{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T17:24:50Z","timestamp":1786123490490,"version":"build-2736575974"},"reference-count":59,"publisher":"American Medical Association (AMA)","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JAMA Netw Open"],"abstract":"\n Importance<\/jats:title>\n Brain maturation varies between individuals, particularly during dynamic developmental periods such as adolescence. Directly assessing the differences in longitudinal trajectories can reveal deviations from normative patterns.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n To ascertain the association of longitudinal change in brain volumes with birth weight, gestational age, and longitudinal changes in psychopathology.<\/jats:p>\n <\/jats:sec>\n \n Design, Setting, and Participants<\/jats:title>\n In this cohort study, cross-sectional and longitudinal normative models were developed for brain volumes from the first 2 neuroimaging data collection time points (baseline: 2016-2018; follow-up: 2019-2021) of the Adolescent Brain Cognitive Development (ABCD) Study, an ongoing community-based longitudinal cohort study at 21 US sites. Longitudinal models indexed an individual\u2019s expected brain volume at follow-up, conditioned on their baseline measurement, and thus were conditional-longitudinal models. Split-half subsets on demographically matched samples were used to fit the models. ABCD Study participants were recruited through the US school systems. Exclusion criteria included severe medical conditions that interfered with the study protocols. The present analysis further excluded the sample based on imaging quality flags and missing data. Data analysis was performed between May 2024 and August 2025.<\/jats:p>\n <\/jats:sec>\n \n Exposures<\/jats:title>\n Birth weight and gestational age derived from parent-reported questionnaires. General psychopathology and subfactor scores were calculated using a bifactor model.<\/jats:p>\n <\/jats:sec>\n \n Main Outcomes and Measures<\/jats:title>\n Brain volumes and change in volume between time points 1 (baseline) and 2 (follow-up). Cross-sectional and longitudinal centiles were used to quantify deviations in volumes.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n The sample included 10 830 ABCD Study participants with neuroimaging data collected at baseline (mean [SD] age, 9.9 [0.62] years; 5609 males [51.8%]) and 7262 with data collected at follow-up (mean [SD] age, 12.0 [0.65] years; 3875 males [53.4%]). Longitudinal centiles were sensitive to individual-specific changes in brain volumes. Lower birth weight was associated with lower longitudinal centiles, suggesting larger decreases in brain volumes over time (n = 27 regions, \u03b2 range\u2009=\u20090.030-0.083). Lower longitudinal centiles were associated with greater increases in psychopathology, suggesting decreasing brain volumes with increasing psychopathology scores (n =\u200937 regions, \u03b2 range\u2009=\u2009\u22120.061 to \u22120.031). Changes in psychopathology were not associated with brain volumes at either time point when indexed by cross-sectional centiles.<\/jats:p>\n <\/jats:sec>\n \n Conclusions and Relevance<\/jats:title>\n In this cohort study, conditional-longitudinal models captured individual-level deviations from expected growth trajectories, providing information beyond static positions on a growth curve to assess differences in maturation. Robust associations were observed between individual trajectory deviations, birth weight, and longitudinally assessed mental health symptoms. Conditional-longitudinal models hold promise for applications across psychiatric neuroscience, from development to aging.<\/jats:p>\n <\/jats:sec>","DOI":"10.1001\/jamanetworkopen.2026.27643","type":"journal-article","created":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T15:30:20Z","timestamp":1786116620000},"page":"e2627643","source":"Crossref","is-referenced-by-count":0,"title":["Perinatal Factors and Neuroimaging Changes for Brain Maturation Among Adolescents"],"prefix":"10.1001","volume":"9","author":[{"given":"Eren","family":"Kafadar","sequence":"first","affiliation":[{"name":"Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia"},{"name":"Department of Child and Adolescent Psychiatry and Behavioral Science, The Children\u2019s Hospital of Philadelphia (CHOP), Philadelphia, Pennsylvania"},{"name":"Lifespan Brain Institute of CHOP and Penn, Philadelphia, Pennsylvania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Margaret","family":"Gardner","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia"},{"name":"Department of Child and Adolescent