Brain scaling in mammalian evolution as a consequence of concerted and mosaic changes in numbers of neurons and average neuronal cell size

Extensive and diverse patterns of cell death sculpt neural networks in insects

Changes to the structure and function of neural networks are thought to underlie the evolutionary adaptation of animal behaviours. Among the many developmental phenomena that generate change programmed cell death (PCD) appears to play a key role. We show that cell death occurs continuously throughout insect neurogenesis and happens soon after neurons are born. Mimicking an evolutionary role for increasing cell numbers, we artificially block PCD in the medial neuroblast lineage in Drosophila melanogaster, which results in the production of ‘undead’ neurons with complex arborisations and distinct neurotransmitter identities. Activation of these ‘undead’ neurons and recordings of neural activity in behaving animals demonstrate that they are functional. Focusing on two dipterans which have lost flight during evolution we reveal that reductions in populations of flight interneurons are likely caused by increased cell death during development. Our findings suggest that the evolutionary modulation of death-based patterning could generate novel network configurations.

Just like a sculptor chips away at a block of granite to make a statue, the nervous system reaches its mature state by eliminating neurons during development through a process known as programmed cell death.

In vertebrates, this mechanism often involves newly born neurons shrivelling away and dying if they fail to connect with others during development. Most studies in insects have focused on the death of neurons that occurs at metamorphosis, during the transition between larva to adult, when cells which are no longer needed in the new life stage are eliminated.

Pop et al. harnessed a newly designed genetic probe to point out that, in fruit flies, programmed cell death of neurons at metamorphosis is not the main mechanism through which cells die. Rather, the majority of cell death takes place as soon as neurons are born throughout all larval stages, when most of the adult nervous system is built. To gain further insight into the role of this ‘early’ cell death, the neurons were stopped from dying, showing that these cells were able to reach maturity and function. Together, these results suggest that early cell death may be a mechanism fine-tuned by evolution to shape the many and varied nervous systems of insects.

To explore this, Pop et al. looked for hints of early cell death in relatives of fruit flies that are unable to fly: the swift lousefly and the bee lousefly. This analysis showed that early cell death is likely to occur in these two insects, but it follows different patterns than in the fruit fly, potentially targeting the neurons that would have controlled flight in these flies’ ancestors.

Brains are the product of evolution: learning how neurons change their connections and adapt could help us understand how the brain works in health and disease. This knowledge may also be relevant to work on artificial intelligence, a discipline that often bases the building blocks and connections in artificial ‘brains’ on how neurons communicate with one another.

Relationship between binge eating and associated eating behaviors with subcortical brain volumes and cortical thickness

BACKGROUND

Binge eating disorder (BED) is the most prevalent eating disorder. We examined the presence of binge eating (BE) and three associated eating behaviors in relation to subcortical regional volumes and cortical thickness from brain scans.

METHODS

We processed structural MRI brain scans for 466 individuals from the Nathan Kline Institute Rockland Sample using Freesurfer. We investigated subcortical volumes and cortical thicknesses among those with and without BE and in relation to the scores on dietary restraint, disinhibition, and hunger from the Three-Factor Eating Questionnaire (TFEQ). We conducted a whole-brain analysis and a region of analysis (ROI) using a priori regions associated with BE and with the three eating factors. We also compared scores on the three TFEQ factors for the BE and non-BE.

RESULTS

The BE group had higher scores for dietary restraint (p = .013), disinhibition (p = 1.22E-07), and hunger (p = 5.88E-07). In the whole-brain analysis, no regions survived correction for multiple comparisons (FDR corrected p<0.01) for either BE group or interaction with TFEQ. However, disinhibition scores correlated positively with left nucleus accumbens (NAc) volume (p < 0.01 FDR corrected). In the ROI analysis, those with BE also had greater left NAc volume (p = 0.008, uncorrected) compared to non-BE.

LIMITATIONS

Limitations include potential self-report bias on the EDE-Q and TFEQ.

CONCLUSIONS

The findings show that BE and disinhibition scores were each associated with greater volumes in the left NAc, a reward area, consistent with a greater drive and pleasure for food.

Brain Volume Fractions in Mammals in Relation to Behavior in Carnivores, Primates, Ungulates, and Rodents

The volume fraction (VF) of a given brain region, or the proper mass, ought to reflect the importance of that region in the life of a given species. This study sought to examine the VF of various brain regions across 61 different species of mammals to discern if there were regularities or differences among mammalian orders. We examined the brains of carnivores (n = 17), ungulates (n = 8), rodents (n = 7), primates (n = 11), and other mammals (n = 18) from the online collections at the National Museum of Health and Medicine. We measured and obtained the VF of several brain regions: the striatum, thalamus, neocortex, cerebellum, hippocampus, and piriform area. We refined our analyses by using phylogenetic size correction, yielding the corrected (c)VF. Our groups showed marked differences in gross brain architecture. Primates and carnivores were divergent in some measures, particularly the cVF of the striatum, even though their overall brain size range was roughly the same. Rodents predictably had relatively large cVFs of subcortical structures due to the fact that their neocortical cVF was smaller, particularly when compared to primates. Not so predictably, rodents had the largest cerebellar cVF, and there were marked discrepancies in cerebellar data across groups. Ungulates had a larger piriform area than primates, perhaps due to their olfactory processing abilities. We provide interpretations of our results in the light of the comparative behavioral and neuroanatomical literature.

Allometric Scaling Rules of the Cerebellum in Galliform Birds

Although the internal circuitry of the cerebellum is highly conserved across vertebrate species, the size and shape of the cerebellum varies considerably. Recent comparative studies have examined the allometric rules between cerebellar mass and number of neurons, but data are lacking on the numbers and sizes of Purkinje and granule cells or scaling of cerebellar foliation. Here, we investigate the allometric rules that govern variation in the volumes of the layers of the cerebellum, the numbers and sizes of Purkinje cells and granule cells and the degree of the cerebellar foliation across 7 species of galliform birds. We selected Galliformes because they vary greatly in body and brain sizes. Our results show that the molecular, granule and white matter layers all increase in volume at the same rate relative to total cerebellum volume. Both numbers and sizes of Purkinje cells increased with cerebellar volume, but numbers of Purkinje cells increased at a much faster rate than size. Granule cell numbers increased with cerebellar volume, but size did not. Sizes and numbers of Purkinje cells as well as numbers of granule cells were positively correlated with the degree of cerebellar foliation, but granule cell size decreased with higher degrees of foliation. The concerted changes among the volumes of cerebellar layers likely reflects the conserved neural circuitry of the cerebellum. Also, our data indicate that the scaling of cell sizes can vary markedly across neuronal populations, suggesting that evolutionary changes in cell sizes might be more complex than what is often assumed.

