2024
Inter-Modality Source Coupling: A Fully-Automated Whole-Brain Data-Driven Structure-Function Fingerprint Shows Replicable Links to Reading in a Large-Scale (N8K) Analysis
Kotoski A, Liu J, Morris R, Calhoun V. Inter-Modality Source Coupling: A Fully-Automated Whole-Brain Data-Driven Structure-Function Fingerprint Shows Replicable Links to Reading in a Large-Scale (N8K) Analysis. IEEE Transactions On Biomedical Engineering 2024, 71: 3383-3389. PMID: 38968021, PMCID: PMC11700228, DOI: 10.1109/tbme.2024.3423703.Peer-Reviewed Original ResearchReading abilityBrain structuresSchool-aged childrenResting-stateStructural magnetic resonance imagingInferior frontal areasFunctional brain changesInferior parietal lobuleHigher reading abilityFunctional connectivity patternsLow reading abilityLingual gyrusNeural basisParietal lobuleReading developmentBrain changesCognitive processesReplication linksRs-fMRICortical regionsReading scoresBrain functionCognitive growthFrontal areasConnectivity patternsLinking neuroimaging and mental health data from the ABCD Study to UrbanSat measurements of macro environmental factors
Goldblatt R, Holz N, Tate G, Sherman K, Ghebremicael S, Bhuyan S, Al-Ajlouni Y, Santillanes S, Araya G, Abad S, Herting M, Thompson W, Thapaliya B, Sapkota R, Xu J, Liu J, Schumann G, Calhoun V. Linking neuroimaging and mental health data from the ABCD Study to UrbanSat measurements of macro environmental factors. Nature Mental Health 2024, 2: 1285-1297. DOI: 10.1038/s44220-024-00318-x.Peer-Reviewed Original ResearchSymptoms of mental illnessAdolescent Brain Cognitive DevelopmentResidential addressesAdolescent Brain Cognitive Development StudyMental illnessMental healthSubject's residential addressMental health dataDevelopmental periods of childhoodChild healthHealth dataEnvironmental factorsBaseline visitPeriod of childhoodObservational studyPopulation characteristicsHealthIndividual symptomsStudy dataUrban livingIllnessNeurobehavioral researchBrain structuresCognitive developmentAdolescentsGenomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries
GarcĂa-MarĂn L, Campos A, Diaz-Torres S, Rabinowitz J, Ceja Z, Mitchell B, Grasby K, Thorp J, Agartz I, Alhusaini S, Ames D, Amouyel P, Andreassen O, Arfanakis K, Arias-Vasquez A, Armstrong N, Athanasiu L, Bastin M, Beiser A, Bennett D, Bis J, Boks M, Boomsma D, Brodaty H, Brouwer R, Buitelaar J, Burkhardt R, Cahn W, Calhoun V, Carmichael O, Chakravarty M, Chen Q, Ching C, Cichon S, Crespo-Facorro B, Crivello F, Dale A, Smith G, de Geus E, De Jager P, de Zubicaray G, Debette S, DeCarli C, Depondt C, Desrivières S, Djurovic S, Ehrlich S, Erk S, Espeseth T, Fernández G, Filippi I, Fisher S, Fleischman D, Fletcher E, Fornage M, Forstner A, Francks C, Franke B, Ge T, Goldman A, Grabe H, Green R, Grimm O, Groenewold N, Gruber O, Gudnason V, HĂĄberg A, Haukvik U, Heinz A, Hibar D, Hilal S, Himali J, Ho B, Hoehn D, Hoekstra P, Hofer E, Hoffmann W, Holmes A, Homuth G, Hosten N, Ikram M, Ipser J, Jack Jr C, Jahanshad N, Jönsson E, Kahn R, Kanai R, Klein M, Knol M, Launer L, Lawrie S, Hellard S, Lee P, LemaĂ®tre H, Li S, Liewald D, Lin H, Longstreth W, Lopez O, Luciano M, Maillard P, Marquand A, Martin N, Martinot J, Mather K, Mattay V, McMahon K, Mecocci P, Melle I, Meyer-Lindenberg A, Mirza-Schreiber N, Milaneschi Y, Mosley T, MĂĽhleisen T, MĂĽller-Myhsok B, Maniega S, Nauck M, Nho K, Niessen W, Nöthen M, Nyquist P, Oosterlaan J, Pandolfo M, Paus T, Pausova Z, Penninx B, Pike G, Psaty B, PĂĽtz B, Reppermund S, Rietschel M, Risacher S, Romanczuk-Seiferth N, Romero-Garcia R, Roshchupkin G, Rotter J, Sachdev P, Sämann P, Saremi A, Sargurupremraj M, Saykin A, Schmaal L, Schmidt H, Schmidt R, Schofield P, Scholz M, Schumann G, Schwarz E, Shen L, Shin J, Sisodiya S, Smith A, Smoller J, Soininen H, Steen V, Stein D, Stein J, Thomopoulos S, Toga A, Tordesillas-GutiĂ©rrez D, Trollor J, Valdes-Hernandez M, van ′t Ent D, van Bokhoven H, van der Meer D, van der Wee N, Vázquez-Bourgon J, Veltman D, Vernooij M, Villringer A, Vinke L, Völzke H, Walter H, Wardlaw J, Weinberger D, Weiner M, Wen W, Westlye L, Westman E, White T, Witte A, Wolf C, Yang J, Zwiers M, Ikram M, Seshadri S, Thompson P, Satizabal C, Medland S, RenterĂa M. Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries. Nature Genetics 2024, 56: 2333-2344. PMID: 39433889, PMCID: PMC12088653, DOI: 10.1038/s41588-024-01951-z.Peer-Reviewed Original ResearchSubcortical brain volumesBrain volumePolygenic scoresEffects of brain volumeAttention-deficit/hyperactivity disorderIndividuals of diverse ancestryComorbid neuropsychiatric disordersSubcortical brain structuresGenome-wide association study meta-analysesBrain substratesParticipants of European ancestryAttention-deficit/hyperactivityGene expression patternsNeuropsychiatric disordersDifferentiation time pointsBrain structuresGenomic analysisDiverse ancestryBrain developmentStudy meta-analysesGenetic variantsNeural cell typesPhenotypic varianceRisk genesAging-related processesIntegrated brain connectivity analysis with fMRI, DTI, and sMRI powered by interpretable graph neural networks
Qu G, Zhou Z, Calhoun V, Zhang A, Wang Y. Integrated brain connectivity analysis with fMRI, DTI, and sMRI powered by interpretable graph neural networks. Medical Image Analysis 2024, 103: 103570. PMID: 39253637, PMCID: PMC11383444, DOI: 10.1016/j.media.2025.103570.Peer-Reviewed Original ResearchFunctional magnetic resonance imagingDiffusion tensor imagingStructural MRIBrain connectivity analysisBrain connectivityNeural connectionsGraph neural networksStructural connectivityBrain structuresCognitive functionConnectivity analysisNeuroimaging modelsNeural networkCognitive developmentFunctional networksGray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity
Bi Y, Abrol A, Jia S, Sui J, Calhoun V. Gray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity. NeuroImage 2024, 297: 120674. PMID: 38851549, DOI: 10.1016/j.neuroimage.2024.120674.Peer-Reviewed Original ResearchFunctional network connectivityMedial prefrontal cortexBrain structuresFunctional network connectivity matricesPrefrontal cortexStructural MRINetwork connectivityGray matterSelf-attention mechanismGenerative adversarial networkDeep learning architectureBrain disordersDorsolateral prefrontal cortexResearch of schizophreniaNeural signal processingIdentified functional connectivityCross-domain analysisAttention mapsStructural biomarkersAdversarial networkLearning architectureDL-PFCICA algorithmSchizophrenia patientsHigh-dimensional fMRI dataMRI morphometry of the anterior and posterior cerebellar vermis and its relationship to sensorimotor and cognitive functions in children
Hodgdon E, Anderson R, Al Azzawi H, Wilson T, Calhoun V, Wang Y, Solis I, Greve D, Stephen J, Ciesielski K. MRI morphometry of the anterior and posterior cerebellar vermis and its relationship to sensorimotor and cognitive functions in children. Developmental Cognitive Neuroscience 2024, 67: 101385. PMID: 38713999, PMCID: PMC11096723, DOI: 10.1016/j.dcn.2024.101385.Peer-Reviewed Original ResearchConceptsLobules I-VCognitive functionCerebellar vermis volumePosterior brain structuresCerebellar vermisVI-VIIAnterior cerebellar vermisLobules VI-VIIWASI-IIEmotional processingVermis volumeNeuropsychological scoresPosterior cerebellar vermisBrain structuresDevelopmental trajectoriesMRI morphometryCerebellar anatomyPosterior vermisSensorimotorDevelopmental studiesHuman cerebellumHealthy adultsAdult volumeVermisHigh-resolution MRI
2023
F71. NETWORK OF CO-METHYLATION ASSOCIATED WITH GREY MATTER MATURATION IN HUMAN ADOLESCENCE
Jensen D, Chen J, Turner J, Stephen J, Wang Y, Wilson T, Calhoun V, Liu J. F71. NETWORK OF CO-METHYLATION ASSOCIATED WITH GREY MATTER MATURATION IN HUMAN ADOLESCENCE. European Neuropsychopharmacology 2023, 75: s258-s259. DOI: 10.1016/j.euroneuro.2023.08.455.Peer-Reviewed Original ResearchStructural MRIBrain maturationNeuronal systemsCo-methylation network analysisPeriod of brain maturationAdolescent brain developmentAdolescent brain maturationPhases of neurodevelopmentIndependent component analysisGray matterHuman brain structureGM maturationDNAm changesCo-methylation modulesPrefrontal cortexExecutive functionFrontal poleGM volumeTime pointsSubjects aged 9Brain structuresCpG sitesSynaptic pruningBrain developmentDNA methylationBeyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers
Boen R, Kaufmann T, van der Meer D, Frei O, Agartz I, Ames D, Andersson M, Armstrong N, Artiges E, Atkins J, Bauer J, Benedetti F, Boomsma D, Brodaty H, Brosch K, Buckner R, Cairns M, Calhoun V, Caspers S, Cichon S, Corvin A, Crespo-Facorro B, Dannlowski U, David F, de Geus E, de Zubicaray G, Desrivières S, Doherty J, Donohoe G, Ehrlich S, Eising E, Espeseth T, Fisher S, Forstner A, Fortaner-Uyà L, Frouin V, Fukunaga M, Ge T, Glahn D, Goltermann J, Grabe H, Green M, Groenewold N, Grotegerd D, Grøntvedt G, Hahn T, Hashimoto R, Hehir-Kwa J, Henskens F, Holmes A, Håberg A, Haavik J, Jacquemont S, Jansen A, Jockwitz C, Jönsson E, Kikuchi M, Kircher T, Kumar K, Le Hellard S, Leu C, Linden D, Liu J, Loughnan R, Mather K, McMahon K, McRae A, Medland S, Meinert S, Moreau C, Morris D, Mowry B, Mühleisen T, Nenadić I, Nöthen M, Nyberg L, Ophoff R, Owen M, Pantelis C, Paolini M, Paus T, Pausova Z, Persson K, Quidé Y, Marques T, Sachdev P, Sando S, Schall U, Scott R, Selbæk G, Shumskaya E, Silva A, Sisodiya S, Stein F, Stein D, Straube B, Streit F, Strike L, Teumer A, Teutenberg L, Thalamuthu A, Tooney P, Tordesillas-Gutierrez D, Trollor J, van ’t Ent D, van den Bree M, van Haren N, Vázquez-Bourgon J, Völzke H, Wen W, Wittfeld K, Ching C, Westlye L, Thompson P, Bearden C, Selmer K, Alnæs D, Andreassen O, Sønderby I, Group E. Beyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers. Biological Psychiatry 2023, 95: 147-160. PMID: 37661008, PMCID: PMC7615370, DOI: 10.1016/j.biopsych.2023.08.018.Peer-Reviewed Original ResearchConceptsMedial visual cortexCortical surface areaBrain differencesCortical thicknessTemporal poleVisual cortexDeletion carriersGlobal brain measuresRegional brain differencesCopy number variantsSuperior temporal cortexSomatosensory cortexBrain valuesAltered neurodevelopmentAuditory cortexGlobal differencesRegional differencesTemporal cortexNumber variantsPosterior cingulateCortexBrain structuresBrain measuresStandardized differenceNoncarriersEpigenetic associations with adolescent grey matter maturation and cognitive development
Jensen D, Chen J, Turner J, Stephen J, Wang Y, Wilson T, Calhoun V, Liu J. Epigenetic associations with adolescent grey matter maturation and cognitive development. Frontiers In Genetics 2023, 14: 1222619. PMID: 37529779, PMCID: PMC10390095, DOI: 10.3389/fgene.2023.1222619.Peer-Reviewed Original ResearchGM volume increaseGray matter maturationPatterns of brain maturationImprove cognitive performanceGray matterExecutive functionEpisodic memoryCognitive performanceCognitive testsBrain structuresProcessing speedBrain maturationCognitive AssessmentCognitive scoresBrain imagingAged 9BrainEpigenetic associationsAdolescentsLongitudinal cohortDNA methylationHuman neurodevelopmentDNA methylation of genesCytosine-phosphate-guanine (CpG) sitesBrain tissueICA-based Individualized Differential Structure Similarity Networks for Predicting Symptom Scores in Adolescents with Major Depressive Disorder
Li X, Xu M, Jiang R, Li X, Calhoun V, Zhou X, Sui J. ICA-based Individualized Differential Structure Similarity Networks for Predicting Symptom Scores in Adolescents with Major Depressive Disorder. Annual International Conference Of The IEEE Engineering In Medicine And Biology Society (EMBC) 2023, 00: 1-5. PMID: 38082692, DOI: 10.1109/embc40787.2023.10340456.Peer-Reviewed Original ResearchConceptsMajor depressive disorderGray matter volumeDepressive disorderWhole-brain structural covariance networksConnectome-based predictive modelingAdolescent MDD patientsComplex mood disorderMeasure individual differencesDefault-mode networkStructural brain alterationsStructural covariance networksHamilton Depression ScaleHamilton Anxiety ScaleSpatially constrained ICAMDD patientsMood disordersBrain alterationsMatter volumeIndividual differencesBrain structuresCovariance networksAnxiety ScaleVisual networkDepression ScaleStructure similarity networkAssociations 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 strategies
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply