{"doi":"10.1073/pnas.2216798120","title":"Mapping human brain charts cross-sectionally and longitudinally","abstract":"<jats:p>Brain scans acquired across large, age-diverse cohorts have facilitated recent progress in establishing normative brain aging charts. Here, we ask the critical question of whether cross-sectional estimates of age-related brain trajectories resemble those directly measured from longitudinal data. We show that age-related brain changes inferred from cross-sectionally mapped brain charts can substantially underestimate actual changes measured longitudinally. We further find that brain aging trajectories vary markedly between individuals and are difficult to predict with population-level age trends estimated cross-sectionally. Prediction errors relate modestly to neuroimaging confounds and lifestyle factors. Our findings provide explicit evidence for the importance of longitudinal measurements in ascertaining brain development and aging trajectories.</jats:p>","journal":"Proceedings of the National Academy of Sciences","year":2023,"id":628668,"datarank":0.7050720548688626,"base_score":4.700480365792417,"endowment":4.700480365792417,"self_citation_contribution":0.7050720548688626,"citation_network_contribution":0.0,"self_endowment_contribution":0.7050720548688626,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":109,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":34919,"name":"Ye Ella Tian","orcid":"0000-0003-3107-5550","position":1,"is_corresponding":false},{"id":52342,"name":"Richard A. 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Here, we ask the critical question of whether cross-sectional estimates of age-related brain trajectories resemble those directly measured from longitudinal data. We show that age-related brain changes inferred from cross-sectionally mapped brain charts can substantially underestimate actual changes measured longitudinally. We further find that brain aging trajectories vary markedly between individuals and are difficult to predict with population-level age trends estimated cross-sectionally. Prediction errors relate modestly to neuroimaging confounds and lifestyle factors. 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