Psychiatry and Behavioral Science, The Children\u2019s Hospital of Philadelphia (CHOP), Philadelphia, Pennsylvania"},{"name":"Lifespan Brain Institute of CHOP and Penn, Philadelphia, Pennsylvania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lena","family":"Dorfschmidt","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia"},{"name":"Department of Child and Adolescent Psychiatry and Behavioral Science, The Children\u2019s Hospital of Philadelphia (CHOP), Philadelphia, Pennsylvania"},{"name":"Lifespan Brain Institute of CHOP and Penn, Philadelphia, Pennsylvania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonathan A.","family":"Berken","sequence":"additional","affiliation":[{"name":"Lifespan Brain Institute of CHOP and Penn, Philadelphia, Pennsylvania"},{"name":"Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia"},{"name":"Division of Neonatology, Department of Pediatrics, The Children\u2019s Hospital of Philadelphia, Philadelphia, Pennsylvania"},{"name":"Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, The Children\u2019s Hospital of Philadelphia, Philadelphia, Pennsylvania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Audrey C.","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia"},{"name":"Lifespan Brain Institute of CHOP and Penn, Philadelphia, Pennsylvania"},{"name":"Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kevin Y.","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia"},{"name":"Department of Child and Adolescent Psychiatry and Behavioral Science, The Children\u2019s Hospital of Philadelphia (CHOP), Philadelphia, Pennsylvania"},{"name":"Lifespan Brain Institute of CHOP and Penn, Philadelphia, Pennsylvania"},{"name":"Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard A. I.","family":"Bethlehem","sequence":"additional","affiliation":[{"name":"Department of Psychology, University of Cambridge, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sara B.","family":"DeMauro","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia"},{"name":"Division of Neonatology, Department of Pediatrics, The Children\u2019s Hospital of Philadelphia, Philadelphia, Pennsylvania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ran","family":"Barzilay","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia"},{"name":"Department of Child and Adolescent Psychiatry and Behavioral Science, The Children\u2019s Hospital of Philadelphia (CHOP), Philadelphia, Pennsylvania"},{"name":"Lifespan Brain Institute of CHOP and Penn, Philadelphia, Pennsylvania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Varun","family":"Warrier","sequence":"additional","affiliation":[{"name":"Department of Psychology, University of Cambridge, Cambridge, United Kingdom"},{"name":"Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tyler M.","family":"Moore","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia"},{"name":"Lifespan Brain Institute of CHOP and Penn, Philadelphia, Pennsylvania"},{"name":"Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jakob","family":"Seidlitz","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia"},{"name":"Department of Child and Adolescent Psychiatry and Behavioral Science, The Children\u2019s Hospital of Philadelphia (CHOP), Philadelphia, Pennsylvania"},{"name":"Lifespan Brain Institute of CHOP and Penn, Philadelphia, Pennsylvania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heather H.","family":"Burris","sequence":"additional","affiliation":[{"name":"Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia"},{"name":"Division of Neonatology, Department of Pediatrics, The Children\u2019s Hospital of Philadelphia, Philadelphia, Pennsylvania"},{"name":"Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia"},{"name":"Department of Obstetrics and Gynecology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia"},{"name":"Associate Editor, JAMA Network Open"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Theodore D.","family":"Satterthwaite","sequence":"additional","affiliation":[{"name":"Lifespan Brain Institute of CHOP and Penn, Philadelphia, Pennsylvania"},{"name":"Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Russell T.","family":"Shinohara","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia"},{"name":"Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia"},{"name":"Center for Artificial Intelligence and Data Science for Integrated Diagnostics, University of Pennsylvania, Philadelphia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aaron F.","family":"Alexander-Bloch","sequence":"additional","affiliation":[{"name":"Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia"},{"name":"Department