Variation of the Orbital Rim Using Elliptic Fourier Analysis

The shape of the orbital rim is one of the essential craniofacial features that play a crucial role in face perception, recognition, or personal identification. As a consequence, it continues to attract a large variety of researchers, e.g., skeletal or forensic anthropologists, anatomists, physicians, psychologists etc. Despite being a focus since the rise of traditional anthropometrics, the 3-D nature of the orbital rim has not been satisfactorily quantified. This paper presents an approach to numerically describe the withinand among-population shape variation of the orbital rim, its curviness and spatial orientation using elliptic Fourier analysis. The sample consisted of 336 crania from present-day skeletal collections (Czech Republic, Portugal). For each specimen, a pair of orbital outlines was recorded using the MicroScribe G2X, a portable digitizer. Regardless of the body side, the trace line started and ended at dacryon located on the inner margin of the orbital rim. Cartesian coordinates of three fixed points defining a 3-D Frankfurt Horizontal plane were also acquired. In order to align for spatial orientation of the orbits, each pair was rotated to the Frankfurt Horizontal. The outlines were divided into 150 evenly distributed points and subsequently processed using elliptic Fourier analysis with 20 harmonics. The results showed that the specimen’s population affinity, sex, age and body size are factors responsible for the shape of the orbital rim. In contrast to the generally assumed pattern of sex differences, the shape of frontallyviewed orbits failed to act as a good sex predictor. Sex-related differences, as described by 3D shape analysis, were linked mostly to a specific “curviness” and to spatial arrangement of orbits within the craniofacial skeleton. Whereas the male orbital outline is characteristically curved and placed in the frontal plane, the female outline is flat and diverged. The results demonstrate that elliptic Fourier analysis is a powerful methodological tool that can provide new insights into the structural relationships within biological objects.