Category Archives: Anatomy

Brain regional scaling

Reardon and colleagues recently published a study on the variation of human brain organization and its relationship with brain size. Using neuroimaging data from more than 3000 individuals they calculated the local surface area and estimated the areal scaling in relation to the total cortical area in order to generate a reference map for areal scaling in cortical and subcortical structures. By using three separate cohorts, three different platforms of image-acquisition, and two distinct imaging processing pipelines, they obtained the same results. Regions with positive scaling, i.e. which area increases with increasing total cortical size, were found with the prefrontal, lateral temporoparietal, and medial parietal cortices, whereas the limbic, primary visual, and primary somatosensory regions showed negative scaling. These patterns of cortical area distribution relatively to normative brain size variation were also reproduced at the individual level in terms of proportion, as, for instance, areas of positive scaling regions were positively correlated with the total cortical area. These patterns of areal scaling distribution are also comparable with patterns of brain expansion during human development and primate evolution (humans vs. macaques). In terms of cytoarchitecture, the regions of positive scaling were concentrated within association cortices, such as the default mode, dorsal attention, and frontoparietal networks, while the negative scaling regions were found within the limbic network. The association of areal scaling patterns with known patterns of mitochondria-related gene expression suggests these regions that are expanded in larger brains might differ in their metabolic profile. The authors concluded that the similarity of the areal scaling maps across development and evolution, and at the individual level, suggests a shared scaling gradient of the primate cortex. Larger brains tend to preferentially expand association cortex, specialized for integration of information, which might point to a need for an increase of the neural subtracts, such as dendrites or synapses, in order to maintain or enhance brain function in an expanded brain. Further study designs are required to investigate the relationship between cortical areal patterns and brain function.

Sofia Pedro


Woolly mammoth brain

Endocranial casts are usually the only resource for studying brain gross anatomy of an extinct species. However, sometimes, a frozen mummy can add information not only on the cortical features but also on the internal structures of the brain. Some years ago, Anastasia Kharlamova and Paul Manger published a study on the mummified brain of a Pleistocene woolly mammoth. This Yuka woolly mammoth specimen, dated approximately to 38,000 years ago, was determined to be an adolescent female aged between 6 and 9 years. Its mummified brain is unique in the state of preservation, allowing access to its external and internal morphology through the use of CT imaging techniques. Furthermore, it gave the opportunity to compare mammoths with extant African elephants’ brain, in order to characterize Elephantidae brain evolution, by determining whether elephant-specific features were already present in this specimen. The authors first compared the brains of the two species in terms of overall organization, concluding the Yuka mammoth displays the typical structure of the Elephantidae family. Direct volume comparisons were possible only for the structures which borders were clearly visible on the CT scans. The brain volume of the Yuka mammoth shrank during mummification, due to dehydration, and occupies only about 55% of the endocranial volume. Therefore, the calculated structure masses had to be corrected for such shrinkage. Moreover, due to differences in tissue fat composition, this shrinkage was heterogeneous, differing between hemispheres and between these and the cerebellum, which showed the least shrinkage. Based on subdural volume and on regression equations using extant mammals, the brain mass was determined to range between 4,230 and 4,340g. Given the average brain mass of an adult female elephant is only 300 to 400 g heavier, and that this specimen is immature, the values appear to be close to what would be expected for an adolescent woolly mammoth female. The size of the corpus callosum was also similar to that of female African and Asian elephants suggesting that, like elephants, mammoths also displayed sexual dimorphism in this structure. The comparable size of the amygdala suggests a similar organization of the limbic system, and the similarity in size and organization of the cerebellum point to a similar role in control of the trunk. This further indicates the Elephantidae family holds the largest cerebellum of all mammals, and that the cerebellar sensorimotor integration and learning movements of the trunk is a feature of this family. As the Elephantidae brain structure seems to be evolutionarily conservative, it can be assumed that the woolly mammoth could have achieved the same cognitive capacities as the extant elephants. However, further predictions of behavior and specializations would need a more detailed histological examination, which was not possible in the Yuka specimen. Nonetheless, this study provided an exceptional glimpse into the brain of an extinct species, and helped extending the understanding of the Elephantidae family.


