Size and density of glial and neuronal cells within the cerebral neocortex of various insectivorian species

Comparative analysis of astrocytes in the prefrontal cortex of primates: Insights into the evolution of human brain energetics

Astrocytes are the main homeostatic cell of the brain involved in many processes related to cognition, immune response, and energy expenditure. It has been suggested that the distribution of astrocytes is associated with brain size, and that they are specialized in humans. To evaluate these, we quantified astrocyte density, soma volume, and total glia density in layer I and white matter in Brodmann's area 9 of humans, chimpanzees, baboons, and macaques. We found that layer I astrocyte density, soma volume, and ratio of astrocytes to total glia cells were highest in humans and increased with brain size. Overall glia density in layer I and white matter were relatively invariant across brain sizes, potentially due to their important metabolic functions on a per volume basis. We also quantified two transporters involved in metabolism through the astrocyte-neuron lactate shuttle, excitatory amino acid transporter 2 (EAAT2) and glucose transporter 1 (GLUT1). We expected these transporters would be increased in human brains due to their high rate of metabolic consumption and associated gene activity. While humans have higher EAAT2 cell density, GLUT1 vessel volume, and GLUT1 area fraction compared to baboons and chimpanzees, they did not differ from macaques. Therefore, EAAT2 and GLUT1 are not related to increased energetic demands of the human brain. Taken together, these data provide evidence that astrocytes play a unique role in both brain expansion and evolution among primates, with an emphasis on layer I astrocytes having a potentially significant role in human-specific metabolic processing and cognition.

Cortical synapses of the world's smallest mammal: An FIB/SEM study in the Etruscan shrew

The main aim of the present study was to determine if synapses from the exceptionally small brain of the Etruscan shrew show any peculiarities compared to the much larger human brain. We analyzed the cortical synaptic density and a variety of structural characteristics of 7,239 3D reconstructed synapses, using using Focused Ion Beam/Scanning Electron Microscopy (FIB/SEM). We found that some of the general synaptic characteristics are remarkably similar to those found in the human cerebral cortex. However, the cortical volume of the human brain is about 50,000 times larger than the cortical volume of the Etruscan shrew, while the total number of cortical synapses in human is only 20,000 times the number of synapses in the shrew, and synaptic junctions are 35% smaller in the Etruscan shrew. Thus, the differences in the number and size of synapses cannot be attributed to a brain size scaling effect but rather to adaptations of synaptic circuits to particular functions.

Comparative Study of Brain Size Ontogeny: Marsupials and Placental Mammals

There exists a negative allometry between vertebrate brain size and body size. It has been well studied among placental mammals but less is known regarding marsupials. Consequently, this study explores brain/body ontogenetic growth in marsupials and compares it with placental mammals. Pouch young samples of 43 koalas (Phascolarctos cinereus), 28 possums (Trichosurus vulpecula), and 36 tammar wallabies (Macropus eugenii) preserved in a solution of 10% buffered formalin, as well as fresh juveniles and adults of 43 koalas and 40 possums, were studied. Their brain size/body size allometry was compared to that among humans, rhesus monkeys, dogs, cats, rats, guinea pigs, rabbits, wild pigs, and mice. Two patterns of allometric curves were found: a logarithmic one (marsupials, rabbits, wild pigs, and guinea pigs) and a logistic one (the rest of mammals).

The relationship between diffusion heterogeneity and microstructural changes in high-grade gliomas using Monte Carlo simulations

PURPOSE

Diffusion-weighted imaging (DWI) may aid accurate tumor grading. Decreased diffusivity and increased diffusion heterogeneity measures have been observed in high-grade gliomas using the non-monoexponential models for DWI. However, DWI measures concerning tissue characteristics in terms of pathophysiological and structural changes are yet to be established. Thus, this study aims to investigate the relationship between the diffusion measurements and microstructural changes in the presence of high-grade gliomas using a three-dimensional Monte Carlo simulation with systematic changes of microstructural parameters.

METHODS

Water diffusion was simulated in a microenvironment along with changes associated with the presence of high-grade gliomas, including increases in cell density, nuclear volume, extracellular volume (VF_ex), and extracellular tortuosity (λ_ex), and changes in membrane permeability (P_mem). DWI signals were simulated using a pulsed gradient spin-echo sequence. The sequence parameters, including the maximum gradient strength and diffusion time, were set to be comparable to those of clinical scanners and advanced human MRI systems. The DWI signals were fitted using the gamma distribution and diffusional kurtosis models with b-values up to 6000 and 2500 s/mm², respectively.

RESULTS

The diffusivity measures (apparent diffusion coefficients (ADC), D_gamma of the gamma distribution model and D_app of the diffusional kurtosis model) decreased with increases in cell density and λ_ex, and a decrease in P_mem. These diffusivity measures increased with increases in nuclear volume and VF_ex. The diffusion heterogeneity measures (σ_gamma of the gamma distribution model and K_app of the diffusional kurtosis model) increased with increases in cell density or nuclear volume at the low P_mem, and a decrease in P_mem. Increased σ_gamma was also associated with an increase in VF_ex.

CONCLUSION

Among simulated microstructural changes, only increases in cell density at low P_mem or decreases in P_mem corresponded to both the decreased diffusivity and increased diffusion heterogeneity measures. The results suggest that increases in cell density at low P_mem or decreases in P_mem may be associated with the diffusion changes observed in high-grade gliomas.

