2024
Cross‐cohort replicable resting‐state functional connectivity in predicting symptoms and cognition of schizophrenia
Zhao C, Jiang R, Bustillo J, Kochunov P, Turner J, Liang C, Fu Z, Zhang D, Qi S, Calhoun V. Cross‐cohort replicable resting‐state functional connectivity in predicting symptoms and cognition of schizophrenia. Human Brain Mapping 2024, 45: e26694. PMID: 38727014, PMCID: PMC11083889, DOI: 10.1002/hbm.26694.Peer-Reviewed Original ResearchConceptsFunctional magnetic resonance imagingNegative symptomsFunctional connectivityCognitive impairmentPrediction of negative symptomsResting-state functional connectivityAssociated with reduced cognitive functionDebilitating mental illnessHealthy controlsPredicting functional connectivityEarly adulthood onsetPositive symptomsNeural underpinningsSchizophreniaCognitive functionSensorimotor networkPredicting symptomsMental illnessConnectivity patternsClinical interventionsMagnetic resonance imagingAdulthood onsetSymptomsImpairmentResonance imagingCortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC
Rootes-Murdy K, Panta S, Kelly R, Romero J, Quidé Y, Cairns M, Loughland C, Carr V, Catts S, Jablensky A, Green M, Henskens F, Kiltschewskij D, Michie P, Mowry B, Pantelis C, Rasser P, Reay W, Schall U, Scott R, Watkeys O, Roberts G, Mitchell P, Fullerton J, Overs B, Kikuchi M, Hashimoto R, Matsumoto J, Fukunaga M, Sachdev P, Brodaty H, Wen W, Jiang J, Fani N, Ely T, Lorio A, Stevens J, Ressler K, Jovanovic T, van Rooij S, Federmann L, Jockwitz C, Teumer A, Forstner A, Caspers S, Cichon S, Plis S, Sarwate A, Calhoun V. Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC. Patterns 2024, 5: 100987. PMID: 39081570, PMCID: PMC11284501, DOI: 10.1016/j.patter.2024.100987.Peer-Reviewed Original ResearchPsychiatric disordersStructural neuroimaging studiesPattern of gray matterAutism spectrum disorderGray matterDepressive disorderMood disordersNeuroimaging studiesNeuroanatomical basisSubcortical regionsGM alterationsSpectrum disorderVBM analysisMental illnessGM patternsDisordersCollaborative InformaticsSchizophreniaMoodNeuroimaging Suite ToolkitAutismNeuroimagingVulnerabilityLarge-scale dataDeficits
2023
Addressing Global Environmental Challenges to Mental Health Using Population Neuroscience
Schumann G, Andreassen O, Banaschewski T, Calhoun V, Clinton N, Desrivieres S, Brandlistuen R, Feng J, Hese S, Hitchen E, Hoffmann P, Jia T, Jirsa V, Marquand A, Nees F, Nöthen M, Novarino G, Polemiti E, Ralser M, Rapp M, Schepanski K, Schikowski T, Slater M, Sommer P, Stahl B, Thompson P, Twardziok S, van der Meer D, Walter H, Westlye L, Heinz A, Lett T, Vaidya N, Serin E, Neidhart M, Jentsch M, Eils R, Taron U, Schütz T, Banks J, Meyer-Lindenberg A, Tost H, Holz N, Schwarz E, Stringaris A, Christmann N, Jansone K, Siehl S, Ask H, Fernández-Cabello S, Kjelkenes R, Tschorn M, Böttger S, Bernas A, Marr L, Feixas Viapiana G, Eiroa-Orosa F, Gallego J, Pastor A, Forstner A, Claus I, Miller A, Heilmann-Heimbach S, Boye M, Wilbertz J, Schmitt K, Petkoski S, Pitel S, Otten L, Athanasiadis A, Pearmund C, Spanlang B, Alvarez E, Sanchez M, Giner A, Renner P, Gong Y, Dai Y, Xia Y, Chang X, Liu J, Young A, Ogoh G. Addressing Global Environmental Challenges to Mental Health Using Population Neuroscience. JAMA Psychiatry 2023, 80: 1066-1074. PMID: 37610741, DOI: 10.1001/jamapsychiatry.2023.2996.Peer-Reviewed Original ResearchConceptsMental illnessMechanisms of mental illnessSymptoms of depressionEvidence-based interventionsBrain mechanismsPopulation neuroscienceSocioeconomic inequalitiesEnvironmental adversityMental healthSubstance misuseBrain healthPsychosocial effectsDigital healthCohort dataDeep phenotyping dataObjective biomarkersHealthIllnessBrainDevelopment of objective biomarkersImprove outcomesPopulation levelCOVID-19 pandemicPollution measurementsResearch strategy