A Large-Scale High-Density Weighted Structural Connectome of the Macaque Brain Acquired by Predicting Missing Links

As a substrate for function, large-scale brain structural networks are crucial for fundamental and systems-level understanding of primate brains. However, it is challenging to acquire a complete primate whole-brain structural connectome using track tracing techniques. Here, we acquired a weighted brain structural network across 91 cortical regions of a whole macaque brain hemisphere with a connectivity density of 59% by predicting missing links from the CoCoMac-based binary network with a low density of 26.3%. The prediction model combines three factors, including spatial proximity, topological similarity, and cytoarchitectural similarity-to predict missing links and assign connection weights. The model was tested on a recently obtained high connectivity density yet partial-coverage experimental weighted network connecting 91 sources to 29 target regions; the model showed a prediction sensitivity of 74.1% in the predicted network. This predicted macaque hemisphere-wide weighted network has module segregation closely matching functional domains. Interestingly, the areas that act as integrators linking the segregated modules are mainly distributed in the frontoparietal network and correspond to the regions with large wiring costs in the predicted weighted network. This predicted weighted network provides a high-density structural dataset for further exploration of relationships between structure, function, and metabolism in the primate brain.

Investigation of cognitive mechanisms and strategy on solving multiple string-pulling problems in Azure-winged magpie (Cyanopica cyanus)

String-pulling tasks are a widely used paradigm in animal cognition research. The present study tested whether ten azure-winged magpies (Cyanopica cyanus) could solve a series of multiple-strings problems with the aim of systematically investigating which rules this species uses to solve different-patterned string tasks, i.e., tasks in which subjects have to choose between two strings only one of which is connected to bait. When the subjects faced the parallel strings task (T1), five birds (C3, C5, C8, C9, and C10) were able to solve the task and acted in a goal-directed manner. Three birds (C5, C8, and C9) successfully solved the oblique parallel strings task (T3). The azure-winged magpies exhibited proximity selection in the oblique parallel strings task (C1 and C4 in T2), and the task with one string folded at a right angle (C3, C6 and C8 in T5). Several subjects also performed simple strategies in other unresolved tasks, e.g., random selection, trial-and-error learning, and side bias strategies (i.e., a certain degree of "left-handed" tendency). These results demonstrated that the azure-winged magpie possesses the potential to solve simple multiple-string tasks, although when faced with more difficult problems they could not solve them.

Mini-review: Aging of the neuroendocrine system: Insights from nonhuman primate models

The neuroendocrine system (NES) plays a crucial role in synchronizing the physiology and behavior of the whole organism in response to environmental constraints. The NES consists of a hypothalamic-pituitary-target organ axis that acts in coordination to regulate growth, reproduction, stress and basal metabolism. The growth (or somatotropic), hypothalamic-pituitary-gonadal (HPG), hypothalamic-pituitary-adrenal (HPA) and hypothalamic-pituitary-thyroid (HPT) axes are therefore finely tuned by the hypothalamus through the successive release of hypothalamic and pituitary hormones to control the downstream physiological functions. These functions rely on a complex set of mechanisms requiring tight synchronization between peripheral organs and the hypothalamic-pituitary complex, whose functionality can be altered during aging. Here, we review the results of research on the effects of aging on the NES of nonhuman primate (NHP) species in wild and captive conditions. A focus on the age-related dysregulation of the master circadian pacemaker, which, in turn, alters the synchronization of the NES with the organism environment, is proposed. Finally, practical and ethical considerations of using NHP models to test the effects of nutrition-based or hormonal treatments to combat the deterioration of the NES are discussed.

Quantification of neurons in the olfactory bulb of the catsharks Scyliorhinus canicula (Linnaeus, 1758) and Galeus melastomus (Rafinesque, 1810)

In vertebrates, the olfactory bulb (OB) is the zone of the brain devoted to receiving the olfactory stimuli. The size of the OB relative to the size of the brain has been positively correlated to a good olfactory capability but, recently, this correlation was questioned after new investigation techniques were developed. Among them, the isotropic fractionator allows to estimate the number of neurons and non-neurons in a given portion of nervous tissue. To date, this technique has been applied in a number of species; in particular the OB was separately analyzed in numerous mammals and in a single crocodile species. Thus, a quantitative description of the OB's cells is available for a small portion of vertebrates. Main aim of this work was to apply isotropic fractionator to investigate the olfactory capability of elasmobranch fishes, whose traditional concept of outstanding olfaction has recently been scaled down by anatomical and physiological studies. For this purpose, the OB of two elasmobranch species, Galeus melastomus and Scyliorhinus canicula, was studied leading to the determination of the number of neurons vs non-neurons in the OB of the specimens. In addition, the obtained cell quantification was related to the olfactory epithelium surface area to obtain a new parameter that encapsulates both information on the peripheral olfactory organ and the OB. The analyzed species resulted in an overall similar quantitative organization of the peripheral olfactory system; slight differences were detected possibly reflecting different environment preference and feeding strategy. Moreover, the non-neurons/neurons ratio of these species, compared to those available in the literature, seems to place elasmobranch fishes among the vertebrate species in which olfaction plays an important role.

The microtubule skeleton and the evolution of neuronal complexity in vertebrates

The evolution of a highly developed nervous system is mirrored by the ability of individual neurons to develop increased morphological complexity. As microtubules (MTs) are crucially involved in neuronal development, we tested the hypothesis that the evolution of complexity is driven by an increasing capacity of the MT system for regulated molecular interactions as it may be implemented by a higher number of molecular players and a greater ability of the individual molecules to interact. We performed bioinformatics analysis on different classes of components of the vertebrate neuronal MT cytoskeleton. We show that the number of orthologs of tubulin structure proteins, MT-binding proteins and tubulin-sequestering proteins expanded during vertebrate evolution. We observed that protein diversity of MT-binding and tubulin-sequestering proteins increased by alternative splicing. In addition, we found that regions of the MT-binding protein tau and MAP6 displayed a clear increase in disorder extent during evolution. The data provide evidence that vertebrate evolution is paralleled by gene expansions, changes in alternative splicing and evolution of coding sequences of components of the MT system. The results suggest that in particular evolutionary changes in tubulin-structure proteins, MT-binding proteins and tubulin-sequestering proteins were prominent drivers for the development of increased neuronal complexity.

