2025
Impaired spatial dynamic functional network connectivity and neurophysiological correlates in functional hemiparesis
Premi E, Cantoni V, Benussi A, Iraji A, Calhoun V, Corbo D, Gasparotti R, Tinazzi M, Borroni B, Magoni M. Impaired spatial dynamic functional network connectivity and neurophysiological correlates in functional hemiparesis. NeuroImage Clinical 2025, 45: 103731. PMID: 39764901, PMCID: PMC11762193, DOI: 10.1016/j.nicl.2025.103731.Peer-Reviewed Original ResearchDynamic functional network connectivitySomatomotor networkSalience networkFunctional network connectivityGABAergic neurotransmissionResting-state functional MRI scansResting-state fMRI dataFunctional MRI scansDynamic brain statesBrain network dynamicsStatic functional connectivityDynamic brain networksBrain networksGlutamatergic transmissionNeurophysiological correlatesFunctional connectivityTranscranial magnetic stimulation protocolFMRI dataGABAergic inhibitionMagnetic stimulation protocolBrain statesNeurotransmissionHealthy controlsDMNNetwork connectivity
2024
Exploring nonlinear dynamics in brain functionality through phase portraits and fuzzy recurrence plots
Li Q, Calhoun V, Pham T, Iraji A. Exploring nonlinear dynamics in brain functionality through phase portraits and fuzzy recurrence plots. Chaos An Interdisciplinary Journal Of Nonlinear Science 2024, 34: 103123. PMID: 39393183, DOI: 10.1063/5.0203926.Peer-Reviewed Original ResearchConceptsFuzzy recurrence plotsPhase portraitsComplex brain networksConnectivity descriptorsLow-dimensional dynamicsField of statistical physicsNonlinear dynamicsNeural mass modelMass modelRecurrence plotsStatistical physicsNeural time seriesFunctional connectivityLimit cycle attractorNonlinear phenomenaHidden informationComplex networksLatent informationPhase trajectoriesHigh-dimensionalDynamical theoryBrain functional connectivityBrain connectivityBrain networksNeural dynamicsAssociations of alcohol and tobacco use with psychotic, depressive and developmental disorders revealed via multimodal neuroimaging
Qiu L, Liang C, Kochunov P, Hutchison K, Sui J, Jiang R, Zhi D, Vergara V, Yang X, Zhang D, Fu Z, Bustillo J, Qi S, Calhoun V. Associations of alcohol and tobacco use with psychotic, depressive and developmental disorders revealed via multimodal neuroimaging. Translational Psychiatry 2024, 14: 326. PMID: 39112461, PMCID: PMC11306356, DOI: 10.1038/s41398-024-03035-2.Peer-Reviewed Original ResearchConceptsFronto-limbic networkSalience networkAssociated with cognitionFronto-basal gangliaDevelopmental disordersBrain networksLimbic systemAlcohol useAssociated with alcohol useMultimodal brain networksTobacco useAssociation of alcoholPsychiatric disordersMultimodal neuroimagingDMNBrain featuresCognitionAlcohol/tobacco useDisordersAssociated with tobacco useDepressionSymptomsFunctional abnormalitiesAlcoholBrain4D dynamic spatial brain networks at rest linked to cognition show atypical variability and coupling in schizophrenia
Pusuluri K, Fu Z, Miller R, Pearlson G, Kochunov P, Van Erp T, Iraji A, Calhoun V. 4D dynamic spatial brain networks at rest linked to cognition show atypical variability and coupling in schizophrenia. Human Brain Mapping 2024, 45: e26773. PMID: 39045900, PMCID: PMC11267451, DOI: 10.1002/hbm.26773.Peer-Reviewed Original ResearchConceptsBrain networksFunctional magnetic resonance imagingAssociated with cognitive performanceDynamics of functional brain networksAssociated with cognitionFunctional brain networksVoxel-wise changesVolumetric couplingDynamical variablesCognitive performanceTypical controlsSchizophreniaCognitive impairmentNetwork pairsMagnetic resonance imagingPair of networksCognitionAtypical variabilityResonance imagingCouplingNetwork connectivityNetwork growthImpairmentBrainStatic networksCopula linked parallel ICA jointly estimates linked structural and functional MRI brain networks
