2025
An Explainable Unified Framework of Spatio-Temporal Coupling Learning With Application to Dynamic Brain Functional Connectivity Analysis
Gao B, Yu A, Qiao C, Calhoun V, Stephen J, Wilson T, Wang Y. An Explainable Unified Framework of Spatio-Temporal Coupling Learning With Application to Dynamic Brain Functional Connectivity Analysis. IEEE Transactions On Medical Imaging 2025, 44: 941-951. PMID: 39320999, DOI: 10.1109/tmi.2024.3467384.Peer-Reviewed Original ResearchSpatio-temporal informationDeep learning networkInter-node connectivitySpatio-temporal correlationMachine learning modelsNode representationsPoor explainabilityCoupling learningLearning frameworkDeep learningLearning networkLearning modelsExplainabilityTime series dataExperimental resultsCoupling associationFramework constructionLearningDynamic functional connectivityFrameworkBrain functional connectivity analysisBrain dynamic functional connectivityInformationConnectionNetwork
2024
Federated Privacy-Preserving Visualization: A Vision Paper
Tao Y, Sarwate A, Panta S, Plis S, Calhoun V. Federated Privacy-Preserving Visualization: A Vision Paper. 2024, 00: 8035-8041. DOI: 10.1109/bigdata62323.2024.10825849.Peer-Reviewed Original ResearchFederated learningRisk of data leakagePrivacy-preserving techniquesDifferential privacyData leakageSensitive informationVision paperFL applicationsModel trainingData visualizationExploratory data analysisCorrelation visualizationCentralized systemPrivacyLocal dataVisualizationDistribution dataData analysisMonitoring dataTaskDataLearningImplementationVisionInformationEfficient federated learning for distributed neuroimaging data
Thapaliya B, Ohib R, Geenjaar E, Liu J, Calhoun V, Plis S. Efficient federated learning for distributed neuroimaging data. Frontiers In Neuroinformatics 2024, 18: 1430987. PMID: 39315000, PMCID: PMC11416982, DOI: 10.3389/fninf.2024.1430987.Peer-Reviewed Original ResearchFederated learningCommunication overheadsSparse modelModel sparsityClient siteTraining phaseAdolescent Brain Cognitive DevelopmentData sharingEfficient communicationLarge modelsLocal trainingResource capabilitiesDatasetCommunicationLearningSparsityActual dataOverheadsPrivacyNeuroimaging dataCognitive developmentDataScientific communitySharingA Cross-Feature Mutual Learning Framework to Integrate Functional Connectivity and Activity for Brain Disorder Classification
Zhao M, Xu R, Zhi D, Yu S, Calhoun V, Sui J. A Cross-Feature Mutual Learning Framework to Integrate Functional Connectivity and Activity for Brain Disorder Classification. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40038938, DOI: 10.1109/embc53108.2024.10781810.Peer-Reviewed Original ResearchConceptsLearning frameworkMutual learning frameworkEnd-to-endDeep learning approachMutual knowledge transferEnsemble decisionClassification performanceCross featuresJoint lossLearning approachNetwork connectivityKnowledge transferEncodingAdaptive integrationIndependent componentsCollaborative learningDynamic dependenceTC-specificRobust characteristicsLearningStudy of brain disordersDisorder classificationEmpirical resultsCross-modal modulationAccuracyCGDM-GAN: An Adversarial Network Approach with Self-supervised Learning for Site Effect Removal
Cui X, Zhi D, Yan W, Calhoun V, Zhuo C, Sui J. CGDM-GAN: An Adversarial Network Approach with Self-supervised Learning for Site Effect Removal. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40039732, DOI: 10.1109/embc53108.2024.10782176.Peer-Reviewed Original ResearchConceptsSelf-supervised learningIntrinsic image propertiesGeneralization of modelsSynthetic datasetsClassification performanceGenerative modelDiscrepancy minimizationImage dataNetwork approachDatasetData harmonizationImaging propertiesLearningNeuroimaging classificationCycleGANData harmonization methodsAdversaryABCD datasetAcquisition protocolsPerformanceEffective wayDataTaskCross-Sampling Rate Transfer Learning for Enhanced Raw EEG Deep Learning Classifier Performance in Major Depressive Disorder Diagnosis
Ellis C, Miller R, Calhoun V. Cross-Sampling Rate Transfer Learning for Enhanced Raw EEG Deep Learning Classifier Performance in Major Depressive Disorder Diagnosis. 2024, 00: 1-5. DOI: 10.1109/isbi56570.2024.10635743.Peer-Reviewed Original ResearchTransfer learningDeep learning classifier’s performanceEarly convolutional layersConvolutional neural networkDeep learning modelsDeep learning studiesConvolutional layersClassifier performanceDiagnosis tasksExplainability analysisNeural networkSleep datasetsRaw electroencephalographyLearning modelsIncreased robustnessDatasetChannel lossSampling rateModel accuracyMDD modelLearningRepresentationTaskLearning studiesElectroencephalography
2023
Flexible Multisubject Multiset FMRI Data Analysis Using Robust Discriminative Dictionary Learning
Jin R, Xu S, Kim S, Calhoun V. Flexible Multisubject Multiset FMRI Data Analysis Using Robust Discriminative Dictionary Learning. 2023, 00: 1458-1462. DOI: 10.1109/ieeeconf59524.2023.10476781.Peer-Reviewed Original ResearchDictionary learning methodDiscriminative dictionary learningGroup sparsity constraintData setsDictionary learningAttribute labelsSparsity constraintLearning methodsFMRI data setsNeural activation mapsPre-specifyingActivation mapsMap typesFunctional magnetic resonance imagingNumerical testsMapsDictionaryAlgorithmSetsDataLearningSubject-specific attributesMethodData analysisConstraintsNew Interpretable Patterns and Discriminative Features from Brain Functional Network Connectivity using Dictionary Learning
Ghayem F, Yang H, Kantar F, Kim S, Calhoun V, Adali T. New Interpretable Patterns and Discriminative Features from Brain Functional Network Connectivity using Dictionary Learning. 2023, 00: 1-5. DOI: 10.1109/icassp49357.2023.10096473.Peer-Reviewed Original ResearchDictionary learningIndependent component analysisLearned atomsDiscovery of hidden informationNetwork connectivityMulti-subject functional magnetic resonance imagingFunctional magnetic resonance imagingFunctional network connectivityDiscriminative featuresFeature vectorHidden informationEffective classificationSZ groupHealthy controlsResting-state fMRI dataExperimental resultsICA resultsDictionaryBrain functional network connectivityBrain networksMental disordersFMRI dataLearningRepresentationMental diseases
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