Category Archives: Skull

Human craniofacial evolution

In evolutionary biology, microevolution and macroevolution impact on the variation and covariation between genotype and phenotype. A related concept is the biological ability of an organism to adapt and evolve, or its evolvability, which is of keen interest to evolutionary biologists. The quantification of genetic change is analysed via the genetic variance-covariance matrix (G-matrix) while phenotypic change is analysed via the phenotypic variance-covariance (P-Matrix). Under the assumption of a neutral evolutionary model with the absence of genetic drift, the G-matrix should be proportional to a P-matrix. Although there is potential for theoretical complications arising from organisms with higher evolvability biasing the rates of evolutionary change, this is not fully investigated and seems to warrant further empirical studies.

The diversity of craniofacial form observed in fossil species of genus Homo and modern humans has been examined in terms of craniofacial adaptation to various biomechanical and environmental stressors. The absence of recovered genomes from species of fossil Homo beyond Homo neanderthalensis and fossil Homo sapiens has required studies of fossil human phylogenetics to rely on high uncertainties in the estimation of fossil hominin phylogeny and further restricted by small sample sizes.

In a recent study, Baab (2018) used the rate of evolutionary change in populations of modern Homo sapiens to estimate evolutionary rates in species of fossil Homo, analyzing craniofacial shape change, diversification and evolvability in the genus Homo. Results were consistent with independent conclusions that a neutral evolutionary model was adequate to generate the diversity in craniofacial form observed in the genus Homo. Once accounting for the small fossil sample size and the degree of evolutionary rate being higher than chance, there was no statistically significant support for higher rates of evolvability generating more rapid rates of evolutionary change across the entire genus Homo.

In contrast, the more recent lineages showed some evidence for selection acting at a greater magnitude in H. neanderthalensis and early H. sapiens, generating a more rapid rate of evolutionary change.  Baab (2018) suggests brain expansion may be a likely contributor influencing the more rapid evolutionary rate change in craniofacial shape as observed in early H. sapiens and H. neanderthalensis and why only the more recent lineages of the genus Homo were affected by such rapid changes in craniofacial form.

Alannah Pearson

 

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Forgotten boneyard

 

Medusa’s skull

[archive]


Modelling brain-skull interface

Precise computational modelling of the brain-skull interface is necessary for the prediction, prevention and treatment of acquired brain-injuries. The brain-skull interface comprises complex layers including the osseous cranial tissues, meninges, sub-arachnoidal space and tissues, cerebrospinal fluid (CSF), pia mater and the gray and white cerebral matter. While the tissue properties of the brain-skull interface are known, there is no consensus on how these layers interact during head impact.  To generate computational models of the brain-skull interface with greater accuracy, knowing the boundary conditions or constraints is necessary. Previous experimental studies have relied on modelling the deformation of the brain-skull interface using neural density targets (NDTs) implanted into the cadaver brain, collecting information on tissue displacement during front and rear impact in motor vehicle crash-tests.

Wang et al. (2018) utilized computational bio-mechanics and finite element analysis (FEA), placing nodes in the 3D model in close approximation to the position of the experimental NDTs. Four hypotheses of the brain-skull interface were modeled, each approach placing different boundary conditions to model deformation during simulated head impact. All analyses were validated against previous experimental studies. Results showed that how the brain-skull interface was modeled appreciably affected the results. The 3D model showing the closest agreement with the experimental data, included all tissues of the brain-skull interface, allowed for displacement without separation of the skull and brain tissues, and strongly corresponded with known neuroanatomy. This 3D model indicated that non-linear stress-strain associations between brain and skull tissues best matched experimental results. Further, this 3D model could be closely predicted using an Ogden Hyperviscoelastic Constitutive model which did not over- or under-estimate deformations during head impact. The risks of over- and under-estimating head impact during motor vehicle accidents has implications for vehicle construction and prevention of serious brain trauma during accidents. Ultimately, a better understanding of the interaction between layers of the brain-skull interface can produce more accurate predictions of the likely impact during motor vehicle accidents and prevent violent head injury. Extrapolation of this research into paleoneurology could allow investigations into the structural interaction between the brain and braincase, testing if the resistence of brain-skull tissues during deformation evolved in human species as primary adaptations or secondary adjustments such as allometric responses.

