2024
Investigating Brain State Engagement Variability in Individuals With Opioid Use Disorder Using Naturalistic and Task-Based fMRI Data
Ye J, Mehta S, Peterson H, Ibrahim A, Saeed G, Linsky S, Kreinin I, Tsang S, Nwanaji-Enwerem U, Raso A, Yip S, Tokoglu F, Arora J, Constable R, Barry D, Redeker N, Yaggi H, Scheinost D. Investigating Brain State Engagement Variability in Individuals With Opioid Use Disorder Using Naturalistic and Task-Based fMRI Data. Biological Psychiatry 2024, 95: s6. DOI: 10.1016/j.biopsych.2024.02.022.Peer-Reviewed Original ResearchExperiences of Stigma and Discrimination Compounded by Intersecting Identities among Individuals Receiving Medication for Opioid Use Disorder.
Nwanaji-Enwerem U, Redeker N, O'Connell M, Barry D, Iheanacho T, Knobf T, Scheinost D, Wang K, Yaggi K, Sadler L. Experiences of Stigma and Discrimination Compounded by Intersecting Identities among Individuals Receiving Medication for Opioid Use Disorder. Journal Of Health Care For The Poor And Underserved 2024, 35: 94-115. PMID: 38661862, DOI: 10.1353/hpu.2024.a919810.Peer-Reviewed Original ResearchOpioid use disorderExperiences of stigmaIndividuals experience stigmaMarginalized social positionsIdentity of peopleUse disorderIntersectional identitiesMarginalized identitiesSupport interventionsSocial positionQualitative findingsStigmaNegative experiencesNortheast United StatesUnited StatesImprove outcomesIdentityTreatment centersMOUDIndividual vulnerabilityMedicationPeopleDiscriminationIndividuals
2023
Transdiagnostic Connectome-Based Prediction of Craving
Garrison K, Sinha R, Potenza M, Gao S, Liang Q, Lacadie C, Scheinost D. Transdiagnostic Connectome-Based Prediction of Craving. American Journal Of Psychiatry 2023, 180: 445-453. PMID: 36987598, DOI: 10.1176/appi.ajp.21121207.Peer-Reviewed Original ResearchConceptsConnectome-based predictive modelingImagery conditionFunctional connectomeSelf-reported cravingStudy of motivationDefault mode networkFunctional connectivity dataIndependent samplesKey phenomenological featuresNeural signaturesTransdiagnostic sampleTransdiagnostic perspectiveMode networkMotivated behaviorCentral constructAddictive disordersHuman behaviorConnectivity dataPhenomenological featuresStrongest predictorCravingTaskSubstance use-related disordersConnectomeIndividuals
2022
Brain–phenotype models fail for individuals who defy sample stereotypes
Greene AS, Shen X, Noble S, Horien C, Hahn CA, Arora J, Tokoglu F, Spann MN, Carrión CI, Barron DS, Sanacora G, Srihari VH, Woods SW, Scheinost D, Constable RT. Brain–phenotype models fail for individuals who defy sample stereotypes. Nature 2022, 609: 109-118. PMID: 36002572, PMCID: PMC9433326, DOI: 10.1038/s41586-022-05118-w.Peer-Reviewed Original ResearchConceptsBrain-phenotype relationshipsBrain functional organizationCognitive constructsIndividual differencesNeurocognitive measuresBrain activityNeurocognitive scoresStereotypical profileNeural targetsClinical interventionsNeural circuitsFunctional organizationIndividualsSuch relationshipsData-driven approachRelationshipStereotypesLarge-scale differences in functional organization of left- and right-handed individuals using whole-brain, data-driven analysis of connectivity
Tejavibulya L, Peterson H, Greene A, Gao S, Rolison M, Noble S, Scheinost D. Large-scale differences in functional organization of left- and right-handed individuals using whole-brain, data-driven analysis of connectivity. NeuroImage 2022, 252: 119040. PMID: 35272202, PMCID: PMC9013515, DOI: 10.1016/j.neuroimage.2022.119040.Peer-Reviewed Original ResearchConceptsHanded individualsFunctional connectivityLanguage areasWhole-brain functional connectivityRight-handed individualsFunctional organizationWhole-brain levelIndividual differencesHandedness differencesHandedness effectsFunctional connectomeBrain levelsSomatosensory cortexNetworks of interestWhole brainSex differencesBrainConnectomeIndividualsData-driven analysisConnectivityDistinct patternsLateralizationDifferencesSimilar amounts
2020
Functional connectivity predicts changes in attention observed across minutes, days, and months
