2025
A telescopic independent component analysis on functional magnetic resonance imaging dataset
Mirzaeian S, Faghiri A, Calhoun V, Iraji A. A telescopic independent component analysis on functional magnetic resonance imaging dataset. Network Neuroscience 2025, 9: 61-76. PMCID: PMC11949590, DOI: 10.1162/netn_a_00421.Peer-Reviewed Original ResearchRight frontoparietal networkVisual networkIndependent component analysisBrain functionExtraction of informationFunctional magnetic resonance imaging datasetsImage datasetsFrontoparietal networkMagnetic resonance imaging datasetFMRI dataGroup differencesLeverage informationSmall networksDMNNetworkComponent analysisIncomplete viewAbstract Brain functionFunctional sourceMultimodal MRI accurately identifies amyloid status in unbalanced cohorts in Alzheimer’s disease continuum
Dolci G, Ellis C, Cruciani F, Brusini L, Abrol A, Galazzo I, Menegaz G, Calhoun V, . Multimodal MRI accurately identifies amyloid status in unbalanced cohorts in Alzheimer’s disease continuum. Network Neuroscience 2025, 9: 259-279. PMCID: PMC11949592, DOI: 10.1162/netn_a_00423.Peer-Reviewed Original ResearchNeuropathological hallmarks of Alzheimer's diseaseHallmarks of Alzheimer's diseaseHyperphosphorylated tau proteinAmyloid-bTau proteinNeurofibrillary tanglesNeuropathological hallmarksAmyloid accumulationAlzheimer's diseaseAb accumulationDepositional signatureIdentification of individualsAmyloid statusAccumulationAmyloidShed lightTanglesAlzheimer's disease continuumProteinAn Explainable Unified Framework of Spatio-Temporal Coupling Learning With Application to Dynamic Brain Functional Connectivity Analysis
Gao B, Yu A, Qiao C, Calhoun V, Stephen J, Wilson T, Wang Y. An Explainable Unified Framework of Spatio-Temporal Coupling Learning With Application to Dynamic Brain Functional Connectivity Analysis. IEEE Transactions On Medical Imaging 2025, 44: 941-951. PMID: 39320999, DOI: 10.1109/tmi.2024.3467384.Peer-Reviewed Original ResearchSpatio-temporal informationDeep learning networkInter-node connectivitySpatio-temporal correlationMachine learning modelsNode representationsPoor explainabilityCoupling learningLearning frameworkDeep learningLearning networkLearning modelsExplainabilityTime series dataExperimental resultsCoupling associationFramework constructionLearningDynamic functional connectivityFrameworkBrain functional connectivity analysisBrain dynamic functional connectivityInformationConnectionNetworkGenetic Etiology Link to Brain Function Underlying ADHD Symptoms and its Interaction with Sleep Disturbance: An ABCD Study
Feng A, Zhi D, Fu Z, Yu S, Luo N, Calhoun V, Sui J. Genetic Etiology Link to Brain Function Underlying ADHD Symptoms and its Interaction with Sleep Disturbance: An ABCD Study. Neuroscience Bulletin 2025, 1-13. PMID: 39827443, DOI: 10.1007/s12264-025-01349-9.Peer-Reviewed Original ResearchAttention deficit hyperactivity disorderPolygenic risk scoresSleep disturbanceAttention deficit hyperactivity disorder symptomsBrain functionAdolescent Brain Cognitive Development StudySevere attentional deficitsAssociated with polygenic risk scoresAttention deficit hyperactivity disorder casesCentral executive networkCognitive Development StudyDeficit hyperactivity disorderFunctional networksSensory-motor networkADHD symptomsExecutive networkAttention deficitMode networkHyperactivity disorderABCD studyBehavior problemsMaintaining sleepNeurodevelopmental disordersSensory-motorExperience sleep disturbancesImpaired spatial dynamic functional network connectivity and neurophysiological correlates in functional hemiparesis
