2024
Constrained 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 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 analysisSolutionConstrained 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 dataMethodMultilinear