Archive for the 'Brain morphology' Category

Surfin’ endocasts

Endocasts and brains are difficult to analyze through traditional anatomical landmarks, because of the smooth morphology, blurred boundaries, and a noticeable individual variation. Currently, semilandmarks and surface analyses are good alternatives. Nonetheless, these two methods analyze the geometry of an “object”, ignoring its anatomical nature. If such geometrical modelling is interpreted too strictly, it may generate speculations and even incorrect conclusions. Numerical transformations behind spatial and geometrical models can be very complex and entangled, and the long chains of algorithms cannot be disentangled in any research article (the same occurs in any other field, like molecular biology, where long chains of reactions and engineering processes can’t be resumed in detail in every single paper and, necessarily, we must blindly rely on their proper functioning). In those many numerical steps, we must be aware that there may be incorrect passages, or simply algebraic assumptions that are not consistent with the real biological and evolutionary processes. More importantly, the brain is formed by so many independent elements, histological components, and cortical areas, and a pooled geometrical analysis can generate hybrid results. Anatomical landmarks are still necessary to mark boundaries and proportions, as to evaluate the real contribution of each element. Of course, anatomical landmarks are difficult to assess, they require experience, and they require inferences: as in every experimental paradigm, as in every field of science. Shape analyses deals with models, not with real anatomical entities. And models only take into considerations some specific properties of those anatomical systems, following algebraic rules that, right or wrong, represent conventional and operational assumptions. Here an opinion paper on all these issues.

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Australopithecus africanus

Amélie Beaudet and coauthors have published a shape analysis of the endocranial surface of two specimens included in the hypodigm of Australopithecus africanus, namely Sts 5 and Sts 60. They used a deformation-based approach, as to quantify the global endocranial surface variations. They compared the endocasts of the two specimens with modern humans (Homo sapiens) and chimps (Pan troglodytes and Pan paniscus). The endocranial geometry of the two piths is similar to the shape displayed by the apes. The incomplete Sts 60 lies right in between the two chimpanzees, while Sts 5 is slightly displaced toward the human form. The main difference between humans and the two australopiths can be localized in the parietal surface (larger in our species). Nonetheless, piths may present some minor shape difference on the frontal (orbital) cortex, when compared with chimps. Back in the ’20s Raymond Dart stated that, if extant African apes show a primitive scheme, a displacement of the lunate sulcus in Australopithecus might suggest a relative enlargement of the parietal cortex in these early hominids. Unfortunately, there are still disagreements on this point, because of the uncertainties associated with the identification of sulcal landmarks on fossil endocasts. Also frontal changes have been already proposed for other australopithecines. However, in this case the spatial interaction between frontal cortex and the facial system (orbits and ethmomaxillary block) may hamper a straight separation of the effects due to actual brain changes and those due to cranial constraints.

Precuneus and primates

The precuneus displays a remarkable variability in size and shape among adult humans, and it also represents a main difference between human and chimp brain morphology, being larger in our species. It can be argued that precuneus expansion in humans is due to an allometric pattern shared among primates. In this case, a large precuneus is a by-product of a big brain and scaling rules. We have now published a brain shape analysis in non-human primates, suggesting that this seems not the case. The midsagittal brain morphology in non-human primates is probably influenced by cranial architecture more than by brain differences. And, precuneus morphology is apparently not influenced by brain size, with no major differences between monkeys and apes. Therefore, its expansion in humans is likely to be a species-specific character, and not an allometric consequence of a large brain. The exact histological factors involved in this change is still to be investigated, as well as its functional (cognitive) consequences. In general, precuneus morphology is very variable also within other primate species, suggesting a noticeable plasticity. Its areas are crucial for coordination between body and vision (visuospatial integration, visual imaging, simulation, body cognition, autonoesis, etc.), and are influenced by both genetic and environmental factors (i.e., visuospatial training and practice). Its position physically matches those brain districts supposed to have undergone an expansion in the evolution of Homo sapiens, when compared with fossil hominids.

Brains and eyes

After our first survey on the morphological relationships between eyes and brains, here a comprehensive second study on this same topic. We have analyzed data from computed tomography (orbits and endocranial space) and magnetic resonance (eyes and brain), investigating modern humans, apes, and fossils. Soft tissue variation mainly deals with the distance between eyes and temporal lobes. Cranial variation mainly concerns the orientation of the orbits, probably influenced by parietal morphology and variation of the head functional axis. Phylogenetic differences are generally associated with the distance between orbits and braincase, with fossil humans showing an intermediate position between modern humans and apes. Here a Skull Box post with more details.

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.

Brainstorm …

As properly remarked in the prequel of the Planet of the Apes, we know everything about our brain, except how it does work. We are aware of such lack of knowledge, at least in theory. In practice, papers are replete of firm sentences and conclusive statements. But we use complex programs and devices, and we should not forget that these tools can only generate models of reality. Models based on algorithms that are trying to represent and simulate only some specific physical or spatial properties. Our brain models are but statistical outputs, not real “brains”. We identify brain activity through indirect blood or metabolic functions, assuming there is a strict correspondence between those signals and our concept of “at work”. A correspondence that is reasonable, but not that strict. Even basic anatomical issues can be blurred after a more detailed scrutiny, mostly when previous knowledge is based on information that has been copy-and-pasted through decades. We are more and more finding strange factors influencing our results. Apparently, the brain undergoes daily variations, and the braincase may suffer seasonal changes. Brain structure and function can be even influenced by head position and posture. These unexpected effects recommend further caution when making too general conclusions from specific and punctual results. Let’s take into account that we still miss much information on gross neuroanatomical components. For example, we still ignore the function of the cerebellum, that has four time the number of neurons of the brain, and we still don’t know all the functions of the glial cells, that may be nine times more numerous than neurons. And, we don’t know how much brain anatomy and functions are the result of genetic programs or environmental influences. In only few weeks, training can easily improve or demote brain complexity. Nothing new under the sun: science is about hypotheses, and hypotheses need to be tested and validated. Our models are tentatively designed with this scope in mind. This summer post is a summary of articles concerning some methodological limitations and some curious result dealing with brain structure and function. And an invitation to interpret results for what they are: evidences supporting or rejecting hypotheses. Remember that those are not neurons: just pixels! Take it easy …

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.


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