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Maturational trajectories of pericortical contrast in typical brain development

In the last few years, a significant amount of work has aimed to characterize maturational trajectories of cortical development. The role of pericortical microstructure putatively characterized as the gray-white matter contrast (GWC) at the pericortical gray-white matter boundary and its relationshi...

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Autores principales: Drakulich, Stefan, Thiffault, Anne-Charlotte, Olafson, Emily, Parent, Olivier, Labbe, Aurelie, Albaugh, Matthew D., Khundrakpam, Budhachandra, Ducharme, Simon, Evans, Alan, Chakravarty, Mallar M., Karama, Sherif
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278832/
https://www.ncbi.nlm.nih.gov/pubmed/33766753
http://dx.doi.org/10.1016/j.neuroimage.2021.117974
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author Drakulich, Stefan
Thiffault, Anne-Charlotte
Olafson, Emily
Parent, Olivier
Labbe, Aurelie
Albaugh, Matthew D.
Khundrakpam, Budhachandra
Ducharme, Simon
Evans, Alan
Chakravarty, Mallar M.
Karama, Sherif
author_facet Drakulich, Stefan
Thiffault, Anne-Charlotte
Olafson, Emily
Parent, Olivier
Labbe, Aurelie
Albaugh, Matthew D.
Khundrakpam, Budhachandra
Ducharme, Simon
Evans, Alan
Chakravarty, Mallar M.
Karama, Sherif
author_sort Drakulich, Stefan
collection PubMed
description In the last few years, a significant amount of work has aimed to characterize maturational trajectories of cortical development. The role of pericortical microstructure putatively characterized as the gray-white matter contrast (GWC) at the pericortical gray-white matter boundary and its relationship to more traditional morphological measures of cortical morphometry has emerged as a means to examine finer grained neuroanatomical underpinnings of cortical changes. In this work, we characterize the GWC developmental trajectories in a representative sample (n = 394) of children and adolescents (~4 to ~22 years of age), with repeated scans (1–3 scans per subject, total scans n = 819). We tested whether linear, quadratic, or cubic trajectories of contrast development best described changes in GWC. A best-fit model was identified vertex-wise across the whole cortex via the Akaike Information Criterion (AIC). GWC across nearly the whole brain was found to significantly change with age. Cubic trajectories were likeliest for 63% of vertices, quadratic trajectories were likeliest for 20% of vertices, and linear trajectories were likeliest for 16% of vertices. A main effect of sex was observed in some regions, where males had a higher GWC than females. However, no sex by age interactions were found on GWC. In summary, our results suggest a progressive decrease in GWC at the pericortical boundary throughout childhood and adolescence. This work contributes to efforts seeking to characterize typical, healthy brain development and, by extension, can help elucidate aberrant developmental trajectories.
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spelling pubmed-82788322021-07-15 Maturational trajectories of pericortical contrast in typical brain development Drakulich, Stefan Thiffault, Anne-Charlotte Olafson, Emily Parent, Olivier Labbe, Aurelie Albaugh, Matthew D. Khundrakpam, Budhachandra Ducharme, Simon Evans, Alan Chakravarty, Mallar M. Karama, Sherif Neuroimage Article In the last few years, a significant amount of work has aimed to characterize maturational trajectories of cortical development. The role of pericortical microstructure putatively characterized as the gray-white matter contrast (GWC) at the pericortical gray-white matter boundary and its relationship to more traditional morphological measures of cortical morphometry has emerged as a means to examine finer grained neuroanatomical underpinnings of cortical changes. In this work, we characterize the GWC developmental trajectories in a representative sample (n = 394) of children and adolescents (~4 to ~22 years of age), with repeated scans (1–3 scans per subject, total scans n = 819). We tested whether linear, quadratic, or cubic trajectories of contrast development best described changes in GWC. A best-fit model was identified vertex-wise across the whole cortex via the Akaike Information Criterion (AIC). GWC across nearly the whole brain was found to significantly change with age. Cubic trajectories were likeliest for 63% of vertices, quadratic trajectories were likeliest for 20% of vertices, and linear trajectories were likeliest for 16% of vertices. A main effect of sex was observed in some regions, where males had a higher GWC than females. However, no sex by age interactions were found on GWC. In summary, our results suggest a progressive decrease in GWC at the pericortical boundary throughout childhood and adolescence. This work contributes to efforts seeking to characterize typical, healthy brain development and, by extension, can help elucidate aberrant developmental trajectories. 2021-03-22 2021-07-15 /pmc/articles/PMC8278832/ /pubmed/33766753 http://dx.doi.org/10.1016/j.neuroimage.2021.117974 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) )
spellingShingle Article
Drakulich, Stefan
Thiffault, Anne-Charlotte
Olafson, Emily
Parent, Olivier
Labbe, Aurelie
Albaugh, Matthew D.
Khundrakpam, Budhachandra
Ducharme, Simon
Evans, Alan
Chakravarty, Mallar M.
Karama, Sherif
Maturational trajectories of pericortical contrast in typical brain development
title Maturational trajectories of pericortical contrast in typical brain development
title_full Maturational trajectories of pericortical contrast in typical brain development
title_fullStr Maturational trajectories of pericortical contrast in typical brain development
title_full_unstemmed Maturational trajectories of pericortical contrast in typical brain development
title_short Maturational trajectories of pericortical contrast in typical brain development
title_sort maturational trajectories of pericortical contrast in typical brain development
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278832/
https://www.ncbi.nlm.nih.gov/pubmed/33766753
http://dx.doi.org/10.1016/j.neuroimage.2021.117974
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