2024
Mapping the structure-function relationship along macroscale gradients in the human brain
Collins E, Chishti O, Obaid S, McGrath H, King A, Shen X, Arora J, Papademetris X, Constable R, Spencer D, Zaveri H. Mapping the structure-function relationship along macroscale gradients in the human brain. Nature Communications 2024, 15: 7063. PMID: 39152127, PMCID: PMC11329792, DOI: 10.1038/s41467-024-51395-6.Peer-Reviewed Original Research
2022
Sex differences in default mode network connectivity in healthy aging adults
Ficek-Tani B, Horien C, Ju S, Xu W, Li N, Lacadie C, Shen X, Scheinost D, Constable T, Fredericks C. Sex differences in default mode network connectivity in healthy aging adults. Cerebral Cortex 2022, 33: 6139-6151. PMID: 36563018, PMCID: PMC10183749, DOI: 10.1093/cercor/bhac491.Peer-Reviewed Original ResearchConceptsDefault mode networkPreclinical Alzheimer's diseaseAlzheimer's diseaseSex differencesBrain connectivity changesDefault mode network connectivityIntrinsic connectivity distributionSeed-based analysisMode network connectivityMedial prefrontal cortexPosterior DMN nodesHealthy aging adultsImpact of sexLifetime riskDMN connectivityWhole brainPosterior cingulateDMN nodesSignificant sex differencesPrefrontal cortexConnectivity changesAging AdultsHealthy participantsDMN functionMode networkCoordinated anatomical and functional variability in the human brain during adolescence
Bero J, Li Y, Kumar A, Humphries C, Nag S, Lee H, Ahn W, Hahn S, Constable R, Kim H, Lee D. Coordinated anatomical and functional variability in the human brain during adolescence. Human Brain Mapping 2022, 44: 1767-1778. PMID: 36479851, PMCID: PMC9921246, DOI: 10.1002/hbm.26173.Peer-Reviewed Original ResearchConceptsCortical thicknessCortical areasFunctional connectivityResting-state functional connectivityAssociation cortical areasMultiple cortical areasCortical information processingAge-related changesCortical myelinationAdult brainCytoarchitectural featuresBrain developmentInformation processingBrainDevelopmental changesHuman brainAdolescenceMyelinationPatterns of coordinationMeasuresRegional variationMyelin
2020
Loss of nucleus accumbens low-frequency fluctuations is a signature of chronic pain
Makary MM, Polosecki P, Cecchi GA, DeAraujo IE, Barron DS, Constable TR, Whang PG, Thomas DA, Mowafi H, Small DM, Geha P. Loss of nucleus accumbens low-frequency fluctuations is a signature of chronic pain. Proceedings Of The National Academy Of Sciences Of The United States Of America 2020, 117: 10015-10023. PMID: 32312809, PMCID: PMC7211984, DOI: 10.1073/pnas.1918682117.Peer-Reviewed Original ResearchConceptsChronic low back pain patientsLow back pain patientsChronic painPain patientsChronic phaseChronic back pain patientsBack pain patientsRostral anterior cingulate cortexAnterior cingulate cortexAdditional independent datasetsRisk of transitionResting-state activityPersistent painBack painAccumbens volumeHealthy controlsNucleus accumbensPainSeparate cohortPatientsCingulate cortexPrevalent diseaseFunctional connectivityLoss of nucleiSubcortical signatures
2019
Differential Resting State Connectivity Responses to Glycemic State in Type 1 Diabetes