of Child and Adolescent Psychiatry and Behavioral Science, The Children\u2019s Hospital of Philadelphia (CHOP), Philadelphia, Pennsylvania"},{"name":"Lifespan Brain Institute of CHOP and Penn, Philadelphia, Pennsylvania"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10","published-online":{"date-parts":[[2026,8,7]]},"reference":[{"issue":"7906","key":"zoi260758r1","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1038\/s41586-022-04554-y","article-title":"Brain charts for the human lifespan.","volume":"604","author":"Bethlehem","year":"2022","journal-title":"Nature"},{"key":"zoi260758r2","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.85082","article-title":"Evidence for embracing normative modeling.","volume":"12","author":"Rutherford","year":"2023","journal-title":"Elife"},{"issue":"20","key":"zoi260758r4","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2216798120","article-title":"Mapping human brain charts cross-sectionally and longitudinally.","volume":"120","author":"Di Biase","year":"2023","journal-title":"Proc Natl Acad Sci U S A"},{"issue":"3","key":"zoi260758r5","doi-asserted-by":"publisher","first-page":"e211","DOI":"10.1016\/S2589-7500(23)00250-9","article-title":"Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation.","volume":"6","author":"Ge","year":"2024","journal-title":"Lancet Digit Health"},{"key":"zoi260758r6","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.95823.4","article-title":"Using normative models pre-trained on cross-sectional data to evaluate intra-individual longitudinal changes in neuroimaging data.","volume":"13","author":"Rehak Buckova","year":"2025","journal-title":"Elife"},{"issue":"5","key":"zoi260758r7","doi-asserted-by":"publisher","first-page":"2069","DOI":"10.1214\/009053606000000623","article-title":"Conditional growth charts.","volume":"34","author":"Wei","year":"2006","journal-title":"Ann Stat"},{"issue":"5","key":"zoi260758r8","doi-asserted-by":"publisher","first-page":"382","DOI":"10.3109\/03014460.2012.694475","article-title":"The development of growth references and growth charts.","volume":"39","author":"Cole","year":"2012","journal-title":"Ann Hum Biol"},{"key":"zoi260758r9","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.dcn.2018.03.001","article-title":"The Adolescent Brain Cognitive Development (ABCD) Study: imaging acquisition across 21 sites.","volume":"32","author":"Casey","year":"2018","journal-title":"Dev Cogn Neurosci"},{"issue":"6","key":"zoi260758r10","doi-asserted-by":"publisher","first-page":"896","DOI":"10.1016\/j.jpeds.2009.12.052","article-title":"Effects of gestational age and birth weight on brain volumes in healthy 9 year-old children.","volume":"156","author":"van Soelen","year":"2010","journal-title":"J Pediatr"},{"issue":"5","key":"zoi260758r11","doi-asserted-by":"publisher","first-page":"578","DOI":"10.1016\/j.ejpn.2014.04.004","article-title":"Brain volumes and cognitive function in very-low-birth-weight (VLBW) young adults.","volume":"18","author":"Bjuland","year":"2014","journal-title":"Eur J Paediatr Neurol"},{"key":"zoi260758r12","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1016\/j.neuroimage.2017.09.039","article-title":"Volumetric grey matter alterations in adolescents and adults born very preterm suggest accelerated brain maturation.","volume":"163","author":"Karolis","year":"2017","journal-title":"Neuroimage"},{"key":"zoi260758r13","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2021.102776","article-title":"Birth weight is associated with brain tissue volumes seven decades later but not with MRI markers of brain ageing.","volume":"31","author":"Wheater","year":"2021","journal-title":"Neuroimage Clin"},{"issue":"1","key":"zoi260758r14","doi-asserted-by":"publisher","first-page":"12446","DOI":"10.1038\/s41598-023-39663-9","article-title":"Size at birth predicts later brain volumes.","volume":"13","author":"Nivins","year":"2023","journal-title":"Sci Rep"},{"issue":"1","key":"zoi260758r15","doi-asserted-by":"publisher","first-page":"696","DOI":"10.1038\/s41467-020-14334-9","article-title":"Tracking regional brain growth up to age 13 in children born term and very preterm.","volume":"11","author":"Thompson","year":"2020","journal-title":"Nat Commun"},{"issue":"4","key":"zoi260758r16","doi-asserted-by":"publisher","first-page":"1526","DOI":"10.1093\/brain\/awad348","article-title":"Cortical growth from infancy to adolescence in preterm and term-born children.","volume":"147","author":"Kelly","year":"2024","journal-title":"Brain"},{"issue":"1","key":"zoi260758r18","doi-asserted-by":"publisher","first-page":"8269","DOI":"10.1038\/s41467-025-63967-1","article-title":"Heterogeneous, temporally