2024
More reliable biomarkers and more accurate prediction for mental disorders using a label-noise filtering-based dimensional prediction method
Xing Y, van Erp T, Pearlson G, Kochunov P, Calhoun V, Du Y. More reliable biomarkers and more accurate prediction for mental disorders using a label-noise filtering-based dimensional prediction method. IScience 2024, 27: 109319. PMID: 38482500, PMCID: PMC10933544, DOI: 10.1016/j.isci.2024.109319.Peer-Reviewed Original ResearchDiagnosis of mental disordersMental disordersDiagnostic labelsIntegration of neuroimagingSchizophrenia patientsNeuroimaging measuresNeuroimaging perspectiveFMRI dataStable abnormalitiesNeuroimagingDisordersHealthy controlsIndependent subjectsSchizophreniaFMRIDimensional predictionsSubjectsAccurate diagnosisClassification accuracy
2022
Brain-behavior relationships of simulated naturalistic automobile driving under the influence of acute cannabis intoxication: A double-blind, placebo-controlled study
Meda S, Stevens M, Boer E, Boyle C, Book G, Ward N, Pearlson G. Brain-behavior relationships of simulated naturalistic automobile driving under the influence of acute cannabis intoxication: A double-blind, placebo-controlled study. 2022 DOI: 10.26828/cannabis.2022.02.000.32.Peer-Reviewed Original ResearchBrain-behavior relationshipsEffects of cannabisFunctional MRICar followingMotion-sensitive visual cortexSpecific driving skillsInferior frontal gyrusSuperior temporal gyrusFrequent cannabis usersComplex everyday activitiesGroup independent component analysisInfluence of cannabisAcute cannabis intoxicationBehavioral factorsKey brain areasIndependent component analysisFrontal gyrusDriving skillsBehavior factorsTemporal gyrusDifferent driving behaviorsSafe overtakingCannabis usersConnectivity differencesFMRI data
2015
Identifying Brain Dynamic Network States VIA GIG-ICA: Application to Schizophrenia, Bipolar and Schizoaffective Disorders
Du Y, Pearlson G, He H, Wu L, Chen J, Calhoun V. Identifying Brain Dynamic Network States VIA GIG-ICA: Application to Schizophrenia, Bipolar and Schizoaffective Disorders. 2015, 478-481. DOI: 10.1109/isbi.2015.7163915.Peer-Reviewed Original ResearchFunctional connectivity statesSchizoaffective disorderBipolar disorderSAD patientsDynamic functional networksFunctional networksConnectivity statesResting-state fMRI dataBP patientsHealthy controlsPatientsSZ patientsFunctional connectivitySimilar symptomsFMRI dataDisordersSchizophreniaMental diseasesSignificant differences