Sofia Pedro

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

A History of Surgery

The Chirurgeon’s Apprentice is a popular blog on the website of medical historian Dr Lindsey Fitzharris who received her doctorate from University of Oxford in medical, technology and science history. Dr Fitzharris discusses the apt naming of the blog with the word ‘chirurgeon‘ the first historical reference to a practitioner of surgery. The website illuminates the often grisly but fascinating historical developments in Medicine and Surgery with focus on the Victorian era and the rapidly developing techniques and methods occurring in all scientific disciplines at this time.  Under the Knife is a well-researched and often darkly humorous video series delivered by Fitzharris where each episode details different aspects of the history of Surgery and Medicine. Dr Lindsey Fitzharris is also the author of a recent book The Butchering Art about the Victorian surgical pioneer Jospeh Lister and the development of antiseptic practices.

Alannah Pearson

Seasonal brain changes

As we already discussed, small mammal species with short life spans and high metabolisms which experience seasonal fluctuation of resources tend to undergo seasonal changes in skull size and morphology. More recently, Lázaro et al. examined how this seasonal variation affected brain size and organization in the common shrew (Sorex araneus). They collected specimens in Southern Germany, covering all seasons and the whole lifespan of the shrew, which is about 18 months. The sample was divided into three age groups: summer juvenile, winter subadult, and spring-summer adult (sexually mature). Right hemispheres were used to investigate the volumes of the different brain regions, and the left hemispheres for examining neuron morphology. They confirmed the patterns of seasonal volume variation, and observed there were differences between brain regions and between sexes. The overall volume decrease from summer to winter was more pronounced in females, while spring regrowth was similar for both sexes, thus resulting in adult sexual dimorphism with females having smaller brain volumes. Regarding the brain regions, most significant changes were observed in the hypothalamus and the thalamus, both in the winter decrease and spring regrowth. Neocortex and striatum (mostly caudoputamen) volumes decreased in winter but did not regrow in spring. Cerebellar volumes were smaller in females during winter, but reached the same volumes as males during spring regrowth. According to the authors, as the volume reduction from juveniles to subadults occurs before winter, it is more likely genetically encoded than a direct result of temperature or resources fluctuation. Furthermore, the independent variation of the different brain regions suggests a mosaic adaptation of each structure to the cognitive requirements and energetic limitations of each season. Other explanations for the different patterns of variation between the different regions might be associated with differences in energetic demands and in the potential for plasticity between brain structures. However, the authors could not find correlations between seasonal volume changes and functional demands, developmental timing, or metabolic consumption of the different brain regions. They conclude the variation in each brain structure might be influenced by functional adaptations and plasticity to different degrees. The authors also registered the variation in neuron size and morphology in three regions. The caudoputamen showed a decline in dendritic length and volume, in soma size, and in spine number and density, from juvenile to adult. The somatosensory cortex displayed only decline in soma size from summer to winter and in spine density from winter to adult. In the anterior cingulate cortex there was a reduction in soma size from juvenile to adult but in dendrite volume only from juvenile to subadult. These results cannot explain adequately the observed volumetric changes in the respective regions, and other factors that might affect volume, such as the space between cells and neuron density, should be considered in further studies. Moreover, changes in axonal innervations and myelin, and in the density of microvessels should be considered as these can also influence energetic costs.

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.


Visiting Peter Dockery and the amazing facilities of the brand new Human Biology Building at the National University of Ireland, Galway

Brain and Muscles

Among mammals, primates exhibit a trend toward increasing encephalisation. Attempts to explain the development of this trend focus on the energetic and metabolic trade-offs required to increase brain mass. The most widely discussed are variants of the Expensive Tissue Hypothesis (ETH) which proposes for any increase in brain mass other metabolically expensive tissues must decrease in size. The brain is metabolically costly with primates having larger brain sizes than other mammals and devoting up to 20% more basal metabolic rate to brain maintenance. Brain maintenance relies on aerobic cellular respiration processes, thus requiring oxygen to efficiently function. In a resting-state, up to 90% of brain maintenance is sourced from aerobic respiration. The brain does not source oxygen directly but relies on aerobic cellular respiration, converting glucose into adenosine triphosphate (ATP) to produce energy. In humans, the brain consumes, on average, around 30% of total glucose allocation. Skeletal muscle is another expensive tissue type. Muscle consumes up to 30% of resting energy expenditure with nearly 100-fold increase during high activity. Mammals have nearly 50% of their total body mass accounted for by muscle mass while primates have only 35% of total body mass accounted for by muscle mass. Of primates, humans possess 50% less muscle mass than expected for body size. Skeletal muscle comprises a mixture of fibers known as Type I (slow-twitch for prolonged activity) and Type II (fast-twitch for short, sudden activity). Both fiber types require constant oxygen supply and glucose to convert to ATP via mitochondria. Although Type II fibers consume a higher net-amount of glucose than Type I, this is done for short periods of time. Type I fibers used for prolonged activities possess greater capillary density and more mitochondria than Type II, potentially allowing significantly more efficient conversion of glucose to ATP. This could suggest muscle mass is in direct competition with the brain through glucose requirement and that any increase in brain size could require a corresponding decrease in muscle mass as evidenced in primates, especially humans.

