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Structural brain development between childhood and adulthood: Convergence across four longitudinal samples

Longitudinal studies including brain measures acquired through magnetic resonance imaging (MRI) have enabled population models of human brain development, crucial for our understanding of typical development as well as neurodevelopmental disorders. Brain development in the first two decades generall...

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Autores principales: Mills, Kathryn L., Goddings, Anne-Lise, Herting, Megan M., Meuwese, Rosa, Blakemore, Sarah-Jayne, Crone, Eveline A., Dahl, Ronald E., Güroğlu, Berna, Raznahan, Armin, Sowell, Elizabeth R., Tamnes, Christian K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5035135/
https://www.ncbi.nlm.nih.gov/pubmed/27453157
http://dx.doi.org/10.1016/j.neuroimage.2016.07.044
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author Mills, Kathryn L.
Goddings, Anne-Lise
Herting, Megan M.
Meuwese, Rosa
Blakemore, Sarah-Jayne
Crone, Eveline A.
Dahl, Ronald E.
Güroğlu, Berna
Raznahan, Armin
Sowell, Elizabeth R.
Tamnes, Christian K.
author_facet Mills, Kathryn L.
Goddings, Anne-Lise
Herting, Megan M.
Meuwese, Rosa
Blakemore, Sarah-Jayne
Crone, Eveline A.
Dahl, Ronald E.
Güroğlu, Berna
Raznahan, Armin
Sowell, Elizabeth R.
Tamnes, Christian K.
author_sort Mills, Kathryn L.
collection PubMed
description Longitudinal studies including brain measures acquired through magnetic resonance imaging (MRI) have enabled population models of human brain development, crucial for our understanding of typical development as well as neurodevelopmental disorders. Brain development in the first two decades generally involves early cortical grey matter volume (CGMV) increases followed by decreases, and monotonic increases in cerebral white matter volume (CWMV). However, inconsistencies regarding the precise developmental trajectories call into question the comparability of samples. This issue can be addressed by conducting a comprehensive study across multiple datasets from diverse populations. Here, we present replicable models for gross structural brain development between childhood and adulthood (ages 8–30 years) by repeating analyses in four separate longitudinal samples (391 participants; 852 scans). In addition, we address how accounting for global measures of cranial/brain size affect these developmental trajectories. First, we found evidence for continued development of both intracranial volume (ICV) and whole brain volume (WBV) through adolescence, albeit following distinct trajectories. Second, our results indicate that CGMV is at its highest in childhood, decreasing steadily through the second decade with deceleration in the third decade, while CWMV increases until mid-to-late adolescence before decelerating. Importantly, we show that accounting for cranial/brain size affects models of regional brain development, particularly with respect to sex differences. Our results increase confidence in our knowledge of the pattern of brain changes during adolescence, reduce concerns about discrepancies across samples, and suggest some best practices for statistical control of cranial volume and brain size in future studies.
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spelling pubmed-50351352016-11-01 Structural brain development between childhood and adulthood: Convergence across four longitudinal samples Mills, Kathryn L. Goddings, Anne-Lise Herting, Megan M. Meuwese, Rosa Blakemore, Sarah-Jayne Crone, Eveline A. Dahl, Ronald E. Güroğlu, Berna Raznahan, Armin Sowell, Elizabeth R. Tamnes, Christian K. Neuroimage Article Longitudinal studies including brain measures acquired through magnetic resonance imaging (MRI) have enabled population models of human brain development, crucial for our understanding of typical development as well as neurodevelopmental disorders. Brain development in the first two decades generally involves early cortical grey matter volume (CGMV) increases followed by decreases, and monotonic increases in cerebral white matter volume (CWMV). However, inconsistencies regarding the precise developmental trajectories call into question the comparability of samples. This issue can be addressed by conducting a comprehensive study across multiple datasets from diverse populations. Here, we present replicable models for gross structural brain development between childhood and adulthood (ages 8–30 years) by repeating analyses in four separate longitudinal samples (391 participants; 852 scans). In addition, we address how accounting for global measures of cranial/brain size affect these developmental trajectories. First, we found evidence for continued development of both intracranial volume (ICV) and whole brain volume (WBV) through adolescence, albeit following distinct trajectories. Second, our results indicate that CGMV is at its highest in childhood, decreasing steadily through the second decade with deceleration in the third decade, while CWMV increases until mid-to-late adolescence before decelerating. Importantly, we show that accounting for cranial/brain size affects models of regional brain development, particularly with respect to sex differences. Our results increase confidence in our knowledge of the pattern of brain changes during adolescence, reduce concerns about discrepancies across samples, and suggest some best practices for statistical control of cranial volume and brain size in future studies. Academic Press 2016-11-01 /pmc/articles/PMC5035135/ /pubmed/27453157 http://dx.doi.org/10.1016/j.neuroimage.2016.07.044 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mills, Kathryn L.
Goddings, Anne-Lise
Herting, Megan M.
Meuwese, Rosa
Blakemore, Sarah-Jayne
Crone, Eveline A.
Dahl, Ronald E.
Güroğlu, Berna
Raznahan, Armin
Sowell, Elizabeth R.
Tamnes, Christian K.
Structural brain development between childhood and adulthood: Convergence across four longitudinal samples
title Structural brain development between childhood and adulthood: Convergence across four longitudinal samples
title_full Structural brain development between childhood and adulthood: Convergence across four longitudinal samples
title_fullStr Structural brain development between childhood and adulthood: Convergence across four longitudinal samples
title_full_unstemmed Structural brain development between childhood and adulthood: Convergence across four longitudinal samples
title_short Structural brain development between childhood and adulthood: Convergence across four longitudinal samples
title_sort structural brain development between childhood and adulthood: convergence across four longitudinal samples
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5035135/
https://www.ncbi.nlm.nih.gov/pubmed/27453157
http://dx.doi.org/10.1016/j.neuroimage.2016.07.044
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