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 source
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, 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 MRIA Method for Multimodal IVA Fusion Within a MISA Unified Model Reveals Markers of Age, Sex, Cognition, and Schizophrenia in Large Neuroimaging Studies
Silva R, Damaraju E, Li X, Kochunov P, Ford J, Mathalon D, Turner J, van Erp T, Adali T, Calhoun V. A Method for Multimodal IVA Fusion Within a MISA Unified Model Reveals Markers of Age, Sex, Cognition, and Schizophrenia in Large Neuroimaging Studies. Human Brain Mapping 2024, 45: e70037. PMID: 39560198, PMCID: PMC11574741, DOI: 10.1002/hbm.70037.Peer-Reviewed Original ResearchConceptsMultimodal neuroimaging datasetSchizophrenia patientsNeuroimaging studiesCognitive performanceGroup differencesSchizophreniaSex effectsNeuroimaging datasetsMagnetic resonance imagingCognitionAge-associated declineControl subjectsMarkers of agingResonance imagingNon-imaging variablesSubject profilesSexNeuroimagingUK Biobank datasetFusion of Novel FMRI Features Using Independent Vector Analysis for a Multifaceted Characterization of Schizophrenia
Jia C, Abu Baker Siddique Akhonda M, Yang H, Calhoun V, Adali T. Fusion of Novel FMRI Features Using Independent Vector Analysis for a Multifaceted Characterization of Schizophrenia. 2015 23rd European Signal Processing Conference (EUSIPCO) 2024, 1112-1116. DOI: 10.23919/eusipco63174.2024.10715096.Peer-Reviewed Original ResearchFractional amplitude of low-frequency fluctuationAmplitude of low-frequency fluctuationResting-state functional magnetic resonanceCharacterization of schizophreniaFunctional magnetic resonanceBrain activity changesLow-frequency fluctuationsVisual cortexSchizophrenia patientsSchizophrenia NetworkBrain alterationsPsychiatric conditionsBrain regionsSchizophrenia biomarkersSchizophreniaFMRI featuresFractional amplitudeGroup differencesFMRI dataNeuroimaging analysisIndependent vector analysisActivity changesHealthy controlsBrainHigher-order statistical informationA new transfer entropy method for measuring directed connectivity from complex-valued fMRI data
Li W, Lin Q, Zhang C, Han Y, Calhoun V. A new transfer entropy method for measuring directed connectivity from complex-valued fMRI data. Frontiers In Neuroscience 2024, 18: 1423014. PMID: 39050665, PMCID: PMC11266018, DOI: 10.3389/fnins.2024.1423014.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingFMRI dataBrain regionsAnatomical Automatic LabelingTransfer entropyFunctional magnetic resonance imaging dataConnectivity of brain regionsFrontal-parietal regionsConsistent with previous findingsSignificant group differencesRight frontal-parietal regionPartial transfer entropyPredicting mental disordersMental disordersParietal regionsGroup differencesMagnitude effectExperimental fMRI dataDirectional connectivityComplex-valued fMRI dataSchizophreniaMagnetic resonance imagingComplex-valued approachEntropyMagnitude dataBrain community detection in the general children population
Farahdel B, Thapaliya B, Suresh P, Ray B, Calhoun V, Liu J. Brain community detection in the general children population. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-6. PMID: 40040186, DOI: 10.1109/embc53108.2024.10782157.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 imagingRevealing Alzheimer's Disease Dementia Patterns in [18F]Florbetapir PET with Independent Component Analysis
Khasayeva N, Eierud C, Jensen K, Premi E, Borroni B, Calhoun V, Iraji A. Revealing Alzheimer's Disease Dementia Patterns in [18F]Florbetapir PET with Independent Component Analysis. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40039485, DOI: 10.1109/embc53108.2024.10782873.Peer-Reviewed Original ResearchConceptsPositron emission tomographyFrontal componentIndependent component analysisAlzheimer's Disease Neuroimaging InitiativeInteraction effects of diagnosisPositron emission tomography brain imagingEffect of diagnosisSignificant group effectAlzheimer's diseasePotential of independent component analysisAD dementia groupsSignificant interaction effectEvaluate group differencesGroup differencesDementia groupGeneralized linear modelGroup effectBrain imagingSalienceIC weightsEmission tomographyAD dementiaDementiaDementia patternsNeurobiologySubgroup Identification Through Multiplex Community Structure Within Functional Connectivity Networks
