{"doi":"10.1002/wcs.1389","title":"Individual differences in human brain development","abstract":"<jats:p>This article discusses recent scientific advances in the study of individual differences in human brain development. Focusing on structural neuroimaging measures of brain morphology and tissue properties, two kinds of variability are related and explored: differences across individuals of the same age and differences across age as a result of development. A recent multidimensional modeling study is explained, which was able to use brain measures to predict an individual's chronological age within about one year on average, in children, adolescents, and young adults between 3 and 20 years old. These findings reveal great regularity in the sequence of the aggregate brain state across different ages and phases of development, despite the pronounced individual differences people show on any single brain measure at any given age. Future research is suggested, incorporating additional measures of brain activity and function.<jats:italic>WIREs Cogn Sci</jats:italic>2017, 8:e1389. doi: 10.1002/wcs.1389</jats:p><jats:p>This article is categorized under:<jats:list list-type=\"explicit-label\"><jats:list-item><jats:p>Psychology &gt; Brain Function and Dysfunction</jats:p></jats:list-item><jats:list-item><jats:p>Psychology &gt; Development and Aging</jats:p></jats:list-item></jats:list></jats:p>","journal":"WIREs Cognitive Science","year":2017,"id":594219,"datarank":0.5289540786924243,"base_score":3.5263605246161616,"endowment":3.5263605246161616,"self_citation_contribution":0.5289540786924243,"citation_network_contribution":0.0,"self_endowment_contribution":0.5289540786924243,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":33,"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":1161340,"name":"Timothy T. Brown","orcid":"0000-0003-4475-1546","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Individual differences in human brain development","abstract":"<jats:p>This article discusses recent scientific advances in the study of individual differences in human brain development. Focusing on structural neuroimaging measures of brain morphology and tissue properties, two kinds of variability are related and explored: differences across individuals of the same age and differences across age as a result of development. A recent multidimensional modeling study is explained, which was able to use brain measures to predict an individual's chronological age within about one year on average, in children, adolescents, and young adults between 3 and 20 years old. These findings reveal great regularity in the sequence of the aggregate brain state across different ages and phases of development, despite the pronounced individual differences people show on any single brain measure at any given age. Future research is suggested, incorporating additional measures of brain activity and function.<jats:italic>WIREs Cogn Sci</jats:italic>2017, 8:e1389. doi: 10.1002/wcs.1389</jats:p><jats:p>This article is categorized under:<jats:list list-type=\"explicit-label\"><jats:list-item><jats:p>Psychology &gt; Brain Function and Dysfunction</jats:p></jats:list-item><jats:list-item><jats:p>Psychology &gt; Development and Aging</jats:p></jats:list-item></jats:list></jats:p>","is_dataset_classified":null,"base_score":3.5263605246161616,"endowment":3.5263605246161616,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"27906499","pmcid":"PMC5682852","openalex_id":"https://openalex.org/W2559882404","authors":[],"funders":[{"funder_name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","grant_id":"R24HD075489","title":null},{"funder_name":"National Science Foundation","grant_id":"SMA1041755","title":null},{"funder_name":"National Institute on Drug Abuse","grant_id":"R01DA038958","title":null},{"funder_name":"National Institute on Drug Abuse","grant_id":"RC2DA029475","title":null}],"total_grants":4,"fwci":1.0499,"citation_percentile":0.76206597,"influential_citations":0,"citation_trend":[{"year":2016,"count":1},{"year":2018,"count":3},{"year":2019,"count":3},{"year":2020,"count":5},{"year":2021,"count":4},{"year":2022,"count":4},{"year":2023,"count":4},{"year":2024,"count":4},{"year":2025,"count":2},{"year":2026,"count":3}],"oa_status":"hybrid","license":"cc-by-nc-nd","oa_locations":[{"url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/wcs.1389","host_type":"journal"},{"url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/wcs.1389","host_type":"publisher"},{"url":"https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fwcs.1389","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1002/wcs.1389","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/full-xml/10.1002/wcs.1389","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/am-pdf/10.1002%2Fwcs.1389","host_type":"publisher"},{"url":"https://wires.onlinelibrary.wiley.com/doi/pdf/10.1002/wcs.1389","host_type":"publisher"},{"url":"https://doi.org/10.1002/wcs.1389","host_type":"journal"},{"url":"https://pubmed.ncbi.nlm.nih.gov/27906499","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5682852","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC5682852","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC5682852?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":["Functional Brain Connectivity Studies","Advanced Neuroimaging Techniques and Applications","EEG and Brain-Computer Interfaces"],"mesh_terms":["Adolescent","Adult","Age Factors","Brain","Child","Child, Preschool","Humans","Individuality","Young Adult","Neuroimaging"],"keywords":["Neuroimaging","Psychology","Brain development","Brain function","Brain morphometry","Human brain","Brain Structure and Function","Developmental psychology","Cognitive psychology","Neuroscience","Medicine"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-27T13:55:33.008224Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}