Vince Calhoun, PhD
About
Research
Publications
2024
A core tensor sparsity enhancement method for solving Tucker-2 model of multi-subject fMRI data
Han Y, Lin Q, Kuang L, Zhao B, Gong X, Cong F, Wang Y, Calhoun V. A core tensor sparsity enhancement method for solving Tucker-2 model of multi-subject fMRI data. Biomedical Signal Processing And Control 2024, 95: 106471. DOI: 10.1016/j.bspc.2024.106471.Peer-Reviewed Original ResearchTucker-2 modelMulti-subject fMRI dataFactor matricesCore tensorHalf-quadratic splittingTensor structure informationLow-rank constraintTensor sparsitySparsity constraintQuadratic splittingTask-related fMRI dataImprovement of accuracyEnhancement methodOrthogonality constraintsFMRI dataProcrustes solutionSimulated fMRI dataTucker-3 modelSparsityTemporal evidenceResting-state fMRI dataIdentity matrixDecomposition modelIntrinsic relationshipStructural informationFrequency modulation increases the specificity of time-resolved connectivity: A resting-state fMRI study
Faghiri A, Yang K, Faria A, Ishizuka K, Sawa A, Adali T, Calhoun V. Frequency modulation increases the specificity of time-resolved connectivity: A resting-state fMRI study. Network Neuroscience 2024, 1-28. DOI: 10.1162/netn_a_00372.Peer-Reviewed Original ResearchSliding window Pearson correlationTime-resolved networksSingle sideband modulationTime-resolved connectivityResting-state fMRI studiesSideband modulationFunctional magnetic resonance imagingFunctional network connectivityResting-state functional magnetic resonance imagingActivity time seriesTypical controlsFrequency modulationLow-frequency informationStateEpisode of psychosisNetwork connectivityHuman brainSub-corticalSuperior performanceFMRI studyCortical regionsAssociations 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 abnormalitiesAlcoholBrainAbsence of BOLD adaptation in chronic fatigue syndrome revealed by task functional MRI.
Schönberg L, Mohamed A, Yu Q, Kwiatek R, Del Fante P, Calhoun V, Shan Z. Absence of BOLD adaptation in chronic fatigue syndrome revealed by task functional MRI. Cerebrovascular And Brain Metabolism Reviews 2024, 271678x241270528. PMID: 39113421, DOI: 10.1177/0271678x241270528.Peer-Reviewed Original ResearchBlood oxygen level-dependentFunctional MRIME/CFS participantsHealthy controlsTask-based functional MRISymbol Digit Modalities TestFatigue syndromeRight postcentral gyrusTask functional MRIFMRI signal changesOxygen level-dependentMyalgic encephalomyelitis/chronic fatigue syndromeLeft primary motor cortexChronic fatigue syndromeTask blocksCognitive tasksPostcentral gyrusCognitive cortexBOLD adaptationNeurophysiological processesNeurophysiological mechanismsPrimary motor cortexLevel-dependentModal testingFatigue severityA 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, 1-17. 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 performanceBrainCognitive 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 networksConstrained 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, PP: 1-12. PMID: 39042541, 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 analysisInformationEffects of endogenous testosterone on oscillatory activity during verbal working memory in youth
Killanin A, Ward T, Embury C, Calhoun V, Wang Y, Stephen J, Picci G, Heinrichs‐Graham E, Wilson T. Effects of endogenous testosterone on oscillatory activity during verbal working memory in youth. Human Brain Mapping 2024, 45: e26774. PMID: 38949599, PMCID: PMC11215982, DOI: 10.1002/hbm.26774.Peer-Reviewed Original ResearchConceptsVerbal working memoryVerbal working memory processingWorking memory processesWorking memoryEffects of chronological ageEndogenous testosterone levelsMemory processesOscillatory activitySternberg verbal working memory taskEffects of testosteroneLeft-lateralized language networkVerbal working memory taskAlpha oscillationsSalivary testosterone samplesWorking memory encodingWorking memory taskLeft temporal cortexRight cerebellar cortexNeural oscillatory activitySignificant oscillatory responsesNeural oscillatory dynamicsHuman brain structureCerebellar cortexYouth aged 6Chronological ageIdentifying EEG Biomarkers of Depression with Novel Explainable Deep Learning Architectures
Ellis C, Sancho M, Miller R, Calhoun V. Identifying EEG Biomarkers of Depression with Novel Explainable Deep Learning Architectures. Communications In Computer And Information Science 2024, 2156: 102-124. DOI: 10.1007/978-3-031-63803-9_6.Peer-Reviewed Original ResearchDeep learning modelsExplainability methodsExplainability analysisConvolutional neural network architectureLearning modelsRaw electroencephalogramNeural network architectureDeep learning architectureMajor depressive disorderLearning architectureNetwork architectureDeep learningModel architectureMultichannel electroencephalogramTraining approachArchitectureBiomarkers of depressionFrequency bandElectroencephalogramResearch contextDepressive disorderElectroencephalogram biomarkerAccuracyRight hemisphereExplainability
Links & Media
News
- February 02, 2006
New MRI Technology at Yale: Brain Images that Show Structure and Function
- November 18, 2004
Brain Imaging Study of Drunk Drivers Pinpoints Neurological Changes
- July 20, 2004
NARSAD Funds 11 Yale University and Affiliated Researchers
- April 21, 2004
Imaging Test Could Be Used To Diagnose Schizophrenia