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, 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
2023
Network controllability of structural connectomes in the neonatal brain
Sun H, Jiang R, Dai W, Dufford A, Noble S, Spann M, Gu S, Scheinost D. Network controllability of structural connectomes in the neonatal brain. Nature Communications 2023, 14: 5820. PMID: 37726267, PMCID: PMC10509217, DOI: 10.1038/s41467-023-41499-w.Peer-Reviewed Original ResearchAssessing a multivariate model of brain-mediated genetic influences on disordered eating in the ABCD cohort
Westwater M, Mallard T, Warrier V, Bethlehem R, Scheinost D, Grillon C, Fletcher P, Seidlitz J, Ernst M. Assessing a multivariate model of brain-mediated genetic influences on disordered eating in the ABCD cohort. Nature Mental Health 2023, 1: 573-585. DOI: 10.1038/s44220-023-00101-4.Peer-Reviewed Original ResearchNeurobiological factorsPsychopathology symptomsFactor scoresCanonical brain networksThree-factor structureStructural equation modelingCritical developmental periodGray matter volumeCortical thicknessGreater genetic riskDisorder symptomatologyABCD studyEarly adolescenceDefault modeBrain networksAnxiety disordersGenetic riskIntervention effortsABCD cohortEquation modelingSubcortical gray matter volumesPsychopathology factorDevelopmental periodFear factorBrain structures
2022
High-Risk Drinkers Engage Distinct Stress-Predictive Brain Networks
Goldfarb EV, Scheinost D, Fogelman N, Seo D, Sinha R. High-Risk Drinkers Engage Distinct Stress-Predictive Brain Networks. Biological Psychiatry Cognitive Neuroscience And Neuroimaging 2022, 7: 805-813. PMID: 35272096, PMCID: PMC9378362, DOI: 10.1016/j.bpsc.2022.02.010.Peer-Reviewed Original ResearchConceptsRisky drinkersHigh-risk drinkersBrain networksMajor public health problemExcessive alcohol intakeWhole-brain functional connectivityPublic health problemEarly preventive interventionsAlcohol use disorderDaily ecological momentary assessmentsAlcohol intakeControl subjectsRisky drinking behaviorsEmotional stress responsesUse disordersEarly markerHealth problemsPreventive interventionsBrain circuitryLight drinkersFunctional connectivityStress protocolHeavy drinkingDrinkersEcological momentary assessment
2020
Transdiagnostic, Connectome-Based Prediction of Memory Constructs Across Psychiatric Disorders
Barron DS, Gao S, Dadashkarimi J, Greene AS, Spann MN, Noble S, Lake EMR, Krystal JH, Constable RT, Scheinost D. Transdiagnostic, Connectome-Based Prediction of Memory Constructs Across Psychiatric Disorders. Cerebral Cortex 2020, 31: 2523-2533. PMID: 33345271, PMCID: PMC8023861, DOI: 10.1093/cercor/bhaa371.Peer-Reviewed Original ResearchConceptsMacroscale brain networksIndividual differencesBrain networksMemory deficitsFunctional connectivityAttention deficit hyper-activity disorderTask-based functional MRI dataLong-term memoryWhole-brain functional connectivityDiagnostic groupsWhole-brain patternsDefault mode networkFunctional MRI dataHuman Connectome ProjectPsychiatric disordersMemory constructsMemory performanceTransdiagnostic sampleBrain correlatesMode networkFunctional connectomeConnectome ProjectLimbic networkHealthy participantsMemoryThe Constrained Network-Based Statistic: A New Level of Inference for Neuroimaging
Noble S, Scheinost D. The Constrained Network-Based Statistic: A New Level of Inference for Neuroimaging. Lecture Notes In Computer Science 2020, 12267: 458-468. PMID: 33870336, PMCID: PMC8052680, DOI: 10.1007/978-3-030-59728-3_45.Peer-Reviewed Original ResearchNetwork-based statisticsLarge-scale networksConstrained networksLarge-scale brain networksHuman Connectome ProjectHigher effect sizesBrain networksGround truth mapConnectome ProjectTask dataTruth effectNew levelReproducible discoveryEffect sizeNBS methodTruth mapNetwork organizationNetworkLocal neighborhoodValid inferencesInferenceNeuroscienceImportant formCluster levelMajor initiatives
2019
The Application of Connectome-Based Predictive Modeling to the Maternal Brain: Implications for Mother–Infant Bonding
Rutherford HJV, Potenza MN, Mayes LC, Scheinost D. The Application of Connectome-Based Predictive Modeling to the Maternal Brain: Implications for Mother–Infant Bonding. Cerebral Cortex 2019, 30: 1538-1547. PMID: 31690936, PMCID: PMC7132918, DOI: 10.1093/cercor/bhz185.Peer-Reviewed Original ResearchConceptsConnectome-based predictive modelingAuditory networkMaternal anxietyMaternal bondingContext of anxietyMaternal Brain NetworkMother-infant bondBrain functional connectivityChild developmentMother-infant bondingBrain networksFunctional connectivityAnxietyBehavioral qualitiesBonding relationshipsBonding impairmentBrain structuresMaternal brainMother's mindGreater segregationNetwork connectivityMindGreater integrationConnectivityMonths postpartum
