2025
Movies reveal the fine-grained organization of infant visual cortex
Ellis C, Yates T, Arcaro M, Turk-Browne N. Movies reveal the fine-grained organization of infant visual cortex. ELife 2025, 12: rp92119. PMID: 40047799, PMCID: PMC11884787, DOI: 10.7554/elife.92119.Peer-Reviewed Original ResearchMovies reveal the fine-grained organization of infant visual cortex
Ellis C, Yates T, Arcaro M, Turk-Browne N. Movies reveal the fine-grained organization of infant visual cortex. ELife 2025, 12 DOI: 10.7554/elife.92119.4.Peer-Reviewed Original ResearchBrain activityInfant visual systemMagnetic resonance imagingFunctional magnetic resonance imagingInfants' visual processingAdults' brain activityVentral visual cortexInfant brain activityShort attention spanAdult brainVisual cortexInfants' perceptionCognitive tasksBrain organizationBrain structuresInfant scansInfant mindFMRI dataInfant brain structureSensory processingNeurodevelopmental conditionsVisual processingAttention spanHomotopic areasInfant brainA telescopic independent component analysis on functional magnetic resonance imaging dataset
Mirzaeian S, Faghiri A, Calhoun V, Iraji A. A telescopic independent component analysis on functional magnetic resonance imaging dataset. Network Neuroscience 2025, 9: 61-76. PMID: 40161992, PMCID: PMC11949590, DOI: 10.1162/netn_a_00421.Peer-Reviewed Original ResearchRight frontoparietal networkVisual networkIndependent component analysisBrain functionExtraction of informationFunctional magnetic resonance imaging datasetsImage datasetsFrontoparietal networkMagnetic resonance imaging datasetFMRI dataGroup differencesLeverage informationSmall networksDMNNetworkComponent analysisIncomplete viewAbstract Brain functionFunctional sourcePrediction of alcohol intake patterns with olfactory and gustatory brain connectivity networks
Agarwal K, Chaudhary S, Tomasi D, Volkow N, Joseph P. Prediction of alcohol intake patterns with olfactory and gustatory brain connectivity networks. Neuropsychopharmacology 2025, 50: 1167-1175. PMID: 39962224, PMCID: PMC12089591, DOI: 10.1038/s41386-025-02058-7.Peer-Reviewed Original ResearchVentral attention networkBrain connectivity patternsHuman Connectome ProjectResting-state fMRI dataConnectivity patternsRisk of AUDYoung adultsBrain network connectivityAlcohol intake patternsAlcohol intakeAlcohol consumption behaviorOlfactory perceptionFMRI dataFunctional connectomePast-weekLongitudinal researchAttention networkYoung adult cohortChemosensory cuesBrain connectivity networksConnectome ProjectPast-yearConnectivity networksAlcohol drinkersAlcoholStatic and Dynamic Cross‐Network Functional Connectivity Shows Elevated Entropy in Schizophrenia Patients
Maksymchuk N, Miller R, Bustillo J, Ford J, Mathalon D, Preda A, Pearlson G, Calhoun V. Static and Dynamic Cross‐Network Functional Connectivity Shows Elevated Entropy in Schizophrenia Patients. Human Brain Mapping 2025, 46: e70134. PMID: 39924889, PMCID: PMC11808047, DOI: 10.1002/hbm.70134.Peer-Reviewed Original ResearchConceptsSZ patientsCognitive controlBrain networksFunctional connectivityHealthy controlsBrain domainsConnection strengthAnalyzed fMRI dataFunctional brain networksDiagnosed mental health conditionDynamic functional connectivityMental health conditionsSchizophrenia patientsSchizophreniaFMRI dataBrain statesEntropy correlationBrainDiseased brain statesSensorimotorControl groupK-means cluster analysisDMNConnection levelHealth conditionsRepresenting brain-behavior associations by retaining high-motion minoritized youth
