Precuneus form and folds

bruner-et-al-aa2017One more paper on the morphology of the precuneus. This time we have analyzed a racially heterogenous sample, confirming that precuneus size is a major source of brain form variation also when a wider genetic variability is taken into account. It is a variation that is apparently independent from sex, race, or hemisphere, although males could have slightly larger proportions than females. A larger precuneus can be associated with additional folds, often in its anterior district, although this association is feeble. Geometric models suggest that the areas involved in this variations are the anterior-dorsal ones, roughly corresponding to area 7a. This area is the largest and more variable of the precuneus, and it includes the medial cortex but also the dorsal external cortex of the upper parietal lobule. It is functionally associated with the integration of somatic and visual information, and with self-centered mental imagery. These results also suggest that upper and lower areas of the precuneus should be considered separately when dealing with functional or evolutionary neuroanatomy. Our former papers on this topic concerned the shape of the precuneus, its cortical surface area, its sulcal patterns and  lateral extension, and the differences between humans and chimpanzees. Apart from the relevance in modern neuroanatomy, these same endocranial regions also display a corresponding spatial enlargement in modern human evolution.

Frontal surfaces


More surfaces. This week we have published a surface comparison of the frontal endocranial morphology in OH9, Buia, and Bodo. The methods are the same applied previously by Amélie Beaudet and colleagues. Despite the importance generally assigned to the frontal cortex in our species, paleoneurology has not managed to reveal clear and patent changes in its gross form. Endocasts can only supply information on the general external appearance of the cortical anatomy, so we should expect they cannot be used to trace many aspects  associated with evolutionary variations. Also, the bad habits to defend firm statements based on single (and often reconstructed and fragmented) individuals unpleasantly crashes against the basic scientific principle of hypothesis testing, something that needs quantification, large samples and statistics. In this paper we compare these three specimens with the general scope of discussing some issues about frontal lobe evolution and paleoneurology. When compared with a modern human endocast, the younger fossils (Buia and Bodo) display flatter dorsal-lateral areas, while the older one (OH9) show a more extensive flattening of the whole dorsal surface. They all fit within a general trend observed in humans and hominoids: the more the eyes go below the frontal cortex, the more the frontal lobe bulges. So it seems reasonable to think that the curvature of the frontal lobes is but a structural consequence of the spatial relationships between face and braincase. In paleoneurology, we should exclude structural changes (cranial constraints and secondary consequences) if we want to localize functional ones, or if we want to reveal specific adaptations and primary evolutionary variations. Surface analysis is one more tool to go in that direction.

Evolution of Nervous Systems


Second Edition of this outstanding reference in neuroscience and evolution edited by Jon H. Kaas, with four volumes dedicated to vertebrates, mammals, primates, and humans. Here a presentation of the contents, and a chapter on paleoneurology.

Brains and teeth

gomez-robles-et-al-pnas2017In anthropology it is commonly accepted that the evolution of larger brains was associated with the reduction of posterior teeth. Factors ranging from diet to cognitive ability have been used to explain this inverse correlation between cerebral complexity and masticatory structures. Aida Gómez-Robles and colleagues have analyzed brain and teeth changes using a multiple-variance Brownian motion approach, providing evidence against a brain-teeth phylogenetic association. Brain shape was analyzed by using eight linear variables as measured on endocasts. Teeth shape was analyzed through geometric morphometrics. The study found that endocranial proportions and dental geometry are largely characterized by similar rates of variation, which are indicative of a neutral and non-directional pattern of evolution. Brain size and tooth size show different rates of change throughout the phylogenetic tree, and the hypothesis of a reciprocal and inverse correlation is not supported. This seems to suggest independent factors at environmental and/or genetic level. Two characters show faster rates of change in specific lineages, and are probably associated with specific selective and adaptive processes: brain size in early Homo and brain globularity in Homo sapiens. The first result suggests that brain evolution in the genus Homo is strongly based on size increase rather than on changes of specific cortical proportions. However, caution is needed in this sense: the study is based on simple linear metrics such as arcs and chords, and reflects only the external appearance of endocranial anatomy. Despite these limitations, this result is consistent with other kinds of evidence. The second result reflects an exception to this size-only pattern of change: the globular brain shape in modern humans. Parietal lobe variations are again an issue.