consistent, and plastic brain development after preterm birth.","volume":"16","author":"Thalhammer","year":"2025","journal-title":"Nat Commun"},{"issue":"9","key":"zoi260758r19","doi-asserted-by":"publisher","first-page":"923","DOI":"10.1001\/archgenpsychiatry.2010.100","article-title":"Birth weight, schizophrenia, and adult mental disorder: is risk confined to the smallest babies?","volume":"67","author":"Abel","year":"2010","journal-title":"Arch Gen Psychiatry"},{"issue":"5","key":"zoi260758r20","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1007\/s10802-021-00859-0","article-title":"Birth weight and childhood psychopathology in the ABCD cohort: association is strongest for attention problems and is moderated by sex.","volume":"50","author":"Dooley","year":"2022","journal-title":"Res Child Adolesc Psychopathol"},{"issue":"10","key":"zoi260758r21","doi-asserted-by":"publisher","first-page":"2067","DOI":"10.1007\/s00787-022-02045-z","article-title":"The persistent effects of foetal growth on child and adolescent mental health: longitudinal evidence from a large population-based cohort.","volume":"32","author":"Dooley","year":"2023","journal-title":"Eur Child Adolesc Psychiatry"},{"issue":"2","key":"zoi260758r22","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1177\/07067437251389872","article-title":"Preterm birth and risk of psychiatric disorders: a register-linkage cohort study: liens entre la naissance pr\u00e9matur\u00e9e et le risque de troubles psychiatriques: une \u00e9tude de cohorte avec couplage de registres.","volume":"71","author":"Balit","year":"2026","journal-title":"Can J Psychiatry"},{"issue":"8043","key":"zoi260758r23","doi-asserted-by":"publisher","first-page":"719","DOI":"10.1038\/s41586-024-08260-9","article-title":"Study design features increase replicability in brain-wide association studies.","volume":"636","author":"Kang","year":"2024","journal-title":"Nature"},{"issue":"12","key":"zoi260758r24","doi-asserted-by":"publisher","first-page":"947","DOI":"10.1038\/nrn2513","article-title":"Why do many psychiatric disorders emerge during adolescence?","volume":"9","author":"Paus","year":"2008","journal-title":"Nat Rev Neurosci"},{"issue":"12","key":"zoi260758r25","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1097\/00004583-201012000-00005","article-title":"Neurobiology of the adolescent brain and behavior: implications for substance use disorders.","volume":"49","author":"Casey","year":"2010","journal-title":"J Am Acad Child Adolesc Psychiatry"},{"issue":"7","key":"zoi260758r26","doi-asserted-by":"publisher","first-page":"677","DOI":"10.1037\/abn0000601","article-title":"Criterion validity and relationships between alternative hierarchical dimensional models of general and specific psychopathology.","volume":"129","author":"Moore","year":"2020","journal-title":"J Abnorm Psychol"},{"issue":"8","key":"zoi260758r27","doi-asserted-by":"publisher","first-page":"895","DOI":"10.1016\/j.jaac.2023.02.002","article-title":"Brain structure relations with psychopathology trajectories in the ABCD Study.","volume":"62","author":"Romer","year":"2023","journal-title":"J Am Acad Child Adolesc Psychiatry"},{"issue":"6","key":"zoi260758r28","doi-asserted-by":"publisher","DOI":"10.1038\/tp.2016.111","article-title":"Trajectories of adolescent conduct problems in relation to cortical thickness development: a longitudinal MRI study.","volume":"6","author":"Oostermeijer","year":"2016","journal-title":"Transl Psychiatry"},{"issue":"9","key":"zoi260758r29","doi-asserted-by":"publisher","first-page":"994","DOI":"10.1111\/jcpp.12895","article-title":"Emerging depression in adolescence coincides with accelerated frontal cortical thinning.","volume":"59","author":"Bos","year":"2018","journal-title":"J Child Psychol Psychiatry"},{"issue":"3","key":"zoi260758r30","doi-asserted-by":"publisher","first-page":"968","DOI":"10.1016\/j.neuroimage.2006.01.021","article-title":"An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.","volume":"31","author":"Desikan","year":"2006","journal-title":"Neuroimage"},{"issue":"3","key":"zoi260758r31","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1016\/S0896-6273(02)00569-X","article-title":"Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain.","volume":"33","author":"Fischl","year":"2002","journal-title":"Neuron"},{"issue":"9946","key":"zoi260758r33","doi-asserted-by":"publisher","first-page":"857","DOI":"10.1016\/S0140-6736(14)60932-6","article-title":"International standards for newborn weight, length, and head circumference by gestational