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A comparison of metrics for quantifying cranial suture complexity

Cranial sutures play critical roles in facilitating postnatal skull development and function. The diversity of function is reflected in the highly variable suture morphology and complexity. Suture complexity has seldom been studied, resulting in little consensus on the most appropriate approach for...

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Detalles Bibliográficos
Autores principales: White, Heather E., Clavel, Julien, Tucker, Abigail S., Goswami, Anjali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653371/
https://www.ncbi.nlm.nih.gov/pubmed/33023399
http://dx.doi.org/10.1098/rsif.2020.0476
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author White, Heather E.
Clavel, Julien
Tucker, Abigail S.
Goswami, Anjali
author_facet White, Heather E.
Clavel, Julien
Tucker, Abigail S.
Goswami, Anjali
author_sort White, Heather E.
collection PubMed
description Cranial sutures play critical roles in facilitating postnatal skull development and function. The diversity of function is reflected in the highly variable suture morphology and complexity. Suture complexity has seldom been studied, resulting in little consensus on the most appropriate approach for comparative, quantitative analyses. Here, we provide the first comprehensive comparison of current approaches for quantifying suture morphology, using a wide range of two-dimensional suture outlines across extinct and extant mammals (n = 79). Five complexity metrics (sinuosity index (SI), suture complexity index (SCI), fractal dimension (FD) box counting, FD madogram and a windowed short-time Fourier transform with power spectrum density (PSD) calculation) were compared with each other and with the shape variation in the dataset. Analyses of suture shape demonstrate that the primary axis of variation captured attributes other than complexity, supporting the use of a complexity metric over raw shape data for sutural complexity analyses. Each approach captured different aspects of complexity. PSD successfully discriminates different sutural features, such as looping patterns and interdigitation amplitude and number, while SCI best-captured variation in interdigitation number alone. Therefore, future studies should consider the relevant attributes for their question when selecting a metric for comparative analysis of suture variation, function and evolution.
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spelling pubmed-76533712020-11-17 A comparison of metrics for quantifying cranial suture complexity White, Heather E. Clavel, Julien Tucker, Abigail S. Goswami, Anjali J R Soc Interface Life Sciences–Mathematics interface Cranial sutures play critical roles in facilitating postnatal skull development and function. The diversity of function is reflected in the highly variable suture morphology and complexity. Suture complexity has seldom been studied, resulting in little consensus on the most appropriate approach for comparative, quantitative analyses. Here, we provide the first comprehensive comparison of current approaches for quantifying suture morphology, using a wide range of two-dimensional suture outlines across extinct and extant mammals (n = 79). Five complexity metrics (sinuosity index (SI), suture complexity index (SCI), fractal dimension (FD) box counting, FD madogram and a windowed short-time Fourier transform with power spectrum density (PSD) calculation) were compared with each other and with the shape variation in the dataset. Analyses of suture shape demonstrate that the primary axis of variation captured attributes other than complexity, supporting the use of a complexity metric over raw shape data for sutural complexity analyses. Each approach captured different aspects of complexity. PSD successfully discriminates different sutural features, such as looping patterns and interdigitation amplitude and number, while SCI best-captured variation in interdigitation number alone. Therefore, future studies should consider the relevant attributes for their question when selecting a metric for comparative analysis of suture variation, function and evolution. The Royal Society 2020-10 2020-10-07 /pmc/articles/PMC7653371/ /pubmed/33023399 http://dx.doi.org/10.1098/rsif.2020.0476 Text en © 2020 The Authors. http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/http://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Life Sciences–Mathematics interface
White, Heather E.
Clavel, Julien
Tucker, Abigail S.
Goswami, Anjali
A comparison of metrics for quantifying cranial suture complexity
title A comparison of metrics for quantifying cranial suture complexity
title_full A comparison of metrics for quantifying cranial suture complexity
title_fullStr A comparison of metrics for quantifying cranial suture complexity
title_full_unstemmed A comparison of metrics for quantifying cranial suture complexity
title_short A comparison of metrics for quantifying cranial suture complexity
title_sort comparison of metrics for quantifying cranial suture complexity
topic Life Sciences–Mathematics interface
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7653371/
https://www.ncbi.nlm.nih.gov/pubmed/33023399
http://dx.doi.org/10.1098/rsif.2020.0476
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