The amygdala of the common shrew, guinea pig, rabbit, fox and pig: five flavours of the mammalian amygdala as a consequence of clade-specific mosaic-like evolution

The amygdala is a part of neural networks that contribute to the regulation of emotional behaviours and emotional learning, stress response, and olfactory, pheromonal and reproductive functions. All these various functions are processed by the three main functional systems, frontotemporal, autonomic and olfactory, which are derived from different telencephalic sources (claustrum, striatum and olfactory cortex) and are represented, respectively, by the basolateral complex (BLC), the central complex (CC) and corticomedial complex (CMC) of the amygdala. The question arises of how these three functional systems evolved during mammalian phylogeny to fit the amygdala to specific needs of various animals. In the present study, we provide quantitative information regarding the individual volumes and neuron numbers in the BLC, CC and CMC of the common shrew, guinea pig, rabbit, fox and pig, a series of animals arranged according to increasing size and complexity of the brain. The results show that, in this series of animals, the BLC underwent a gradual size increase in volume and number of neurons, whereas the CMC was gradually reduced with regard to both these measures. The CC was more or less conserved across studied species. For example, the volume of the amygdala in pigs is ~250 times larger than that in shrews and it also has almost 26 times as many neurons as the amygdala of shrews. However, the volumes of the BLC, CC and CMC were ~380, 208 and 148 times larger, respectively, in pigs than in shrews. The number of neurons in these three regions was ~38, 23 and 20 times greater, respectively, in pigs than in shrews. The results also show striking morphometric similarities of the amygdala in the guinea pig and rabbit as well as fox and pig. For example, the percentages of neurons in the fox and pig are 42.23% and 42.78%, respectively, for the BLC, 16.64% and 16.58%, respectively, for the CC, and 41.12% and 40.64%, respectively, for the CMC. In conclusion, our results indicate that the amygdala does not evolve as a single unit but, instead, the three main functional systems evolved independently, which suggests that brain structures with major functional links evolve together independently of evolutionary changes in other unrelated structures. The size progression of the BLC parallels the size progression of the neocortex with which it is strongly functionally linked, whereas the CMC is strongly connected to olfactory regions, and all these structures follow the same regression course. Remarkable morphometric similarity of the amygdala in the guinea pig and rabbit as well as in the fox and pig, however, suggest that there must also be another mechanism shaping the morphology of the amygdala and the brain during evolution. The gradual nature of size changes in the BLC and CMC support this hypothesis as well.

Artificial selection on brain size leads to matching changes in overall number of neurons

Neurons are the basic computational units of the brain, but brain size is the predominant surrogate measure of brain functional capacity in comparative and cognitive neuroscience. This approach is based on the assumption that larger brains harbor higher numbers of neurons and their connections, and therefore have a higher information-processing capacity. However, recent studies have shown that brain mass may be less strongly correlated with neuron counts than previously thought. Till now, no experimental test has been conducted to examine the relationship between evolutionary changes in brain size and the number of brain neurons. Here, we provide such a test by comparing neuron number in artificial selection lines of female guppies (Poecilia reticulata) with >15% difference in relative brain mass and numerous previously demonstrated cognitive differences. Using the isotropic fractionator, we demonstrate that large-brained females have a higher overall number of neurons than small-brained females, but similar neuronal densities. Importantly, this difference holds also for the telencephalon, a key region for cognition. Our study provides the first direct experimental evidence that selection for brain mass leads to matching changes in number of neurons and shows that brain size evolution is intimately linked to the evolution of neuron number and cognition.

Life history changes accompany increased numbers of cortical neurons: A new framework for understanding human brain evolution

Narratives of human evolution have focused on cortical expansion and increases in brain size relative to body size, but considered that changes in life history, such as in age at sexual maturity and thus the extent of childhood and maternal dependence, or maximal longevity, are evolved features that appeared as consequences of selection for increased brain size, or increased cognitive abilities that decrease mortality rates, or due to selection for grandmotherly contribution to feeding the young. Here I build on my recent finding that slower life histories universally accompany increased numbers of cortical neurons across warm-blooded species to propose a simpler framework for human evolution: that slower development to sexual maturity and increased post-maturity longevity are features that do not require selection, but rather inevitably and immediately accompany evolutionary increases in numbers of cortical neurons, thus fostering human social interactions and cultural and technological evolution as generational overlap increases.

Rethinking the Effects of Body Size on the Study of Brain Size Evolution

Body size correlates with most structural and functional components of an organism’s phenotype – brain size being a prime example of allometric scaling with animal size. Therefore, comparative studies of brain evolution in vertebrates rely on controlling for the scaling effects of body size variation on brain size variation by calculating brain weight/body weight ratios. Differences in the brain size-body size relationship between taxa are usually interpreted as differences in selection acting on the brain or its components, while selection pressures acting on body size, which are among the most prevalent in nature, are rarely acknowledged, leading to conflicting and confusing conclusions. We address these problems by comparing brain-body relationships from across >1,000 species of birds and non-avian reptiles. Relative brain size in birds is often assumed to be 10 times larger than in reptiles of similar body size. We examine how differences in the specific gravity of body tissues and in body design (e.g., presence/absence of a tail or a dense shell) between these two groups can affect estimates of relative brain size. Using phylogenetic comparative analyses, we show that the gap in relative brain size between birds and reptiles has been grossly exaggerated. Our results highlight the need to take into account differences between taxa arising from selection pressures affecting body size and design, and call into question the widespread misconception that reptile brains are small and incapable of supporting sophisticated behavior and cognition.

The reliability of the isotropic fractionator method for counting total cells and neurons

BACKGROUND

The Isotropic Fractionator (IF) is a method to determine the cellular composition of nervous tissue. It has been mostly applied to assess variation across species, where differences are expected to be large enough not to be masked by methodological error. However, understanding the sources of variation in the method is important if the goal is to detect smaller differences, for example, in same-species comparisons. Comparisons between different mice strains suggest that the IF is consistent enough to detect these differences. Nevertheless, the reliability of the method has not yet been examined directly.

METHOD

In this study, we evaluate the reliability of the method for the determination of cellular and neuronal numbers of Swiss mice. We performed repeated cell counts of the same material by different experimenters to quantify different sources of variation.

RESULTS

In total cell counts, we observed that for the cerebral cortex most of the variance was at the counter level. For the cerebellum, most of the variance is attributed to the sample itself. As for neurons, random error along with the immunostaining correspond to most of the variation, both in the cerebral cortex and in the cerebellum. Test-retest reliability coefficients were relatively high, especially for cell counts.

CONCLUSIONS

Although biases between counters and random variation in staining could be problematic when aggregating data from different sources, we offer practical suggestions to improve the reliability of the method. While small, this study is a most needed step towards more precise measurement of the brain's cellular composition.

White matter volume and white/gray matter ratio in mammalian species as a consequence of the universal scaling of cortical folding

Because the white matter of the cerebral cortex contains axons that connect distant neurons in the cortical gray matter, the relationship between the volumes of the 2 cortical compartments is key for information transmission in the brain. It has been suggested that the volume of the white matter scales universally as a function of the volume of the gray matter across mammalian species, as would be expected if a global principle of wiring minimization applied. Using a systematic analysis across several mammalian clades, here we show that the volume of the white matter does not scale universally with the volume of the gray matter across mammals and is not optimized for wiring minimization. Instead, the ratio between volumes of gray and white matter is universally predicted by the same equation that predicts the degree of folding of the cerebral cortex, given the clade-specific scaling of cortical thickness, such that the volume of the gray matter (or the ratio of gray to total cortical volumes) divided by the square root of cortical thickness is a universal function of total cortical volume, regardless of the number of cortical neurons. Thus, the very mechanism that we propose to generate cortical folding also results in compactness of the white matter to a predictable degree across a wide variety of mammalian species.

