Objectives: We analyzed the main anatomical traits found in the human frontal bone by using a geometric morphometric approach. The objectives of this study are to explore how the frontal bone morphology varies between the sexes and to detect which part of the frontal bone are sexually dimorphic. Materials and methods: The sample is composed of 161 skulls of European and North American individuals of known sex. For each cranium, we collected 3D landmarks and semilandmarks on the frontal bone, to examine the entire morphology and separate modules (frontal squama, supraorbital ridges, glabellar region, temporal lines, and mid-sagittal profile). We used Procrustes ANOVAs and LDAs (linear discriminant analyses) to evaluate the relation between frontal bone morphology and sexual dimorphism and to calculate precision and accuracy in the classification of sex. Results: All the frontal bone traits are influenced by sexual dimorphism, though each in a different manner. Variation in shape and size differs between the sexes, and this study confirmed that the supraorbital ridges and glabella are the most important regions for sex determination, although there is no covariation between them. The variable size does not contribute significantly to the discrimination between sexes. Thanks to a geometric morphometric analysis, it was found that the size variable is not an important element for the determination of sex in the frontal bone. Conclusion: The usage of geometric morphometrics in analyzing the frontal bone has led to new knowledge on the morphological variations due to sexual dimorphism. The proposed protocol permits to quantify morphological covariation between modules, to calculate the shape variations related to sexual dimorphism including or omitting the variable size.

The morphology of the human cranium allows for reconstructing important information about the identity of an individual, such as age, ancestry, sex, and health status. The estimation of sex from morphology is a key component of the work of physical anthropologists, and in the last decade, the field has witnessed an increase in the use of novel algorithm-based methodologies to tackle the aforementioned task. Nevertheless, several limitations (e.g., small training/testing sample size, training-test data relatedness, limited population inclusiveness, overfitting) have hampered the application of such methods as a standardised procedure in the field. Here, we propose a population-inclusive protocol for estimating sex from a small set of cranial metric traits (10 measurements) based on a neural network architecture trained to maximise the probability of sex attribution and prevent overfitting. The cross-validation returned an accuracy of 86.7% ± 0.02% and log loss of 0.34 ± 0.03. The protocol developed was tested on data unrelated to that of the training and validation phase and returned an estimated accuracy of 84.3% and log loss of 0.348. The model and the related code to use it are made publicly available.

The observation and the quantification of asymmetry in biological structures are deeply investigated in geometric morphometrics. Patterns of asymmetry were explored in both living and fossil species. In living organisms, levels of directional and fluctuating asymmetry are informative about developmental processes and health status of the individuals. Paleontologists are primarily interested in asymmetric features introduced by the taphonomic process, as they may significantly alter the original shape of the biological remains, hampering the interpretation of morphological features which may have profound evolutionary significance. Here, we provide a new R tool that produces the numerical quantification of fluctuating and directional asymmetry and charts asymmetry directly on the specimens under study, allowing the visual inspection of the asymmetry pattern. We tested this show.asymmetry algorithm, written in the R language, on fossil and living cranial remains of the genus Homo. show.asymmetry proved successful in discriminating levels of asymmetry among sexes in Homo sapiens, to tell apart fossil from living Homo skulls, to map effectively taphonomic distortion directly on the fossil skulls, and to provide evidence that digital restoration obliterates natural asymmetry to unnaturally low levels.