2024
The brain structure, inflammatory, and genetic mechanisms mediate the association between physical frailty and depression
Jiang R, Noble S, Rosenblatt M, Dai W, Ye J, Liu S, Qi S, Calhoun V, Sui J, Scheinost D. The brain structure, inflammatory, and genetic mechanisms mediate the association between physical frailty and depression. Nature Communications 2024, 15: 4411. PMID: 38782943, PMCID: PMC11116547, DOI: 10.1038/s41467-024-48827-8.Peer-Reviewed Original ResearchConceptsIncident depressionPre-frailPhysical frailtyFrail individualsPopulation attributable fraction analysisRisk factors of depressionMendelian randomization analysisFactors of depressionPotential causal effectModifiable risk factorsNon-frail individualsCross-sectional studyEffect of frailtyHigher disease burdenUK BiobankRandomization analysisBrain volumeDepression casesDisease burdenFrailtyRegional brain volumesIncreased riskDepressionHigh riskFollow-up
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 networkAssociations between grip strength, brain structure, and mental health in > 40,000 participants from the UK Biobank
Jiang R, Westwater ML, Noble S, Rosenblatt M, Dai W, Qi S, Sui J, Calhoun VD, Scheinost D. Associations between grip strength, brain structure, and mental health in > 40,000 participants from the UK Biobank. BMC Medicine 2022, 20: 286. PMID: 36076200, PMCID: PMC9461129, DOI: 10.1186/s12916-022-02490-2.Peer-Reviewed Original ResearchConceptsGray matter volumeMental healthBrain structuresCognitive declineMatter volumeMental health outcomesHigher life satisfactionBetter mental healthBaseline grip strengthNeural correlatesCognitive functioningCognitive performanceBaseline neuroticismAnxiety symptomsBehavioral outcomesLife satisfactionMediation analysisNeuroimaging datasetsTemporal cortexOlder adultsLinear mixed effects modelsSubcortical regionsFinancial satisfactionLongitudinal dataGrip strengthAssociations among Household and Neighborhood Socioeconomic Disadvantages, Resting-state Frontoamygdala Connectivity, and Internalizing Symptoms in Youth
Ip KI, Sisk LM, Horien C, Conley MI, Rapuano KM, Rosenberg MD, Greene AS, Scheinost D, Constable RT, Casey BJ, Baskin-Sommers A, Gee DG. Associations among Household and Neighborhood Socioeconomic Disadvantages, Resting-state Frontoamygdala Connectivity, and Internalizing Symptoms in Youth. Journal Of Cognitive Neuroscience 2022, 34: 1810-1841. PMID: 35104356, DOI: 10.1162/jocn_a_01826.Peer-Reviewed Original ResearchConceptsSocioeconomic disadvantageNeighbourhood deprivationResting-state functional connectivityInternalizing symptomsSymptoms 1 yearHigher neighborhood deprivationNeighborhood socioeconomic disadvantageCognitive Development StudyAdolescent Brain Cognitive Development (ABCD) studyEarly interventionBilateral amygdalaElevated symptomsNegative connectivitySymptomsFunctional connectivityMental healthPositive connectivityBaselineHigher internalizing symptomsFrontoparietal networkOFC regionsFunctional couplingDeleterious effectsHigh disadvantageNeeds ratioLarge-scale differences in functional organization of left- and right-handed individuals using whole-brain, data-driven analysis of connectivity
Tejavibulya L, Peterson H, Greene A, Gao S, Rolison M, Noble S, Scheinost D. Large-scale differences in functional organization of left- and right-handed individuals using whole-brain, data-driven analysis of connectivity. NeuroImage 2022, 252: 119040. PMID: 35272202, PMCID: PMC9013515, DOI: 10.1016/j.neuroimage.2022.119040.Peer-Reviewed Original ResearchConceptsHanded individualsFunctional connectivityLanguage areasWhole-brain functional connectivityRight-handed individualsFunctional organizationWhole-brain levelIndividual differencesHandedness differencesHandedness effectsFunctional connectomeBrain levelsSomatosensory cortexNetworks of interestWhole brainSex differencesBrainConnectomeIndividualsData-driven analysisConnectivityDistinct patternsLateralizationDifferencesSimilar amounts
