Siehl S, Ask H, Fernández-Cabello S, Kjelkenes R, Tschorn M, Böttger S, Bernas A, Marr L, Feixas Viapiana G, Eiroa-Orosa F, Gallego J, Pastor A, Forstner A, Claus I, Miller A, Heilmann-Heimbach S, Boye M, Wilbertz J, Schmitt K, Petkoski S, Pitel S, Otten L, Athanasiadis A, Pearmund C, Spanlang B, Alvarez E, Sanchez M, Giner A, Renner P, Gong Y, Dai Y, Xia Y, Chang X, Liu J, Young A, Ogoh G. Addressing Global Environmental Challenges to Mental Health Using Population Neuroscience. JAMA Psychiatry 2023, 80: 1066-1074. PMID: 37610741, DOI: 10.1001/jamapsychiatry.2023.2996.Peer-Reviewed Original ResearchConceptsMental illnessMechanisms of mental illnessSymptoms of depressionEvidence-based interventionsBrain mechanismsPopulation neuroscienceSocioeconomic inequalitiesEnvironmental adversityMental healthSubstance misuseBrain healthPsychosocial effectsDigital healthCohort dataDeep phenotyping dataObjective biomarkersHealthIllnessBrainDevelopment of objective biomarkersImprove outcomesPopulation levelCOVID-19 pandemicPollution measurementsResearch strategyDeep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity
Qiao C, Gao B, Liu Y, Hu X, Hu W, Calhoun V, Wang Y. Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity. Medical Image Analysis 2023, 90: 102941. PMID: 37683445, DOI: 10.1016/j.media.2023.102941.Peer-Reviewed Original ResearchFunctional connectivityBrain functional connectivityBrain networksDynamic brain functional connectivityDeep networksFunctional brain networksInformation processing abilityBrain development studiesEmotional processingDeep learning approachFeature selection strategyMachine learning modelsProcessing abilityBrain developmentCognitive activityDeep learningAccuracy-orientedSound processingBrainDevelopmental patternsLearning approachLearning modelsMental regulationSelection strategyInformation transmission mechanismEpigenetic associations with adolescent grey matter maturation and cognitive development
Jensen D, Chen J, Turner J, Stephen J, Wang Y, Wilson T, Calhoun V, Liu J. Epigenetic associations with adolescent grey matter maturation and cognitive development. Frontiers In Genetics 2023, 14: 1222619. PMID: 37529779, PMCID: PMC10390095, DOI: 10.3389/fgene.2023.1222619.Peer-Reviewed Original ResearchGM volume increaseGray matter maturationPatterns of brain maturationImprove cognitive performanceGray matterExecutive functionEpisodic memoryCognitive performanceCognitive testsBrain structuresProcessing speedBrain maturationCognitive AssessmentCognitive scoresBrain imagingAged 9BrainEpigenetic associationsAdolescentsLongitudinal cohortDNA methylationHuman neurodevelopmentDNA methylation of genesCytosine-phosphate-guanine (CpG) sitesBrain tissueA Deep Learning Approach for Psychosis Spectrum Label Noise Detection from Multimodal Neuroimaging Data
Rokham H, Falakshahi H, Calhoun V. A Deep Learning Approach for Psychosis Spectrum Label Noise Detection from Multimodal Neuroimaging Data. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2023, 00: 1-4. PMID: 38082903, DOI: 10.1109/embc40787.2023.10339949.Peer-Reviewed Original ResearchConceptsStructural MRI dataResting-state functional MRI dataFunctional MRI dataFunctional magnetic resonance imaging dataMRI dataMagnetic resonance imaging dataSchizophrenia patientsFunctional connectivity featuresBrain imaging modalitiesMental disordersNeuroimaging dataNeuroimaging techniquesBorderline subjectsHealthy control groupSchizophrenia datasetSchizophreniaConnectivity featuresBrainPsychosisMoodNosologyControl groupDisordersLabel noiseSubjectsFunctional 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 connectivityA Multivariate Method for Estimating and comparing whole brain functional connectomes from fMRI and PET data
Saha D, Bohsali A, Saha R, Hajjar I, Calhoun V. A Multivariate Method for Estimating and comparing whole brain functional connectomes from fMRI and PET data. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2023, 00: 1-4. PMID: 38083351, DOI: 10.1109/embc40787.2023.10340631.Peer-Reviewed Original ResearchConceptsWhole-brain functional connectomePositron emission tomographyResting fMRIResting fMRI dataBrain positron emission tomographyBrain functional connectomePositron emission tomography dataResting networksMagnetic resonance imagingConnectomeFunctional connectomeBrain networksConnectome patternsFMRIFMRI dataBrain functionSubject expressionPiB-PET scansBrainEmission tomographySpatial mappingSpatial networksClinical Relevance-This studyPET scansResonance imaging