Agcaoglu O, Alacam D, Adalı T, Calhoun V, Silva R, Plis S, Bostami B. Copula linked parallel ICA jointly estimates linked structural and functional MRI brain networks. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40040121, DOI: 10.1109/embc53108.2024.10781658.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingStructural MRIAmplitude of low frequency fluctuationsBrain imaging methodsStructural MRI dataFunctional network connectivityLow frequency fluctuationsEstimated independent sourcesBrain networksRegional homogeneityFMRI networksTemporal informationMagnetic resonance imagingFrequency fluctuationsAlzheimer's studiesBrainResonance imagingFusion approachUnmixing matrixNetwork connectivityReal-dataSensorimotorNetworkCerebellumPath-based Differential Analysis in Near-centenarians and Centenarians Brain Network
Falakshahi H, Rokham H, Calhoun V. Path-based Differential Analysis in Near-centenarians and Centenarians Brain Network. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40039654, DOI: 10.1109/embc53108.2024.10781732.Peer-Reviewed Original ResearchConceptsCognitive control domainsBrain networksCognitive functionPreservation of cognitive functionPromote cognitive healthInvestigate brain networksGaussian graphical modelsControl domainCognitive agingNeural mechanismsGraph theory techniquesGraphical modelsCognitive healthIntricate informationBrain graphsNear-centenariansGroup graphGraphNetworkGraph metricsGraph theoryAging StudyBrainTargeted interventionsYounger groupScepter: Weakly Supervised Framework for Spatiotemporal Dense Prediction of 4D Dynamic Brain Networks
Kazemivash B, Suresh P, Liu J, Ye D, Calhoun V. Scepter: Weakly Supervised Framework for Spatiotemporal Dense Prediction of 4D Dynamic Brain Networks. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40039527, DOI: 10.1109/embc53108.2024.10781876.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingDynamic brain networksDense predictionBrain networksDynamic patterns of neural activityPatterns of neural activityBrain dynamicsSpatiotemporal brain dynamicsConsistent with previous findingsWeakly supervised frameworkComputer visionWeak supervisionModel architectureNetwork issuesSupervised frameworkFMRI dataBrain parcellation methodBrain functionNeural activityNeuroscience researchComplexity of brain functionNeural interactionsDeep-stackingExperimental resultsNetworkBeyond Artifacts: Rethinking Motion-Related Signals in Resting-State fMRI Analysis
Kumar S, Kinsey S, Jensen K, Bajracharya P, Calhoun V, Iraji A. Beyond Artifacts: Rethinking Motion-Related Signals in Resting-State fMRI Analysis. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-4. PMID: 40040138, DOI: 10.1109/embc53108.2024.10782518.Peer-Reviewed Original ResearchConceptsFunctional network connectivityBOLD time seriesImpact of head motionHead motion dataLarge-scale brain networksIntrinsic brain functional connectivityResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingFunctional brain connectivityResting-state fMRI analysisRsfMRI dataBOLD fMRIHead motionBrain functional connectivityHealthy controlsBOLD signalBrain connectivityBrain networksMotion dataFMRI analysisFunctional connectivityClinical populationsMotion-related signalsClinical implicationsBOLDA Deep Biclustering Framework for Brain Network Analysis
Rahaman A, Fu Z, Iraji A, Calhoun V. A Deep Biclustering Framework for Brain Network Analysis. 2024, 00: 5075-5085. DOI: 10.1109/cvprw63382.2024.00514.Peer-Reviewed Original ResearchDeep neural networksBrain networksState-of-the-artFunctional connectivityNeural networkFeature dimensionsBiclustering frameworkSuboptimal solutionBrain functional connectivityNeuroimaging datasetsBrain network analysisHuman brain dynamicsNetworkNeurobiological mechanismsBiclustering methodsNeural systemsAssigned probability distributionsProbability distributionBrain componentsBrain dynamicsCluster generalizationBiclusteringBrainFrameworkBN edgesThe dynamics of dynamic time warping in fMRI data: A method to capture inter-network stretching and shrinking via warp elasticity
