reverse-dissection-dicect-reveal-otherwise-hidden-data-evolution

Reverse Dissection and DiceCT Reveal Otherwise Hidden Data in the Evolution of the Primate Face

Facial expressions, or facial displays, of social or emotional intent are produced by many mammalian taxa as a means of visually communicating with ...

Duke University

Three-dimensional geometric morphometric (3DGM) methods for placing landmarks on digitized bones have become increasingly sophisticated in the last 20 years, including greater degrees of automation. One aspect shared by all 3DGM methods is that the researcher must designate initial landmarks. Thus, researcher interpretations of homology and correspondence are required for and influence representations of shape. We present an algorithm allowing fully automatic placement of correspondence points on samples of 3D digital models representing bones of different individuals/species, which can then be input into standard 3DGM software and analyzed with dimension reduction techniques. We test this algorithm against several samples, primarily a dataset of 106 primate calcanei represented by 1,024 correspondence points per bone. Results of our automated analysis of these samples are compared to a published study using a traditional 3DGM approach with 27 landmarks on each bone. Data were analyzed with morphologika(2.5) and PAST. Our analyses returned strong correlations between principal component scores, similar variance partitioning among components, and similarities between the shape spaces generated by the automatic and traditional methods. While cluster analyses of both automatically generated and traditional datasets produced broadly similar patterns, there were also differences. Overall these results suggest to us that automatic quantifications can lead to shape spaces that are as meaningful as those based on observer landmarks, thereby presenting potential to save time in data collection, increase completeness of morphological quantification, eliminate observer error, and allow comparisons of shape diversity between different types of bones. We provide an R package for implementing this analysis.

A new fully automated approach for aligning and comparing shapes.

Multiple meaningful ecological characterizations of a species revolve around body mass. Because body mass cannot be directly measured in extinct taxa, reliable body mass predictors are needed. Many published body mass prediction equations rely on dental dimensions, but certain skeletal dimensions may have a more direct and consistent relationship with body mass. We seek to evaluate the reliability of prediction equations for inferring euarchontan body mass based on measurements of the articular facet areas of the astragalus and calcaneus.

Predicting euarchontan body mass: A comparison of tarsal and dental variables.

The talus is one of the most commonly preserved post-cranial elements in the platyrrhine fossil record. Talar morphology can provide information about postural adaptations because it is the anatomical structure responsible for transmitting body mass forces from the leg to the foot. The aim of this study is to test whether the locomotor behaviour of fossil Miocene platyrrhines could be inferred from their talus morphology. The extant sample was classified into three different locomotor categories and then talar strength was compared using finite-element analysis. Geometric morphometrics were used to quantify talar shape and to assess its association with biomechanical strength. Finally, several machine-learning (ML) algorithms were trained using both the biomechanical and morphometric data from the extant taxa to infer the possible locomotor behaviour of the Miocene fossil sample. The obtained results show that the different locomotor categories are distinguishable using either biomechanical or morphometric data. The ML algorithms categorized most of the fossil sample as arboreal quadrupeds. This study has shown that a combined approach can contribute to the understanding of platyrrhine talar morphology and its relationship with locomotion. This approach is likely to be beneficial for determining the locomotor habits in other fossil taxa.

Inferring locomotor behaviours in Miocene New World monkeys using finite element analysis, geometric morphometrics and machine-learning classification techniques applied to talar morphology.

Justin T. Gladman

Shared Materials Instrumentation Facility

Duke University

Reverse Dissection and DiceCT Reveal Otherwise Hidden Data in the Evolution of the Primate Face

Justin T. Gladman

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Shared Materials Instrumentation Facility

Duke University

Reverse Dissection and DiceCT Reveal Otherwise Hidden Data in the Evolution of the Primate Face

Shared Materials Instrumentation Facility