2021
Resample aggregating improves the generalizability of connectome predictive modeling
O’Connor D, Lake EMR, Scheinost D, Constable RT. Resample aggregating improves the generalizability of connectome predictive modeling. NeuroImage 2021, 236: 118044. PMID: 33848621, PMCID: PMC8282199, DOI: 10.1016/j.neuroimage.2021.118044.Peer-Reviewed Original Research
2020
Big data approaches to identifying sex differences in long-term memory
Tejavibulya L, Scheinost D. Big data approaches to identifying sex differences in long-term memory. Cognitive Neuroscience 2020, 12: 185-186. PMID: 33356847, PMCID: PMC8222419, DOI: 10.1080/17588928.2020.1866520.Peer-Reviewed Original ResearchTransdiagnostic, Connectome-Based Prediction of Memory Constructs Across Psychiatric Disorders
Barron DS, Gao S, Dadashkarimi J, Greene AS, Spann MN, Noble S, Lake EMR, Krystal JH, Constable RT, Scheinost D. Transdiagnostic, Connectome-Based Prediction of Memory Constructs Across Psychiatric Disorders. Cerebral Cortex 2020, 31: 2523-2533. PMID: 33345271, PMCID: PMC8023861, DOI: 10.1093/cercor/bhaa371.Peer-Reviewed Original ResearchConceptsMacroscale brain networksIndividual differencesBrain networksMemory deficitsFunctional connectivityAttention deficit hyper-activity disorderTask-based functional MRI dataLong-term memoryWhole-brain functional connectivityDiagnostic groupsWhole-brain patternsDefault mode networkFunctional MRI dataHuman Connectome ProjectPsychiatric disordersMemory constructsMemory performanceTransdiagnostic sampleBrain correlatesMode networkFunctional connectomeConnectome ProjectLimbic networkHealthy participantsMemoryLow-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 motionProtocolBehavioral 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 imagingAssociation of Prefrontal-Striatal Functional Pathology With Alcohol Abstinence Days at Treatment Initiation and Heavy Drinking After Treatment Initiation
Blaine SK, Wemm S, Fogelman N, Lacadie C, Seo D, Scheinost D, Sinha R. Association of Prefrontal-Striatal Functional Pathology With Alcohol Abstinence Days at Treatment Initiation and Heavy Drinking After Treatment Initiation. American Journal Of Psychiatry 2020, 177: 1048-1059. PMID: 32854534, PMCID: PMC7606814, DOI: 10.1176/appi.ajp.2020.19070703.Peer-Reviewed Original ResearchConceptsAlcohol use disorderTreatment initiationAlcohol abstinenceHeavy drinkingFunctional MRIEarly treatment outcomesEarly treatment phaseHealthy control subjectsEarly outpatient treatmentNumber of daysStress imagesDrinking outcomesChronic alcohol abuseHeavy drinking daysSignificant hyperreactivityControl subjectsOutpatient treatmentStriatal dysfunctionEarly treatmentTreatment outcomesBrain stressFunctional pathologyProspective assessmentTreatment phaseAlcohol abuseHow Tasks Change Whole-Brain Functional Organization to Reveal Brain-Phenotype Relationships
Greene AS, Gao S, Noble S, Scheinost D, Constable RT. How Tasks Change Whole-Brain Functional Organization to Reveal Brain-Phenotype Relationships. Cell Reports 2020, 32: 108066. PMID: 32846124, PMCID: PMC7469925, DOI: 10.1016/j.celrep.2020.108066.Peer-Reviewed Original ResearchFunctional brain connectivity in ex utero premature infants compared to in utero fetuses
De Asis-Cruz J, Kapse K, Basu SK, Said M, Scheinost D, Murnick J, Chang T, du Plessis A, Limperopoulos C. Functional brain connectivity in ex utero premature infants compared to in utero fetuses. NeuroImage 2020, 219: 117043. PMID: 32534962, PMCID: PMC7493786, DOI: 10.1016/j.neuroimage.2020.117043.Peer-Reviewed Original ResearchConceptsPremature infantsHealthy fetusesBrain connectivityStructural brain injuryBlood oxygenation level-dependent (BOLD) signalBrain structural changesStress-related areasNormal brain MRIState functional MRIFunctional connectivity strengthFunctional brain connectivityLevel-dependent signalMedial temporal lobeNetwork-based statisticsSeed-based correlation analysisUtero fetusesBasal gangliaBrain injuryTerm ageBrain MRITemporal lobeExposure altersInfantsRegion of interestFunctional MRIDe novo damaging variants associated with congenital heart diseases contribute to the connectome
Ji W, Ferdman D, Copel J, Scheinost D, Shabanova V, Brueckner M, Khokha MK, Ment LR. De novo damaging variants associated with congenital heart diseases contribute to the connectome. Scientific Reports 2020, 10: 7046. PMID: 32341405, PMCID: PMC7184603, DOI: 10.1038/s41598-020-63928-2.Peer-Reviewed Original ResearchMeSH KeywordsConnectomeDNA HelicasesDNA-Binding ProteinsExomeFemaleHeart Defects, CongenitalHistone-Lysine N-MethyltransferaseHomeodomain ProteinsHumansMaleMi-2 Nucleosome Remodeling and Deacetylase ComplexMutationMutation, MissenseMyeloid-Lymphoid Leukemia ProteinNerve Tissue ProteinsProtein Tyrosine Phosphatase, Non-Receptor Type 11Receptor, Notch1ConceptsDe novo variantsNDD genesCardiac patterningDe novo damaging variantsDamaging de novo variantsCHD genesDamaging variantsGenesProtein truncatingGenetic originNovo variantsGene mutationsPatterningRecent studiesDendritic developmentVariantsMutationsNeurogenesisSynaptogenesisBonferroni correctionConnectome-based neurofeedback: A pilot study to improve sustained attention
Scheinost D, Hsu TW, Avery EW, Hampson M, Constable RT, Chun MM, Rosenberg MD. Connectome-based neurofeedback: A pilot study to improve sustained attention. NeuroImage 2020, 212: 116684. PMID: 32114151, PMCID: PMC7165055, DOI: 10.1016/j.neuroimage.2020.116684.Peer-Reviewed Original ResearchConceptsFunctional connectivityRt-fMRIReal-time functional magnetic resonance imaging (rt-fMRI) neurofeedbackWhole-brain functional connectivityClinical trial designFunctional magnetic resonance imaging (fMRI) neurofeedbackDistinct brain areasConnectome-based modelsClinical symptomsTrial designBrain areasBrain regionsSustained attentionTherapeutic toolPilot studyBrain activityFunctional connectionsSymptomsNeurofeedbackFunctional networksTraining durationAttention taskComplex functional networksPilot sampleFunctional connectivity predicts changes in attention observed across minutes, days, and months
Rosenberg MD, Scheinost D, Greene AS, Avery EW, Kwon YH, Finn ES, Ramani R, Qiu M, Constable RT, Chun MM. Functional connectivity predicts changes in attention observed across minutes, days, and months. Proceedings Of The National Academy Of Sciences Of The United States Of America 2020, 117: 3797-3807. PMID: 32019892, PMCID: PMC7035597, DOI: 10.1073/pnas.1912226117.Peer-Reviewed Original ResearchConceptsConnectome-based predictive modelsAttentional stateSustained attentionIndividual differencesSustained attention functionFunctional connectivity signaturesFunctional brain connectivityFunctional connectivity patternsAttention functionConnectivity signaturesFunctional connectivityBrain connectivityConnectivity patternsAttentionSingle personSame patternIndividualsConnectivityIndependent studiesRecent workState changesPersonsPeopleDifferencesAbility
2019
There is no single functional atlas even for a single individual: Functional parcel definitions change with task
Salehi M, Greene AS, Karbasi A, Shen X, Scheinost D, Constable RT. There is no single functional atlas even for a single individual: Functional parcel definitions change with task. NeuroImage 2019, 208: 116366. PMID: 31740342, DOI: 10.1016/j.neuroimage.2019.116366.Peer-Reviewed Original ResearchDifferential 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 1Combining 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 ProjectAn 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