 

Alannah Pearson


Cranial vault thickness in South African Australopiths

In a recent paper, Beaudet and colleagues analyze the cranial vault thickness of StW 578, a partial cranium of Australopithecus not yet assigned to a species. The authors explore the utility of cranial vault thickness and of the organization of the diploe and cortical tables as potential diagnostic criteria for hominin species. For that, they also analyze a comparative sample including other South African Late Pliocene-Early Pleistocene fossils, extant humans, and chimpanzee specimens. Fossils include specimens of Australopithecus and Paranthropus recovered from Sterkfontein, Swartkrans, and Makapansgat sites. Based on cranial landmarks, the authors defined homologous parasagittal and coronal sections on the CT scans, preferentially on the right hemisphere, which is better preserved in StW 578. The thickness of the diploe, the thickness of the inner and outer cortical tables, and the total thickness were measured automatically in various points sampled throughout the length of the sections. The proportion of each layer was computed by dividing the thickness by the surface area calculated between two successive points. Specimens that preserved only the left side were used for qualitative comparison. Results emphasize differences between Australopithecus and Paranthropus. The former genus tends to have thicker vaults, with a larger proportion of the diploic layer, while the latter tends to have thinner vaults, with a larger proportion of the inner and outer tables. The distribution of thickness also differs, as StW 578 and other Australopithecus crania from Sterkfontein display disproportionately thicker frontal and posterosuperior parietal regions, while Paranthropus (SK 46) and extant chimpanzees have thickest regions on cranial superstructures (supraorbital and occipital tori). As the authors suggest, thickening of the cranial vault in frontal and parietal regions needs further investigation, as to unveil a possible correlation between bone thickness and brain anatomy. Moreover, as the increase in thickness is associated with an increase in diploe proportions, variation in this layer might indicate physiological (thermoregulation) or biomechanical differences between Australopithecus and Paranthropus. In sum, cranial vault thickness patterns of StW 578 are equivalent to those of other specimens from Sterkfontein (StW 505 and Sts 71). The presence of a Paranthropus-like pattern in two of the three Mangapansgat specimens further indicates the presence of different morphs or species of Australopithecus in this site. This methodology and results provide a fine base for further studies on the taxonomic significance of the cranial vault thickness. The authors suggest beginning by including more Paranthropus specimens, and by evaluating chronological, geographic, and taxonomic variation.

 

Sofia Pedro


Pulling faces

Two different papers have been published this month on the evolution of the supraorbital anatomy in humans. The first article is on Neanderthal facial morphology, and it was coordinated by Stephen Wroe, of the FEAR lab. Here a comment on the Daily Mail. The second article, by Ricardo Miguel Godinho and coauthors, links supraorbital morphology and social dynamics, and it was commented in a News and Views by Markus Bastir.


Digital Endocasts

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Primate Cranial Complexes

The primate skull is comprised of complexes including the cranial base, vault and facial region. How these complexes respond to different developmental and growth processes as well as varied selective pressures like diet, locomotion and sexual selection have been investigated in terms of modularity and integration. The concepts of modularity and integration concern the co-variance or independence of these complexes.

Profico et al. used several recent statistical methods to test previous research conclusions suggesting the primate cranial base and facial complex are strongly integrated. The cranium from 11 extant species of the Cercopithecoidea and Hominoidea were studied utilizing geometric morphometrics to investigate shape variation, the presence of evolutionary allometry and modularity or integration.