Muchlinski et al. (2018) examined the potential trade-off between muscle mass and brain size in non-human primates. Several skeletal muscles were dissected from primate cadavers and immunohistochemistry used to isolate muscle fiber types. Body mass strongly influenced endocranial volume and muscle mass in the primate species so variables were size adjusted. Results indicated an increase in endocranial volume was associated with a decrease in muscle mass. Type I muscle fibers were negatively correlated with endocranial volume but a positive correlation between Type II and endocranial volume was not statistically significant. In general, the primates sampled possessed more Type II than Type I muscle fibers. These results are encouraging but potential bias could be introduced from the small sample size and muscle selection with larger postural and locomotor muscles, erector spinae and scalenes, not examined as the minimum sample content for immunohistochemistry could not be dissected in very small primate species. The use of published literature for endocranial volumes and body mass may introduce additional issues. Despite this, the assumption that muscle may be in direct competition with the brain appears metabolically and energetically viable and a potential avenue for proper consideration in evolutionary primatology.

Alannah Pearson

Digital Endocasts

[Book]   [Post]

Parietal lobes and tool use

The parietal lobe has a unique central location in the brain, and it is involved in higher cognitive functions. Investigating its functions and connectivity is essential to understand its role in uniquely human abilities. Two recent works have put emphasis on the importance of the parietal lobe for tool use.

Catani and colleagues investigated the intralobar parietal connectivity in human and monkey brains, using diffusion imaging tractography. In general, the patterns of white matter connectivity are similar in both species, although with some differences for areas that are distinct in humans. The larger tract connects the superior parietal lobule (SPL) to the angular and supramarginal gyri of the inferior parietal lobule, within the IPS. The authors suggest it might act to mediate the interaction between the two lobules during object manipulation, and to coordinate both dorsal and ventral visuospatial networks. The second and third larger tracts link the postcentral gyrus to the inferior parietal lobule and to the SPL, respectively. These might transmit tactile and proprioceptive information on the body orientation relatively to an object for guiding motor actions and grasp. The connection between the postcentral and the angular gyri was only observed in humans, leading the authors to highlight its role in specific cognitive functions. Particularly, its connections to SPL are key for tool use, mathematical thinking, and language and communication.

Kastner and coworkers reviewed the organization and function of the dorsal pathway of the visual system of monkey and human brains, focusing on the areas of the posterior parietal cortex within and adjacent to the intraparietal sulcus (IPS). Monkeys and humans have diverged in the functional contributions of the IPS since their last common ancestor, as some functionally-defined areas that are located within the IPS in monkeys have been partially relocated outside this sulcus in humans. The authors suggest this relocation might be due to expansion for accommodation of human-specific abilities, such as tool use. They hypothesize that humans might have developed a derived and advanced tool network from the modification of the macaque circuit for object manipulation. First, the human dorsal vision pathway must provide object shape information regardless of size and viewpoint, facilitating object recognition and mental manipulation. Second, object information is integrated with cognitive information such as working memory, allowing maintaining the information over a period of time. Finally, humans have areas that respond specifically to tool use, some of which also integrate frontal and temporal networks involved in action recognition and semantic knowledge related to tools and actions, respectively.

Both studies point at the parietal lobes and visuospatial integration as key elements for human cognitive capacity, as suggested by evidence in paleoneurology, evolutionary neuroanatomy, and cognitive archaeology.


Sofia Pedro