Featured Publications
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 settingsWhy 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 ResearchBrain–phenotype models fail for individuals who defy sample stereotypes
Greene AS, Shen X, Noble S, Horien C, Hahn CA, Arora J, Tokoglu F, Spann MN, Carrión CI, Barron DS, Sanacora G, Srihari VH, Woods SW, Scheinost D, Constable RT. Brain–phenotype models fail for individuals who defy sample stereotypes. Nature 2022, 609: 109-118. PMID: 36002572, PMCID: PMC9433326, DOI: 10.1038/s41586-022-05118-w.Peer-Reviewed Original ResearchConceptsBrain-phenotype relationshipsBrain functional organizationCognitive constructsIndividual differencesNeurocognitive measuresBrain activityNeurocognitive scoresStereotypical profileNeural targetsClinical interventionsNeural circuitsFunctional organizationIndividualsSuch relationshipsData-driven approachRelationshipStereotypesFunctional Connectome–Based Predictive Modeling in Autism
Horien C, Floris DL, Greene AS, Noble S, Rolison M, Tejavibulya L, O'Connor D, McPartland JC, Scheinost D, Chawarska K, Lake EMR, Constable RT. Functional Connectome–Based Predictive Modeling in Autism. Biological Psychiatry 2022, 92: 626-642. PMID: 35690495, PMCID: PMC10948028, DOI: 10.1016/j.biopsych.2022.04.008.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsThe 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
2023
Associations of physical frailty with health outcomes and brain structure in 483 033 middle-aged and older adults: a population-based study from the UK Biobank
Jiang R, Noble S, Sui J, Yoo K, Rosenblatt M, Horien C, Qi S, Liang Q, Sun H, Calhoun V, Scheinost D. Associations of physical frailty with health outcomes and brain structure in 483 033 middle-aged and older adults: a population-based study from the UK Biobank. The Lancet Digital Health 2023, 5: e350-e359. PMID: 37061351, PMCID: PMC10257912, DOI: 10.1016/s2589-7500(23)00043-2.Peer-Reviewed Original ResearchConceptsPopulation-based studyPhysical frailtyHealth-related outcomesBrain structuresMental healthHealth outcomesHealth measuresTotal white matter hyperintensitiesIndicators of frailtySeverity of frailtyLower gray matter volumePoor physical fitnessWhite matter hyperintensitiesGray matter volumeUK BiobankHealth-related measuresPoor mental healthMental health measuresDirection of associationMatter hyperintensitiesUnhealthy lifestyleEarly-life risksPsychiatric disordersNumerous confoundersPreventative strategiesA consensus protocol for functional connectivity analysis in the rat brain
Grandjean J, Desrosiers-Gregoire G, Anckaerts C, Angeles-Valdez D, Ayad F, Barrière D, Blockx I, Bortel A, Broadwater M, Cardoso B, Célestine M, Chavez-Negrete J, Choi S, Christiaen E, Clavijo P, Colon-Perez L, Cramer S, Daniele T, Dempsey E, Diao Y, Doelemeyer A, Dopfel D, Dvořáková L, Falfán-Melgoza C, Fernandes F, Fowler C, Fuentes-Ibañez A, Garin C, Gelderman E, Golden C, Guo C, Henckens M, Hennessy L, Herman P, Hofwijks N, Horien C, Ionescu T, Jones J, Kaesser J, Kim E, Lambers H, Lazari A, Lee S, Lillywhite A, Liu Y, Liu Y, López -Castro A, López-Gil X, Ma Z, MacNicol E, Madularu D, Mandino F, Marciano S, McAuslan M, McCunn P, McIntosh A, Meng X, Meyer-Baese L, Missault S, Moro F, Naessens D, Nava-Gomez L, Nonaka H, Ortiz J, Paasonen J, Peeters L, Pereira M, Perez P, Pompilus M, Prior M, Rakhmatullin R, Reimann H, Reinwald J, Del Rio R, Rivera-Olvera A, Ruiz-Pérez D, Russo G, Rutten T, Ryoke R, Sack M, Salvan P, Sanganahalli B, Schroeter A, Seewoo B, Selingue E, Seuwen A, Shi B, Sirmpilatze N, Smith J, Smith C, Sobczak F, Stenroos P, Straathof M, Strobelt S, Sumiyoshi A, Takahashi K, Torres-García M, Tudela R, van den Berg M, van der Marel K, van Hout A, Vertullo R, Vidal B, Vrooman R, Wang V, Wank I, Watson D, Yin T, Zhang Y, Zurbruegg S, Achard S, Alcauter S, Auer D, Barbier E, Baudewig J, Beckmann C, Beckmann N, Becq G, Blezer E, Bolbos R, Boretius S, Bouvard S, Budinger E, Buxbaum J, Cash D, Chapman V, Chuang K, Ciobanu L, Coolen B, Dalley J, Dhenain M, Dijkhuizen R, Esteban O, Faber C, Febo M, Feindel K, Forloni G, Fouquet J, Garza-Villarreal E, Gass