Parikh L, Seo D, Lacadie C, Belfort-Deaguiar R, Groskreutz D, Hamza M, Dai F, Scheinost D, Sinha R, Constable R, Sherwin R, Hwang JJ. Differential Resting State Connectivity Responses to Glycemic State in Type 1 Diabetes. The Journal Of Clinical Endocrinology & Metabolism 2019, 105: dgz004. PMID: 31511876, PMCID: PMC6936965, DOI: 10.1210/clinem/dgz004.Peer-Reviewed Original ResearchConceptsState functional connectivityHealthy controlsDefault mode networkType 1 diabetes mellitusFunctional connectivityImpact of T1DMAcademic medical centerAngular gyrus connectivityBlood oxygenation levelState connectivity patternsFunctional connectivity analysisHyperinsulinemic euglycemicHypoglycemic unawarenessHypoglycemia unawarenessDiabetes mellitusHypoglycemic clampHypoglycemia awarenessFunctional outcomeMild hypoglycemiaGlycemic stateObservational studyMedical CenterT1DMHC volunteersType 1The 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 datasetDifferencesConnectivity
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
Connectome-based Models Predict Separable Components of Attention in Novel Individuals
Rosenberg MD, Hsu WT, Scheinost D, Constable R, Chun MM. Connectome-based Models Predict Separable Components of Attention in Novel Individuals. Journal Of Cognitive Neuroscience 2017, 30: 160-173. PMID: 29040013, DOI: 10.1162/jocn_a_01197.Peer-Reviewed Original ResearchConceptsConnectome-based predictive modelingAttention Network TaskExecutive controlIntrinsic functional organizationRT variabilityANT performanceInfluential modelFunctional connectivityBrain's intrinsic functional organizationComponents of attentionExecutive control scoresResting-state functional connectivityResting-state dataFunctional brain networksFunctional organizationTask-based dataAttentional abilitiesUpcoming stimulusExplicit taskSustained attentionFMRI scanningAttention factorNovel individualsAdditional independent componentNetwork tasks
2016
Reorganization of brain connectivity in obesity
Geha P, Cecchi G, Constable R, Abdallah C, Small DM. Reorganization of brain connectivity in obesity. Human Brain Mapping 2016, 38: 1403-1420. PMID: 27859973, PMCID: PMC6866793, DOI: 10.1002/hbm.23462.Peer-Reviewed Original ResearchConceptsGlobal brain connectivityDorsal attention networkPeripheral metabolic dysfunctionHum Brain MappSuperior parietal lobuleSomatomotor cortexMetabolic dysfunctionVentrolateral prefrontal cortexPremotor areasCaudate nucleusNeurocognitive impairmentObesityAnterior hippocampusVisual cortexBrain regionsParietal lobuleBrain functionPrefrontal cortexBrain connectivityMilkshake consumptionCortexFeeding decisionsBrain organizationInsulaHomeostatic state
2015
Functional 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
2009
Pancreatic perfusion of healthy individuals and type 1 diabetic patients as assessed by magnetic resonance perfusion imaging
Hirshberg B, Qiu M, Cali AM, Sherwin R, Constable T, Calle RA, Tal MG. Pancreatic perfusion of healthy individuals and type 1 diabetic patients as assessed by magnetic resonance perfusion imaging. Diabetologia 2009, 52: 1561. PMID: 19488737, DOI: 10.1007/s00125-009-1406-8.Peer-Reviewed Original ResearchConceptsType 1 diabetic patientsPancreatic blood flowDiabetic patientsBlood flowIslet massHealthy volunteersPancreatic perfusionArterial spin labeling magnetic resonanceTotal pancreatic blood flowPancreatic beta-cell massConclusions/interpretationOur dataAims/hypothesisLossBeta-cell massMagnetic resonance perfusionSignificant differencesHuman pancreatic isletsDiabetes mellitusVascularised organsIslet functionMurine modelClamp studiesNormal volunteersHealthy individualsPatientsControl tissuesLanguage lateralization in epilepsy patients: fMRI validated with the Wada procedure
