2024
Large-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, PP: 1-13. 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 extensionsScalabilityMethodFusion 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 informationReproducibility and Replicability in Neuroimaging: Constrained IVA as an Effective Assessment Tool
Laport F, Dapena A, Vu T, Yang H, Calhoun V, Adali T. Reproducibility and Replicability in Neuroimaging: Constrained IVA as an Effective Assessment Tool. 2015 23rd European Signal Processing Conference (EUSIPCO) 2024, 802-806. DOI: 10.23919/eusipco63174.2024.10715160.Peer-Reviewed Original ResearchBlind source separationMatrix decomposition techniqueLinear blind source separationMulti-subject functional magnetic resonance imagingIndependent vector analysisPermutation ambiguityBSS techniquesDecomposition techniqueModel order selectionSource separationData-driven approachFunctional magnetic resonance imagingModel matchingModel orderComputational reproducibilityOrder selectionFMRI datasetsSuboptimal resultsMatchingDatasetConstrained 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, 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 analysisInformationIdentifying the Relationship Structure Among Multiple Datasets Using Independent Vector Analysis: Application to Multi-Task fMRI Data
Lehmann I, Hasija T, Gabrielson B, Akhonda M, Calhoun V, Adali T. Identifying the Relationship Structure Among Multiple Datasets Using Independent Vector Analysis: Application to Multi-Task fMRI Data. IEEE Access 2024, 12: 109443-109456. DOI: 10.1109/access.2024.3435526.Peer-Reviewed Original ResearchIndependent vector analysisTask datasetMultiple datasetsFeature extraction approachUser-defined thresholdsHigher-order statisticsMulti-task fMRI dataExtraction approachRelationship structureDatasetSimulation resultsHierarchical clusteringInterpretable componentsVector analysisFMRI-dataFMRI dataEffective wayMethodTaskDataActivated brain regionsHypothesis testingDistributional assumptionsInformation
2023
Reproducibility in Joint Blind Source Separation: Application to fMRI Analysis
Laport F, Vu T, Yang H, Calhoun V, Adali T. Reproducibility in Joint Blind Source Separation: Application to fMRI Analysis. 2023, 00: 1448-1452. DOI: 10.1109/ieeeconf59524.2023.10477028.Peer-Reviewed Original ResearchJoint blind source separationBlind source separationSource separationMulti-subject functional magnetic resonance imagingIndependent vector analysisRandom initializationLocal optimumNon-convexFlexible solutionCost functionModel complexityAccurate solutionsIterative methodFunctional magnetic resonance imaging analysisFMRI dataVector analysisSolutionREGRESSION-ASSISTED INDEPENDENT VECTOR ANALYSIS: A SOLUTION TO LARGE-SCALE FMRI DATA ANALYSIS
Yang H, Gabrielson B, Calhoun V, Adali T. REGRESSION-ASSISTED INDEPENDENT VECTOR ANALYSIS: A SOLUTION TO LARGE-SCALE FMRI DATA ANALYSIS. 2023, 00: 1443-1447. DOI: 10.1109/ieeeconf59524.2023.10476796.Peer-Reviewed Original ResearchFusion of Multi-Modal Neuroimaging Data and Association With Cognitive Data
LoPresto M, Akhonda M, Calhoun V, Adali T. Fusion of Multi-Modal Neuroimaging Data and Association With Cognitive Data. 2023, 00: 1-5. DOI: 10.1109/icasspw59220.2023.10193147.Peer-Reviewed Original ResearchHopkins Verbal Learning TestNeuropsychological assessment batteryCognitive dataNeuroimaging modalitiesBrief Assessment of CognitionSchizophrenia composite scoreVerbal Learning TestAssessment of CognitionMultiple neuroimaging modalitiesBrief AssessmentCross-modal connectionsLearning TestAssessment batteryCross-modal relationshipsNeuroimaging dataBrain benefitsCognitive scoresComposite scoreCognitionData-driven analysisIndependent vector analysisSchizophreniaNeuropsychologyFusion frameworkScoresConstrained Independent Component Analysis Based on Entropy Bound Minimization for Subgroup Identification from Multi-subject fMRI Data
Yang H, Ghayem F, Gabrielson B, Akhonda M, Calhoun V, Adali T. Constrained Independent Component Analysis Based on Entropy Bound Minimization for Subgroup Identification from Multi-subject fMRI Data. 2023, 00: 1-5. DOI: 10.1109/icassp49357.2023.10095816.Peer-Reviewed Original ResearchIndependent vector analysisSynthetic dataConstrained independent component analysisEntropy bound minimizationComputational complexity limitationsDemixing matrixIndependent component analysisComputational costOrthogonality requirementData identificationAlgorithmFunctional networksNetworkComponent analysisDatasetFMRI dataComputerTaskEntropyOrthogonalitySubgroup identificationVector analysisBrain networksDensity modelIndependent Vector Analysis with Multivariate Gaussian Model: a Scalable Method by Multilinear Regression
Gabrielson B, Sun M, Akhonda M, Calhoun V, Adali T. Independent Vector Analysis with Multivariate Gaussian Model: a Scalable Method by Multilinear Regression. 2023, 00: 1-5. DOI: 10.1109/icassp49357.2023.10096698.Peer-Reviewed Original ResearchJoint blind source separationIndependent vector analysisMultivariate Gaussian sourcesBlind source separationOverall estimation performanceGaussian sourceMultivariate Gaussian modelSource separationComputational costJoint decompositionEstimation performanceDatasetCost functionEstimated sourcesGaussian modelIntractable problemVector analysisMultilinear regressionEfficient methodScalable methodRegressorsFMRI dataMethodMultilinearEvaluating Trade-Offs in IVA of Multimodal Neuroimaging using Cross-Platform Multidataset Independent Subspace Analysis
Li X, Khosravinezhad D, Calhoun V, Silva R. Evaluating Trade-Offs in IVA of Multimodal Neuroimaging using Cross-Platform Multidataset Independent Subspace Analysis. 2023, 00: 1-5. DOI: 10.1109/isbi53787.2023.10230492.Peer-Reviewed Original ResearchIndependent vector analysisMultimodal neuroimaging datasetDeep latent variable modelBlind source separation methodMulti-network architectureIndependent Subspace AnalysisNeuroimaging datasetsSource separation methodPerformance trade-offsLatent spaceSubspace analysisTrade-offsPyTorch modulesLoss functionCross-platformMultiple datasetsLatent variable modelsDatasetCritical performance trade-offsOriginal frameworkVariable modelSimulation settingsModel performanceMultiple configurationsPlatformMultimodal Subspace Independent Vector Analysis Better Captures Hidden Relationships in Multimodal Neuroimaging Data
Li X, Adali T, Silva R, Calhoun V. Multimodal Subspace Independent Vector Analysis Better Captures Hidden Relationships in Multimodal Neuroimaging Data. 2023, 00: 1-5. DOI: 10.1109/isbi53787.2023.10230605.Peer-Reviewed Original ResearchSubspace structureIndependent vector analysisSynthetic datasetsMultimodal neuroimaging datasetUnimodal analysisData modalitiesHidden relationshipsCanonical correlation analysisIncorrect onesNeuroimaging datasetsSubspaceLatent sourcesDatasetNeuroimaging modalitiesDataPhenotypic measurementsCorrelation analysis