Yang H, Ortiz-Bouza M, Vu T, Laport F, Calhoun V, Aviyente S, Adali T. Subgroup Identification Through Multiplex Community Structure Within Functional Connectivity Networks. 2024, 00: 2141-2145. DOI: 10.1109/icassp48485.2024.10446076.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingFunctional networksResting-state fMRI dataMultiplex networksMulti-subject functional magnetic resonance imagingNature of psychiatric disordersFunctional connectivity networksDiagnostic heterogeneityPsychotic patientsIndividual functional networksPsychiatric disordersCommunity detectionGroup differencesFMRI dataData-driven methodMultiple networksConnectivity networksMagnetic resonance imagingIdentified subgroupsNetworkSubgroup identificationResonance imagingSubject correlationSubgroup structureDynamic functional connectivity in anorexia nervosa: alterations in states of low connectivity and state transitions
Boehm I, Mennigen E, Geisler D, Poller N, Gramatke K, Calhoun V, Roessner V, King J, Ehrlich S. Dynamic functional connectivity in anorexia nervosa: alterations in states of low connectivity and state transitions. Journal Of Child Psychology And Psychiatry 2024, 65: 1299-1310. PMID: 38480007, DOI: 10.1111/jcpp.13970.Peer-Reviewed Original ResearchConceptsAnorexia nervosaFunctional connectivityResting state functional connectivityResting-state functional MRI dataInternalizing mental disordersAssociated with preoccupationOnset of anorexia nervosaFunctional MRI dataFemale healthy controlsHealthy controlsDynamic functional connectivityDynamics of functional connectivityTemporal dynamics of functional connectivityFunctional connectivity statesMental disordersStatic analytical approachesGroup differencesNervosaFractional timeMRI dataAdolescentsConnectivity statesFemale patientsClinical featuresTemporal dynamics
2023
Identifying psychosis subtypes use individualized covariance structural differential networks and multi-site clustering
Ji Y, Pearlson G, Bustillo J, Kochunov P, Turner J, Jiang R, Shao W, Zhang X, Fu Z, Li K, Liu Z, Xu X, Zhang D, Qi S, Calhoun V. Identifying psychosis subtypes use individualized covariance structural differential networks and multi-site clustering. Schizophrenia Research 2023, 264: 130-139. PMID: 38128344, DOI: 10.1016/j.schres.2023.12.013.Peer-Reviewed Original ResearchPsychosis subtypesSchizoaffective disorderBipolar disorderClinical phenotypeFirst-degree relativesTemporal-occipital cortexAmygdala-hippocampusClinical symptomsNeuroimaging featuresBipolar-Schizophrenia NetworkBrain alterationsHealthy controlsIntermediate Phenotypes (B-SNIP) consortiumOccipital cortexDecreased connectivitySubtypesStructural covarianceFractional amplitudeSubtype IILow-frequency fluctuationsNeurobiological heterogeneityGreater predispositionPsychosis spectrumGroup differencesDiagnostic classification6 Graph Analysis of Resting State Functional Brain Networks and Associations with Cognitive Outcomes in Survivors on Pediatric Brain Tumor
Semmel E, Calhoun V, Hillary F, Morris R, King T. 6 Graph Analysis of Resting State Functional Brain Networks and Associations with Cognitive Outcomes in Survivors on Pediatric Brain Tumor. Journal Of The International Neuropsychological Society 2023, 29: 316-317. DOI: 10.1017/s135561772300437x.Peer-Reviewed Original ResearchSurvivors of pediatric brain tumorsFunctional brain networksWorking memoryBrain networksCognitive outcomesProcessing speedLong-term neuropsychological deficitsResting state functional magnetic resonance imagingFunctional magnetic resonance imagingMeasures of attentionCore cognitive skillsLong-term cognitive outcomesStructural brain changesSmall-moderate effect sizeFunctional network propertiesSurvivors of brain tumorsBrain tumor survivorsGraph metricsResting state dataGlobal efficiencyNeuropsychological deficitsNeuropsychological testsBrain changesGroup differencesIndependence in adulthoodCoupled CP Tensor Decomposition with Shared and Distinct Components for Multi-Task Fmri Data Fusion
Borsoi R, Lehmann I, Akhonda M, Calhoun V, Usevich K, Brie D, Adali T. Coupled CP Tensor Decomposition with Shared and Distinct Components for Multi-Task Fmri Data Fusion. 2023, 00: 1-5. DOI: 10.1109/icassp49357.2023.10096241.Peer-Reviewed Original ResearchCP tensor decompositionTensor factorization approachDataset-specific featuresTensor-based frameworkPost-processing stepExtract featuresFunctional magnetic resonance imagingHyperparameter selectionTensor decompositionData fusionMulti-taskingDiscover componentsMultiple datasetsTaskCoupling matrixFunctional magnetic resonance imaging dataHyperparametersDatasetFeaturesGroup differencesFactor approachDecompositionFusion
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