Ramduny J, Uddin L, Vanderwal T, Feczko E, Fair D, Kelly C, Baskin-Sommers A. Representing brain-behavior associations by retaining high-motion minoritized youth. Biological Psychiatry Cognitive Neuroscience And Neuroimaging 2025 PMID: 39921132, DOI: 10.1016/j.bpsc.2025.01.014.Peer-Reviewed Original ResearchBrain-behavior associationsFunctional MRIAdolescent Brain Cognitive Development<sup>SM<Effect sizeHispanic youthInternalizing psychopathologyCognitive performanceParticipant sexFunctional connectivityFMRI dataMinoritized individualsWhite youthHead motionMinoritized youthYouthSources of noisePsychopathologyDiverse populationsRacial/ethnic groupsAssociationPartial Spearman rank correlationsAdolescentsDisproportionate numberImpaired 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
Anxiety symptoms are differentially associated with facial expression processing in boys and girls
Doucet G, Kruse J, Keefe A, Rice D, Coutant A, Pulliam H, Smith O, Calhoun V, Stephen J, Wang Y, White S, Picci G, Taylor B, Wilson T. Anxiety symptoms are differentially associated with facial expression processing in boys and girls. Social Cognitive And Affective Neuroscience 2024, 19: nsae085. PMID: 39587034, PMCID: PMC11631531, DOI: 10.1093/scan/nsae085.Peer-Reviewed Original ResearchFacial expression processingAssociated with psychiatric disordersExpression processingFacial expressionsFunctional magnetic resonance imagingFace processing taskMedial temporal cortexTypically-developing youthLevels of anxietyEmotional facesNeutral contrastAnxiety symptomsPosterior networkPsychiatric disordersFacial emotionsBrain responsesTemporal cortexNeural mechanismsHigher anxietyFMRI dataAnxietySocial informationAnxiety levelsBehavioral changesMagnetic resonance imagingA simple but tough-to-beat baseline for fMRI time-series classification
Popov P, Mahmood U, Fu Z, Yang C, Calhoun V, Plis S. A simple but tough-to-beat baseline for fMRI time-series classification. NeuroImage 2024, 303: 120909. PMID: 39515403, PMCID: PMC11625415, DOI: 10.1016/j.neuroimage.2024.120909.Peer-Reviewed Original ResearchConceptsComplex machine learning modelsBlack-box natureMulti-layer perceptronMachine learning modelsPrediction accuracyBlack-box modelsFMRI classificationComplex classifiersClassification accuracySequential informationHuman fMRI dataLearning modelsBlack-boxRich modelsSuperior performanceComplex model developmentFMRI dataTime-series fMRI dataTime series dataClassifierStand-alone pieceClassificationAccuracyDesign modelSeries dataFusion of Novel FMRI Features Using Independent Vector Analysis for a Multifaceted Characterization of Schizophrenia
Jia C, Abu Baker Siddique Akhonda M, Yang H, Calhoun V, Adali T. Fusion of Novel FMRI Features Using Independent Vector Analysis for a Multifaceted Characterization of Schizophrenia. 2015 23rd European Signal Processing Conference (EUSIPCO) 2024, 1112-1116. DOI: 10.23919/eusipco63174.2024.10715096.Peer-Reviewed Original ResearchFractional amplitude of low-frequency fluctuationAmplitude of low-frequency fluctuationResting-state functional magnetic resonanceCharacterization of schizophreniaFunctional magnetic resonanceBrain activity changesLow-frequency fluctuationsVisual cortexSchizophrenia patientsSchizophrenia NetworkBrain alterationsPsychiatric conditionsBrain regionsSchizophrenia biomarkersSchizophreniaFMRI featuresFractional amplitudeGroup differencesFMRI dataNeuroimaging analysisIndependent vector analysisActivity changesHealthy controlsBrainHigher-order statistical informationA Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence
