2023
Functional Connectivity MR Imaging
Horien C, Shen X, Scheinost D, Constable R, Hampson M. Functional Connectivity MR Imaging. 2023, 521-541. DOI: 10.1007/978-3-031-10909-6_24.Peer-Reviewed Original ResearchConnectome-based machine learning models are vulnerable to subtle data manipulations
Rosenblatt M, Rodriguez R, Westwater M, Dai W, Horien C, Greene A, Constable R, Noble S, Scheinost D. Connectome-based machine learning models are vulnerable to subtle data manipulations. Patterns 2023, 4: 100756. PMID: 37521052, PMCID: PMC10382940, DOI: 10.1016/j.patter.2023.100756.Peer-Reviewed Original ResearchData manipulationNoise attacksPrediction performanceMachine learning modelsManipulated dataLearning modelHigh trustworthinessConnectome dataTrustworthinessAttacksModel performancePredictive modelDownstream analysisPerformanceAcademic researchMachineRobustnessModelConnectomeConnectome-based modelsFunctional connectomeManipulationWhy 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 ResearchConnectome-based predictive modeling shows sex differences in brain-based predictors of memory performance
Ju S, Horien C, Shen X, Abuwarda H, Trainer A, Constable R, Fredericks C. Connectome-based predictive modeling shows sex differences in brain-based predictors of memory performance. Frontiers In Dementia 2023, 2: 1126016. PMID: 39082002, PMCID: PMC11285565, DOI: 10.3389/frdem.2023.1126016.Peer-Reviewed Original ResearchDefault mode networkConnectome-based predictive modelingMemory performanceMemory taskMemory scoresShort-term memory performanceBrain-based predictorsShort-term memoryPosterior default mode networkAmnestic Alzheimer's diseaseRecollective memoryDMN activityMode networkVisual networkPast researchSex-specific modelsVisual circuitryAlzheimer's diseaseSex differencesMemoryDifferent circuitryTaskElevated riskMachine learning approachesNetwork activity
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 networkRobust prediction of memory and neuroticism in men and women using connectome‐based predictive modeling
Ju S, Horien C, Constable T, Fredericks C. Robust prediction of memory and neuroticism in men and women using connectome‐based predictive modeling. Alzheimer's & Dementia 2022, 18 DOI: 10.1002/alz.063015.Peer-Reviewed Original ResearchConnectome-based predictive modelingAlzheimer's diseaseRAVLT measuresFunctional MRI scansBackground Alzheimer's diseaseHealthy womenNeurobehavioral scoresHealthy subjectsHigh riskMemory performanceMRI scansBrain circuitryBrain connectivityWomenMenSexBrain connectomeDiseasePearson correlationScoresPredictorsConnectivity matrixBrain-based predictorsBehavioral measuresSubjectsFunctional network properties derived from wide-field calcium imaging differ with wakefulness and across cell type
O’Connor D, Mandino F, Shen X, Horien C, Ge X, Herman P, Hyder F, Crair M, Papademetris X, Lake E, Constable. Functional network properties derived from wide-field calcium imaging differ with wakefulness and across cell type. NeuroImage 2022, 264: 119735. PMID: 36347441, PMCID: PMC9808917, DOI: 10.1016/j.neuroimage.2022.119735.Peer-Reviewed Original Research
2021
Sex differences in connectivity in the default mode network in healthy aging adults
Ficek B, Horien C, Lacadie C, Shen X, Scheinost D, Constable T, Fredericks C. Sex differences in connectivity in the default mode network in healthy aging adults. Alzheimer's & Dementia 2021, 17 DOI: 10.1002/alz.056050.Peer-Reviewed Original ResearchIntrinsic connectivity distributionDefault mode networkAlzheimer's diseaseHealthy aging adultsElevated riskAging AdultsLarge cross-sectional studyPosterior default mode networkSex differencesMode networkCross-sectional cohortCross-sectional studyPreclinical Alzheimer's diseaseSymptomatic Alzheimer's diseaseResting-state scansSex-based differencesAnterior nodeAD showDMN connectivityHealthy adultsFunctional MRI dataNormal individualsResults FemalesZ-scoreFunctional connectivityAssociations Between Trauma Exposure, Internalizing Symptoms, and Functional Connectivity in Youth
