2022
A graph theory neuroimaging approach to distinguish the depression of bipolar disorder from major depressive disorder in adolescents and young adults
Goldman DA, Sankar A, Rich A, Kim JA, Pittman B, Constable RT, Scheinost D, Blumberg HP. A graph theory neuroimaging approach to distinguish the depression of bipolar disorder from major depressive disorder in adolescents and young adults. Journal Of Affective Disorders 2022, 319: 15-26. PMID: 36103935, PMCID: PMC9669784, DOI: 10.1016/j.jad.2022.09.016.Peer-Reviewed Original ResearchConceptsAdolescents/young adultsMajor depressive disorderDepressive disorderYoung adultsICD increasesBipolar disorderInterhemispheric functional connectivityFunctional connectivity differencesSeed-based analysisFunctional connectivity patternsSeed-based connectivityFunctional magnetic resonanceFunctional connectivity measuresBasal gangliaFunctional dysconnectivityIllness progressionTreatment strategiesClinical measuresEarly diagnosisHC groupTargeted treatmentConnectivity differencesSuicide thoughtsFunctional connectivityDeleterious treatment
2021
A graph theory‐based whole brain approach to assess mood state differences in adolescents and young adults with bipolar disorder
Goldman DA, Sankar A, Colic L, Villa L, Kim JA, Pittman B, Constable RT, Scheinost D, Blumberg HP. A graph theory‐based whole brain approach to assess mood state differences in adolescents and young adults with bipolar disorder. Bipolar Disorders 2021, 24: 412-423. PMID: 34665907, PMCID: PMC9016085, DOI: 10.1111/bdi.13144.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentBipolar DisorderBrainBrain MappingHumansMagnetic Resonance ImagingPrefrontal CortexYoung AdultConceptsLenticular nucleusFunctional connectivityPrefrontal cortexMood statesYoung adultsLimited brain regionsAcute mood statesRight lenticular nucleusBipolar I disorderDorsal prefrontal cortexPrevious neuroimaging studiesWhole-brain approachTemporal functional connectivityFunctional magnetic resonanceLeft prefrontal cortexBrain dysfunctionContralateral homologuesHealthy controlsI disordersDepression scoresICD increasesRight cerebellumBipolar disorderEarly interventionBrain regionsResample 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 Maternal Prepregnancy Body Mass Index With Fetal Growth and Neonatal Thalamic Brain Connectivity Among Adolescent and Young Women
Spann MN, Scheinost D, Feng T, Barbato K, Lee S, Monk C, Peterson BS. Association of Maternal Prepregnancy Body Mass Index With Fetal Growth and Neonatal Thalamic Brain Connectivity Among Adolescent and Young Women. JAMA Network Open 2020, 3: e2024661. PMID: 33141162, PMCID: PMC7610195, DOI: 10.1001/jamanetworkopen.2020.24661.Peer-Reviewed Original ResearchConceptsMaternal prepregnancy BMIMaternal prepregnancy body mass indexPrepregnancy body mass indexNeonatal functional connectivityPrepregnancy BMIBody mass indexFetal growthFunctional connectivityFetal weightMass indexMAIN OUTCOMEHigher maternal prepregnancy body mass indexElectronic health record reviewAdverse long-term outcomesProspective longitudinal cohort studyColumbia University Irving Medical CenterBrain connectivityHigher maternal BMIHealth record reviewLong-term outcomesRoutine prenatal careLongitudinal cohort studyMajor health problemFetal head circumferenceTime of recruitmentFunctional 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 ResearchCombining 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 ResearchMeSH KeywordsAdultAlgorithmsConnectomeFemaleForecastingHumansMaleModels, NeurologicalPhenotypeYoung AdultConceptsMultiple 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 ProjectThe 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
Data-Driven Analysis of Functional Connectivity Reveals a Potential Auditory Verbal Hallucination Network
