Dustin Scheinost, PhD, BS
Associate Professor of Radiology and Biomedical ImagingCards
About
Research
Publications
2024
Brain age prediction and deviations from normative trajectories in the neonatal connectome
Sun H, Mehta S, Khaitova M, Cheng B, Hao X, Spann M, Scheinost D. Brain age prediction and deviations from normative trajectories in the neonatal connectome. Nature Communications 2024, 15: 10251. PMID: 39592647, PMCID: PMC11599754, DOI: 10.1038/s41467-024-54657-5.Peer-Reviewed Original ResearchConceptsPostmenstrual agePerinatal periodBrain age predictionFunctional connectomeMonths of postnatal lifeMonths of lifePreterm infantsNormative trajectoryConnectome-based predictive modelingThird trimesterPerinatal exposureBrain age gapPostnatal lifeResting-state fMRIInfantsHuman Connectome ProjectNeonatal connectomeDevelopmental trajectoriesBrainBehavioral outcomesNormative dataMonthsConnectome ProjectDTI dataConnectomeBrain-phenotype predictions of language and executive function can survive across diverse real-world data: Dataset shifts in developmental populations
Adkinson B, Rosenblatt M, Dadashkarimi J, Tejavibulya L, Jiang R, Noble S, Scheinost D. Brain-phenotype predictions of language and executive function can survive across diverse real-world data: Dataset shifts in developmental populations. Developmental Cognitive Neuroscience 2024, 70: 101464. PMID: 39447452, PMCID: PMC11538622, DOI: 10.1016/j.dcn.2024.101464.Peer-Reviewed Original ResearchBrain-phenotype associationsConnectome-based predictive modelingBrain-behavior associationsPrediction of languagePhiladelphia Neurodevelopmental CohortHealthy Brain NetworkClinical symptom burdenFMRI taskHuman Connectome ProjectExecutive functionBehavioral measuresDevelopmental populationsNeurodevelopmental CohortBrain networksDevelopmental sampleConnectome ProjectResearch settingsGeneralizabilitySymptom burdenExternal validationFMRIClinical settingAssociationEthnic minority representationTaskOvercoming Atlas Heterogeneity in Federated Learning for Cross-Site Connectome-Based Predictive Modeling
Liang Q, Adkinson B, Jiang R, Scheinost D. Overcoming Atlas Heterogeneity in Federated Learning for Cross-Site Connectome-Based Predictive Modeling. Lecture Notes In Computer Science 2024, 15010: 579-588. DOI: 10.1007/978-3-031-72117-5_54.Peer-Reviewed Original ResearchPrediction of craving across studies: A commentary on conceptual and methodological considerations when using data-driven methods
Antons S, Yip S, Lacadie C, Dadashkarimi J, Scheinost D, Brand M, Potenza M. Prediction of craving across studies: A commentary on conceptual and methodological considerations when using data-driven methods. Journal Of Behavioral Addictions 2024, 13: 695-701. PMID: 39356557, PMCID: PMC11457034, DOI: 10.1556/2006.2024.00050.Peer-Reviewed Original ResearchConceptsAddictive behaviorsDisorders due to addictive behaviorsConnectome-based predictive modelingPrediction of cravingInvestigate neural mechanismsSubstance use disordersNeural mechanismsCravingSubstance useMethodological considerationsDisordersMethodological featuresBehaviorConceptualizationCommentaryStudyFindingsSubstancesNetwork state dynamics underpin basal craving in a transdiagnostic population
Ye J, Garrison K, Lacadie C, Potenza M, Sinha R, Goldfarb E, Scheinost D. Network state dynamics underpin basal craving in a transdiagnostic population. Molecular Psychiatry 2024, 1-10. PMID: 39183336, DOI: 10.1038/s41380-024-02708-0.Peer-Reviewed Original ResearchConnectome-based predictive modelingBrain responsesRegulation of affective statesSample of healthy controlsTransdiagnostic populationTransdiagnostic sampleHigher cravingMotivational stateCravingFMRI methodsAffective statesScan runsExperimental stimuliNetwork engagementBrain dynamicsClinical implicationsHealthy controlsBrainIndividual variationState dynamicsCharacterize individualsReplication datasetPsychopathologyFMRIEngagementApplying fetal, infant, and toddler (FIT) neuroimaging to understand mental health
Spann M, Scheinost D. Applying fetal, infant, and toddler (FIT) neuroimaging to understand mental health. Neuropsychopharmacology 2024, 50: 310-311. PMID: 39117902, PMCID: PMC11525938, DOI: 10.1038/s41386-024-01957-5.Peer-Reviewed Original ResearchPower and reproducibility in the external validation of brain-phenotype predictions