N, Glennon J, Gozzi A, Gröhn O, Harkin A, Heerschap A, Helluy X, Herfert K, Heuser A, Homberg J, Houwing D, Hyder F, Ielacqua G, Jelescu I, Johansen-Berg H, Kaneko G, Kawashima R, Keilholz S, Keliris G, Kelly C, Kerskens C, Khokhar J, Kind P, Langlois J, Lerch J, López-Hidalgo M, Manahan-Vaughan D, Marchand F, Mars R, Marsella G, Micotti E, Muñoz-Moreno E, Near J, Niendorf T, Otte W, Pais-Roldán P, Pan W, Prado-Alcalá R, Quirarte G, Rodger J, Rosenow T, Sampaio-Baptista C, Sartorius A, Sawiak S, Scheenen T, Shemesh N, Shih Y, Shmuel A, Soria G, Stoop R, Thompson G, Till S, Todd N, Van Der Linden A, van der Toorn A, van Tilborg G, Vanhove C, Veltien A, Verhoye M, Wachsmuth L, Weber-Fahr W, Wenk P, Yu X, Zerbi V, Zhang N, Zhang B, Zimmer L, Devenyi G, Chakravarty M, Hess A. A consensus protocol for functional connectivity analysis in the rat brain. Nature Neuroscience 2023, 26: 673-681. PMID: 36973511, PMCID: PMC10493189, DOI: 10.1038/s41593-023-01286-8.Peer-Reviewed Original 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 networkAssociations 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 ratioArousal impacts distributed hubs modulating the integration of brain functional connectivity
Lee K, Horien C, O’Connor D, Garand-Sheridan B, Tokoglu F, Scheinost D, Lake EMR, Constable RT. Arousal impacts distributed hubs modulating the integration of brain functional connectivity. NeuroImage 2022, 258: 119364. PMID: 35690257, PMCID: PMC9341222, DOI: 10.1016/j.neuroimage.2022.119364.Peer-Reviewed Original Research
2021
Imaging and Reimagining the Mind: fMRI and Psychiatric Illness
Horien C, Constable RT, Ross DA. Imaging and Reimagining the Mind: fMRI and Psychiatric Illness. Biological Psychiatry 2021, 89: e45-e47. PMID: 33858592, PMCID: PMC8695861, DOI: 10.1016/j.biopsych.2021.02.013.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 imagingConnectome-based models can predict early symptom improvement in major depressive disorder
Ju Y, Horien C, Chen W, Guo W, Lu X, Sun J, Dong Q, Liu B, Liu J, Yan D, Wang M, Zhang L, Guo H, Zhao F, Zhang Y, Shen X, Constable RT, Li L. Connectome-based models can predict early symptom improvement in major depressive disorder. Journal Of Affective Disorders 2020, 273: 442-452. PMID: 32560939, DOI: 10.1016/j.jad.2020.04.028.Peer-Reviewed Original ResearchConceptsMajor depressive disorderSymptom improvementAntidepressant treatmentMDD patientsDepressive disorderTreatment outcomesEarly symptom improvementIndividual therapeutic responseInitial MR scansUntreated MDD patientsResting-state functional connectivity patternsFirst-line treatmentThree-month time pointTime pointsAntidepressant treatment outcomeBaseline functional connectivityHamilton Rating ScaleSeverity of depressionResting-state connectivityFunctional connectivity patternsResting-state fMRI dataDifferent time pointsTherapeutic responseClinical practiceFunctional brain networks
2019
Regions and Connections: Complementary Approaches to Characterize Brain Organization and Function
Horien C, Greene AS, Constable RT, Scheinost D. Regions and Connections: Complementary Approaches to Characterize Brain Organization and Function. The Neuroscientist 2019, 26: 117-133. PMID: 31304866, PMCID: PMC7079335, DOI: 10.1177/1073858419860115.Peer-Reviewed Original ResearchTen simple rules for predictive modeling of individual differences in neuroimaging
Scheinost D, Noble S, Horien C, Greene AS, Lake EM, Salehi M, Gao S, Shen X, O’Connor D, Barron DS, Yip SW, Rosenberg MD, Constable RT. Ten simple rules for predictive modeling of individual differences in neuroimaging. NeuroImage 2019, 193: 35-45. PMID: 30831310, PMCID: PMC6521850, DOI: 10.1016/j.neuroimage.2019.02.057.Peer-Reviewed Original Research
2017
Considering factors affecting the connectome-based identification process: Comment on Waller et al.
Horien C, Noble S, Finn ES, Shen X, Scheinost D, Constable RT. Considering factors affecting the connectome-based identification process: Comment on Waller et al. NeuroImage 2017, 169: 172-175. PMID: 29253655, PMCID: PMC5856612, DOI: 10.1016/j.neuroimage.2017.12.045.Peer-Reviewed Original Research