Scheinost D, Tokoglu F, Hampson M, Hoffman R, Constable RT. Data-Driven Analysis of Functional Connectivity Reveals a Potential Auditory Verbal Hallucination Network. Schizophrenia Bulletin 2018, 45: 415-424. PMID: 29660081, PMCID: PMC6403094, DOI: 10.1093/schbul/sby039.Peer-Reviewed Original ResearchConceptsAuditory Hallucination Rating ScaleIntrinsic connectivity distributionAuditory verbal hallucinationsHealthy controlsFunctional connectivityLateralized connectivitySevere global health problemSeed connectivity analysesBest treatment strategyGlobal health problemWhole-brain connectivityMedial prefrontal cortexPosterior cingulate cortexDefault mode networkSuch patientsPatient groupLeft putamenTreatment strategiesPatientsActionable targetsSchizoaffective disorderCingulate cortexHealth problemsVoxel-based measurePrefrontal cortexMaternal Immune Activation During the Third Trimester Is Associated with Neonatal Functional Connectivity of the Salience Network and Fetal to Toddler Behavior
Spann MN, Monk C, Scheinost D, Peterson BS. Maternal Immune Activation During the Third Trimester Is Associated with Neonatal Functional Connectivity of the Salience Network and Fetal to Toddler Behavior. Journal Of Neuroscience 2018, 38: 2877-2886. PMID: 29487127, PMCID: PMC5852665, DOI: 10.1523/jneurosci.2272-17.2018.Peer-Reviewed Original ResearchConceptsMaternal immune activationC-reactive proteinFetal heart rate variabilityNeonatal functional connectivityInterleukin-6Postmenstrual ageImmune activationSalience networkFunctional connectivityPsychiatric disordersCRP levelsEpidemiological studiesMaternal C-reactive proteinResting-state imaging dataC-reactive protein levelsMaternal CRP levelsMaternal IL-6Months postmenstrual agePrenatal maternal immune activationSame psychiatric disordersWeeks postmenstrual ageIL-6 levelsAlters functional connectivityAltered brain developmentSame gestational ageResting-state functional connectivity predicts neuroticism and extraversion in novel individuals
Hsu WT, Rosenberg MD, Scheinost D, Constable RT, Chun MM. Resting-state functional connectivity predicts neuroticism and extraversion in novel individuals. Social Cognitive And Affective Neuroscience 2018, 13: 224-232. PMID: 29373729, PMCID: PMC5827338, DOI: 10.1093/scan/nsy002.Peer-Reviewed Original Research
2017
Connectome-based predictive modeling of attention: Comparing different functional connectivity features and prediction methods across datasets
Yoo K, Rosenberg MD, Hsu WT, Zhang S, Li CR, Scheinost D, Constable RT, Chun MM. Connectome-based predictive modeling of attention: Comparing different functional connectivity features and prediction methods across datasets. NeuroImage 2017, 167: 11-22. PMID: 29122720, PMCID: PMC5845789, DOI: 10.1016/j.neuroimage.2017.11.010.Peer-Reviewed Original ResearchConnectome-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 tasksMultimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder
Scheinost D, Holmes SE, DellaGioia N, Schleifer C, Matuskey D, Abdallah CG, Hampson M, Krystal JH, Anticevic A, Esterlis I. Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder. Neuropsychopharmacology 2017, 43: 1119-1127. PMID: 28944772, PMCID: PMC5854800, DOI: 10.1038/npp.2017.229.Peer-Reviewed Original ResearchConceptsMajor depressive disorderAnterior cingulate cortexIntrinsic functional connectivityMedial prefrontal cortexFunctional connectivityLarge-scale brain networksDepressive disorderMDD groupAnatomical covarianceBrain networksUnmedicated major depressive disorderWhole-brain intrinsic functional connectivitySystem-level disorderIntrinsic connectivity distributionRegional brain structureMultiple brain networksAltered connectivityCommon findingHealthy comparison participantsDepressive symptomsAltered volumeUnmedicated individualsLocal circuitryCingulate cortexDepressive symptomatologyMulti-modal analysis of functional connectivity and cerebral blood flow reveals shared and unique effects of propofol in large-scale brain networks
Qiu M, Scheinost D, Ramani R, Constable RT. Multi-modal analysis of functional connectivity and cerebral blood flow reveals shared and unique effects of propofol in large-scale brain networks. NeuroImage 2017, 148: 130-140. PMID: 28069540, PMCID: PMC5410383, DOI: 10.1016/j.neuroimage.2016.12.080.Peer-Reviewed Original ResearchConceptsCerebral blood flowIntrinsic connectivity distributionLarge-scale brain networksFunctional connectivityReduced consciousnessBlood flowBrain networksSedation conditionsWhole-brain connectivityAltered connectivityMotor networkCBF dataRs-fMRIPharmacological alterationsConnectivity differencesPropofolMultiple large-scale brain networksUnique neural correlatesBlow flowFrontoparietal networkAnesthesiaKey markersDefault modeNeural correlatesSame subjects
