2021
Functional Connectivity during Encoding Predicts Individual Differences in Long-Term Memory
Lin Q, Yoo K, Shen X, Constable TR, Chun MM. Functional Connectivity during Encoding Predicts Individual Differences in Long-Term Memory. Journal Of Cognitive Neuroscience 2021, 33: 2279-2296. PMID: 34272957, PMCID: PMC8497062, DOI: 10.1162/jocn_a_01759.Peer-Reviewed Original ResearchConceptsLong-term memoryN-back taskIndividual differencesFunctional connectivityMemory modelWhole-brain functional connectivity networksSubsequent memory effectsRecognition memory modelsMedial temporal lobeWhole-brain functional networksRetention of informationRecollection memoryRecognition memoryMemory performanceNeural basisFunctional connectivity networksLTM formationFMRI dataTemporal lobeMemoryBrain regionsFunctional networksConnectivity networksTaskLittle predictive power
2020
Behavioral and brain signatures of substance use vulnerability in childhood
Rapuano KM, Rosenberg MD, Maza MT, Dennis NJ, Dorji M, Greene AS, Horien C, Scheinost D, Constable R, Casey BJ. Behavioral and brain signatures of substance use vulnerability in childhood. Developmental Cognitive Neuroscience 2020, 46: 100878. PMID: 33181393, PMCID: PMC7662869, DOI: 10.1016/j.dcn.2020.100878.Peer-Reviewed Original ResearchConceptsConnectome-based predictive modelingSubstance useFunctional connectivityCognitive Development StudyFuture substance useSubstance use vulnerabilityAdolescent substance useSubstance use increasesSubstance use outcomesIndividual differencesAdolescent brainBrain signaturesTask conditionsBehavioral measuresFamilial risk factorsUse outcomesRisky behaviorsLatent dimensionsFamilial factorsBrain modelCurrent studyWeak predictorDevelopment studiesEarly susceptibilityFunctional imagingDistributed Patterns of Functional Connectivity Predict Working Memory Performance in Novel Healthy and Memory-impaired Individuals
Avery EW, Yoo K, Rosenberg MD, Greene AS, Gao S, Na DL, Scheinost D, Constable TR, Chun MM. Distributed Patterns of Functional Connectivity Predict Working Memory Performance in Novel Healthy and Memory-impaired Individuals. Journal Of Cognitive Neuroscience 2020, 32: 241-255. PMID: 31659926, PMCID: PMC8004893, DOI: 10.1162/jocn_a_01487.Peer-Reviewed Original ResearchConceptsFunctional connectivity patternsFluid intelligenceMemory performanceIndividual differencesAttention modelConnectome-based predictive modelingConnectome-based predictive modelsWhole-brain functional connectivity patternsGeneral cognitive abilitySuch individual differencesConnectivity patternsAdult life spanHuman Connectome ProjectHuman Connectome Project dataMemory relateCognitive abilitiesNeural basisSustained attentionMemory scoresParietal regionsFunctional connectivityConnectome ProjectMemory modelOlder adultsMemory
2019
The individual functional connectome is unique and stable over months to years
Horien C, Shen X, Scheinost D, Constable RT. The individual functional connectome is unique and stable over months to years. NeuroImage 2019, 189: 676-687. PMID: 30721751, PMCID: PMC6422733, DOI: 10.1016/j.neuroimage.2019.02.002.Peer-Reviewed Original ResearchConceptsHigh ID ratesIndividual differencesFunctional connectomeIndividual functional connectomesStable individual differencesID rateResting-state fMRI datasetsFrontoparietal networkFunctional connectivityParietal cortexFMRI datasetsIdiosyncratic aspectsConnectomeHead motionEntire brainFMRIBrainCortexSpecific datasetDifferencesConnectivityChapter 4 The uniqueness of the individual functional connectome
Horien C, Scheinost D, Constable R. Chapter 4 The uniqueness of the individual functional connectome. 2019, 63-81. DOI: 10.1016/b978-0-12-813838-0.00004-2.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingIndividual differencesIndividual functional connectomesBrain functionConnectivity dataGroup-level differencesFunctional connectivity dataHuman neuroimagingBehavioral measuresFunctional connectomeMagnetic resonance imagingResonance imagingInterindividual heterogeneityNext turnConnectomeCognitionBest predictive modelNeuroimagingDifferencesParticipantsDisease
2018
Combining Multiple Connectomes via Canonical Correlation Analysis Improves Predictive Models