The causal influence of brain size on human intelligence: Evidence from within-family phenotypic associations and GWAS modeling

There exists a moderate correlation between MRI-measured brain size and the general factor of IQ performance (g), but the question of whether the association reflects a theoretically important causal relationship or spurious confounding remains somewhat open. Previous small studies (n < 100) looking for the persistence of this correlation within families failed to find a tendency for the sibling with the larger brain to obtain a higher test score. We studied the within-family relationship between brain volume and intelligence in the much larger sample provided by the Human Connectome Project (n = 1,022) and found a highly significant correlation (disattenuated ρ = 0.18, p < .001). We replicated this result in the Minnesota Center for Twin and Family Research (n = 2,698), finding a highly significant within-family correlation between head circumference and intelligence (disattenuated ρ = 0.19, p < .001). We also employed novel methods of causal inference relying on summary statistics from genome-wide association studies (GWAS) of head size (n ≈ 10,000) and measures of cognition (257,000 < n < 767,000). Using bivariate LD Score regression, we found a genetic correlation between intracranial volume (ICV) and years of education (EduYears) of 0.41 (p < .001). Using the Latent Causal Variable method, we found a genetic causality proportion of 0.72 (p < .001); thus the genetic correlation arises from an asymmetric pattern, extending to sub-significant loci, of genetic variants associated with ICV also being associated with EduYears but many genetic variants associated with EduYears not being associated with ICV. This is the pattern of genetic results expected from a causal effect of brain size on intelligence. These findings give reason to take up the hypothesis that the dramatic increase in brain volume over the course of human evolution has been the result of natural selection favoring general intelligence.

Local transgene expression and whole-body transgenesis to model brain diseases in nonhuman primate

Animal model is an essential tool in the life sciences research, notably in understanding the pathogenesis of the diseases and for further therapeutic intervention success. Rodents have been the most frequently used animals to model human disease since the establishment of gene manipulation technique. However, they remain inadequate to fully mimic the pathophysiology of human brain disease, partially due to huge differences between rodents and humans in terms of anatomy, brain function, and social behaviors. Nonhuman primates are more suitable in translational perspective. Thus, genetically modified animals have been generated to investigate neurologic and psychiatric disorders. The classical transgenesis technique is not efficient in that model; so, viral vector-mediated transgene delivery and the new genome-editing technologies have been promoted. In this review, we summarize some of the technical progress in the generation of an ad hoc animal model of brain diseases by gene delivery and real transgenic nonhuman primate.

Flightless birds are not neuroanatomical analogs of non-avian dinosaurs

Background

In comparative neurobiology, major transitions in behavior are thought to be associated with proportional size changes in brain regions. Bird-line theropod dinosaurs underwent a drastic locomotory shift from terrestrial to volant forms, accompanied by a suite of well-documented postcranial adaptations. To elucidate the potential impact of this locomotor shift on neuroanatomy, we first tested for a correlation between loss of flight in extant birds and whether the brain morphology of these birds resembles that of their flightless, non-avian dinosaurian ancestors. We constructed virtual endocasts of the braincase for 80 individuals of non-avian and avian theropods, including 25 flying and 19 flightless species of crown group birds. The endocasts were analyzed using a three-dimensional (3-D) geometric morphometric approach to assess changes in brain shape along the dinosaur-bird transition and secondary losses of flight in crown-group birds (Aves).

Results

While non-avian dinosaurs and crown-group birds are clearly distinct in endocranial shape, volant and flightless birds overlap considerably in brain morphology. Phylogenetically informed analyses show that locomotory mode does not significantly account for neuroanatomical variation in crown-group birds. Linear discriminant analysis (LDA) also indicates poor predictive power of neuroanatomical shape for inferring locomotory mode. Given current sampling, Archaeopteryx, typically considered the oldest known bird, is inferred to be terrestrial based on its endocranial morphology.

Conclusion

The results demonstrate that loss of flight does not correlate with an appreciable amount of neuroanatomical changes across Aves, but rather is partially constrained due to phylogenetic inertia, evident from sister taxa having similarly shaped endocasts. Although the present study does not explicitly test whether endocranial changes along the dinosaur-bird transition are due to the acquisition of powered flight, the prominent relative expansion of the cerebrum, in areas associated with flight-related cognitive capacity, suggests that the acquisition of flight may have been an important initial driver of brain shape evolution in theropods.

Electronic supplementary material

The online version of this article (10.1186/s12862-018-1312-0) contains supplementary material, which is available to authorized users.

Extreme Enlargement of the Cerebellum in a Clade of Teleost Fishes that Evolved a Novel Active Sensory System

Brains, and the distinct regions that make up brains, vary widely in size across vertebrates [1, 2]. Two prominent hypotheses have been proposed to explain brain region scaling evolution. The mosaic hypothesis proposes that changes in the relative sizes of particular brain regions are the result of selection acting independently on those regions [2, 3]. The concerted hypothesis proposes that the brain evolves as a coordinated structure due to developmental constraints [4]. These hypotheses have been widely debated [3-7], and recent studies suggest a combination of the two best describes vertebrate brain region scaling [8-10]. However, no study has addressed how the mosaic and concerted models relate to the evolution of novel behavioral phenotypes. We addressed this question using African mormyroid fishes. The mormyroids have evolved a novel active electrosensory system and are well known for having extreme encephalization [11] and a large cerebellum [2, 12], which is cited as a possible example of mosaic evolution [2]. We found that compared to outgroups without active electrosensing, mormyroids experienced mosaic increases in the sizes of the cerebellum and hindbrain, and mosaic decreases in the sizes of the telencephalon, optic tectum, and olfactory bulb. However, the evolution of extreme encephalization within mormyroids was associated with concerted changes in the sizes of all brain regions. This suggests that mosaic evolutionary change in the regional composition of the brain is most likely to occur alongside the evolution of novel behavioral functions, but not with the evolution of extreme encephalization.

Inferring Evolutionary Process From Neuroanatomical Data

Brain evolution has interested neuroanatomists for over a century. These interests often fall on how free the brain is to evolve independently of the body, how free brain regions are to evolve independently of each other, and how different environmental and ecological factors affect the brain over evolutionary time. But despite major advances in phylogenetic methods, comparative neuroanatomists have tended to limit their macroevolutionary toolbox to regression-based analyses and ignored the scope of evolutionary process-based models at their disposal. This Review summarizes the history of comparative neuroanatomy and highlights the pitfalls of the methodologies traditionally used. It provides an overview of evolutionary process-based modeling approaches for investigating univariate and multivariate data, as well as more sophisticated methods that incorporate hypotheses about biotic and abiotic pressures that may drive brain evolution. The benefits of evolutionary process-based models, and shortcomings of regression-based ones, are illustrated with widely used neuroanatomical data. Ultimately, the intent of this Review is to be a guide for subsuming macroevolutionary methods not typically used in comparative neuroanatomy, in order to improve our understanding of how the brain evolves.

