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 ResearchConceptsStructure-function correspondenceBrain regionsMacroscale gradientWhite matter connectivityHuman brain regionsStructure-function couplingNeural network propertiesAssociation cortexCognitive functionBridging neuroscienceFunctional coactivationOrganizational axisCortical thicknessHuman brainMotor cortexLanguage processingBrainCortexMotor functionNatural language processingNetwork propertiesMotorNeuroscienceNatural languageData repositoriesConstrained alternating minimization for parameter mapping (CAMP)
Elsaid N, Dispenza N, Hu C, Peters D, Constable R, Tagare H, Galiana G. Constrained alternating minimization for parameter mapping (CAMP). Magnetic Resonance Imaging 2024, 110: 176-183. PMID: 38657714, PMCID: PMC11193090, DOI: 10.1016/j.mri.2024.04.029.Peer-Reviewed Original ResearchConceptsAlternating minimizationAccelerated parameter mappingImage qualityReconstructed image qualityEfficient reconstruction algorithmSacrificing model accuracyParameter mapsPhantom studyK-space samplingAcceleration datasetsK-spaceUndersampling artifactsCartesian acquisitionConsecutive imagesReconstruction algorithmIndividual imagesModel cost functionExponential decayEcho timeReconstruction methodCost functionReduce artifactsPhantomScan timeObjective functionMultimodal measures of spontaneous brain activity reveal both common and divergent patterns of cortical functional organization
Vafaii H, Mandino F, Desrosiers-Grégoire G, O’Connor D, Markicevic M, Shen X, Ge X, Herman P, Hyder F, Papademetris X, Chakravarty M, Crair M, Constable R, Lake E, Pessoa L. Multimodal measures of spontaneous brain activity reveal both common and divergent patterns of cortical functional organization. Nature Communications 2024, 15: 229. PMID: 38172111, PMCID: PMC10764905, DOI: 10.1038/s41467-023-44363-z.Peer-Reviewed Original Research
2023
Clinical Promise of Brain-Phenotype Modeling
Greene A, Constable R. Clinical Promise of Brain-Phenotype Modeling. JAMA Psychiatry 2023, 80: 848-854. PMID: 37314790, DOI: 10.1001/jamapsychiatry.2023.1419.Peer-Reviewed Original ResearchImpact of postnatal weight gain on brain white matter maturation in very preterm infants
Bobba P, Weber C, Higaki A, Mukherjee P, Scheinost D, Constable R, Ment L, Taylor S, Payabvash S. Impact of postnatal weight gain on brain white matter maturation in very preterm infants. Journal Of Neuroimaging 2023, 33: 991-1002. PMID: 37483073, PMCID: PMC10800683, DOI: 10.1111/jon.13145.Peer-Reviewed Original ResearchConceptsBirth weight z-scoreMagnetic resonance imagingVery preterm infantsPostnatal weight gainWeight z-scoreWhite matter maturationBirth weightDiffusion tensor imagingNeurological outcomePreterm infantsGestational ageWeight gainCorpus callosumHigher birth weight z-scoresBrain white matter maturationLong-term neurological deficitsZ-scoreBrain developmentWeight z-score changeWM tractsZ-score changeWM maturationWeeks of lifeNeurological deficitsNutritional interventionBrain responses to nutrients are severely impaired and not reversed by weight loss in humans with obesity: a randomized crossover study
van Galen K, Schrantee A, ter Horst K, la Fleur S, Booij J, Constable R, Schwartz G, DiLeone R, Serlie M. Brain responses to nutrients are severely impaired and not reversed by weight loss in humans with obesity: a randomized crossover study. Nature Metabolism 2023, 5: 1059-1072. PMID: 37308722, DOI: 10.1038/s42255-023-00816-9.Peer-Reviewed Original ResearchConceptsDiet-induced weight lossCerebral neuronal activityStriatal dopamine releaseWeight lossCrossover studyDopamine releaseNeuronal activityIntragastric glucoseNeuronal responsesSuccessful weight lossHealthy body weightSignificant weight lossBrain responsesPathological feeding behaviorsWeight regainHunger scoresLipid infusionLean participantsCaloric intakePlasma hormonesObesityBody weightInfusionNutrient signalsHigh rateWhy is everyone talking about brain state?
