facial growth and development trajectories based on 3D images: geometric morphometrics with a deformation perspective

Developmental changes of facial shape are commonly investigated through geometric morphometrics. A limitation with this approach is the inability to investigate patterns of morphological changes at local scale. This could be addressed through quantifying the deformation required to deform one shape to another. This study aimed to investigate changes in mean, rate, and variance of facial shape at local scale using geometric morphometrics through deformation perspective. 2112 Europeans 3 to 40 years-old from the 3D Facial Norms project were included. Shape and rate trajectories from partial least-squares regressions revealed that the developmentally protrusive nasal bridge was due to local expansion in surrounding tissues as opposed to shape changes in nasal bridge per-ser. Local expansion of the supraorbital region, in particular the medial part in males, resulted in the sloping forehead and deep-situated eyes with development. Facial shape variation increased non-linearly with age (p &l..., Custom script to calculate Procrustes variance for non-linearly modelled shape data., , # Facial growth and development trajectories based on 3D images: geometric morphometrics with a deformation perspective

## Code/Software

The script calculates morphological disparity for one or more groups of specimens and performs tests of statistical significances among groups. The script is based on the morphol.disparity function in the geomorph package (version 4.0.6). In the morphol.disparity function, shape data can only be modelled linearly. This script allows for comparison of morphological disparity for non-linearly modelled shape data.

Input arguments and output from the function are detailed inside the script. An example of using this script is provided in Appendix Text 4 of the accompanying article.

Script Version: Dated July 19, 2023.

Software: R 4.3.1

Loaded package: RRPP 1.4.0