Shape variation of the primate cranial base and facial complex was assessed by Principal Component Analysis. Among taxa, shape variation of the cranial base reflected patterns in locomotion, cranial base flexion and the size of the foramen magnum. The shape variation of the facial complex reflected size-related and sex-linked morphology, the degree of lower and mid-facial prognathism and associated changes to narrowing of the nasal-orbital regions. Evolutionary allometry was tested by multivariate regression of size on shape and indicated the facial complex but not the cranial base was influenced by evolutionary allometry. Modularity and integration was analyzed using Partial Least Squares to test the degree of co-variation between the facial complex and cranial base which proved to be low. These combined results suggested the cranial base and facial complex complied with the concept of modularity rather than integration contrasting with previous studies.

An important reminder that although a pattern of similarity was found between Pongo pygmaeus and Hylobates lar this does not imply a close biological relationship, rather these taxa share similar cranial base and facial block morphology, potentially as a by-product of orthograde posture and the absence of quadrupedalism found in the other primate taxa with the exception of modern humans which are obligate bipeds. In light of the current findings, a more comprehensive reconsideration may be necessary of the effects from variation in the facial complex and cranial base morphology throughout primate evolution.

Alannah Pearson


Howlers

Fiorenza L., Bruner E. 2017. Cranial shape variation in adult howler monkeys (Alouatta seniculus). Am. J. Primatol. [link]


Close-range Photogrammetry or Surface Scanner?

postRecently, Evin et al. 2016 have published a study comparing the accuracy of the three-dimensional reconstruction of five wolf crania using both photogrammetry and high-resolution surface scanner. For the photogrammetric images acquisition, they used an 8-megapixel (DSLR) Canon EOS 30D camera, mounted with a Canon EF 24–105mmf/4 L IS USMlens. The scanner-based 3D models were created using a Breuckmann StereoScan structured light scanner (http://www.breuckmann.com). The resulting 3D models were compared first through visual observation, and second with the computation of a mesh-to-mesh deviation map. The pairs of models were spatially aligned (using a least-square optimisation best-fit criterion), followed by a 3D landmark-based geometric morphometric approach using corresponding analyses. The results show that photogrammetric 3D models are as accurate in terms of coloration, texture, and geometry, as the highest-end surface scanners. Minimal differences between photogrammetric 3D models and surface scanner-based models have been only identified on intricate topological regions, such the tooth row. Photogrammetry is becoming a common tool in archaeological and anthropological research. The major advantage of this technique is the speed and ease of image acquisition and reconstruction. Photogrammetry is an equally good alternative and less expensive than other more common techniques, such as structured light or surface scanners. In terms of archaeological samples conservation, photogrammetry could be in the future an excellent alternative to provide accurate replica models that can be widely accessible for research, without affecting the original collections.

Gizéh Rangel de Lázaro


Skulls and brains in reptiles and birds

In a recent paper, Fabbri et al analyzed the relationship between brain and cranial vault shape in the transition from reptiles to birds. To assess the evolution of this relationship they used a broad sample including Aves, Lepidosauria, Crocodylia, Archosauria, and Reptilia. To assess developmental differences they included an ontogenetic sample of Alligator mississipiensis and Gallus gallus. The results showed that the relationship between the vault bones and the brain is conserved across these taxa, with the frontal bone positioned over the forebrain and the parietal bone over the midbrain or over midbrain and posterior forebrain. Nonetheless, they observed some shape variations, namely on the relative sizes of the frontal and parietal bones and in the position of the fronto-parietal suture relative to the forebrain-midbrain boundary. These two structures are significantly correlated, with the fronto-parietal suture being either anterior to (e.g. stem reptiles) or nearly aligned with (e.g. crown birds) the forebrain-midbrain boundary. In terms of ontogeny, chickens have a shorter ontogenetic trajectory than alligators, as the brain and skull of embryos are similar to the adult ones. The brain and skull of alligators develop with negative allometry, with the brain relatively large in early stages but becoming relatively small during growth. Conversely, the skull and brain of chicken grow with positive allometry, and the authors suggest the brain should be considered peramorphic in Aves. Overall the results stress the important role of the brain in shaping the cranial vault. The authors wonder whether the intimate relationship between brain and frontal and parietal bones is the key for the conservation of the cranial vault across vertebrates.

Sofia Pedro