Greene A, Horien C, Barson D, Scheinost D, Constable R. Why is everyone talking about brain state? Trends In Neurosciences 2023, 46: 508-524. PMID: 37164869, PMCID: PMC10330476, DOI: 10.1016/j.tins.2023.04.001.Peer-Reviewed Original ResearchAssociation of Body Mass Index and Waist Circumference With Imaging Metrics of Brain Integrity and Functional Connectivity in Children Aged 9 to 10 Years in the US, 2016-2018
Kaltenhauser S, Weber C, Lin H, Mozayan A, Malhotra A, Constable R, Acosta J, Falcone G, Taylor S, Ment L, Sheth K, Payabvash S. Association of Body Mass Index and Waist Circumference With Imaging Metrics of Brain Integrity and Functional Connectivity in Children Aged 9 to 10 Years in the US, 2016-2018. JAMA Network Open 2023, 6: e2314193. PMID: 37200030, PMCID: PMC10196880, DOI: 10.1001/jamanetworkopen.2023.14193.Peer-Reviewed Original ResearchConceptsBody mass indexHigher body mass indexWaist circumferenceBMI z-scoreCross-sectional studyBrain healthCross-sectional analysisFunctional connectivityMass indexMean ageInterval developmentCorpus callosumAssociation of BMIHigher baseline body mass indexBaseline cross-sectional analysisBaseline body mass indexBrain integrityResting-state functional connectivityLongitudinal analysisFuture treatment trialsABCD studyLower microstructural integrityCognitive Development StudyAdolescent Brain Cognitive Development (ABCD) studyCardiovascular implicationsFunctional brain networks reflect spatial and temporal autocorrelation
Shinn M, Hu A, Turner L, Noble S, Preller K, Ji J, Moujaes F, Achard S, Scheinost D, Constable R, Krystal J, Vollenweider F, Lee D, Anticevic A, Bullmore E, Murray J. Functional brain networks reflect spatial and temporal autocorrelation. Nature Neuroscience 2023, 26: 867-878. PMID: 37095399, DOI: 10.1038/s41593-023-01299-3.Peer-Reviewed Original Research
2022
A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth
Horien C, Greene A, Shen X, Fortes D, Brennan-Wydra E, Banarjee C, Foster R, Donthireddy V, Butler M, Powell K, Vernetti A, Mandino F, O'Connor D, Lake E, McPartland J, Volkmar F, Chun M, Chawarska K, Rosenberg M, Scheinost D, Constable R. A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth. Cerebral Cortex 2022, 33: 6320-6334. PMID: 36573438, PMCID: PMC10183743, DOI: 10.1093/cercor/bhac506.Peer-Reviewed Original ResearchConceptsAttention taskAttentional stateConnectome-based predictive modelingNeurodiverse conditionsSustained attention taskAttention network modelSample of youthNeurotypical participantsSustained attentionBrain correlatesNeurobiological correlatesAttention networkIndividual participantsSeparate samplesYouthParticipantsHead motionTaskCorrelatesAttentionAutismConfoundsNetwork modelGeneralizesHealthcare settingsSex 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 variationMyelinHuman visual consciousness involves large scale cortical and subcortical networks independent of task report and eye movement activity
Kronemer S, Aksen M, Ding J, Ryu J, Xin Q, Ding Z, Prince J, Kwon H, Khalaf A, Forman S, Jin D, Wang K, Chen K, Hu C, Agarwal A, Saberski E, Wafa S, Morgan O, Wu J, Christison-Lagay K, Hasulak N, Morrell M, Urban A, Todd Constable R, Pitts M, Mark Richardson R, Crowley M, Blumenfeld H. Human visual consciousness involves large scale cortical and subcortical networks independent of task report and eye movement activity. Nature Communications 2022, 13: 7342. PMID: 36446792, PMCID: PMC9707162, DOI: 10.1038/s41467-022-35117-4.Peer-Reviewed Original ResearchConceptsSubcortical networksConscious visual perceptionVisual perception taskNeurophysiology of consciousnessExecutive control networkMajor brain networksDefault mode networkFrontal eye fieldOvert reportPerception taskVisual consciousnessConscious perceptionFusiform cortexVisual perceptionAnterior insulaConscious experienceSalience networkBrain networksMode networkAnterior cingulateEye fieldTask reportControl networkFMRI changesNeural circuits
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 powerUsing functional connectivity models to characterize relationships between working and episodic memory
Stark GF, Avery EW, Rosenberg MD, Greene AS, Gao S, Scheinost D, Constable R, Chun MM, Yoo K. Using functional connectivity models to characterize relationships between working and episodic memory. Brain And Behavior 2021, 11: e02105. PMID: 34142458, PMCID: PMC8413720, DOI: 10.1002/brb3.2105.Peer-Reviewed Original ResearchConceptsConnectome-based predictive modelsN-back task performanceEpisodic memoryMemory test scoresFunctional connectivityTask performanceN-back memory taskWord scoresTest scoresCritical cognitive abilityPicture-sequencing taskHuman Connectome Project participantsN-back taskFunctional magnetic resonance imaging (fMRI) dataWhole-brain functional connectivityTask functional connectivityFunctional brain connectionsFunctional connectivity modelsFunctional connectionsMemory taskCognitive processesMemory testCognitive abilitiesSequence taskList Sorting
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 imagingLoss 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 datasetDifferencesConnectivityMultisite reliability and repeatability of an advanced brain MRI protocol
Schwartz DL, Tagge I, Powers K, Ahn S, Bakshi R, Calabresi PA, Constable R, Grinstead J, Henry RG, Nair G, Papinutto N, Pelletier D, Shinohara R, Oh J, Reich DS, Sicotte NL, Rooney WD, Cooperative O. Multisite reliability and repeatability of an advanced brain MRI protocol. Journal Of Magnetic Resonance Imaging 2019, 50: 878-888. PMID: 30652391, PMCID: PMC6636359, DOI: 10.1002/jmri.26652.Peer-Reviewed Original Research