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 representationTask
2023
Test-Retest Reliability of Functional Connectivity in Adolescents With Depression
Camp C, Noble S, Scheinost D, Stringaris A, Nielson D. Test-Retest Reliability of Functional Connectivity in Adolescents With Depression. Biological Psychiatry Cognitive Neuroscience And Neuroimaging 2023, 9: 21-29. PMID: 37734478, PMCID: PMC10843837, DOI: 10.1016/j.bpsc.2023.09.002.Peer-Reviewed Original ResearchConceptsMajor depressive disorderIntraclass correlation coefficientTest-retest reliabilityPsychiatric illnessFunctional connectivityMean intraclass correlation coefficientFunctional magnetic resonance imagingMagnetic resonance imagingAverage intraclass correlation coefficientEffect sizeDepressive disorderLongitudinal cohortHealthy individualsMultivariate analysisResonance imagingSymptom severityReproducible biomarkersBrain-behavior associationsGroup differencesDepressionHealthy samplesCorrelation coefficientIllnessAdolescentsBiomarker identification
2020
Big data approaches to identifying sex differences in long-term memory
Tejavibulya L, Scheinost D. Big data approaches to identifying sex differences in long-term memory. Cognitive Neuroscience 2020, 12: 185-186. PMID: 33356847, PMCID: PMC8222419, DOI: 10.1080/17588928.2020.1866520.Peer-Reviewed Original Research
2019
The Functional Brain Organization of an Individual Allows Prediction of Measures of Social Abilities Transdiagnostically in Autism and Attention-Deficit/Hyperactivity Disorder
Lake EMR, Finn ES, Noble SM, Vanderwal T, Shen X, Rosenberg MD, Spann MN, Chun MM, Scheinost D, Constable RT. The Functional Brain Organization of an Individual Allows Prediction of Measures of Social Abilities Transdiagnostically in Autism and Attention-Deficit/Hyperactivity Disorder. Biological Psychiatry 2019, 86: 315-326. PMID: 31010580, PMCID: PMC7311928, DOI: 10.1016/j.biopsych.2019.02.019.Peer-Reviewed Original ResearchConceptsAttention-deficit/hyperactivity disorderAutism spectrum disorderSpectrum disorderFunctional connectivity profilesHyperactivity disorderBrain organizationAutism Brain Imaging Data ExchangeConnectome-based predictive modelingAutism Diagnostic Observation ScheduleAutism spectrum disorder traitsAutism spectrum disorder severitySocial Responsiveness Scale scoresADHD Rating Scale scoresFunctional magnetic resonance imagingBrain-behavior associationsSocial Responsiveness ScaleResting-state functional magnetic resonanceFunctional brain organizationFunctional magnetic resonanceADHD traitsNeurofunctional basisADHD symptomsSplit-half analysisResponsiveness ScaleSocial abilitiesTen simple rules for predictive modeling of individual differences in neuroimaging
Scheinost D, Noble S, Horien C, Greene AS, Lake EM, Salehi M, Gao S, Shen X, O’Connor D, Barron DS, Yip SW, Rosenberg MD, Constable RT. Ten simple rules for predictive modeling of individual differences in neuroimaging. NeuroImage 2019, 193: 35-45. PMID: 30831310, PMCID: PMC6521850, DOI: 10.1016/j.neuroimage.2019.02.057.Peer-Reviewed Original ResearchConceptsBrain-behavior associations