Evaluating the gray and white matter energy budgets of human brain function

The insatiable appetite for energy to support human brain function is mainly supplied by glucose oxidation (CMR_glc(ox)). But how much energy is consumed for signaling and nonsignaling processes in gray/white matter is highly debated. We examined this issue by combining metabolic measurements of gray/white matter and a theoretical calculation of bottom-up energy budget using biophysical properties of neuronal/glial cells in conjunction with species-exclusive electrophysiological and morphological data. We calculated a CMR_glc(ox)-derived budget and confirmed it with experimental results measured by PET, autoradiography, ¹³C-MRS, and electrophysiology. Several conserved principles were observed regarding the energy costs for brain's signaling and nonsignaling components in both human and rat. The awake resting cortical signaling processes and mass-dependent nonsignaling processes, respectively, demand ∼70% and ∼30% of CMR_glc(ox). Inhibitory neurons and glia need 15-20% of CMR_glc(ox), with the rest demanded by excitatory neurons. Nonsignaling demands dominate in white matter, in near opposite contrast to gray matter demands. Comparison between ¹³C-MRS data and calculations suggests ∼1.2 Hz glutamatergic signaling rate in the awake human cortex, which is ∼4 times lower than signaling in the rat cortex. Top-down validated bottom-up budgets could allow computation of anatomy-based CMR_glc(ox) maps and accurate cellular level interpretation of brain metabolic imaging.

The Epigenetic Basis of Individuality

This commentary reviews the concept of experience-dependent epigenetic modifications in the CNS as a core mechanism underlying individuality and individuation at the behavioral level. I use the term individuation to refer to the underlying neurobiological processes that result in individuality, with the discussion focusing on individuality of cognitive, emotional, and behavioral repertoire. The review describes recent work supporting the concept of neuroepigenetic mechanisms underlying individuation, possible roles of transgenerational effects, and implications for precision medicine.

Overproduction of Neurons Is Correlated with Enhanced Cortical Ensembles and Increased Perceptual Discrimination

Brains vary greatly in neuronal number and density, even across individuals within the same species, yet it remains unclear whether such variation leads to differences in brain function or behavior. By imaging cortical activity of a mouse model in which neuronal production is moderately enhanced in utero, we find that animals with more cortical neurons also develop enhanced functional correlations and more distinct neuronal ensembles in primary visual cortex. These mice also have sharper orientation discrimination in their visual behavior. These results unveil a correlation between neuronal ensembles and behavior and suggest that neuronal number is linked to functional modularity and perceptual discrimination of visual cortex. By experimentally linking differences in neuronal number and behavior, our findings could help explain how evolutionary and developmental variability of individual and species brain size may lead to perceptual and cognitive differences.

Concerted and mosaic evolution of functional modules in songbird brains

Vertebrate brains differ in overall size, composition and functional capacities, but the evolutionary processes linking these traits are unclear. Two leading models offer opposing views: the concerted model ascribes major dimensions of covariation in brain structures to developmental events, whereas the mosaic model relates divergent structures to functional capabilities. The models are often cast as incompatible, but they must be unified to explain how adaptive changes in brain structure arise from pre-existing architectures and developmental mechanisms. Here we show that variation in the sizes of discrete neural systems in songbirds, a species-rich group exhibiting diverse behavioural and ecological specializations, supports major elements of both models. In accordance with the concerted model, most variation in nucleus volumes is shared across functional domains and allometry is related to developmental sequence. Per the mosaic model, residual variation in nucleus volumes is correlated within functional systems and predicts specific behavioural capabilities. These comparisons indicate that oscine brains evolved primarily as a coordinated whole but also experienced significant, independent modifications to dedicated systems from specific selection pressures. Finally, patterns of covariation between species and brain areas hint at underlying developmental mechanisms.

Dogs Have the Most Neurons, Though Not the Largest Brain: Trade-Off between Body Mass and Number of Neurons in the Cerebral Cortex of Large Carnivoran Species

Carnivorans are a diverse group of mammals that includes carnivorous, omnivorous and herbivorous, domesticated and wild species, with a large range of brain sizes. Carnivory is one of several factors expected to be cognitively demanding for carnivorans due to a requirement to outsmart larger prey. On the other hand, large carnivoran species have high hunting costs and unreliable feeding patterns, which, given the high metabolic cost of brain neurons, might put them at risk of metabolic constraints regarding how many brain neurons they can afford, especially in the cerebral cortex. For a given cortical size, do carnivoran species have more cortical neurons than the herbivorous species they prey upon? We find they do not; carnivorans (cat, mongoose, dog, hyena, lion) share with non-primates, including artiodactyls (the typical prey of large carnivorans), roughly the same relationship between cortical mass and number of neurons, which suggests that carnivorans are subject to the same evolutionary scaling rules as other non-primate clades. However, there are a few important exceptions. Carnivorans stand out in that the usual relationship between larger body, larger cortical mass and larger number of cortical neurons only applies to small and medium-sized species, and not beyond dogs: we find that the golden retriever dog has more cortical neurons than the striped hyena, African lion and even brown bear, even though the latter species have up to three times larger cortices than dogs. Remarkably, the brown bear cerebral cortex, the largest examined, only has as many neurons as the ten times smaller cat cerebral cortex, although it does have the expected ten times as many non-neuronal cells in the cerebral cortex compared to the cat. We also find that raccoons have dog-like numbers of neurons in their cat-sized brain, which makes them comparable to primates in neuronal density. Comparison of domestic and wild species suggests that the neuronal composition of carnivoran brains is not affected by domestication. Instead, large carnivorans appear to be particularly vulnerable to metabolic constraints that impose a trade-off between body size and number of cortical neurons.

Brain evolution and development: adaptation, allometry and constraint

Phenotypic traits are products of two processes: evolution and development. But how do these processes combine to produce integrated phenotypes? Comparative studies identify consistent patterns of covariation, or allometries, between brain and body size, and between brain components, indicating the presence of significant constraints limiting independent evolution of separate parts. These constraints are poorly understood, but in principle could be either developmental or functional. The developmental constraints hypothesis suggests that individual components (brain and body size, or individual brain components) tend to evolve together because natural selection operates on relatively simple developmental mechanisms that affect the growth of all parts in a concerted manner. The functional constraints hypothesis suggests that correlated change reflects the action of selection on distributed functional systems connecting the different sub-components, predicting more complex patterns of mosaic change at the level of the functional systems and more complex genetic and developmental mechanisms. These hypotheses are not mutually exclusive but make different predictions. We review recent genetic and neurodevelopmental evidence, concluding that functional rather than developmental constraints are the main cause of the observed patterns.