Sisk L, Conley M, Greene A, Horien C, Rapuano K, Rosenberg M, Scheinost D, Constable R, Casey B, Gee D. Associations Between Trauma Exposure, Internalizing Symptoms, and Functional Connectivity in Youth. Biological Psychiatry 2021, 89: s323-s324. DOI: 10.1016/j.biopsych.2021.02.806.Peer-Reviewed Original ResearchBrainhack: Developing a culture of open, inclusive, community-driven neuroscience
Gau R, Noble S, Heuer K, Bottenhorn K, Bilgin I, Yang Y, Huntenburg J, Bayer J, Bethlehem R, Rhoads S, Vogelbacher C, Borghesani V, Levitis E, Wang H, Van Den Bossche S, Kobeleva X, Legarreta J, Guay S, Atay S, Varoquaux G, Huijser D, Sandström M, Herholz P, Nastase S, Badhwar A, Dumas G, Schwab S, Moia S, Dayan M, Bassil Y, Brooks P, Mancini M, Shine J, O’Connor D, Xie X, Poggiali D, Friedrich P, Heinsfeld A, Riedl L, Toro R, Caballero-Gaudes C, Eklund A, Garner K, Nolan C, Demeter D, Barrios F, Merchant J, McDevitt E, Oostenveld R, Craddock R, Rokem A, Doyle A, Ghosh S, Nikolaidis A, Stanley O, Uruñuela E, Community T, Anousheh N, Arnatkeviciute A, Auzias G, Bachar D, Bannier E, Basanisi R, Basavaraj A, Bedini M, Bellec P, Benn R, Berluti K, Bollmann S, Bollmann S, Bradley C, Brown J, Buchweitz A, Callahan P, Chan M, Chandio B, Cheng T, Chopra S, Chung A, Close T, Combrisson E, Cona G, Constable R, Cury C, Dadi K, Damasceno P, Das S, De Vico Fallani F, DeStasio K, Dickie E, Dorfschmidt L, Duff E, DuPre E, Dziura S, Esper N, Esteban O, Fadnavis S, Flandin G, Flannery J, Flournoy J, Forkel S, Franco A, Ganesan S, Gao S, Alanis J, Garyfallidis E, Glatard T, Glerean E, Gonzalez-Castillo J, van Praag C, Greene A, Gupta G, Hahn C, Halchenko Y, Handwerker D, Hartmann T, Hayot-Sasson V, Heunis S, Hoffstaedter F, Hohmann D, Horien C, Ioanas H, Iordan A, Jiang C, Joseph M, Kai J, Karakuzu A, Kennedy D, Keshavan A, Khan A, Kiar G, Klink P, Koppelmans V, Koudoro S, Laird A, Langs G, Laws M, Licandro R, Liew S, Lipic T, Litinas K, Lurie D, Lussier D, Madan C, Mais L, L S, Manzano-Patron J, Maoutsa D, Marcon M, Margulies D, Marinato G, Marinazzo D, Markiewicz C, Maumet C, Meneguzzi F, Meunier D, Milham M, Mills K, Momi D, Moreau C, Motala A, Moxon-Emre I, Nichols T, Nielson D, Nilsonne G, Novello L, O’Brien C, Olafson E, Oliver L, Onofrey J, Orchard E, Oudyk K, Park P, Parsapoor M, Pasquini L, Peltier S, Pernet C, Pienaar R, Pinheiro-Chagas P, Poline J, Qiu A, Quendera T, Rice L, Rocha-Hidalgo J, Rutherford S, Scharinger M, Scheinost D, Shariq D, Shaw T, Siless V, Simmonite M, Sirmpilatze N, Spence H, Sprenger J, Stajduhar A, Szinte M, Takerkart S, Tam A, Tejavibulya L, de Schotten M, Thome I, da Silva L, Traut N, Uddin L, Vallesi A, VanMeter J, Vijayakumar N, di Oleggio Castello M, Vohryzek J, Vukojević J, Whitaker K, Whitmore L, Wideman S, Witt S, Xie H, Xu T, Yan C, Yeh F, Yeo B, Zuo X. Brainhack: Developing a culture of open, inclusive, community-driven neuroscience. Neuron 2021, 109: 1769-1775. PMID: 33932337, PMCID: PMC9153215, DOI: 10.1016/j.neuron.2021.04.001.Peer-Reviewed Original Research
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 imaging
2019
The 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 datasetDifferencesConnectivityChapter 4 The uniqueness of the individual functional connectome
Horien C, Scheinost D, Constable R. Chapter 4 The uniqueness of the individual functional connectome. 2019, 63-81. DOI: 10.1016/b978-0-12-813838-0.00004-2.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingIndividual differencesIndividual functional connectomesBrain functionConnectivity dataGroup-level differencesFunctional connectivity dataHuman neuroimagingBehavioral measuresFunctional connectomeMagnetic resonance imagingResonance imagingInterindividual heterogeneityNext turnConnectomeCognitionBest predictive modelNeuroimagingDifferencesParticipantsDisease