Archive for the 'Methods' Category

Parietal cortex

In November 2017 Ashley Morhardt organized a Karger Workshop at Hyattsville (USA), entitled “From fossils to function: integrative and diverse approaches to vertebrate evolutionary neuroscience“. The workshop was included in the activities of the J. B. Johnston Club, and papers are  now published in Brain Behavior and Evolution. My contribution is a review on the evolution of the parietal cortex in the human genus. Articles will be freely accessible for the next six months. Have a look!

Electrodermal archaeology

After all those surveys on parietal lobes and parietal evolution, some years ago we began investigating some functions particularly associated with the parietal cortex, and generically labeled as visuospatial integration. Some visuospatial behaviors can be inferred in fossils, according to anatomical and archaeological evidence. In my lab, we are interested in aspects bridging cognition, body, and tools. In a recent paper published in Progress in Brain Research we have applied electrodermal analysis to investigate the cognitive response during a haptic experience with stone tools. Electrodermal signals have been employed here to evaluate changes in emotion and attention during stone tool manipulation, as to evidence whether different tools exert different cognitive responses when handled. New methods for cognitive archaeology!

 

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The paper is part of a volume entitled “Cerebral Lateralization and Cognition: Evolutionary and Developmental Investigations of Behavioral Biases“, edited by Gillian Forrester, William Hopkins, Kristelle Hudry and Annukka Lindell.

Digital Endocasts

A new Springer book: Digital Endocasts: from skulls to brains. Chapter 1 (Holloway) is an introduction to physical casting. Chapter 2 (Ogihara et al.) deals with digital reconstructions of Neandertals and early modern humans’ endocasts. Chapter 3 (Kobayashi et al.) is about inferences on cortical subdivision from skull morphology. Chapter 4 (Beaudet and Gilissen) introduces paleoneurology on non-human primates, and Chapter 5 (Walsh and Knoll) is on birds and dinosaurs. Chapter 6 (Rangel de Lázaro et al.) reviews  craniovascular traits. Chapter 7 (Bruner) is on functional craniology and multivatiate statistics. Chapter 8 (Gómez-Robles et al.) concerns brain and landmarks, and Chapter 9 (Pereira-Pedro and Bruner) concerns endocasts and landmarks. Chapter 10 (Dupej et al.) is on endocranial surface comparisons. Chapter 11 (Kochiyama et al.) presents computed tools to infer brain morphology in fossil species. Chapter 12 (Neubauer and Gunz) deals with brain ontogeny and phylogeny. Chapter 13 (Bruner et al.) is on an application of network analysis to brain parcellation and cortical spatial contiguity. Then, there are chapters dedicated to the evolution of the frontal lobes (Chapter 14 – Parks and Smaers), of the parietal lobes (Chapter 15 – Bruner et al.), of the temporal lobes (Chapter 16 – Bryant and Preuss), of the occipital lobes (Chapter 17 – Todorov and de Sousa) and of the cerebellum (Chapter 18 – Tanabe et al.). The aim of the book is to provide a comprehensive perspective on issues associated with endocasts and brain evolution, and to promote a general overview of current methods in paleoneurology. The book has been published within the series “Replacement of Neanderthals by Modern Humans“. Here on the Springer webpage.

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.

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 …

Endocasting

I have found a very useful article published one year ago by Amy Balanoff and colleagues on Journal of Anatomy, a guide on “Best Practice for Digitally Constructing Endocranial Casts”. The paper is a detailed and comprehensive methodological overview on digital endocasting, introducing techniques, parameters, programs, problems, tools, and many suggestions on procedures and operational choices. Although the paper is more focused on birds and dinosaurs, it can be perfectly suited for human paleoneurology as well. The authors have organized the article as a set of replies to essential questions dealing with endocranial cast digital reconstruction. Pretty clear flow charts supply quick solutions for basic technical issues. The paper takes into account technical aspects (machines, physics, programs) as well as biological aspects (bone, skull, brain). Indeed, an extremely useful lecture for those who want to step into digital anatomy and paleoneurology.

Frontal surfaces

beaudet-and-bruner-2017

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.


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