Comparative morphology of gigantopyramidal neurons in primary motor cortex across mammals

Gigantopyramidal neurons, referred to as Betz cells in primates, are characterized by large somata and extensive basilar dendrites. Although there have been morphological descriptions and drawings of gigantopyramidal neurons in a limited number of species, quantitative investigations have typically been limited to measures of soma size. The current study thus employed two separate analytical approaches: a morphological investigation using the Golgi technique to provide qualitative and quantitative somatodendritic measures of gigantopyramidal neurons across 19 mammalian species from 7 orders; and unbiased stereology to compare the soma volume of layer V pyramidal and gigantopyramidal neurons in primary motor cortex between 11 carnivore and 9 primate species. Of the 617 neurons traced in the morphological analysis, 181 were gigantopyramidal neurons, with deep (primarily layer V) pyramidal (n = 203) and superficial (primarily layer III) pyramidal (n = 233) neurons quantified for comparative purposes. Qualitatively, dendritic morphology varied considerably across species, with some (sub)orders (e.g., artiodactyls, perissodactyls, feliforms) exhibiting bifurcating, V-shaped apical dendrites. Basilar dendrites exhibited idiosyncratic geometry across and within taxonomic groups. Quantitatively, most dendritic measures were significantly greater in gigantopyramidal neurons than in superficial and deep pyramidal neurons. Cluster analyses revealed that most taxonomic groups could be discriminated based on somatodendritic morphology for both superficial and gigantopyramidal neurons. Finally, in agreement with Brodmann, gigantopyramidal neurons in both the morphological and stereological analyses were larger in feliforms (especially in the Panthera species) than in other (sub)orders, possibly due to specializations in muscle fiber composition and musculoskeletal systems.

Layered-up regulation in the developing brain

Modification of messenger RNAs through a process called m6A methylation facilitates dynamic temporal regulation of RNA levels in neural precursor cells, enabling fine-tuning of developing neuronal circuits in the brain.

Nasonia Parasitic Wasps Escape from Haller's Rule by Diphasic, Partially Isometric Brain-Body Size Scaling and Selective Neuropil Adaptations

Haller's rule states that brains scale allometrically with body size in all animals, meaning that relative brain size increases with decreasing body size. This rule applies both on inter- and intraspecific comparisons. Only 1 species, the extremely small parasitic wasp Trichogramma evanescens, is known as an exception and shows an isometric brain-body size relation in an intraspecific comparison between differently sized individuals. Here, we investigated if such an isometric brain-body size relationship also occurs in an intraspecific comparison with a slightly larger parasitic wasp, Nasonia vitripennis, a species that may vary 10-fold in body weight upon differences in levels of scramble competition during larval development. We show that Nasonia exhibits diphasic brain-body size scaling: larger wasps scale allometrically, following Haller's rule, whereas the smallest wasps show isometric scaling. Brains of smaller wasps are, therefore, smaller than expected and we hypothesized that this may lead to adaptations in brain architecture. Volumetric analysis of neuropil composition revealed that wasps of different sizes differed in relative volume of multiple neuropils. The optic lobes and mushroom bodies in particular were smaller in the smallest wasps. Furthermore, smaller brains had a relatively smaller total neuropil volume and larger cellular rind than large brains. These changes in relative brain size and brain architecture suggest that the energetic constraints on brain tissue outweigh specific cognitive requirements in small Nasonia wasps.

Coevolution of cultural intelligence, extended life history, sociality, and brain size in primates

Explanations for primate brain expansion and the evolution of human cognition and culture remain contentious despite extensive research. While multiple comparative analyses have investigated variation in brain size across primate species, very few have addressed why primates vary in how much they use social learning. Here, we evaluate the hypothesis that the enhanced reliance on socially transmitted behavior observed in some primates has coevolved with enlarged brains, complex sociality, and extended lifespans. Using recently developed phylogenetic comparative methods we show that, across primate species, a measure of social learning proclivity increases with absolute and relative brain volume, longevity (specifically reproductive lifespan), and social group size, correcting for research effort. We also confirm relationships of absolute and relative brain volume with longevity (both juvenile period and reproductive lifespan) and social group size, although longevity is generally the stronger predictor. Relationships between social learning, brain volume, and longevity remain when controlling for maternal investment and are therefore not simply explained as a by-product of the generally slower life history expected for larger brained species. Our findings suggest that both brain expansion and high reliance on culturally transmitted behavior coevolved with sociality and extended lifespan in primates. This coevolution is consistent with the hypothesis that the evolution of large brains, sociality, and long lifespans has promoted reliance on culture, with reliance on culture in turn driving further increases in brain volume, cognitive abilities, and lifespans in some primate lineages.

Genetics of Cerebellar and Neocortical Expansion in Anthropoid Primates: A Comparative Approach

What adaptive changes in brain structure and function underpin the evolution of increased cognitive performance in humans and our close relatives? Identifying the genetic basis of brain evolution has become a major tool in answering this question. Numerous cases of positive selection, altered gene expression or gene duplication have been identified that may contribute to the evolution of the neocortex, which is widely assumed to play a predominant role in cognitive evolution. However, the components of the neocortex co-evolve with other functionally interdependent regions of the brain, most notably in the cerebellum. The cerebellum is linked to a range of cognitive tasks and expanded rapidly during hominoid evolution. Here we present data that suggest that, across anthropoid primates, protein-coding genes with known roles in cerebellum development were just as likely to be targeted by selection as genes linked to cortical development. Indeed, based on currently available gene ontology data, protein-coding genes with known roles in cerebellum development are more likely to have evolved adaptively during hominoid evolution. This is consistent with phenotypic data suggesting an accelerated rate of cerebellar expansion in apes that is beyond that predicted from scaling with the neocortex in other primates. Finally, we present evidence that the strength of selection on specific genes is associated with variation in the volume of either the neocortex or the cerebellum, but not both. This result provides preliminary evidence that co-variation between these brain components during anthropoid evolution may be at least partly regulated by selection on independent loci, a conclusion that is consistent with recent intraspecific genetic analyses and a mosaic model of brain evolution that predicts adaptive evolution of brain structure.

Testing hypotheses of developmental constraints on mammalian brain partition evolution, using marsupials

There is considerable debate about whether the partition volumes of the mammalian brain (e.g. cerebrum, cerebellum) evolve according to functional selection, or whether developmental constraints of conserved neurogenetic scheduling cause predictable partition scaling with brain size. Here we provide the first investigation of developmental constraints on partition volume growth, derived from contrast-enhanced micro-computed tomography of hydrogel-stabilized brains from three marsupial species. ANCOVAs of partition vs. brain volume scaling, as well as growth curve comparisons, do not support several hypotheses consistent with developmental constraints: brain partition growth significantly differs between species, or between developing vs. adult marsupials. Partition growth appears independent of adult brain volume, with no discernable growth spurts/lags relatable to internal structural change. Rather, adult proportion differences appear to arise through growth rate/duration heterochrony. Substantial phylogenetic signal in adult brain partitions scaling with brain volume also counters expectations of development-mediated partition scaling conservatism. However, the scaling of olfactory bulb growth is markedly irregular, consistent with suggestions that it is less constrained. The very regular partition growth curves suggest intraspecific developmental rigidity. We speculate that a rigid, possibly neuromer-model-like early molecular program might be responsible both for regular growth curves within species and impressions of a link between neurogenesis and partition evolution.