Wiafe S, Faghiri A, Fu Z, Miller R, Preda A, Calhoun V. The dynamics of dynamic time warping in fMRI data: A method to capture inter-network stretching and shrinking via warp elasticity. Imaging Neuroscience 2024, 2: 1-23. DOI: 10.1162/imag_a_00187.Peer-Reviewed Original ResearchDynamic time warpingDynamics of brain networksBrain networksBrain network interactionsFunctional magnetic resonance imagingFunctional connectivity measuresComplexity of brain functionDiverse timescalesTime warpingBrain dynamicsVisual cortexFunctional magnetic resonance imaging dataTimescalesFunctional connectivityBrain connectivityCoupled stretchingCouplingDynamic time warping methodBrain regionsTransient couplingConnectivity measuresFunctional connectivity metricsNeuroimaging researchCluster centroidsIntricate dynamicsCoupling between Time-Varying EEG Spectral Bands and Spatial Dynamic FMRI Networks
Phadikar S, Pusuluri K, Jensen K, Wu L, Iraji A, Calhoun V. Coupling between Time-Varying EEG Spectral Bands and Spatial Dynamic FMRI Networks. 2024, 00: 1-4. DOI: 10.1109/isbi56570.2024.10635622.Peer-Reviewed Original ResearchFunctional brain networksDynamic brain networksBrain networksSpectral propertiesDynamics of functional brain networksFMRI networksSpectral bandsSpatial dimensionsResting-state functional magnetic resonance imagingConnectivity matrixCouplingBandFunctional magnetic resonance imagingDynamic networksSimultaneous electroencephalographyPersonalized treatment approachesElectroencephalography spectral powerResting stateMagnetic resonance imagingExplainable Multimodal Graph Isomorphism Network for Interpreting Sex Differences in Adolescent Neurodevelopment
Patel B, Orlichenko A, Patel A, Qu G, Wilson T, Stephen J, Calhoun V, Wang Y. Explainable Multimodal Graph Isomorphism Network for Interpreting Sex Differences in Adolescent Neurodevelopment. Applied Sciences 2024, 14: 4144. DOI: 10.3390/app14104144.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingBlood oxygen level-dependentGraph isomorphism networkGraph neural networksBrain networksFunctional magnetic resonance imaging paradigmFunctional magnetic resonance imaging blood oxygen level-dependentSex differencesClassification accuracyExploration of sex differencesInterpreting sex differencesOxygen level-dependentState-of-the-art algorithmsAdolescent neurodevelopmentState-of-the-artNeuropsychiatric conditionsFunctional connectivityTask-related dataDeep learning modelsLevel-dependentMouth movementsFMRI datasetsFunctional networksGraph structureAdolescentsTopological state-space estimation of functional human brain networks
Chung M, Huang S, Carroll I, Calhoun V, Goldsmith H. Topological state-space estimation of functional human brain networks. PLOS Computational Biology 2024, 20: e1011869. PMID: 38739671, PMCID: PMC11115255, DOI: 10.1371/journal.pcbi.1011869.Peer-Reviewed Original ResearchThe risk of cannabis use disorder is mediated by altered brain connectivity: A chronnectome study
Fazio G, Olivo D, Wolf N, Hirjak D, Schmitgen M, Werler F, Witteman M, Kubera K, Calhoun V, Reith W, Wolf R, Sambataro F. The risk of cannabis use disorder is mediated by altered brain connectivity: A chronnectome study. Addiction Biology 2024, 29: e13395. PMID: 38709211, PMCID: PMC11072977, DOI: 10.1111/adb.13395.Peer-Reviewed Original ResearchConceptsRisk of cannabis use disorderCannabis use disorderDynamic functional connectivityFunctional connectivityUse disorderTreatment of cannabis use disorderAt-risk individualsResting-state functional magnetic resonance imagingFunctional magnetic resonance imagingCannabis-related problemsDefault-mode networkPatterns of FCCognitive-controlCUDIT-RBrain mechanismsSubcortical functionBrain networksSelf-screening questionnaireBrain connectivityBrain functionSensory-motorNeurostimulation treatmentsMagnetic resonance imagingBrainCluster statesAnalysis of High-Order Brain Networks Resolved in Time and Frequency Using CP Decomposition
