Posts Tagged 'cortical folding'

Sulcal imprints

The fuzzy geometry of the brain surface shapes the endocranial wall, and endocasts can show traces and imprints of the cortical sulcal patterns. Individual variation is noticeable, and the precise mechanisms behind these folding schemes are not clear at all. Hence, it is not recommended to use this information in a simplistic “phrenological” fashion, as unfortunately it has been done in many evolutionary studies. At the same time, cortical morphology is the direct result of neurons growth and development, and therefore even the pretentious rejection of this information seems unwise. Many authors dismiss any result based on brain gross morphology, simply because it is “just brain form”. This is probably because they ignore the developmental processes behind that forms, and they don’t take into account that when we talk about “brain form” we are implicitly referring to those processes, and not to a crude geometrical appearance. At least, sulcal patterns are useful (and the only available macroscopic) boundaries to detect the absolute or relative extension of some cerebral districts or cortical areas. So, despite all the uncertainties, they are directly providing information on cortical proportions. Proportions means “some areas are larger and some others are smaller”. Size is not always a matter of more or less neurons, but it is however matter of more or less “something”. Whatever it is, it should be functional, and maybe even adaptive some way, associated with some specific histological factor, or with some indirect physiological consequence. This is why the issue is not trivial.

Sulcal imprints are generally more visible on smaller and younger skulls. A recent study investigates the expression of the sulcal traces in macaques. Anterior folds (frontal and temporal lobes) leave more traces than the posterior ones (parietal and occipital). There are no many differences among young ontogenetic stages but then, during aging, the expression of the traces decreases noticeably, and imprints become more blurred. Local anatomical differences in the barrier between brain and skull (meninges, vessels, etc) can have a role in this size-related differences. Nonetheless, probably it is a matter of growth. In earlier ages, the brain generates a constant pressure on the vault bones, shaping the bone surface. But in later ages, when brain growth is concluded, that intimate physical relationship is looser. During aging, the brain even undergoes a shrinkage of about 7-8%, and the contact is further lost. This study is simple and effective, a good paper to approach the topic. Between an uncritical phrenological approach and a snobbish rejection of the evidence, we should consider an intermediate approach, in which we evaluate what kind of information we can obtain from these traits. To do that, we have to investigate their phenotypic factors and their mechanical influences, their structural associations and their variability.



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.

Folding brains

Tallinen et al 2016An amazing article has been published in Nature Physics. Brain cortical folding is influenced by genetic and physiological factors, but there are also many hypotheses concerning the possible role of mechanical forces associated with the cerebral tissues. These hypotheses are largely based on theoretical approaches and numerical simulations, integrating geometry and biomechanics. Because of the mechanical properties of cells and tissues, growth forces can be redistributed within and among the elements of the anatomical system, channeling morphogenesis and shaping the spatial organization of the anatomical components. This month Tuomas Tallinen and colleagues provide a further mathematical model of the growing cortex, introducing constraints associated with the sulcal pattern. But, more incredibly, they provide an extremely elegant and efficient experimental evidence. After MRI imaging, they prepare a physical model of the fetal brain with two gel components. The outer thin layer (simulating the cortex) swells when in contact with a solvent, undergoing a tangential expansion. When this happens, the growing outer surface and the stable inner volume must properly interact in terms of physical forces and distribution of the surface to volume adjustments. The result is amazing, because it really mimics the human cortical folding! There is an incredible correspondence between the real and simulated folding pattern, in terms of topology and degree of convolution. No programming here except the growing schedule, just physical properties, structural interaction, and forces redistribution.

“Morphology is not only a study of material things and of the forms of material things, but has its dynamical aspect, under which we deal with the interpretation, in terms of force, of the operations of energy.”
(D’Arcy Wentworth Thompson – On Growth and Form, 1942)

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