Is behavioural flexibility evidence of cognitive complexity? How evolution can inform comparative cognition

Behavioural flexibility is often treated as the gold standard of evidence for more sophisticated or complex forms of animal cognition, such as planning, metacognition and mindreading. However, the evidential link between behavioural flexibility and complex cognition has not been explicitly or systematically defended. Such a defence is particularly pressing because observed flexible behaviours can frequently be explained by putatively simpler cognitive mechanisms. This leaves complex cognition hypotheses open to 'deflationary' challenges that are accorded greater evidential weight precisely because they offer putatively simpler explanations of equal explanatory power. This paper challenges the blanket preference for simpler explanations, and shows that once this preference is dispensed with, and the full spectrum of evidence-including evolutionary, ecological and phylogenetic data-is accorded its proper weight, an argument in support of the prevailing assumption that behavioural flexibility can serve as evidence for complex cognitive mechanisms may begin to take shape. An adaptive model of cognitive-behavioural evolution is proposed, according to which the existence of convergent trait-environment clusters in phylogenetically disparate lineages may serve as evidence for the same trait-environment clusters in other lineages. This, in turn, could permit inferences of cognitive complexity in cases of experimental underdetermination, thereby placing the common view that behavioural flexibility can serve as evidence for complex cognition on firmer grounds.

Comparison of estimates of neuronal number obtained using the isotropic fractionator method and unbiased stereology in day old chicks (Gallus domesticus)

BACKGROUND

The relative size and neuronal density of brain regions are important metrics in both comparative and experimental studies in neuroscience. Consequently, it is imperative to have accurate, reliable and reproducible methods of quantifying cell number.

NEW METHOD

The isotropic fractionator (IF) method estimates the number of neurons and non-neurons in the central nervous system by homogenizing tissue into discrete nuclei and determining the proportion of neurons from non-neurons using immunohistochemistry (Herculano- Herculano-Houzel and Lent, 2005).

COMPARISON WITH EXISTING METHOD

One of the advantages of IF is that it is considerably faster than stereology. However, as the method is relatively new, concerns about its accuracy remain, particularly whether homogenization results in underestimation of cell number. In this study, we compared estimates of neuronal number in the telencephalon and 'rest of brain' (i.e. the diencephalon and brainstem excluding the optic lobes) of day old chicks using the IF method and stereology.

RESULTS

In the telencephalon, there was a significant difference in estimates of neuronal number between the 2 methods, but not estimates of neuronal density (neurons/mg of tissue). Whereas in the 'rest of brain', there was a significant difference in estimates of neuronal density, but not neuronal number. In all cases, stereological estimates were lower than those obtained using the IF method.

CONCLUSION

Despite the statistically significant differences, there was considerable overlap (all estimates were within 16% of one another) between estimates obtained using the two methods suggesting that the two methods provide comparable estimates of neuronal number in birds.

Cellular Scaling Rules for the Brains of Marsupials: Not as "Primitive" as Expected

In the effort to understand the evolution of mammalian brains, we have found that common relationships between brain structure mass and numbers of nonneuronal (glial and vascular) cells apply across eutherian mammals, but brain structure mass scales differently with numbers of neurons across structures and across primate and nonprimate clades. This suggests that the ancestral scaling rules for mammalian brains are those shared by extant nonprimate eutherians - but do these scaling relationships apply to marsupials, a sister group to eutherians that diverged early in mammalian evolution? Here we examine the cellular composition of the brains of 10 species of marsupials. We show that brain structure mass scales with numbers of nonneuronal cells, and numbers of cerebellar neurons scale with numbers of cerebral cortical neurons, comparable to what we have found in eutherians. These shared scaling relationships are therefore indicative of mechanisms that have been conserved since the first therians. In contrast, while marsupials share with nonprimate eutherians the scaling of cerebral cortex mass with number of neurons, their cerebella have more neurons than nonprimate eutherian cerebella of a similar mass, and their rest of brain has fewer neurons than eutherian structures of a similar mass. Moreover, Australasian marsupials exhibit ratios of neurons in the cerebral cortex and cerebellum over the rest of the brain, comparable to artiodactyls and primates. Our results suggest that Australasian marsupials have diverged from the ancestral Theria neuronal scaling rules, and support the suggestion that the scaling of average neuronal cell size with increasing numbers of neurons varies in evolution independently of the allocation of neurons across structures.

Sexual selection predicts brain structure in dragon lizards

Phenotypic traits such as ornaments and armaments are generally shaped by sexual selection, which often favours larger and more elaborate males compared to females. But can sexual selection also influence the brain? Previous studies in vertebrates report contradictory results with no consistent pattern between variation in brain structure and the strength of sexual selection. We hypothesize that sexual selection will act in a consistent way on two vertebrate brain regions that directly regulate sexual behaviour: the medial preoptic nucleus (MPON) and the ventromedial hypothalamic nucleus (VMN). The MPON regulates male reproductive behaviour whereas the VMN regulates female reproductive behaviour and is also involved in male aggression. To test our hypothesis, we used high-resolution magnetic resonance imaging combined with traditional histology of brains in 14 dragon lizard species of the genus Ctenophorus that vary in the strength of precopulatory sexual selection. Males belonging to species that experience greater sexual selection had a larger MPON and a smaller VMN. Conversely, females did not show any patterns of variation in these brain regions. As the volumes of both these regions also correlated with brain volume (BV) in our models, we tested whether they show the same pattern of evolution in response to changes in BV and found that the do. Therefore, we show that the primary brain nuclei underlying reproductive behaviour in vertebrates can evolve in a mosaic fashion, differently between males and females, likely in response to sexual selection, and that these same regions are simultaneously evolving in concert in relation to overall brain size.

Distributions of Cells and Neurons across the Cortical Sheet in Old World Macaques

According to previous research, cell and neuron densities vary across neocortex in a similar manner across primate taxa. Here, we provide a more extensive examination of this effect in macaque monkeys. We separated neocortex from the underlying white matter in 4 macaque monkey hemispheres (1 Macaca nemestrina, 2 Macaca radiata, and 1 Macaca mulatta), manually flattened the neocortex, and divided it into smaller tissue pieces for analysis. The number of cells and neurons were determined for each piece across the cortical sheet using flow cytometry. Primary visual cortex had the most densely packed neurons and primary motor cortex had the least densely packed neurons. With respect to differences in brain size between cases, there was little variability in the total cell and neuron numbers within specific areas, and overall trends were similar to what has been previously described in Old World baboons and other primates. The average hemispheric total cell number per hemisphere ranged from 2.9 to 3.7 billion, while the average total neuron number ranged from 1.3 to 1.7 billion neurons. The visual cortex neuron densities were predictably higher, ranging from 18.2 to 34.7 million neurons/cm2 in macaques, in comparison to a range of 9.3-17.7 million neurons/cm2 across cortex as a whole. The results support other evidence that neuron surface densities vary across the cortical sheet in a predictable pattern within and across primate taxa.

