2024
Identifying 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
Extraction of One Time Point Dynamic Group Features via Tucker Decomposition of Multi-subject FMRI Data: Application to Schizophrenia
Han Y, Lin Q, Kuang L, Hao Y, Li W, Gong X, Calhoun V. Extraction of One Time Point Dynamic Group Features via Tucker Decomposition of Multi-subject FMRI Data: Application to Schizophrenia. Communications In Computer And Information Science 2023, 1963: 518-527. DOI: 10.1007/978-981-99-8138-0_41.Peer-Reviewed Original ResearchAmplitude of low frequency fluctuationsFMRI dataLow frequency fluctuationsSchizophrenia groupHealthy controlsMulti-subject fMRI dataInferior parietal lobuleProperties of brain functionParietal lobuleFMRI-dataMental disordersSchizophreniaBrain functionActivity differencesFrequency fluctuationsTwo-sample t-testSliding-window techniqueTucker decomposition