2020
Low-motion fMRI data can be obtained in pediatric participants undergoing a 60-minute scan protocol
Horien C, Fontenelle S, Joseph K, Powell N, Nutor C, Fortes D, Butler M, Powell K, Macris D, Lee K, Greene AS, McPartland JC, Volkmar FR, Scheinost D, Chawarska K, Constable RT. Low-motion fMRI data can be obtained in pediatric participants undergoing a 60-minute scan protocol. Scientific Reports 2020, 10: 21855. PMID: 33318557, PMCID: PMC7736342, DOI: 10.1038/s41598-020-78885-z.Peer-Reviewed Original ResearchConceptsPediatric participantsMRI protocolMagnetic resonance imaging (MRI) scansFunctional magnetic resonance imaging (fMRI) scansShorter MRI protocolsScan protocolResonance imaging scansImaging scansMRI sessionsFMRI connectivity analysisFMRI dataFMRI findingsSignificant confoundScansReplication groupConnectivity analysisAutism spectrum disorderMock scanSpectrum disorderParticipantsHead motionProtocol
2019
Dissociable neural substrates of opioid and cocaine use identified via connectome-based modelling
Lichenstein SD, Scheinost D, Potenza MN, Carroll KM, Yip SW. Dissociable neural substrates of opioid and cocaine use identified via connectome-based modelling. Molecular Psychiatry 2019, 26: 4383-4393. PMID: 31719641, PMCID: PMC7214212, DOI: 10.1038/s41380-019-0586-y.Peer-Reviewed Original ResearchConceptsBrain statesDissociable neural substratesMultiple brain statesSubstance use outcomesHealthy comparison subjectsWhole-brain approachFMRI scanningFrontoparietal networkNeural substratesSubstance use treatmentNeural mechanismsDifferent brain statesFurther clinical relevanceDefault modeFMRI dataSubject replicationTreatment approachesReduced connectivityUse outcomesComparison subjectsNetwork strengthUse disordersSensory networksTreatment respondersSensory connectivityIndividualized functional networks reconfigure with cognitive state
Salehi M, Karbasi A, Barron DS, Scheinost D, Constable RT. Individualized functional networks reconfigure with cognitive state. NeuroImage 2019, 206: 116233. PMID: 31574322, PMCID: PMC7216521, DOI: 10.1016/j.neuroimage.2019.116233.Peer-Reviewed Original ResearchConceptsCognitive stateFunctional networksMultiple cognitive statesFunctional network organizationFunctional organizationBrain functional networksTask demandsFMRI dataSimilar tasksParcellation approachHuman brainNetwork organizationExtensive evidenceMultiple subjectsBrainNetwork membershipTaskOrganizationSubjectsParcellationSuch reconfigurationMeasuresMembershipFindingsSuch definitionsAn information network flow approach for measuring functional connectivity and predicting behavior
Kumar S, Yoo K, Rosenberg MD, Scheinost D, Constable RT, Zhang S, Li C, Chun MM. An information network flow approach for measuring functional connectivity and predicting behavior. Brain And Behavior 2019, 9: e01346. PMID: 31286688, PMCID: PMC6710195, DOI: 10.1002/brb3.1346.Peer-Reviewed Original ResearchConceptsFunctional brain connectivityFunctional magnetic resonance imagingFMRI time coursesIndividual differencesTask performanceMeasures of attentionSustained attention taskAttention task performanceResting-state fMRI dataSample of individualsAttention taskFMRI dataFunctional connectivityFC patternsBrain connectivityPearson correlationInformation theory statisticsInformation flowMachine-learning modelsMeasuresMagnetic resonance imagingAttentionNetwork flow approachTime courseDifferent datasets
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 approachTask-induced brain state manipulation improves prediction of individual traits
Greene AS, Gao S, Scheinost D, Constable RT. Task-induced brain state manipulation improves prediction of individual traits. Nature Communications 2018, 9: 2807. PMID: 30022026, PMCID: PMC6052101, DOI: 10.1038/s41467-018-04920-3.Peer-Reviewed Original ResearchConceptsBrain statesIndividual differencesBrain-behavior relationshipsFluid intelligence scoresTask-based functional connectivity analysisResting-state fMRI dataBrain functional organizationFunctional connectivity analysisCognitive tasksFluid intelligenceIntelligence scoresFunctional connectivityFMRI dataConnectivity analysisHuman behaviorIndividual traitsTaskCertain tasksFunctional organizationOutperform modelsSuch relationshipsCognitionState manipulationIntelligenceVariance