Arora J, Pugh K, Westerveld M, Spencer S, Spencer DD, Constable R. Language lateralization in epilepsy patients: fMRI validated with the Wada procedure. Epilepsia 2009, 50: 2225-2241. PMID: 19490042, DOI: 10.1111/j.1528-1167.2009.02136.x.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingVerbal fluency taskWada procedureSentence comprehensionFluency taskLaterality scoresLanguage lateralizationLaterality indexAuditory sentence comprehensionFMRI language mappingAuditory taskReading taskConjunction analysisHemispheric dominanceLateralization scoresFMRI laterality indicesLanguage mappingWada testingMidline regionWada testLateralizationSpecific patient examplesQuantifying activationTaskComprehension
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 studyVASO‐based calculations of CBV change: Accounting for the dynamic CSF volume
Scouten A, Constable R. VASO‐based calculations of CBV change: Accounting for the dynamic CSF volume. Magnetic Resonance In Medicine 2008, 59: 308-315. PMID: 18228581, PMCID: PMC2737703, DOI: 10.1002/mrm.21427.Peer-Reviewed Original Research
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 studiesCortexConnectivity–behavior analysis reveals that functional connectivity between left BA39 and Broca's area varies with reading ability
Hampson M, Tokoglu F, Sun Z, Schafer RJ, Skudlarski P, Gore JC, Constable RT. Connectivity–behavior analysis reveals that functional connectivity between left BA39 and Broca's area varies with reading ability. NeuroImage 2006, 31: 513-519. PMID: 16497520, DOI: 10.1016/j.neuroimage.2005.12.040.Peer-Reviewed Original Research
2005
Amygdala gray matter concentration is associated with extraversion and neuroticism
Omura K, Constable R, Canli T. Amygdala gray matter concentration is associated with extraversion and neuroticism. Neuroreport 2005, 16: 1905-1908. PMID: 16272876, DOI: 10.1097/01.wnr.0000186596.64458.76.Peer-Reviewed Original ResearchAmygdala responsiveness is modulated by tryptophan hydroxylase-2 gene variation
Canli T, Congdon E, Gutknecht L, Constable R, Lesch K. Amygdala responsiveness is modulated by tryptophan hydroxylase-2 gene variation. Journal Of Neural Transmission 2005, 112: 1479-1485. PMID: 16245070, DOI: 10.1007/s00702-005-0391-4.Peer-Reviewed Original ResearchNeural correlates of temporal-order judgments versus those of spatial-location: Deactivation of hippocampus may facilitate spatial performance
Rekkas P, Westerveld M, Skudlarski P, Zumer J, Pugh K, Spencer D, Constable R. Neural correlates of temporal-order judgments versus those of spatial-location: Deactivation of hippocampus may facilitate spatial performance. Brain And Cognition 2005, 59: 103-113. PMID: 16169136, DOI: 10.1016/j.bandc.2005.05.013.Peer-Reviewed Original ResearchConceptsTemporal order judgmentsMidfrontal gyrusSpatial performanceLeft superior temporal gyrusSpatial location judgmentsRight midfrontal gyrusSpatial memory processingNegative BOLD signal changesSuperior temporal gyrusMedial frontal gyrusSpatial location informationNeural correlatesAutobiographic memoryMemory processingBOLD signal changesFrontal gyrusMemory demandsTemporal gyrusJudgment typeSpatial retrievalTemporal retrievalGyrusInterest analysisJudgmentsBOLD signal intensity
2002
Heschl's gyrus identification using functional MRI: neurosurgical issue.
Carpentier A, Clemenceau S, Constable T, Cornu P, Baulac M, Van Effenterre R. Heschl's gyrus identification using functional MRI: neurosurgical issue. Neurochirurgie 2002, 48: 80-6. PMID: 12053161.Peer-Reviewed Original ResearchConceptsAuditory cortex activationFunctional MRIHeschl's gyrusCortex activationPrimary auditory cortex activationPrimary auditory cortexLeft superior temporal regionLanguage areasSuperior temporal regionsEcho-planar sequenceResectable areaPreoperative toolAuditory cortexNeurosurgical issuesHealthy adultsFunctional imagesTemporal regionsGyrusAuditory paradigmRhythmic stimuliFrequent activationSelective activationMRIActivationPlanar sequence