Gao S, Greene A, Todd Constable R, Scheinost D. Combining Multiple Connectomes via Canonical Correlation Analysis Improves Predictive Models. Lecture Notes In Computer Science 2018, 11072: 349-356. DOI: 10.1007/978-3-030-00931-1_40.Peer-Reviewed Original ResearchTask conditionsDifferent cognitive tasksMultiple task conditionsDifferent task conditionsConnectivity dataDifferent cognitive conditionsFunctional connectivity dataComputational modelHuman Connectome ProjectPrediction of behaviorCognitive tasksIndividual differencesBehavioral measuresBehavioral predictionsCognitive conditionsMultiple connectomesSingle taskFunctional connectivityConnectome ProjectDifferent tasksComplementary informationMultiple tasksTaskPrincipled methodCanonical correlation analysisTask-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 manipulationIntelligenceVarianceTask Integration for Connectome-Based Prediction Via Canonical Correlation Analysis
Gao S, Greene A, Constable R, Scheinost D. Task Integration for Connectome-Based Prediction Via Canonical Correlation Analysis. 2018, 87-91. DOI: 10.1109/isbi.2018.8363529.Peer-Reviewed Original ResearchTask conditionsDifferent tasksDifferent cognitive tasksMultiple task conditionsDifferent task conditionsConnectivity dataDifferent cognitive conditionsFunctional connectivity dataHuman Connectome ProjectComputational modelPrediction of behaviorCognitive tasksFluid intelligenceIndividual differencesBehavioral measuresBehavioral predictionsCognitive conditionsSingle taskFunctional connectivityConnectome ProjectComplementary informationTask integrationTaskProof of conceptCanonical correlation analysis
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 studiesConnectivityTask
2008
Additive effects of serotonin transporter and tryptophan hydroxylase-2 gene variation on neural correlates of affective processing
Canli T, Congdon E, Constable R, Lesch K. Additive effects of serotonin transporter and tryptophan hydroxylase-2 gene variation on neural correlates of affective processing. Biological Psychology 2008, 79: 118-125. PMID: 18314252, DOI: 10.1016/j.biopsycho.2008.01.004.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingEvent-related potentialsNeutral facial expressionsSpecific neural lociWord stimuliEmotional scenesAffective processingAffective stimuliEmotional stimuliVerbal stimuliNeural correlatesIndividual differencesNeural processingNeural locusBrain responsesFacial expressionsConvergent evidenceIndependent study samplesFMRI dataRobust effectCortical regionsStimuliTPH2 genotypeTryptophan hydroxylase 2 geneCurrent study
2006
Brain Connectivity Related to Working Memory Performance
Hampson M, Driesen NR, Skudlarski P, Gore JC, Constable RT. Brain Connectivity Related to Working Memory Performance. Journal Of Neuroscience 2006, 26: 13338-13343. PMID: 17182784, PMCID: PMC2677699, DOI: 10.1523/jneurosci.3408-06.2006.Peer-Reviewed Original ResearchConceptsPosterior cingulate cortexMemory taskCognitive tasksCingulate cortexVentral anterior cingulate cortexDifferent cognitive tasksMedial frontal regionsMedial frontal gyrusDefault mode networkAnterior cingulate cortexFunctional imaging studiesCognitive abilitiesIndividual differencesMemory performanceCognitive performanceFrontal gyrusMode networkFrontal regionsFunctional connectivityBrain connectivityBrain areasTaskFunctional connectionsImaging studiesCortex
1997
Predicting Reading Performance From Neuroimaging Profiles: The Cerebral Basis of Phonological Effects in Printed Word Identification
Pugh K, Shaywitz B, Shaywitz S, Shankweiler D, Katz L, Fletcher J, Skudlarski P, Fulbright R, Constable R, Bronen R, Lacadie C, Gore J. Predicting Reading Performance From Neuroimaging Profiles: The Cerebral Basis of Phonological Effects in Printed Word Identification. Journal Of Experimental Psychology Human Perception & Performance 1997, 23: 299-318. PMID: 9103996, DOI: 10.1037/0096-1523.23.2.299.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingPhonological effectsLexical decision taskLexical decision latenciesLexical-semantic processesBrain activation patternsWord identificationWord recognitionDecision taskDecision latenciesRegularity effectIndividual differencesFMRI measuresHemispheric lateralizationCerebral basisExperimental paradigmActivation patternsCortical regionsLength effectYoung adultsTaskParticipantsReadingMeasuresMagnetic resonance imaging