2018
Dynamic functional connectivity during task performance and rest predicts individual differences in attention across studies
Fong AHC, Yoo K, Rosenberg MD, Zhang S, Li CR, Scheinost D, Constable RT, Chun MM. Dynamic functional connectivity during task performance and rest predicts individual differences in attention across studies. NeuroImage 2018, 188: 14-25. PMID: 30521950, PMCID: PMC6401236, DOI: 10.1016/j.neuroimage.2018.11.057.Peer-Reviewed Original ResearchConceptsAttention task performanceDynamic functional connectivityTask performanceIndividual differencesExecutive control brain networksFunctional connectivityFunctional brain scansAttention performanceTask conditionsAttention scoresBrain networksFMRI dataBrain regionsBetter attentionFC featuresFC matricesDFC matrixPearson's rAttentionIndividualsOne-subjectBrain scansConnectivityConnectomeCross-validation approach
2017
Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder
Scheinost D, Holmes SE, DellaGioia N, Schleifer C, Matuskey D, Abdallah CG, Hampson M, Krystal JH, Anticevic A, Esterlis I. Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder. Neuropsychopharmacology 2017, 43: 1119-1127. PMID: 28944772, PMCID: PMC5854800, DOI: 10.1038/npp.2017.229.Peer-Reviewed Original ResearchConceptsMajor depressive disorderAnterior cingulate cortexIntrinsic functional connectivityMedial prefrontal cortexFunctional connectivityLarge-scale brain networksDepressive disorderMDD groupAnatomical covarianceBrain networksUnmedicated major depressive disorderWhole-brain intrinsic functional connectivitySystem-level disorderIntrinsic connectivity distributionRegional brain structureMultiple brain networksAltered connectivityCommon findingHealthy comparison participantsDepressive symptomsAltered volumeUnmedicated individualsLocal circuitryCingulate cortexDepressive symptomatologyCharacterizing Attention with Predictive Network Models
Rosenberg MD, Finn ES, Scheinost D, Constable RT, Chun MM. Characterizing Attention with Predictive Network Models. Trends In Cognitive Sciences 2017, 21: 290-302. PMID: 28238605, PMCID: PMC5366090, DOI: 10.1016/j.tics.2017.01.011.Peer-Reviewed Original ResearchConceptsAttention deficit hyperactivity disorderAttentional abilitiesLarge-scale brain networksLaboratory-based tasksDeficit hyperactivity disorderExplicit taskCognitive abilitiesHyperactivity disorderBrain networksBrain computationCognitive functionFunctional connectivityFunctional architectureTaskClinical dysfunctionEmpirical evidenceAttentionPredictive network modelsNeuromarkersNetwork modelAbilityRecent workNetwork propertiesDisordersPeopleMulti-modal analysis of functional connectivity and cerebral blood flow reveals shared and unique effects of propofol in large-scale brain networks
Qiu M, Scheinost D, Ramani R, Constable RT. Multi-modal analysis of functional connectivity and cerebral blood flow reveals shared and unique effects of propofol in large-scale brain networks. NeuroImage 2017, 148: 130-140. PMID: 28069540, PMCID: PMC5410383, DOI: 10.1016/j.neuroimage.2016.12.080.Peer-Reviewed Original ResearchConceptsCerebral blood flowIntrinsic connectivity distributionLarge-scale brain networksFunctional connectivityReduced consciousnessBlood flowBrain networksSedation conditionsWhole-brain connectivityAltered connectivityMotor networkCBF dataRs-fMRIPharmacological alterationsConnectivity differencesPropofolMultiple large-scale brain networksUnique neural correlatesBlow flowFrontoparietal networkAnesthesiaKey markersDefault modeNeural correlatesSame subjects
2016
Methylphenidate Modulates Functional Network Connectivity to Enhance Attention
Rosenberg MD, Zhang S, Hsu WT, Scheinost D, Finn ES, Shen X, Constable RT, Li CS, Chun MM. Methylphenidate Modulates Functional Network Connectivity to Enhance Attention. Journal Of Neuroscience 2016, 36: 9547-9557. PMID: 27629707, PMCID: PMC5039242, DOI: 10.1523/jneurosci.1746-16.2016.Peer-Reviewed Original ResearchConceptsAttention-deficit/hyperactivity disorderSustained attentionWhole-brain connectivity patternsFunctional brain networksHyperactivity disorderBrain networksConnectivity patternsConnectome-based predictive modeling approachWhole-brain functional connectivity patternsWhole-brain functional connectivity networksSustained attention taskStop-signal taskDose of methylphenidateFunctional network connectivityCausal roleFunctional connectivity patternsHealthy adultsAttention taskCognitive abilitiesPromising neuromarkerNetwork strengthBehavioral predictionsADHD treatmentConnectivity signaturesFunctional connectivity networksFunctional Connectivity During Exposure to Favorite-Food, Stress, and Neutral-Relaxing Imagery Differs Between Smokers and Nonsmokers
Garrison KA, Sinha R, Lacadie CM, Scheinost D, Jastreboff AM, Constable RT, Potenza MN. Functional Connectivity During Exposure to Favorite-Food, Stress, and Neutral-Relaxing Imagery Differs Between Smokers and Nonsmokers. Nicotine & Tobacco Research 2016, 18: 1820-1829. PMID: 26995796, PMCID: PMC4978981, DOI: 10.1093/ntr/ntw088.Peer-Reviewed Original ResearchConceptsFunctional connectivityBrain regionsSupramarginal gyrusFavorite-food cuesSmoking-related alterationsMagnetic resonance imaging studyBrain functional connectivity patternsPrevious functional magnetic resonance imaging (fMRI) studiesTobacco use disorderBrain networksIntrinsic connectivity distributionResonance imaging studyFunctional magnetic resonance imaging studyFunctional connectivity patternsMultiple brain networksSmoking cessationNonsmokersPosterior insulaRolandic operculumSmokersFunctional brain networksImaging studiesGreater connectivityNeural responsesRecent reports
2015
Meditation leads to reduced default mode network activity beyond an active task
Garrison KA, Zeffiro TA, Scheinost D, Constable RT, Brewer JA. Meditation leads to reduced default mode network activity beyond an active task. Cognitive, Affective, & Behavioral Neuroscience 2015, 15: 712-720. PMID: 25904238, PMCID: PMC4529365, DOI: 10.3758/s13415-015-0358-3.Peer-Reviewed Original ResearchConceptsDefault mode networkDefault mode network activityBrain activation patternsDefault mode processingActive cognitive taskMode networkCognitive tasksActive tasksActivation patternsSelf-related thinkingDefault-mode activityPosterior cingulate/precuneusLong-term meditationAnterior cingulate cortexPrevious imaging studiesEffortful taskCentral neural processesNeural processesTask interactionBrain networksCingulate cortexNetwork activityMeditationReduced activation
2013
Disruption of Functional Networks in Dyslexia: A Whole-Brain, Data-Driven Analysis of Connectivity
Finn ES, Shen X, Holahan JM, Scheinost D, Lacadie C, Papademetris X, Shaywitz SE, Shaywitz BA, Constable RT. Disruption of Functional Networks in Dyslexia: A Whole-Brain, Data-Driven Analysis of Connectivity. Biological Psychiatry 2013, 76: 397-404. PMID: 24124929, PMCID: PMC3984371, DOI: 10.1016/j.biopsych.2013.08.031.Peer-Reviewed Original ResearchConceptsFunctional connectivity analysisVisual word form areaConnectivity analysisWord form areaNon-impaired readersFunctional magnetic resonance imaging (fMRI) dataInferior frontal gyrusWhole-brain functional connectivity analysisAnterior language regionsVisual association areasWhole-brain connectivityAdult readersNeural basisImportance of synchronyFrontal gyrusSuccessful readingVisual stimuliLanguage regionsAttention areasBrain networksDiverse brain regionsMagnetic resonance imaging dataVisual informationDyslexiaVisual propertiesOrbitofrontal cortex neurofeedback produces lasting changes in contamination anxiety and resting-state connectivity
Scheinost D, Stoica T, Saksa J, Papademetris X, Constable RT, Pittenger C, Hampson M. Orbitofrontal cortex neurofeedback produces lasting changes in contamination anxiety and resting-state connectivity. Translational Psychiatry 2013, 3: e250-e250. PMID: 23632454, PMCID: PMC3641411, DOI: 10.1038/tp.2013.24.Peer-Reviewed Original ResearchConceptsResting-state connectivityContamination anxietyBrain regionsNF trainingBrain connectivityResting-state functional connectivityFunctional magnetic resonance imaging (fMRI) neurofeedbackPotential of neurofeedbackRelevant brain networksResting-state fMRIDorsolateral prefrontal cortexTarget brain regionsBrain functional architectureUseful therapyLimbic circuitryMatched subjectsOrbitofrontal regionsOrbitofrontal cortexFunctional connectivityPrefrontal cortexHuman emotionsFeedback control tasksSubclinical anxietyAnxiety regulationBrain networks