2024
Neurodevelopmental subtypes of functional brain organization in the ABCD study using a rigorous analytic framework
DeRosa J, Friedman N, Calhoun V, Banich M. Neurodevelopmental subtypes of functional brain organization in the ABCD study using a rigorous analytic framework. NeuroImage 2024, 299: 120827. PMID: 39245397, DOI: 10.1016/j.neuroimage.2024.120827.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentBrainChildChild DevelopmentCognitionConnectomeFemaleHumansMagnetic Resonance ImagingMaleReproducibility of ResultsConceptsResting-state functional connectivityAdolescent Brain Cognitive DevelopmentIndividual’s resting-state functional connectivityAdolescent Brain Cognitive Development StudyFunctional brain organizationMental health profilesMental health characteristicsRsFC dataBrain organizationFunctional connectivityDevelopmental trajectoriesChildren aged 9Emotional functioningCognitive developmentLate childhoodAged 9SubtypesAdolescentsHealth characteristicsHealth profileChildhoodSearching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities
Fu Z, Batta I, Wu L, Abrol A, Agcaoglu O, Salman M, Du Y, Iraji A, Shultz S, Sui J, Calhoun V. Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities. NeuroImage 2024, 292: 120617. PMID: 38636639, PMCID: PMC11416721, DOI: 10.1016/j.neuroimage.2024.120617.Peer-Reviewed Original ResearchConceptsFunctional MRIStructural MRIResting-state scanSpatial similarity analysisMental health researchBrain markersDiffusion MRIAge differencesBrain featuresNeuromarkersBrain disordersYoung adult cohortBrain developmentWell-replicatedHuman brainBrainDiffusion MRI dataData-driven analysisDisordersSimilarity analysisAge cohortsGeneralizabilityPopulation-based researchAdult cohortAge-specific adaptationSMART (Splitting-Merging Assisted Reliable) Independent Component Analysis for Extracting Accurate Brain Functional Networks
He X, Calhoun V, Du Y. SMART (Splitting-Merging Assisted Reliable) Independent Component Analysis for Extracting Accurate Brain Functional Networks. Neuroscience Bulletin 2024, 40: 905-920. PMID: 38491231, DOI: 10.1007/s12264-024-01184-4.Peer-Reviewed Original ResearchConceptsIndependent component analysisFunctional magnetic resonance imagingClustering independent componentsFunctional networksIndependent component analysis methodMulti-subject fMRI dataIndependent componentsBrain functional networksFMRI dataSubject-specific functional networksFunctional magnetic resonance imaging dataOptimal model orderSmartComponent analysis
2023
Automated Interpretation of Clinical Electroencephalograms Using Artificial Intelligence
Tveit J, Aurlien H, Plis S, Calhoun V, Tatum W, Schomer D, Arntsen V, Cox F, Fahoum F, Gallentine W, Gardella E, Hahn C, Husain A, Kessler S, Kural M, Nascimento F, Tankisi H, Ulvin L, Wennberg R, Beniczky S. Automated Interpretation of Clinical Electroencephalograms Using Artificial Intelligence. JAMA Neurology 2023, 80: 805-812. PMID: 37338864, PMCID: PMC10282956, DOI: 10.1001/jamaneurol.2023.1645.Peer-Reviewed Original ResearchMeSH KeywordsAdultArtificial IntelligenceElectroencephalographyEpilepsyHumansMaleNeural Networks, ComputerReproducibility of ResultsConceptsPublishing AI modelsAI modelsArtificial intelligenceTesting data setsHuman expertsAutomated interpretationConvolutional neural network modelHuman expert level performanceElectroencephalogram data setsData setsRoutine electroencephalogramNeural network modelExpert-level performanceMulticenter diagnostic accuracy studyReference standardAbnormal EEG recordingsVideo-EEG recordingsDetection of epileptiform abnormalitiesRecords of patientsReceiver operating characteristic curveSingle-center dataArea under the receiver operating characteristic curveDevelopment dataDiagnostic accuracy studiesNetwork model