age and sex: the Newborn Cross-Sectional Study of the INTERGROWTH-21st Project.","volume":"384","author":"Villar","year":"2014","journal-title":"Lancet"},{"issue":"9","key":"zoi260758r34","doi-asserted-by":"publisher","first-page":"524","DOI":"10.1038\/s41576-022-00470-z","article-title":"Polygenic scores in biomedical research.","volume":"23","author":"Kullo","year":"2022","journal-title":"Nat Rev Genet"},{"issue":"1","key":"zoi260758r35","doi-asserted-by":"publisher","first-page":"1776","DOI":"10.1038\/s41467-019-09718-5","article-title":"Polygenic prediction via Bayesian regression and continuous shrinkage priors.","volume":"10","author":"Ge","year":"2019","journal-title":"Nat Commun"},{"issue":"5","key":"zoi260758r36","doi-asserted-by":"publisher","first-page":"804","DOI":"10.1038\/s41588-019-0403-1","article-title":"Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors.","volume":"51","author":"Warrington","year":"2019","journal-title":"Nat Genet"},{"issue":"3","key":"zoi260758r37","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1007\/s10654-019-00502-9","article-title":"The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia: design, results and future prospects.","volume":"34","author":"Middeldorp","year":"2019","journal-title":"Eur J Epidemiol"},{"issue":"3","key":"zoi260758r38","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1111\/j.1467-9876.2005.00510.x","article-title":"Generalized additive models for location, scale and shape.","volume":"54","author":"Rigby","year":"2005","journal-title":"J R Stat Soc Ser C Appl Stat"},{"issue":"1","key":"zoi260758r42","doi-asserted-by":"publisher","first-page":"103.e1","DOI":"10.1016\/j.ajog.2016.01.004","article-title":"Preterm neonatal morbidity and mortality by gestational age: a contemporary cohort.","volume":"215","author":"Manuck","year":"2016","journal-title":"Am J Obstet Gynecol"},{"key":"zoi260758r43","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.cortex.2015.12.001","article-title":"Cortical trajectories during adolescence in preterm born teenagers with very low birthweight.","volume":"75","author":"Rimol","year":"2016","journal-title":"Cortex"},{"issue":"12","key":"zoi260758r44","doi-asserted-by":"publisher","first-page":"1149","DOI":"10.1001\/jamapediatrics.2020.2991","article-title":"Association of gestational age at birth with brain morphometry.","volume":"174","author":"El Marroun","year":"2020","journal-title":"JAMA Pediatr"},{"issue":"1","key":"zoi260758r45","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1186\/s12916-022-02627-3","article-title":"Lower gestational age is associated with lower cortical volume and cognitive and educational performance in adolescence.","volume":"20","author":"Ma","year":"2022","journal-title":"BMC Med"},{"issue":"2","key":"zoi260758r46","doi-asserted-by":"publisher","DOI":"10.1016\/j.xhgg.2022.100091","article-title":"Stability of polygenic scores across discovery genome-wide association studies.","volume":"3","author":"Schultz","year":"2022","journal-title":"HGG Adv"},{"issue":"1","key":"zoi260758r47","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1093\/emph\/eoad019","article-title":"Low birthweight is associated with epigenetic age acceleration in the first 3 years of life.","volume":"11","author":"Quinn","year":"2023","journal-title":"Evol Med Public Health"},{"issue":"10","key":"zoi260758r48","doi-asserted-by":"publisher","first-page":"847","DOI":"10.1016\/j.tins.2023.07.007","article-title":"A critical period plasticity framework for the sensorimotor-association axis of cortical neurodevelopment.","volume":"46","author":"Larsen","year":"2023","journal-title":"Trends Neurosci"},{"issue":"4","key":"zoi260758r49","doi-asserted-by":"publisher","first-page":"998","DOI":"10.1007\/s11682-019-00057-z","article-title":"Longitudinal growth of the basal ganglia and thalamus in very preterm children.","volume":"14","author":"Loh","year":"2020","journal-title":"Brain Imaging Behav"},{"issue":"8","key":"zoi260758r50","doi-asserted-by":"publisher","first-page":"1772","DOI":"10.1038\/s41593-025-01991-6","article-title":"Human thalamocortical structural connectivity develops in line with a hierarchical axis of cortical plasticity.","volume":"28","author":"Sydnor","year":"2025","journal-title":"Nat Neurosci"},{"issue":"9","key":"zoi260758r51","doi-asserted-by":"publisher","first-page":"1015","DOI":"10.1111\/dmcn.14213","article-title":"Executive function deficits in children born preterm or at low birthweight: a meta-analysis.","volume":"61","author":"van Houdt","year":"2019","journal-title":"Dev Med Child Neurol"},{"issue":"5","key":"zoi260758r52","doi-asserted-by":"publisher","first-page":"564","DOI":"10.1176\/appi.ajp.2013.13070920","article-title":"Structural brain development and depression onset during adolescence: a prospective longitudinal study.","volume":"171","author":"Whittle","year":"2014","journal-title":"Am J Psychiatry"},{"issue":"11","key":"zoi260758r53","doi-asserted-by":"publisher","first-page":"3528","DOI":"10.1111\/cns.14286","article-title":"Emotional and behavioral problems change the development of cerebellar gray matter volume, thickness, and surface area from childhood to adolescence: a longitudinal cohort study.","volume":"29","author":"Wang","year":"2023","journal-title":"CNS Neurosci Ther"},{"key":"zoi260758r54","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.87992","article-title":"Multimodal neural correlates of childhood psychopathology.","volume":"13","author":"Royer","year":"2024","journal-title":"Elife"},{"issue":"1","key":"zoi260758r55","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1038\/s41398-021-01708-w","article-title":"Widespread attenuating changes in brain connectivity associated with the general factor of psychopathology in 9- and 10-year olds.","volume":"11","author":"Sripada","year":"2021","journal-title":"Transl Psychiatry"},{"issue":"4","key":"zoi260758r56","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1016\/0022-3956(82)90038-3","article-title":"Schizophrenia: caused by a fault in programmed synaptic elimination during adolescence?","volume":"17","author":"Feinberg","year":"1982","journal-title":"J Psychiatr Res"},{"issue":"3","key":"zoi260758r57","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1097\/YCO.0000000000000696","article-title":"Abnormal synaptic pruning during adolescence underlying the development of psychotic disorders.","volume":"34","author":"Germann","year":"2021","journal-title":"Curr Opin Psychiatry"},{"issue":"3","key":"zoi260758r58","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1136\/adc.51.3.170","article-title":"Clinical longitudinal standards for height, weight, height velocity, weight velocity, and stages of puberty.","volume":"51","author":"Tanner","year":"1976","journal-title":"Arch Dis Child"},{"issue":"8","key":"zoi260758r59","doi-asserted-by":"publisher","first-page":"1787","DOI":"10.1038\/s41593-025-01990-7","article-title":"Addressing artifactual bias in large, automated MRI analyses of brain development.","volume":"28","author":"Elyounssi","year":"2025","journal-title":"Nat Neurosci"},{"key":"zoi260758r17","first-page":"RP86812","article-title":"Fetal influence on the human brain through the lifespan.","volume-title":"Elife","author":"Walhovd","year":"2024"},{"key":"zoi260758r3","doi-asserted-by":"crossref","unstructured":"Dorfschmidt? L, White? S, Gardner? M, . Charting structural brain asymmetry across the human lifespan.? bioRxiv. Preprint posted online July 24, 2025. doi:10.1101\/2025.07.21.665924?","DOI":"10.1101\/2025.07.21.665924"},{"key":"zoi260758r32","unstructured":"Hafen? R. growthstandards: Anthropometric growth standard calculations. 2025. Accessed July 20, 2026. https:\/\/ki-tools.github.io\/growthstandards\/"},{"key":"zoi260758r39","unstructured":"Cordova? M, Doyle? O, Conan? G, . ABCD Reproducible Matched Samples (ARMS) software. October 5, 2020. Accessed August 22, 2025. https:\/\/osf.io\/7xn4f\/"},{"key":"zoi260758r40","doi-asserted-by":"crossref","unstructured":"Feczko? E, Conan? G, Marek? S, . Adolescent Brain Cognitive Development (ABCD) community MRI collection and utilities.? bioRxiv. Preprint posted online July 11, 2021. doi:10.1101\/2021.07.09.451638?","DOI":"10.1101\/2021.07.09.451638"},{"key":"zoi260758r41","doi-asserted-by":"crossref","unstructured":"Mowinckel? AM, Vidal-Pi\u00f1eiro? D. Visualisation of brain statistics with R-packages ggseg and ggseg3d.? arXiv. Preprint posted online December 17, 2019.","DOI":"10.1177\/2515245920928009"}],"container-title":["JAMA Network Open"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/jamanetwork.com\/journals\/jamanetworkopen\/articlepdf\/2852538\/kafadar_2026_oi_260758_1785443422.32389.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T15:30:22Z","timestamp":1786116622000},"score":1,"resource":{"primary":{"URL":"https:\/\/jamanetwork.com\/journals\/jamanetworkopen\/fullarticle\/2852538"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,7]]},"references-count":59,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2026,8,3]]}},"URL":"https:\/\/doi.org\/10.1001\/jamanetworkopen.2026.27643","relation":{},"ISSN":["2574-3805"],"issn-type":[{"value":"2574-3805","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,7]]}}}