Decreasing sleep requirement with increasing numbers of neurons as a driver for bigger brains and bodies in mammalian evolution

Mammals sleep between 3 and 20 h d(-1), but what regulates daily sleep requirement is unknown. While mammalian evolution has been characterized by a tendency towards larger bodies and brains, sustaining larger bodies and brains requires increasing hours of feeding per day, which is incompatible with a large sleep requirement. Mammalian evolution, therefore, must involve mechanisms that tie increasing body and brain size to decreasing sleep requirements. Here I show that daily sleep requirement decreases across mammalian species and in rat postnatal development with a decreasing ratio between cortical neuronal density and surface area, which presumably causes sleep-inducing metabolites to accumulate more slowly in the parenchyma. Because addition of neurons to the non-primate cortex in mammalian evolution decreases this ratio, I propose that increasing numbers of cortical neurons led to decreased sleep requirement in evolution that allowed for more hours of feeding and increased body mass, which would then facilitate further increases in numbers of brain neurons through a larger caloric intake per hour. Coupling of increasing numbers of neurons to decreasing sleep requirement and increasing hours of feeding thus may have not only allowed but also driven the trend of increasing brain and body mass in mammalian evolution.

Birds have primate-like numbers of neurons in the forebrain

Some birds achieve primate-like levels of cognition, even though their brains tend to be much smaller in absolute size. This poses a fundamental problem in comparative and computational neuroscience, because small brains are expected to have a lower information-processing capacity. Using the isotropic fractionator to determine numbers of neurons in specific brain regions, here we show that the brains of parrots and songbirds contain on average twice as many neurons as primate brains of the same mass, indicating that avian brains have higher neuron packing densities than mammalian brains. Additionally, corvids and parrots have much higher proportions of brain neurons located in the pallial telencephalon compared with primates or other mammals and birds. Thus, large-brained parrots and corvids have forebrain neuron counts equal to or greater than primates with much larger brains. We suggest that the large numbers of neurons concentrated in high densities in the telencephalon substantially contribute to the neural basis of avian intelligence.

Studying avian encephalization with geometric morphometrics

Encephalization is a core concept in comparative neurobiology, aiming to quantify the neurological capacity of organisms. For measuring encephalization, many studies have employed relative brain sizes corrected for expected allometric scaling to body size. Here we highlight the utility of a multivariate geometric morphometric (GM) approach for visualizing and analyzing neuroanatomical shape variation associated with encephalization. GM readily allows the statistical evaluation of covariates, such as size, and many software tools exist for visualizing their effects on shape. Thus far, however, studies using GM have not attempted to translate the meaning of encephalization to shape data. As such, we tested the statistical relationship between size and encephalization quotients (EQs) to brain shape utilizing a broad interspecific sample of avian endocranial data. Although statistically significant, the analyses indicate that allometry accounts for <10% of total neuroanatomical shape variation. Notably, we find that EQs, despite being corrected for allometric scaling based on size, contain size-related neuroanatomical shape changes. In addition, much of what is traditionally considered encephalization comprises clade-specific trends in relative forebrain expansion, particularly driven by landbirds. EQs, therefore, fail to capture 90% of the total neuroanatomical variation after correcting for allometry and shared phylogenetic history. Moving forward, GM techniques provide crucial tools for investigating key drivers of this vast, largely unexplored aspect of avian brain morphology.

Contextualising primate origins--an ecomorphological framework

Ecomorphology - the characterisation of the adaptive relationship between an organism's morphology and its ecological role - has long been central to theories of the origin and early evolution of the primate order. This is exemplified by two of the most influential theories of primate origins: Matt Cartmill's Visual Predation Hypothesis, and Bob Sussman's Angiosperm Co-Evolution Hypothesis. However, the study of primate origins is constrained by the absence of data directly documenting the events under investigation, and has to rely instead on a fragmentary fossil record and the methodological assumptions inherent in phylogenetic comparative analyses of extant species. These constraints introduce particular challenges for inferring the ecomorphology of primate origins, as morphology and environmental context must first be inferred before the relationship between the two can be considered. Fossils can be integrated in comparative analyses and observations of extant model species and laboratory experiments of form-function relationships are critical for the functional interpretation of the morphology of extinct species. Recent developments have led to important advancements, including phylogenetic comparative methods based on more realistic models of evolution, and improved methods for the inference of clade divergence times, as well as an improved fossil record. This contribution will review current perspectives on the origin and early evolution of primates, paying particular attention to their phylogenetic (including cladistic relationships and character evolution) and environmental (including chronology, geography, and physical environments) contextualisation, before attempting an up-to-date ecomorphological synthesis of primate origins.

Continued Growth of the Central Nervous System without Mandatory Addition of Neurons in the Nile Crocodile (Crocodylus niloticus)

It is generally believed that animals with larger bodies require larger brains, composed of more neurons. Across mammalian species, there is a correlation between body mass and the number of brain neurons, albeit with low allometric exponents. If larger bodies imperatively require more neurons to operate them, then such an increase in the number of neurons should be detected across individuals of a continuously growing species, such as the Nile crocodile. In the current study we use the isotropic fractionator method of cell counting to determine how the number of neurons and non-neurons in 6 specific brain regions and the spinal cord change with increasing body mass in the Nile crocodile. The central nervous system (CNS) structures examined all increase in mass as a function of body mass, with allometric exponents of around 0.2, except for the spinal cord, which increases with an exponent of 0.6. We find that numbers of non-neurons increase slowly, but significantly, in all CNS structures, scaling as a function of body mass with exponents ranging between 0.1 and 0.3. In contrast, numbers of neurons scale with body mass in the spinal cord, olfactory bulb, cerebellum and telencephalon, with exponents of between 0.08 and 0.20, but not in the brainstem and diencephalon, the brain structures that receive inputs and send outputs to the growing body. Densities of both neurons and non-neurons decrease with increasing body mass. These results indicate that increasing body mass with growth in the Nile crocodile is associated with a general addition of non-neurons and increasing cell size throughout CNS structures, but is only associated with an addition of neurons in some structures (and at very small rates) and not in those brain structures directly connected to the body. Larger bodies thus do not imperatively require more neurons to operate them.

Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

The term 'synergy' - from the Greek synergia - means 'working together'. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project "The Hand Embodied" (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies.

Cortical cell and neuron density estimates in one chimpanzee hemisphere

The density of cells and neurons in the neocortex of many mammals varies across cortical areas and regions. This variability is, perhaps, most pronounced in primates. Nonuniformity in the composition of cortex suggests regions of the cortex have different specializations. Specifically, regions with densely packed neurons contain smaller neurons that are activated by relatively few inputs, thereby preserving information, whereas regions that are less densely packed have larger neurons that have more integrative functions. Here we present the numbers of cells and neurons for 742 discrete locations across the neocortex in a chimpanzee. Using isotropic fractionation and flow fractionation methods for cell and neuron counts, we estimate that neocortex of one hemisphere contains 9.5 billion cells and 3.7 billion neurons. Primary visual cortex occupies 35 cm(2) of surface, 10% of the total, and contains 737 million densely packed neurons, 20% of the total neurons contained within the hemisphere. Other areas of high neuron packing include secondary visual areas, somatosensory cortex, and prefrontal granular cortex. Areas of low levels of neuron packing density include motor and premotor cortex. These values reflect those obtained from more limited samples of cortex in humans and other primates.