Zhang A, Zhang G, Cai B, Wilson T, Stephen J, Calhoun V, Wang Y. A Bayesian incorporated linear non-Gaussian acyclic model for multiple directed graph estimation to study brain emotion circuit development in adolescence. Network Neuroscience 2024, 8: 791-807. PMID: 39355441, PMCID: PMC11349030, DOI: 10.1162/netn_a_00384.Peer-Reviewed Original ResearchPhiladelphia Neurodevelopmental CohortEmotional circuitryFunctional connectivityBrain's emotional circuitryEmotion identification skillBrain network organizationIndividuals aged 8Emotional processingEmotion perceptionBrain circuitsNeurodevelopmental CohortFMRI dataCognitive developmentIdentification skillsEmotional changesAged 8Adolescent stageAdolescentsNetwork organizationGroup-specific patternsIntermodular connectionsEmotionsCircuit developmentAccurate performanceBrainA core tensor sparsity enhancement method for solving Tucker-2 model of multi-subject fMRI data
Han Y, Lin Q, Kuang L, Zhao B, Gong X, Cong F, Wang Y, Calhoun V. A core tensor sparsity enhancement method for solving Tucker-2 model of multi-subject fMRI data. Biomedical Signal Processing And Control 2024, 95: 106471. DOI: 10.1016/j.bspc.2024.106471.Peer-Reviewed Original ResearchTucker-2 modelMulti-subject fMRI dataFactor matricesCore tensorHalf-quadratic splittingTensor structure informationLow-rank constraintTensor sparsitySparsity constraintQuadratic splittingTask-related fMRI dataImprovement of accuracyEnhancement methodOrthogonality constraintsFMRI dataProcrustes solutionSimulated fMRI dataTucker-3 modelSparsityTemporal evidenceResting-state fMRI dataIdentity matrixDecomposition modelIntrinsic relationshipStructural informationAltered brain connectivity in mild cognitive impairment is linked to elevated tau and phosphorylated tau, but not to GAP-43 and Amyloid-β measurements: a resting-state fMRI study
Sadeghi M, Azargoonjahromi A, Nasiri H, Yaghoobi A, Sadeghi M, Chavoshi S, Baghaeikia S, Mahzari N, Valipour A, Razeghi Oskouei R, Shahkarami F, Amiri F, Mayeli M. Altered brain connectivity in mild cognitive impairment is linked to elevated tau and phosphorylated tau, but not to GAP-43 and Amyloid-β measurements: a resting-state fMRI study. Molecular Brain 2024, 17: 60. PMID: 39215335, PMCID: PMC11363600, DOI: 10.1186/s13041-024-01136-z.Peer-Reviewed Original ResearchConceptsAnterior default mode networkMild cognitive impairmentPosterior DMNLevels of GAP-43Brain connectivityCognitive impairmentResting-state fMRI studiesResting-state fMRI dataIncreased functional connectivityDefault mode networkBrain connectivity changesConnectivity measuresMild cognitive impairment individualsFunctional connectivity measuresImpaired neuronal connectivityAssociated with higher levelsNormal cognitive functionDMN connectivityFMRI studyMode networkCognitive abilitiesBrain activityFunctional connectivityCognitive functionFMRI dataCortical hubs of highly superior autobiographical memory
Orwig W, Diez I, Bueichekú E, Pedale T, Parente F, Campolongo P, Schacter D, Sepulcre J, Santangelo V. Cortical hubs of highly superior autobiographical memory. Cortex 2024, 179: 14-24. PMID: 39094240, DOI: 10.1016/j.cortex.2024.06.018.Peer-Reviewed Original ResearchConceptsSuperior autobiographical memoryAutobiographical memoryCortical hubsWhole-brain connectivity analysisPattern of increased connectivityResting-state fMRI dataWhole-brain analysisAutobiographical memory networkPosterior cingulate cortexMidline areaSeed-based analysisFunctional brain connectivityGraph theory analysisCingulate cortexNeural underpinningsNeuroimaging studiesEnhance memoryRemembering eventsBrain regionsControl participantsConnectivity analysisFMRI dataBrain connectivityCortical regionsWhole-brainA new transfer entropy method for measuring directed connectivity from complex-valued fMRI data
