2024
315-OR: Task-Induced Alterations in the Salience Network amongst Patients with Type 1 Diabetes
SANCHEZ RANGEL E, BELFORT-DEAGUIAR R, LACADIE C, CHUNG T, SCHEINOST D, MASON G, HWANG J. 315-OR: Task-Induced Alterations in the Salience Network amongst Patients with Type 1 Diabetes. Diabetes 2024, 73 DOI: 10.2337/db24-315-or.Peer-Reviewed Original ResearchSalience networkFunctional connectivityCognitive tasksBrain responsesType 1 diabetesBrain functional connectivityResting stateMild hypoglycemiaWorking memoryBrain regionsSalienceContinuous performanceRewardBrainCounterregulatory hormonesStandard preprocessingTaskIndividual traitsMemoryPatientsHypoglycemiaT1DGradCPTStimuliAttention
2019
Cluster failure or power failure? Evaluating sensitivity in cluster-level inference
Noble S, Scheinost D, Constable RT. Cluster failure or power failure? Evaluating sensitivity in cluster-level inference. NeuroImage 2019, 209: 116468. PMID: 31852625, PMCID: PMC8061745, DOI: 10.1016/j.neuroimage.2019.116468.Peer-Reviewed Original ResearchIndividualized 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 definitionsCombining multiple connectomes improves predictive modeling of phenotypic measures
Gao S, Greene AS, Constable RT, Scheinost D. Combining multiple connectomes improves predictive modeling of phenotypic measures. NeuroImage 2019, 201: 116038. PMID: 31336188, PMCID: PMC6765422, DOI: 10.1016/j.neuroimage.2019.116038.Peer-Reviewed Original ResearchConceptsMultiple connectomesLarge open-source datasetOpen-source datasetNovel prediction frameworkPredictive modelingSingle predictive modelPredictive modelArt algorithmsPrediction frameworkMultiple tasksPredictive model approachPrincipled waySpecific algorithmsFunctional connectivity matricesConnectivity matrixDifferent tasksPrediction performanceConnectome-based predictive modelingHuman Connectome ProjectTaskSuperior performanceAlgorithmComplementary informationNaïve extensionsConnectome Project
2018
Task-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
2017
Can brain state be manipulated to emphasize individual differences in functional connectivity?
Finn ES, Scheinost D, Finn DM, Shen X, Papademetris X, Constable RT. Can brain state be manipulated to emphasize individual differences in functional connectivity? NeuroImage 2017, 160: 140-151. PMID: 28373122, PMCID: PMC8808247, DOI: 10.1016/j.neuroimage.2017.03.064.Peer-Reviewed Original ResearchConceptsIndividual differencesFunctional connectivityBrain statesIndividual differences researchBrain functional organizationHuman Connectome ProjectDifferences researchBrain activityConnectome ProjectSubject variabilityNetworks of interestBehavioral phenotypesCertain tasksFunctional organizationDefault stateNeutral backdropOutline questionsFuture studiesConnectivityTaskCharacterizing 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 propertiesDisordersPeople