Premi E, Cantoni V, Benussi A, Iraji A, Calhoun V, Corbo D, Gasparotti R, Tinazzi M, Borroni B, Magoni M. Impaired spatial dynamic functional network connectivity and neurophysiological correlates in functional hemiparesis. NeuroImage Clinical 2025, 45: 103731. PMID: 39764901, PMCID: PMC11762193, DOI: 10.1016/j.nicl.2025.103731.Peer-Reviewed Original ResearchDynamic functional network connectivitySomatomotor networkSalience networkFunctional network connectivityGABAergic neurotransmissionResting-state functional MRI scansResting-state fMRI dataFunctional MRI scansDynamic brain statesBrain network dynamicsStatic functional connectivityDynamic brain networksBrain networksGlutamatergic transmissionNeurophysiological correlatesFunctional connectivityTranscranial magnetic stimulation protocolFMRI dataGABAergic inhibitionMagnetic stimulation protocolBrain statesNeurotransmissionHealthy controlsDMNNetwork connectivity
2024
Corrigendum to “A multimodal neuroimaging-based risk score for mild cognitive impairment” [NeuroImage: Clinical 45 (2025) 103719]
Zendehrouh E, Sendi M, Abrol A, Batta I, Hassanzadeh R, Calhoun V. Corrigendum to “A multimodal neuroimaging-based risk score for mild cognitive impairment” [NeuroImage: Clinical 45 (2025) 103719]. NeuroImage Clinical 2024, 45: 103728. PMID: 39741014, DOI: 10.1016/j.nicl.2024.103728.Peer-Reviewed Original ResearchFederated Privacy-Preserving Visualization: A Vision Paper
Tao Y, Sarwate A, Panta S, Plis S, Calhoun V. Federated Privacy-Preserving Visualization: A Vision Paper. 2024, 00: 8035-8041. DOI: 10.1109/bigdata62323.2024.10825849.Peer-Reviewed Original ResearchFederated learningRisk of data leakagePrivacy-preserving techniquesDifferential privacyData leakageSensitive informationVision paperFL applicationsModel trainingData visualizationExploratory data analysisCorrelation visualizationCentralized systemPrivacyLocal dataVisualizationDistribution dataData analysisMonitoring dataTaskDataLearningImplementationVisionInformationBrain networks and intelligence: A graph neural network based approach to resting state fMRI data
Thapaliya B, Akbas E, Chen J, Sapkota R, Ray B, Suresh P, Calhoun V, Liu J. Brain networks and intelligence: A graph neural network based approach to resting state fMRI data. Medical Image Analysis 2024, 101: 103433. PMID: 39708510, PMCID: PMC11877132, DOI: 10.1016/j.media.2024.103433.Peer-Reviewed Original ResearchConceptsGraph neural networksNeural networkGraph isomorphism networkGraph convolutional layersGraph convolutional networkMachine learning modelsNetwork connectivity matrixCognitive processesConvolutional layersConvolutional networkPrediction taskModel architectureGraph architectureAdolescent Brain Cognitive Development datasetResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingLearning modelsMiddle frontal gyrusPredicting individual differencesResting state fMRI dataPredictive intelligenceIntelligenceNetworkFunctional network connectivity matricesArchitectureLarge-Scale Independent Vector Analysis (IVA-G) via Coresets
Gabrielson B, Yang H, Vu T, Calhoun V, Adali T. Large-Scale Independent Vector Analysis (IVA-G) via Coresets. IEEE Transactions On Signal Processing 2024, 73: 230-244. DOI: 10.1109/tsp.2024.3517323.Peer-Reviewed Original ResearchJoint blind source separationIndependent vector analysisBlind source separationSubset selection methodJoint diagonalizationMultivariate Gaussian modelSource separationSignificant scalabilityComputational costCoresetMultiple datasetsSelection methodDatasetMeasure of discrepancyGaussian modelVector analysisNumerous extensionsScalabilityMethodConsistent frontal-limbic-occipital connections in distinguishing treatment-resistant and non-treatment-resistant schizophrenia
