Link Tejavibulya
Research
Publications
2026
External validation improves generalizability, replicability and reproducibility in predictive models for neuroimaging
Rosenblatt M, Foster M, Adkinson B, Tejavibulya L, Khaitova M, Ye J, Sun H, Rodriguez R, Camp C, Chinta A, McCusker M, Han L, Fields C, Mehta S, Scheinost D. External validation improves generalizability, replicability and reproducibility in predictive models for neuroimaging. Nature Methods 2026, 1-11. PMID: 42203860, DOI: 10.1038/s41592-026-03115-9.Peer-Reviewed Original ResearchWhat effect sizes can we expect in functional neuroimaging?
Shearer H, Rosenblatt M, Ye J, Jiang R, Tejavibulya L, Foster M, Liang Q, Dadashkarimi J, Westwater M, Cheng I, Rolison M, Peterson H, Adkinson B, Mehta S, Camp C, Fischbach A, Cravo F, Meija A, Nichols T, Curtiss J, Scheinost D, Noble S. What effect sizes can we expect in functional neuroimaging? JoCN Forum 2026 DOI: 10.21428/8e6ba8ef.af9f794c.Peer-Reviewed Original ResearchOptimizing functional connectivity scanning conditions for predicting autistic traits
Horien C, Mandino F, Greene A, Shen X, Powell K, Vernetti A, O’Connor D, Adkinson B, Tejavibulya L, McPartland J, Volkmar F, Chun M, Chawarska K, Lake E, Rosenberg M, Satterthwaite T, Scheinost D, Finn E, Constable R. Optimizing functional connectivity scanning conditions for predicting autistic traits. Nature Mental Health 2026, 4: 792-805. PMID: 42137910, PMCID: PMC13167459, DOI: 10.1038/s44220-026-00623-7.Peer-Reviewed Original ResearchSustained attention taskAutistic traitsAttention taskConnectome-based predictive modelingAutism Brain Imaging Data ExchangeBrain-phenotype relationshipsScanning conditionsMagnetic resonance imaging-based studiesMeasures of attentionSocial attention taskOptimal brain stateMeasure of social responsibilityHealthy Brain NetworkSample of youthResting-state conditionNeurobiological correlatesAttentional challengesNeurotypical adultsNeurotypical participantsBrain networksAutistic featuresBrain statesAutismClinically relevant phenotypesImaging-based studiesFeature selection leads to divergent neurobiological interpretations of brain-based machine learning biomarkers
Adkinson B, Rosenblatt M, Sun H, Dadashkarimi J, Tejavibulya L, Horien C, Westwater M, Rodriguez R, Noble S, Scheinost D. Feature selection leads to divergent neurobiological interpretations of brain-based machine learning biomarkers. Nature Human Behaviour 2026, 1-15. PMID: 41986741, DOI: 10.1038/s41562-026-02447-y.Peer-Reviewed Original ResearchNeurobiological interpretationNeurobiological basisBrain-behavior associationsBrain connectivity dataHuman neuroimagingPsychiatric phenotypesBehavioral phenotypesFunctional MRIFunctional connectivityNeuroimaging dataMental healthLarge-scale neuroimaging datasetsConnectivity dataNeuroimaging datasetsNeurobiologyMRI studiesNeuroimagingExternal validationCognitionConnectomeGeneralizabilityParticipants
2025
BrainEffeX: A Web App for Exploring fMRI Effect Sizes
Shearer H, Rosenblatt M, Ye J, Jiang R, Tejavibulya L, Foster M, Liang Q, Dadashkarimi J, Westwater M, Cahill C, Cheng I, Fischbach A, Humphries A, Baskaran A, Rolison M, Peterson H, Adkinson B, Mehta S, Camp C, Nichols T, Curtiss J, Scheinost D, Noble S. BrainEffeX: A Web App for Exploring fMRI Effect Sizes. Aperture Neuro 2025, 5: 10.52294/001c.146251. PMID: 41675933, PMCID: PMC12889895, DOI: 10.52294/001c.146251.Peer-Reviewed Original ResearchVariation in moment-to-moment brain state engagement follows a consistent trajectory during development
Ye J, Tejavibulya L, Dai W, Cope L, Hardee J, Heitzeg M, Lichenstein S, Yip S, Banaschewski T, Baker G, Bokde A, Brühl R, Desrivières S, Flor H, Gowland P, Grigis A, Heinz A, Martinot J, Martinot M, Artiges E, Nees F, Orfanos D, Poustka L, Hohmann S, Holz N, Baeuchl C, Smolka M, Vaidya N, Walter H, Whelan R, Schumann G, Garavan H, Chaarani B, Gee D, Baskin-Sommers A, Casey B, Consortium I, Scheinost D. Variation in moment-to-moment brain state engagement follows a consistent trajectory during development. Neuron 2025, 113: 3863-3875.e6. PMID: 40967219, PMCID: PMC12483157, DOI: 10.1016/j.neuron.2025.08.020.Peer-Reviewed Original ResearchFunctional Connectome Correlates of Laterality Preferences: Insights into Hand, Foot, and Eye Dominance across the Lifespan
Tejavibulya L, Horien C, Fredericks C, Ficek B, Westwater M, Scheinost D. Functional Connectome Correlates of Laterality Preferences: Insights into Hand, Foot, and Eye Dominance across the Lifespan. ENeuro 2025, 12: eneuro.0580-24.2025. PMID: 40473471, PMCID: PMC12244319, DOI: 10.1523/eneuro.0580-24.2025.Peer-Reviewed Original ResearchLateral preferenceFunctional connectomeWhole-brain functional connectomePosterior temporal areasBrain functional connectivityWhole-brain connectomePrefrontal lobeNormative variationCerebellar regionsFunctional connectivityDevelopmental shiftTemporal lobeBrain connectivityWhole-brainLeft-handednessFoot preferenceRight-handednessTemporal areaIncreased connectivityResting-state functional connectomesEffect sizeSignificant associationConnectivity patternsBrain hemispheresHandednessBrain handedness associations depend on how and when handedness is measured
Tejavibulya L, Horien C, Fredricks C, Ficek-Tani B, Westwater M, Scheinost D. Brain handedness associations depend on how and when handedness is measured. Scientific Reports 2025, 15: 9674. PMID: 40113911, PMCID: PMC11926124, DOI: 10.1038/s41598-025-94036-8.Peer-Reviewed Original ResearchConceptsEdinburgh Handedness InventoryLeft-handed individualsHandedness measuresNeuroimaging studiesHandedness InventoryHand preferenceFunctional connectomeResting-state functional connectomesHandednessLeft handBrainNeuroimagingAssociationIndividualsInventoryConnectomeComplex traitsInvestigate generational differencesItemsTraits
2024
Brain-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 representationTaskPower 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 samples