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
Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain
Yang L, Qiao C, Kanamori T, Calhoun V, Stephen J, Wilson T, Wang Y. Tensor dictionary-based heterogeneous transfer learning to study emotion-related gender differences in brain. Neural Networks 2024, 183: 106974. PMID: 39657530, DOI: 10.1016/j.neunet.2024.106974.Peer-Reviewed Original ResearchFeature spaceClassification performanceHeterogeneous transfer learningTensor dictionary learningHeterogeneous knowledge sharingTransfer learning frameworkReduce training costsDictionary learningKnowledge sharing strategyHeterogeneous transferGender classificationTransfer learningLearning frameworkConnectivity dataHeterogeneous dataHeterogeneous knowledgeBrain activity dataPriori knowledgeTraining costsSharing strategyProblem of insufficient sample sizeKnowledge sharingEEG dataExperimental resultsDictionaryImaging‐genomic spatial‐modality attentive fusion for studying neuropsychiatric disorders
Rahaman A, Garg Y, Iraji A, Fu Z, Kochunov P, Hong L, Van Erp T, Preda A, Chen J, Calhoun V. Imaging‐genomic spatial‐modality attentive fusion for studying neuropsychiatric disorders. Human Brain Mapping 2024, 45: e26799. PMID: 39562310, PMCID: PMC11576332, DOI: 10.1002/hbm.26799.Peer-Reviewed Original ResearchConceptsNeural networkDilated convolutional neural networkJoint learning frameworkAttention scoresState-of-the-artDeep neural networksNeural network decisionsConvolutional neural networkAttention fusionFusion moduleDiverse data sourcesArtificial intelligence modelsLearning frameworkAttention moduleJoint learningMultimodal clusteringNetwork decisionsInput streamMultimodal learningHigh-dimensionalIntermediate fusionFused dataSZ classificationIntelligence modelsContextual patternsA 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 modulationAccuracyA Novel Deep Subspace Learning Framework to Automatically Uncover Assessment-Specific Independent Brain Networks
Batta I, Abrol A, Calhoun V. A Novel Deep Subspace Learning Framework to Automatically Uncover Assessment-Specific Independent Brain Networks. 2024, 00: 1-6. DOI: 10.1109/ciss59072.2024.10480204.Peer-Reviewed Original ResearchLearning frameworkBrain subsystemsSubspace learning frameworkBrain networksHigh-dimensional neuroimaging dataConvolutional neural networkLow-dimensional subspaceSupervised learning approachDeep learning frameworkStructural brain featuresPredictive performanceUnsupervised approachNeural networkAutomated frameworkDimensional subspaceAlzheimer's diseaseLearning approachBrain changesFeature importanceTraining procedureNeuroimaging dataBrain featuresSalient networkNetworkBrain disorders
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