Zhang Y, Gao S, Liang C, Bustillo J, Kochunov P, Turner J, Calhoun V, Wu L, Fu Z, Jiang R, Zhang D, Jiang J, Wu F, Peng T, Xu X, Qi S. Consistent frontal-limbic-occipital connections in distinguishing treatment-resistant and non-treatment-resistant schizophrenia. NeuroImage Clinical 2024, 45: 103726. PMID: 39700898, PMCID: PMC11721508, DOI: 10.1016/j.nicl.2024.103726.Peer-Reviewed Original ResearchNon-treatment-resistant schizophreniaTreatment-resistant schizophreniaFunctional connectivityDiagnosis of SZHealthy controlsFrontal-parietalResting-state functional connectivityAutomated anatomical labelingDysfunctional brain connectivityBrain functional connectivityAffiliated Brain Hospital of Nanjing Medical UniversityFrontal limbBrain connectivitySchizophreniaMedication dosageTreatment resistanceNeural pathwaysNanjing Medical UniversityDisease progressionMedical UniversityClinical practiceSpecific biomarkersDiagnosisAnatomical labelingA 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, 8: 1212-1242. PMID: 39735500, PMCID: PMC11674407, 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 MRIGPR-SCSANet: Unequal-Length Time Series Normalization with Split-Channel Residual Convolution and Self-Attention for Brain Age Prediction
Sun F, Liang C, Adali T, Zhang D, Jiang R, Calhoun V, Qi S. GPR-SCSANet: Unequal-Length Time Series Normalization with Split-Channel Residual Convolution and Self-Attention for Brain Age Prediction. 2024, 00: 5097-5103. DOI: 10.1109/bibm62325.2024.10822453.Peer-Reviewed Original ResearchSelf-attention mechanismResidual convolutionGaussian process regressionFunctional magnetic resonance imagingReal-world scenariosAge prediction taskSelf-attentionPrediction taskBrain age estimationAge predictionInherent informationBrain age predictionFMRI time coursesLength of time seriesProcess regressionVariables conflictBrain functional alterationsConvolutionPrediction accuracyUnequal-lengthTraditional methodsMotion artifactsDownstream applicationsTime series normalizationPrediction modelTensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain
Yang L, Qiao C, Kanamori T, Calhoun V, Stephen J, Wilson T, Wang Y. Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain. Neural Networks 2024, 183: 106974. PMID: 39657530, DOI: 10.1016/j.neunet.2024.106974.Peer-Reviewed Original ResearchFeature spaceClassification performanceHeterogeneous transfer learningTensor dictionary learningHeterogeneous knowledge sharingTransfer learning frameworkReduce training costsDictionary learningKnowledge sharing strategyHeterogeneous transferGender classificationTransfer learningLearning frameworkConnectivity dataHeterogeneous dataHeterogeneous knowledgeBrain activity dataPriori knowledgeTraining costsSharing strategyProblem of insufficient sample sizeKnowledge sharingEEG dataExperimental resultsDictionaryA multimodal Neuroimaging-Based risk score for mild cognitive impairment
Zendehrouh E, Sendi M, Abrol A, Batta I, Hassanzadeh R, Calhoun V. A multimodal Neuroimaging-Based risk score for mild cognitive impairment. NeuroImage Clinical 2024, 45: 103719. PMID: 39637673, PMCID: PMC11664180, DOI: 10.1016/j.nicl.2024.103719.Peer-Reviewed Original ResearchMild cognitive impairment riskMild cognitive impairmentMild cognitive impairment groupRisk of mild cognitive impairmentRisk scoreUK Biobank participantsFunctional network connectivityCognitive impairmentPrecursor to ADSignificant cognitive declineBiobank participantsUK BiobankMild cognitive impairment individualsGenetic risk factorsAlzheimer's diseaseFunctional MRIHigh-risk groupStructural MRIAD riskRisk factorsCognitive declineFeatures of CNGray matterDifferentiate CNParticipantsAnxiety symptoms are differentially associated with facial expression processing in boys and girls