Li W, Lin Q, Zhang C, Han Y, Calhoun V. A new transfer entropy method for measuring directed connectivity from complex-valued fMRI data. Frontiers In Neuroscience 2024, 18: 1423014. PMID: 39050665, PMCID: PMC11266018, DOI: 10.3389/fnins.2024.1423014.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingFMRI dataBrain regionsAnatomical Automatic LabelingTransfer entropyFunctional magnetic resonance imaging dataConnectivity of brain regionsFrontal-parietal regionsConsistent with previous findingsSignificant group differencesRight frontal-parietal regionPartial transfer entropyPredicting mental disordersMental disordersParietal regionsGroup differencesMagnitude effectExperimental fMRI dataDirectional connectivityComplex-valued fMRI dataSchizophreniaMagnetic resonance imagingComplex-valued approachEntropyMagnitude dataScepter: 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 resultsNetworkMultiband Group Independent Component Analysis: Unveiling Frequency-Dependent Dynamics of Functional Connectivity in Group-Level fMRI Analyses
Behzadfar N, Iraji A, Calhoun V. Multiband Group Independent Component Analysis: Unveiling Frequency-Dependent Dynamics of Functional Connectivity in Group-Level fMRI Analyses. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2024, 00: 1-5. PMID: 40040173, DOI: 10.1109/embc53108.2024.10782601.Peer-Reviewed Original ResearchConceptsIndependent component analysisTask-related componentsDynamics of functional connectivitySubband informationGroup independent component analysisMultisubject fMRI dataFunctional network connectivityFMRI dataNetwork connectivityBandpass filterSampling rateSubbandBack-reconstructionApplication of bandpass filtersSpatially independent mapsFrequency rangeFunctional connectivityFMRI analysisEstimation of complete mutual information exploiting nonlinear magnitude-phase dependence: Application to spatial FNC for complex-valued fMRI data
Li W, Lin Q, Zhang C, Han Y, Li H, Calhoun V. Estimation of complete mutual information exploiting nonlinear magnitude-phase dependence: Application to spatial FNC for complex-valued fMRI data. Journal Of Neuroscience Methods 2024, 409: 110207. PMID: 38944128, DOI: 10.1016/j.jneumeth.2024.110207.Peer-Reviewed Original ResearchConceptsComplex-valued fMRI dataMutual informationJoint entropyNetwork connectivityComplex-valued signalsFunctional network connectivityMagnitude-phase dependenceDensity estimation methodMI estimationHistogram-basedKernel density estimation methodFMRI dataEstimation accuracyProbability density functionJoint probability density functionSimulated signalsChain rulePhase dependenceEstimation methodHigh-orderDensity functionControl networkInaccurate estimationNonlinear dependenceDependenceCapturing Stretching and Shrinking of Inter-Network Temporal Coupling in FMRI Via WARP Elasticity
Wiafe S, Faghiri A, Fu Z, Miller R, Calhoun V. Capturing Stretching and Shrinking of Inter-Network Temporal Coupling in FMRI Via WARP Elasticity. 2024, 00: 1-4. DOI: 10.1109/isbi56570.2024.10635377.Peer-Reviewed Original ResearchSubgroup Identification Through Multiplex Community Structure Within Functional Connectivity Networks
Yang H, Ortiz-Bouza M, Vu T, Laport F, Calhoun V, Aviyente S, Adali T. Subgroup Identification Through Multiplex Community Structure Within Functional Connectivity Networks. 2024, 00: 2141-2145. DOI: 10.1109/icassp48485.2024.10446076.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingFunctional networksResting-state fMRI dataMultiplex networksMulti-subject functional magnetic resonance imagingNature of psychiatric disordersFunctional connectivity networksDiagnostic heterogeneityPsychotic patientsIndividual functional networksPsychiatric disordersCommunity detectionGroup differencesFMRI dataData-driven methodMultiple networksConnectivity networksMagnetic resonance imagingIdentified subgroupsNetworkSubgroup identificationResonance imagingSubject correlationSubgroup structure
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