Faghiri A, Iraji A, Adali T, Calhoun V. Analysis of High-Order Brain Networks Resolved in Time and Frequency Using CP Decomposition. 2024, 00: 13346-13350. DOI: 10.1109/icassp48485.2024.10446864.Peer-Reviewed Original ResearchInterpretable Cognitive Ability Prediction: A Comprehensive Gated Graph Transformer Framework for Analyzing Functional Brain Networks
Qu G, Orlichenko A, Wang J, Zhang G, Xiao L, Zhang K, Wilson T, Stephen J, Calhoun V, Wang Y. Interpretable Cognitive Ability Prediction: A Comprehensive Gated Graph Transformer Framework for Analyzing Functional Brain Networks. IEEE Transactions On Medical Imaging 2024, 43: 1568-1578. PMID: 38109241, PMCID: PMC11090410, DOI: 10.1109/tmi.2023.3343365.Peer-Reviewed Original ResearchConceptsGraph transformation frameworkBrain imaging datasetsFunctional brain networksPhiladelphia Neurodevelopmental CohortConvolutional deep learningFeature embeddingPropagation weightsGraph embeddingHuman Connectome ProjectAttention mechanismImage datasetsDeep learningGraph transformationFunctional connectivityAnalyze functional brain networksTransformation frameworkDiffusion strategyBrain networksPositional encodingSpatial knowledgePrediction accuracyIndividual cognitive abilitiesEmbeddingNetworkGraphDistribution of Connectivity Strengths Across Functional Regions has Higher Entropy in Schizophrenia Patients than in Controls
Maksymchuk N, Miller R, Calhoun V. Distribution of Connectivity Strengths Across Functional Regions has Higher Entropy in Schizophrenia Patients than in Controls. 2024, 00: 37-40. DOI: 10.1109/ssiai59505.2024.10508663.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingGroup independent component analysisSchizophrenia patientsCognitive controlResting-state functional magnetic resonance imagingIntrinsic connectivity networksHealthy controlsGender-matched healthy controlsSZ patientsNeuropsychiatric disordersBrain areasBrain networksSchizophreniaDisrupted integrityBrain domainsConnection strengthIndependent component analysisConnectivity networksMagnetic resonance imagingSomatomotorDistribution of connection strengthsResonance imagingCross-sectional dataPatientsDiagnostic testsA 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 disordersA Method to Estimate Longitudinal Change Patterns in Functional Network Connectivity of the Developing Brain Relevant to Psychiatric Problems, Cognition, and Age
Saha R, Saha D, Rahaman A, Fu Z, Liu J, Calhoun V. A Method to Estimate Longitudinal Change Patterns in Functional Network Connectivity of the Developing Brain Relevant to Psychiatric Problems, Cognition, and Age. Brain Connectivity 2024, 14: 130-140. PMID: 38308475, PMCID: PMC10954605, DOI: 10.1089/brain.2023.0040.Peer-Reviewed Original ResearchFunctional network connectivityFunctional connectivityPsychiatric problemsFunctional network connectivity matricesNetwork connectivityMultivariate patternsWhole-brain functional networksIntrinsic functional connectivityPattern of functional changesBrain functional connectivityIntrinsic functional relationshipLongitudinal changesAdolescent brainAge-related changesBrain networksStudy developmental changesScanning sessionBrain functionAssociated with longitudinal changesCognitive scoresDevelopmental changesBrain developmentFunctional changesCognitionLongitudinal change patternsRevealing complex functional topology brain network correspondences between humans and marmosets
Li Q, Calhoun V, Iraji A. Revealing complex functional topology brain network correspondences between humans and marmosets. Neuroscience Letters 2024, 822: 137624. PMID: 38218321, DOI: 10.1016/j.neulet.2024.137624.Peer-Reviewed Original ResearchConceptsWhole-brain functional connectivityFunctional brain connectivityDorsal attention networkFunctional connectivity patternsBrain connectivityMarmoset monkey brainBrain networksTopological characteristicsMode networkFunctional connectivityCognitive functionVisual networkNon-human primatesMonkey brainAttention networkConnectivity patternsNeural connectionsBrainFunctional correspondenceConnectome
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply