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
2023
The effects of experience of discrimination and acculturation during pregnancy on the developing offspring brain
Spann M, Alleyne K, Holland C, Davids A, Pierre-Louis A, Bang C, Oyeneye V, Kiflom R, Shea E, Cheng B, Peterson B, Monk C, Scheinost D. The effects of experience of discrimination and acculturation during pregnancy on the developing offspring brain. Neuropsychopharmacology 2023, 49: 476-485. PMID: 37968451, PMCID: PMC10724278, DOI: 10.1038/s41386-023-01765-3.Peer-Reviewed Original ResearchElevated C-reactive protein mediates the liver-brain axis: a preliminary study
Jiang R, Wu J, Rosenblatt M, Dai W, Rodriguez R, Sui J, Qi S, Liang Q, Xu B, Meng Q, Calhoun V, Scheinost D. Elevated C-reactive protein mediates the liver-brain axis: a preliminary study. EBioMedicine 2023, 93: 104679. PMID: 37356206, PMCID: PMC10320521, DOI: 10.1016/j.ebiom.2023.104679.Peer-Reviewed Original ResearchConceptsRegional gray matter volumeGray matter volumeCognitive functioningMost cognitive measuresUnderlying neurobiological factorsEffect sizeLarge effect sizesProspective memoryVisual memoryCognitive measuresExecutive functionTrail MakingCognitive performanceNeurobiological factorsSmall effect sizesProcessing speedVentral striatumParahippocampal gyrusCognitive declineCognitive impairmentMatter volumeMemoryFunctioningCross-sectional associationsLimited 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 networkGraph theory analysis of whole brain functional connectivity to assess disturbances associated with suicide attempts in bipolar disorder
Sankar A, Scheinost D, Goldman DA, Drachman R, Colic L, Villa LM, Kim JA, Gonzalez Y, Marcelo I, Shinomiya M, Pittman B, Lacadie CM, Oquendo MA, Constable RT, Blumberg HP. Graph theory analysis of whole brain functional connectivity to assess disturbances associated with suicide attempts in bipolar disorder. Translational Psychiatry 2022, 12: 7. PMID: 35013103, PMCID: PMC8748935, DOI: 10.1038/s41398-021-01767-z.Peer-Reviewed Original ResearchConceptsIntrinsic connectivity distributionBipolar disorderSuicide attemptsHealthy volunteersFunctional connectivity disturbancesSuicide behaviorWhole-brain functional connectivityPrior suicide attemptsRight anterior insulaBrain functional connectivitySuicidal ideation severityBilateral ventromedial prefrontal cortexFunctional magnetic resonanceSignificant group differencesTemporopolar cortexConnectivity disturbancesBrain targetsFC differencesHigh riskCerebellar cortexVentromedial prefrontal cortexSuicidal ideationOrbitofrontal cortexFunctional connectivitySuicide risk
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
Transdiagnostic, 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 participantsMemoryAssociation 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 abuseMagnetic resonance image connectivity analysis provides evidence of central nervous system mode of action for parasacral transcutaneous electro neural stimulation - A pilot study
Netto JMB, Scheinost D, Onofrey JA, Franco I. Magnetic resonance image connectivity analysis provides evidence of central nervous system mode of action for parasacral transcutaneous electro neural stimulation - A pilot study. Journal Of Pediatric Urology 2020, 16: 536-542. PMID: 32873504, DOI: 10.1016/j.jpurol.2020.08.002.Peer-Reviewed Original ResearchConceptsDorsal lateral prefrontal cortexAnterior cingulate cortexOveractive bladderFunctional connectivityPrefrontal cortexUrinary tract symptomsSacral nerve stimulatorCommon treatment modalityRight scapular regionACC functional connectivityResting-state conditionsMechanism of actionTract symptomsMotor thresholdCentral effectsACC connectivityNerve stimulatorSacral levelTreatment modalitiesFunctional connectivity dataMechanism of effectivenessAdult volunteersFrontal lobeSubcortical regionsCingulate cortexIdentification of a brain fingerprint for overweight and obesity
Farruggia MC, van Kooten MJ, Perszyk EE, Burke MV, Scheinost D, Constable RT, Small DM. Identification of a brain fingerprint for overweight and obesity. Physiology & Behavior 2020, 222: 112940. PMID: 32417645, PMCID: PMC7321926, DOI: 10.1016/j.physbeh.2020.112940.Peer-Reviewed Original ResearchConceptsPercent body fatWaist circumferenceBody fatWhole-brain functional connectivityBrain network patternsGlucose toleranceBlood insulinObesityOverweightPathophysiological phenotypesFunctional connectivity networksFunctional connectivityMilkshake consumptionBrain correlatesBrain fingerprintsBMIAdiposityBrainCircumferenceConnectivity networksFatDiabetesPathophysiologyCentral roleInsulinConnectome-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
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 ResearchThere 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 ResearchThe Application of Connectome-Based Predictive Modeling to the Maternal Brain: Implications for Mother–Infant Bonding
Rutherford HJV, Potenza MN, Mayes LC, Scheinost D. The Application of Connectome-Based Predictive Modeling to the Maternal Brain: Implications for Mother–Infant Bonding. Cerebral Cortex 2019, 30: 1538-1547. PMID: 31690936, PMCID: PMC7132918, DOI: 10.1093/cercor/bhz185.Peer-Reviewed Original ResearchConceptsConnectome-based predictive modelingAuditory networkMaternal anxietyMaternal bondingContext of anxietyMaternal Brain NetworkMother-infant bondBrain functional connectivityChild developmentMother-infant bondingBrain networksFunctional connectivityAnxietyBehavioral qualitiesBonding relationshipsBonding impairmentBrain structuresMaternal brainMother's mindGreater segregationNetwork connectivityMindGreater integrationConnectivityMonths postpartumIndividualized 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 definitionsDifferential 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 datasetsMultivariate approaches improve the reliability and validity of functional connectivity and prediction of individual behaviors
Yoo K, Rosenberg MD, Noble S, Scheinost D, Constable RT, Chun MM. Multivariate approaches improve the reliability and validity of functional connectivity and prediction of individual behaviors. NeuroImage 2019, 197: 212-223. PMID: 31039408, PMCID: PMC6591084, DOI: 10.1016/j.neuroimage.2019.04.060.Peer-Reviewed Original ResearchConceptsFunctional brain organizationFunctional connectivityFunctional connectivity featuresTest-retest sampleMultivariate functional connectivityCognitive skillsMental representationsIndividual differencesFMRI measuresBrain organizationBrain statesStrong predictionSpatial activity patternsFMRI datasetsConnectivity featuresIndividual behaviorProject samplesConnectivity estimatesTimecoursesActivity patternsCognitionPearson correlationIndividualsConnectivityUnivariate approach