beaudet-et-al-jhe2016Amélie Beaudet and colleagues have published a comprehensive and detailed paleoneurological study on South African fossil cercopithecoids. The paper supplies three main advances. First, it provides key information on primate paleoneurology, in particular on Plio-Pleistocene monkeys, belonging to the genera Theropithecus, Parapapio, and Cercopithecoides. Paleoneurology is often more focused on humans and hominoids than on monkeys, and therefore this article is particularly welcome. Furthermore, the study is based on a surface-based method, that compares the rough geometry of the object. Surface analyses can represent an additional and interesting alternative for computing endocast comparisons. There are many complex techniques currently available in shape analysis, and we should always carefully consider that their results depend upon their specific criteria and constraints. Morphometric outputs are “ordered representations” of a given sample variation according to specific numerical and logical assumptions. Consequently, methods are crucial in determining the comparative framework. Different methods, different criteria. For example, surface analysis is not constrained by anatomical correspondence, but it is only sensitive to geometrical correspondence. Hence, the approach misses the information on anatomical boundaries between different elements and areas, distributing variation all through a homogeneous and undifferentiated object.This can be an advantage when taking into consideration form alone, or a disadvantage if one want to investigate the contribution of specific anatomical components. Finally, this study presents a semi-automatic approach for sulcal detection, that is a geometry-based method for the identification of surface relieves, curvature lines, and topographical variations. This approach may seriously represent a major advance in paleoneurology. Nonetheless, it should be taken into account that we still ignore many mechanisms behind cortical folding, and that folding patterns could be the result of passive biomechanical constraints with uncertain phylogenetic or functional meaning.

Integrated paleoneurology

Zollikofer et al 2016Together with the recent article on modern vs Neandertal endocranial ontogeny, the team coordinated by Christoph Zollikofer has now published also a large and comprehensive study on endocranial ontogeny in humans and apes. The paper focuses on a specific question: to what extent endocranial differences are due to brain differences, and to what extent they are due to cranial constraints? Definitely, this is a key-paper in paleoneurology. They considered the integration between and within the main cranial districts to evaluate the influence on brain shape of two major cranial effects: spatial packing and facial orientation. Their analyses suggest that endocranial differences between humans and apes, as well as differences among apes, are the result of all those factors, the cerebral and the cranial ones. Therefore, the endocranial form is due to a complex admixture of specific brain differences (already present at birth) and cranial constraints. Comparisons among endocranial ontogenetic patterns of living hominoids, among adult fossil specimens, and among different neuroanatomical aspects of living species, can give different results, suggesting that the relationships between anatomical, morphological, and cytological elements is far from being understood. In my opinion, a limit of many shape analyses in general concerns the use of surface semi-landmarks to analyze brain geometry. Surface landmarks are necessary because of the lack of good anatomical references on the endocasts. Unfortunately, they can’t take into account the contribution of distinct cerebral areas, and as a consequence they consider brain morphology as a single homogeneous surface. The identification of boundaries or distinct and independent elements within this surface might seriously influence the multivariate output. I am particularly interested in the analysis of the parietal districts. When using surface landmarks the analysis of the parietal surface may give different (and sometimes contrasting) results. Hence, we may wonder whether the observed parietal variations are the result of brain differences (cortical expansion/reduction) or of geometry (bulging and flexion). Nonetheless, previous morphological studies based on cortical landmarks suggest that modern humans show an actual (absolute and relative) increase not only of the parietal “surface”, but also and specifically of the parietal “lobe”, when compared with extinct hominids or with living chimps. The localization of anatomical boundaries on endocasts may be difficult, although those results have been replicated on different samples. The identification of anatomical landmarks in living species is, in contrast, definitely more reliable. Therefore, whatever the result of a global surface analysis of the whole endocranium, we should not forget that comparisons of specific areas are suggesting a differential contribution of distinct brain components.

Imaging brains

Brain glass coasters 2016In the last decade neuroscience has experienced an explosion of brain imaging studies, programs, and databases. The advance has been outstanding, indeed. Nonetheless, we have also been surprised by a large and unexpected number of strange and discordant results. There are so many examples in which similar studies reach different or even opposite conclusions. Differences in raw values, comparisons (from sexual variation to hemispheric asymmetries), or correlations and associations between variables, can be pretty frequent when dealing with specific aspects of brain anatomy. In some cases, these studies apparently deal with “simple” factors, like volumes or linear metrics. We have discovered new kinds of uncertainties on functions, software, and even on basic anatomy. A recent study has discussed the problem of reliability in functional MRI (here a comprehensive post). Of course this is not something strictly associated with neuroanatomy and brain imaging. Any analysis in molecular biology has many more methodological and technical passages which can hide some kind of processing problem and generate noise or even confounding outputs. In neuroimaging, there are at least four main steps which can be problematic. First, data sampling (machines, parameters, and so on). Second, the formatting procedures (databases, archives, platforms). Third, the processing of the data (programs, algorithms, etc.). Fourth, statistics (sample size, statistical power, adequacy of the statistical tools). Whatever it is, it is calling our attention. And this is the good part: we are more and more forced to be less superficial. All these unexpected uncertainties require a critical view, as discussed in this manuscript on future challenges for neuroimaging research. The most patent problem is confusion, and an epidemic spread of wrong information. But there is also another risk: too many discordant results can lead to a consistent loss of confidence in these methods (here another post – in Spanish). And this can have both scientific and economic consequences.

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