2016
Cingulate cortex functional connectivity predicts future relapse in alcohol dependent individuals
Zakiniaeiz Y, Scheinost D, Seo D, Sinha R, Constable RT. Cingulate cortex functional connectivity predicts future relapse in alcohol dependent individuals. NeuroImage Clinical 2016, 13: 181-187. PMID: 27981033, PMCID: PMC5144743, DOI: 10.1016/j.nicl.2016.10.019.Peer-Reviewed Original ResearchConceptsPosterior cingulate cortexAUD patientsFunctional connectivityCingulate cortexCox proportional hazards regressionChronic relapsing illnessWhole-brain investigationProportional hazards regressionFunctional connectivity differencesAlcohol-dependent patientsVoxel-wise connectivityNeutral cuesAlcohol-dependent individualsHealthy control participantsFunctional magnetic resonanceRelapse measuresHazards regressionSubsequent relapseDependent patientsInpatient treatmentAlcohol relapseFuture relapsePatientsAlcohol dependenceConnectivity differencesMultisite reliability of MR-based functional connectivity
Noble S, Scheinost D, Finn ES, Shen X, Papademetris X, McEwen SC, Bearden CE, Addington J, Goodyear B, Cadenhead KS, Mirzakhanian H, Cornblatt BA, Olvet DM, Mathalon DH, McGlashan TH, Perkins DO, Belger A, Seidman LJ, Thermenos H, Tsuang MT, van Erp TGM, Walker EF, Hamann S, Woods SW, Cannon TD, Constable RT. Multisite reliability of MR-based functional connectivity. NeuroImage 2016, 146: 959-970. PMID: 27746386, PMCID: PMC5322153, DOI: 10.1016/j.neuroimage.2016.10.020.Peer-Reviewed Original ResearchConceptsNorth American Prodrome Longitudinal StudyRight motor cortexIntrinsic connectivity distributionPosterior cingulate cortexFunctional connectivity studiesFunctional connectivity measurementsMultisite studyVoxel-wise connectivityConnectivity studiesConnectivity measuresSeed-based connectivityConnectivity analysisMotor cortexHealthy cohortCingulate cortexScan durationSingle-subject levelFcMRI dataFunctional connectivityConnectivity measurementsClinical populationsLittle dataLongitudinal studyMultisite reliabilityScanner manufacturersMethylphenidate Modulates Functional Network Connectivity to Enhance Attention
Rosenberg MD, Zhang S, Hsu WT, Scheinost D, Finn ES, Shen X, Constable RT, Li CS, Chun MM. Methylphenidate Modulates Functional Network Connectivity to Enhance Attention. Journal Of Neuroscience 2016, 36: 9547-9557. PMID: 27629707, PMCID: PMC5039242, DOI: 10.1523/jneurosci.1746-16.2016.Peer-Reviewed Original ResearchConceptsAttention-deficit/hyperactivity disorderSustained attentionWhole-brain connectivity patternsFunctional brain networksHyperactivity disorderBrain networksConnectivity patternsConnectome-based predictive modeling approachWhole-brain functional connectivity patternsWhole-brain functional connectivity networksSustained attention taskStop-signal taskDose of methylphenidateFunctional network connectivityCausal roleFunctional connectivity patternsHealthy adultsAttention taskCognitive abilitiesPromising neuromarkerNetwork strengthBehavioral predictionsADHD treatmentConnectivity signaturesFunctional connectivity networksFluctuations in Global Brain Activity Are Associated With Changes in Whole-Brain Connectivity of Functional Networks
Scheinost D, Tokoglu F, Shen X, Finn ES, Noble S, Papademetris X, Constable RT. Fluctuations in Global Brain Activity Are Associated With Changes in Whole-Brain Connectivity of Functional Networks. IEEE Transactions On Biomedical Engineering 2016, 63: 2540-2549. PMID: 27541328, PMCID: PMC5180443, DOI: 10.1109/tbme.2016.2600248.Peer-Reviewed Original ResearchConceptsGlobal brain activityResting-state networksWhole-brain connectivityBrain activityResting-state functional magnetic resonance imagingTime pointsFunctional resting-state networksFunctional magnetic resonance imagingMagnetic resonance imagingResting-state studyBrain statesRSN connectivitySensory functionSubcortical regionsResonance imagingCognitive functionCoactivation patternsUnique brain statesBrain connectivityActivity stateCritical time pointsFunctional networksSignal intensityVoxel-based methodBrain dynamics