Rosenblatt M, Tejavibulya L, Sun H, Camp C, Khaitova M, Adkinson B, Jiang R, Westwater M, Noble S, Scheinost D. Power and reproducibility in the external validation of brain-phenotype predictions. Nature Human Behaviour 2024, 8: 2018-2033. PMID: 39085406, DOI: 10.1038/s41562-024-01931-7.Peer-Reviewed Original ResearchHuman Connectome ProjectAdolescent Brain Cognitive Development StudyConnectome ProjectCognitive Development StudyPhiladelphia Neurodevelopmental CohortHealthy Brain NetworkStructural connectivity dataMatrix reasoningWorking memoryAnxiety/depression symptomsAttention problemsNeurodevelopmental CohortBrain networksBrain-phenotype associationsEffect sizeConnectivity dataExternal validationRelated processesValidation studySample sizeBrain ProjectDevelopment studiesTraining sample sizeGeneralizability of modelsExternal samplesDevelopmental trajectories of the default mode, frontoparietal, and salience networks from the third trimester through the newborn period
Scheinost D, Chang J, Brennan-Wydra E, Lacadie C, Constable R, Chawarska K, Ment L. Developmental trajectories of the default mode, frontoparietal, and salience networks from the third trimester through the newborn period. Imaging Neuroscience 2024, 2: 1-16. DOI: 10.1162/imag_a_00201.Peer-Reviewed Original ResearchFronto-parietalDevelopmental trajectoriesImpact of maternal mental healthResting-state functional MRIWeeks postmenstrual ageInter-network connectivityIntra-network connectivityMaternal stress levelsMaternal mental healthPostmenstrual ageSalience networkFunctional MRINeurobehavioral disordersNeurodevelopmental disordersDMNMental healthThird trimesterConnectivity measuresSalienceConnectivity valuesEdge-centric network control on the human brain structural network
Sun H, Rosenblatt M, Dadashkarimi J, Rodriguez R, Tejavibulya L, Scheinost D. Edge-centric network control on the human brain structural network. Imaging Neuroscience 2024, 2: 1-15. DOI: 10.1162/imag_a_00191.Peer-Reviewed Original ResearchHuman brain structural networksNetwork control theoryEdge controlWhole-brain networksHuman Connectome ProjectDiffusion MRI dataWhite matter connectivityConnectome ProjectBrain dynamicsExecutive functionBrain structural networksBrain network connectivityBrain connectivityFunctional connectomeState transitionsTransitionEnergy patternsTheory modelBrain energy consumptionDynamic processStructural networkStateNetwork control mechanismsCognitive statesNetwork pairsThe brain structure, inflammatory, and genetic mechanisms mediate the association between physical frailty and depression
Jiang R, Noble S, Rosenblatt M, Dai W, Ye J, Liu S, Qi S, Calhoun V, Sui J, Scheinost D. The brain structure, inflammatory, and genetic mechanisms mediate the association between physical frailty and depression. Nature Communications 2024, 15: 4411. PMID: 38782943, PMCID: PMC11116547, DOI: 10.1038/s41467-024-48827-8.Peer-Reviewed Original ResearchConceptsIncident depressionPre-frailPhysical frailtyFrail individualsPopulation attributable fraction analysisRisk factors of depressionMendelian randomization analysisFactors of depressionPotential causal effectModifiable risk factorsNon-frail individualsCross-sectional studyEffect of frailtyHigher disease burdenUK BiobankRandomization analysisBrain volumeDepression casesDisease burdenFrailtyRegional brain volumesIncreased riskDepressionHigh riskFollow-up
Clinical Trials
Current Trials
Connectivity While Coming of Age
HIC ID2000028368RoleSub InvestigatorPrimary Completion Date12/31/2026Recruiting ParticipantsGenderBothAge18 years - 25 yearsBrain Imaging Study of Emotion Regulation in Children
HIC ID2000031303RoleSub InvestigatorPrimary Completion Date11/30/2023Recruiting ParticipantsGenderBothAge5 years - 15 yearsStudying the Adult Brain
HIC ID2000025671RoleSub InvestigatorPrimary Completion Date07/31/2025Recruiting ParticipantsNeurofeedback of Amygdala Activity for Post-traumatic Stress Disorder (PTSD)
HIC ID2000022668RoleSub InvestigatorPrimary Completion Date06/30/2023Recruiting ParticipantsGenderBothAge18+ yearsGenomic Basis of Neurodevelopmental and Brain Outcomes in Congenital Heart Disease (CHD Brain and Genes)
HIC ID2000020449RoleSub InvestigatorPrimary Completion Date12/31/2027Recruiting ParticipantsGenderBothAge8+ years
News
News
- December 10, 2024Source: Yale News
Opioid Use Disorder is Associated With Changes in Brain Structure, Function
- December 03, 2024Source: Yale News
Advanced Infant Brain Development May Not Always Be a Good Thing
- September 06, 2024Source: Yale News
‘Sticky’ Brain Activity is Linked to Stronger Feelings of Craving
- July 31, 2024Source: Yale News
In probing brain-behavior nexus, big datasets are better