2024
Age of onset of obsessive-compulsive disorder differentially affects white matter microstructure
Vriend C, de Joode N, Pouwels P, Liu F, Otaduy M, Pastorello B, Robertson F, Ipser J, Lee S, Hezel D, van Meter P, Batistuzzo M, Hoexter M, Sheshachala K, Narayanaswamy J, Venkatasubramanian G, Lochner C, Miguel E, Reddy Y, Shavitt R, Stein D, Wall M, Simpson H, van den Heuvel O. Age of onset of obsessive-compulsive disorder differentially affects white matter microstructure. Molecular Psychiatry 2024, 29: 1033-1045. PMID: 38228890, PMCID: PMC11176057, DOI: 10.1038/s41380-023-02390-8.Peer-Reviewed Original ResearchObsessive-compulsive disorderPathophysiology of obsessive-compulsive disorderObsessive-compulsive disorder groupAge of OCD onsetOCD onsetHealthy controlsMedication-free adultsWhite matter microstructural alterationsVisual attention processesWhite matter microstructureStructural brain networksStructural connectome analysisWhite matter tractsBayesian multilevel analysisDirection of effectAttentional processesOCD individualsBrain signaturesBrain networksDiffusion MRI studiesPost hoc analysisSagittal stratumConnectome analysisMultilevel analysisStructural connectome
2023
An Evaluation of Item Harmonization Strategies Between Assessment Tools of Psychopathology in Children and Adolescents
Hoffmann M, Moore T, Axelrud L, Tottenham N, Pan P, Miguel E, Rohde L, Milham M, Satterthwaite T, Salum G. An Evaluation of Item Harmonization Strategies Between Assessment Tools of Psychopathology in Children and Adolescents. Assessment 2023, 31: 502-517. PMID: 37042304, DOI: 10.1177/10731911231163136.Peer-Reviewed Original ResearchPolygenic risk score for attention‐deficit/hyperactivity disorder and brain functional networks segregation in a community‐based sample
Sato J, Biazoli C, Bueno A, Caye A, Pan P, Santoro M, Honorato‐Mauer J, Salum G, Hoexter M, Bressan R, Jackowski A, Miguel E, Belangero S, Rohde L. Polygenic risk score for attention‐deficit/hyperactivity disorder and brain functional networks segregation in a community‐based sample. Genes Brain & Behavior 2023, 22: e12838. PMID: 36811275, PMCID: PMC10067387, DOI: 10.1111/gbb.12838.Peer-Reviewed Original ResearchConceptsCingulo-opercular networkDefault mode networkADHD-PRSAttentional networksFunctional segregationAttention-deficit/hyperactivity disorder (ADHD) symptomsAttention-deficit/hyperactivity disorderLarge-scale brain networksADHD polygenic risk scoresHyperactivity disorder symptomsSegregation of networksFunctional network segregationLongitudinal community-based cohortAttentional processesRs-fMRI dataExecutive functionHyperactivity disorderDisorder symptomsBrain networksCommunity-based sampleProbable ADHDADHDNetwork segregationPolygenic risk scoresDirection of association
2017
Association between abnormal brain functional connectivity in children and psychopathology: A study based on graph theory and machine learning
Sato J, Biazoli C, Salum G, Gadelha A, Crossley N, Vieira G, Zugman A, Picon F, Pan P, Hoexter M, Amaro E, Anés M, Moura L, Del’Aquilla M, Mcguire P, Rohde L, Miguel E, Jackowski A, Bressan R. Association between abnormal brain functional connectivity in children and psychopathology: A study based on graph theory and machine learning. The World Journal Of Biological Psychiatry 2017, 19: 119-129. PMID: 28635541, DOI: 10.1080/15622975.2016.1274050.Peer-Reviewed Original ResearchConceptsBilateral posterior temporal corticesAbnormal brain functional connectivityMental health disordersBilateral posterior cingulateBrain networksBrain functional connectivityResting-state fMRI dataPosterior temporal cortexBrain network organizationLevels of psychopathologyTemporal cortexHealth disordersTemporal polePosterior cingulateMental disordersBrain developmentFunctional connectivityBrain connectivitySignificant decreaseDisordersGraph theory measuresIndividual brain networksBiological measuresPsychopathologySubjects
2016
Connectome hubs at resting state in children and adolescents: Reproducibility and psychopathological correlation
Sato J, Biazoli C, Salum G, Gadelha A, Crossley N, Vieira G, Zugman A, Picon F, Pan P, Hoexter M, Anés M, Moura L, Del’Aquilla M, Amaro E, Mcguire P, Rohde L, Miguel E, Bressan R, Jackowski A. Connectome hubs at resting state in children and adolescents: Reproducibility and psychopathological correlation. Developmental Cognitive Neuroscience 2016, 20: 2-11. PMID: 27288820, PMCID: PMC6987719, DOI: 10.1016/j.dcn.2016.05.002.Peer-Reviewed Original ResearchConceptsAnterior medial prefrontal cortexPsychiatric symptomsLarge-scale functional networksBrain hubsMental disordersHub regionsMedial prefrontal cortexResting-state fMRIFunctional cortical networksIndependent population-based samplesRight IPSPopulation-based sampleIntraparietal sulcusBrain networksPrefrontal cortexCortical networksIntegrative regionsFunctional networksAdolescentsLow centralitySymptomsChildrenDisordersReplicabilityInteresting target
2015
Temporal stability of network centrality in control and default mode networks: Specific associations with externalizing psychopathology in children and adolescents
Sato J, Biazoli C, Salum G, Gadelha A, Crossley N, Satterthwaite T, Vieira G, Zugman A, Picon F, Pan P, Hoexter M, Anés M, Moura L, Del'aquilla M, Amaro E, McGuire P, Lacerda A, Rohde L, Miguel E, Jackowski A, Bressan R. Temporal stability of network centrality in control and default mode networks: Specific associations with externalizing psychopathology in children and adolescents. Human Brain Mapping 2015, 36: 4926-4937. PMID: 26350757, PMCID: PMC6868942, DOI: 10.1002/hbm.22985.Peer-Reviewed Original ResearchConceptsDefault mode networkChild Behavior ChecklistDynamic functional connectivity patternsHigh Risk Cohort StudyBehavior ChecklistAbnormal connectivity patternsFunctional connectivity patternsResting-state fMRIPathological mental statesCohort studyConnectivity patternsPsychiatric disordersFunctional network dynamicsGeneral psychopathologyTotal scoreMode networkNetwork maturationBrain networksMaturation indexEmotional problemsChildrenAge effectsOverall presenceSpecific associationAdolescents
2014
Age effects on the default mode and control networks in typically developing children
Sato J, Salum G, Gadelha A, Picon F, Pan P, Vieira G, Zugman A, Hoexter M, Anés M, Moura L, Del'Aquilla M, Amaro E, McGuire P, Crossley N, Lacerda A, Rohde L, Miguel E, Bressan R, Jackowski A. Age effects on the default mode and control networks in typically developing children. Journal Of Psychiatric Research 2014, 58: 89-95. PMID: 25085608, DOI: 10.1016/j.jpsychires.2014.07.004.Peer-Reviewed Original ResearchConceptsDefault mode networkMode networkYears of ageCross-sectional community sampleRight anterior insulaDefault modePosterior temporal cortexDorsal anteriorAge effectsNeurodevelopment studiesHealthy subjectsTemporal cortexPosterior cingulateState fMRI dataAnterior insulaBrain developmentSame acquisition parametersLeft posterior temporal cortexNeuronal modulesState fMRILate childhoodDevelopmental formationBrain networksCommunity sampleField of neuroimaging