Rosenberg MD, Scheinost D, Greene AS, Avery EW, Kwon YH, Finn ES, Ramani R, Qiu M, Constable RT, Chun MM. Functional connectivity predicts changes in attention observed across minutes, days, and months. Proceedings Of The National Academy Of Sciences Of The United States Of America 2020, 117: 3797-3807. PMID: 32019892, PMCID: PMC7035597, DOI: 10.1073/pnas.1912226117.Peer-Reviewed Original ResearchConceptsConnectome-based predictive modelsAttentional stateSustained attentionIndividual differencesSustained attention functionFunctional connectivity signaturesFunctional brain connectivityFunctional connectivity patternsAttention functionConnectivity signaturesFunctional connectivityBrain connectivityConnectivity patternsAttentionSingle personSame patternIndividualsConnectivityIndependent studiesRecent workState changesPersonsPeopleDifferencesAbility
2019
Toward Addiction Prediction: An Overview of Cross-Validated Predictive Modeling Findings and Considerations for Future Neuroimaging Research
Yip SW, Kiluk B, Scheinost D. Toward Addiction Prediction: An Overview of Cross-Validated Predictive Modeling Findings and Considerations for Future Neuroimaging Research. Biological Psychiatry Cognitive Neuroscience And Neuroimaging 2019, 5: 748-758. PMID: 31932230, PMCID: PMC8274215, DOI: 10.1016/j.bpsc.2019.11.001.Peer-Reviewed Original ResearchConceptsIndividual differencesBrain-behavior modelsFuture neuroimaging researchLikelihood of replicationEvidence-based treatmentsNeuroimaging researchEffect size estimatesSubstance useDirection of associationAnatomical locusBrain functionTreatment outcomesModeling findingsClinical samplesNovel subjectRelapse rateClinical outcomesPredictive modeling approachUnsuccessful treatmentLeading causeIndividualsClinical settingParticular riskSize estimatesOutcomesMultivariate approaches improve the reliability and validity of functional connectivity and prediction of individual behaviors
Yoo K, Rosenberg MD, Noble S, Scheinost D, Constable RT, Chun MM. Multivariate approaches improve the reliability and validity of functional connectivity and prediction of individual behaviors. NeuroImage 2019, 197: 212-223. PMID: 31039408, PMCID: PMC6591084, DOI: 10.1016/j.neuroimage.2019.04.060.Peer-Reviewed Original ResearchConceptsFunctional brain organizationFunctional connectivityFunctional connectivity featuresTest-retest sampleMultivariate functional connectivityCognitive skillsMental representationsIndividual differencesFMRI measuresBrain organizationBrain statesStrong predictionSpatial activity patternsFMRI datasetsConnectivity featuresIndividual behaviorProject samplesConnectivity estimatesTimecoursesActivity patternsCognitionPearson correlationIndividualsConnectivityUnivariate approach
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
An exemplar-based approach to individualized parcellation reveals the need for sex specific functional networks
Salehi M, Karbasi A, Shen X, Scheinost D, Constable RT. An exemplar-based approach to individualized parcellation reveals the need for sex specific functional networks. NeuroImage 2017, 170: 54-67. PMID: 28882628, PMCID: PMC5905726, DOI: 10.1016/j.neuroimage.2017.08.068.Peer-Reviewed Original ResearchConceptsIndividualized parcellationParcellation techniqueFunctional networksCross-validated predictive modelSpecific functional networksCerebral cortexPatient subgroupsFunctional connectivity dataFunctional organizationBrainParcellation schemesClinical applicationParcellation approachParcellationSexSubgroupsConnectivity dataIndividualized studyNetwork organizationIndividualsAmple evidencePatientsCortex
2015
A neuromarker of sustained attention from whole-brain functional connectivity
Rosenberg MD, Finn ES, Scheinost D, Papademetris X, Shen X, Constable RT, Chun MM. A neuromarker of sustained attention from whole-brain functional connectivity. Nature Neuroscience 2015, 19: 165-171. PMID: 26595653, PMCID: PMC4696892, DOI: 10.1038/nn.4179.Peer-Reviewed Original ResearchFunctional connectome fingerprinting: identifying individuals using patterns of brain connectivity
Finn ES, Shen X, Scheinost D, Rosenberg MD, Huang J, Chun MM, Papademetris X, Constable RT. Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity. Nature Neuroscience 2015, 18: 1664-1671. PMID: 26457551, PMCID: PMC5008686, DOI: 10.1038/nn.4135.Peer-Reviewed Original Research