Doucet G, Kruse J, Keefe A, Rice D, Coutant A, Pulliam H, Smith O, Calhoun V, Stephen J, Wang Y, White S, Picci G, Taylor B, Wilson T. Anxiety symptoms are differentially associated with facial expression processing in boys and girls. Social Cognitive And Affective Neuroscience 2024, 19: nsae085. PMID: 39587034, PMCID: PMC11631531, DOI: 10.1093/scan/nsae085.Peer-Reviewed Original ResearchFacial expression processingAssociated with psychiatric disordersExpression processingFacial expressionsFunctional magnetic resonance imagingFace processing taskMedial temporal cortexTypically-developing youthLevels of anxietyEmotional facesNeutral contrastAnxiety symptomsPosterior networkPsychiatric disordersFacial emotionsBrain responsesTemporal cortexNeural mechanismsHigher anxietyFMRI dataAnxietySocial informationAnxiety levelsBehavioral changesMagnetic resonance imagingA 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 connectivityMultimodal predictive modeling: Scalable imaging informed approaches to predict future brain health
Ajith M, Spence J, Chapman S, Calhoun V. Multimodal predictive modeling: Scalable imaging informed approaches to predict future brain health. Journal Of Neuroscience Methods 2024, 414: 110322. PMID: 39608579, PMCID: PMC11687617, DOI: 10.1016/j.jneumeth.2024.110322.Peer-Reviewed Original ResearchStatic functional network connectivityHealth constructsNeuroimaging dataBrain healthResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingSupport vector regressionFunctional network connectivityRandom forestCognitive performanceAssessment-onlyRs-fMRINeural patternsBehavioral outcomesBehavioral dataDiverse data sourcesNeural connectionsPsychological stateTraining stageMagnetic resonance imagingLongitudinal changesNetwork connectivityBrainPerformance evaluationVector regressionConstrained Independent Vector Analysis With Reference for Multi-Subject fMRI Analysis
Vu T, Laport F, Yang H, Calhoun V, Adal T. Constrained Independent Vector Analysis With Reference for Multi-Subject fMRI Analysis. IEEE Transactions On Biomedical Engineering 2024, 71: 3531-3542. PMID: 39042541, PMCID: PMC11754528, DOI: 10.1109/tbme.2024.3432273.Peer-Reviewed Original ResearchIndependent vector analysisIndependent component analysisIVA approachesIndependent vector analysis algorithmMulti-subject functional magnetic resonance imagingHigher-order statistical informationMulti-subject dataSingle-subject mappingModel interferenceMultiple datasetsPrior informationNovel methodStatistical dependenceDatasetSeparation qualityStatistical informationComputational issuesVariable thresholdAlgorithmStatistical diversityModel matchingVector analysisQuality of separationComponent analysisInformationA 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 adultsInter-Modality Source Coupling: A Fully-Automated Whole-Brain Data-Driven Structure-Function Fingerprint Shows Replicable Links to Reading in a Large-Scale (N8K) Analysis
Kotoski A, Liu J, Morris R, Calhoun V. Inter-Modality Source Coupling: A Fully-Automated Whole-Brain Data-Driven Structure-Function Fingerprint Shows Replicable Links to Reading in a Large-Scale (N8K) Analysis. IEEE Transactions On Biomedical Engineering 2024, 71: 3383-3389. PMID: 38968021, PMCID: PMC11700228, DOI: 10.1109/tbme.2024.3423703.Peer-Reviewed Original ResearchReading abilityBrain structuresSchool-aged childrenResting-stateStructural magnetic resonance imagingInferior frontal areasFunctional brain changesInferior parietal lobuleHigher reading abilityFunctional connectivity patternsLow reading abilityLingual gyrusNeural basisParietal lobuleReading developmentBrain changesCognitive processesReplication linksRs-fMRICortical regionsReading scoresBrain functionCognitive growthFrontal areasConnectivity patterns
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