Lizards as models to explore the ecological and neuroanatomical correlates of miniaturization

Extreme body size reductions bring about unorthodox anatomical arrangements and novel ways in which animals interact with the environment. Drawing from studies of vertebrates and invertebrates, we provide a theoretical framework for miniaturization to inform hypotheses using lizards as a study system. Through this approach, we demonstrate the repeated evolution of miniaturization across 11 families and a tendency for miniaturized species to occupy terrestrial microhabitats, possibly driven by physiological constraints. Differences in gross brain morphology between two gecko species demonstrate a proportionally larger telencephalon and smaller olfactory bulbs in the miniaturized species, though more data are needed to generalize this trend. Our study brings into light the potential contributions of miniaturized lizards to explain patterns of body size evolution and its impact on ecology and neuroanatomy. In addition, our findings reveal the need to study the natural history of miniaturized species, particularly in relation to their sensory and physiological ecology.

The Cellular Composition and Glia-Neuron Ratio in the Spinal Cord of a Human and a Nonhuman Primate: Comparison With Other Species and Brain Regions

The cellular composition of brains shows largely conserved, gradual evolutionary trends between species. In the primate spinal cord, however, the glia-neuron ratio was reported to be greatly increased over that in the rodent spinal cord. Here, we re-examined the cellular composition of the spinal cord of one human and one nonhuman primate species by employing two different counting methods, the isotropic fractionator and stereology. We also determined whether segmental differences in cellular composition, possibly reflecting increased fine motor control of the upper extremities, may explain a sharply increased glia-neuron ratio in primates. In the cynomolgus monkey spinal cord, the isotropic fractionator and stereology yielded 206-275 million cells, of which 13.3-25.1% were neurons (28-69 million). Stereological estimates yielded 21.1% endothelial cells and 65.5% glial cells (glia-neuron ratio of 4.9-5.6). In human spinal cords, the isotropic fractionator and stereology generated estimates of 1.5-1.7 billion cells and 197-222 million neurons (13.4% neurons, 12.2% endothelial cells, 74.8% glial cells), and a glia-neuron ratio of 5.6-7.1, with estimates of neuron numbers in the human spinal cord based on morphological criteria. The non-neuronal to neuron ratios in human and cynomolgus monkey spinal cords were 6.5 and 3.2, respectively, suggesting that previous reports overestimated this ratio. We did not find significant segmental differences in the cellular composition between cervical, thoracic and lumbar levels. When compared with brain regions, the spinal cord showed gradual increases of the glia-neuron ratio with increasing brain mass, similar to the cerebral cortex and the brainstem. Anat Rec, 301:697-710, 2018. © 2017 Wiley Periodicals, Inc.

Myths and truths about the cellular composition of the human brain: A review of influential concepts

Over the last 50 years, quantitative methodology has made important contributions to our understanding of the cellular composition of the human brain. Not all of the concepts that emerged from quantitative studies have turned out to be true. Here, I examine the history and current status of some of the most influential notions. This includes claims of how many cells compose the human brain, and how different cell types contribute and in what ratios. Additional concepts entail whether we lose significant numbers of neurons with normal aging, whether chronic alcohol abuse contributes to cortical neuron loss, whether there are significant differences in the quantitative composition of cerebral cortex between male and female brains, whether superior intelligence in humans correlates with larger numbers of brain cells, and whether there are secular (generational) changes in neuron number. Do changes in cell number or changes in ratios of cell types accompany certain diseases, and should all counting methods, even the theoretically unbiased ones, be validated and calibrated? I here examine the origin and the current status of major influential concepts, and I review the evidence and arguments that have led to either confirmation or refutation of such concepts. I discuss the circumstances, assumptions and mindsets that perpetuated erroneous views, and the types of technological advances that have, in some cases, challenged longstanding ideas. I will acknowledge the roles of key proponents of influential concepts in the sometimes convoluted path towards recognition of the true cellular composition of the human brain.

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.

The search for true numbers of neurons and glial cells in the human brain: A review of 150 years of cell counting

For half a century, the human brain was believed to contain about 100 billion neurons and one trillion glial cells, with a glia:neuron ratio of 10:1. A new counting method, the isotropic fractionator, has challenged the notion that glia outnumber neurons and revived a question that was widely thought to have been resolved. The recently validated isotropic fractionator demonstrates a glia:neuron ratio of less than 1:1 and a total number of less than 100 billion glial cells in the human brain. A survey of original evidence shows that histological data always supported a 1:1 ratio of glia to neurons in the entire human brain, and a range of 40-130 billion glial cells. We review how the claim of one trillion glial cells originated, was perpetuated, and eventually refuted. We compile how numbers of neurons and glial cells in the adult human brain were reported and we examine the reasons for an erroneous consensus about the relative abundance of glial cells in human brains that persisted for half a century. Our review includes a brief history of cell counting in human brains, types of counting methods that were and are employed, ranges of previous estimates, and the current status of knowledge about the number of cells. We also discuss implications and consequences of the new insights into true numbers of glial cells in the human brain, and the promise and potential impact of the newly validated isotropic fractionator for reliable quantification of glia and neurons in neurological and psychiatric diseases. J. Comp. Neurol. 524:3865-3895, 2016. © 2016 Wiley Periodicals, Inc.

Mammalian Brains Are Made of These: A Dataset of the Numbers and Densities of Neuronal and Nonneuronal Cells in the Brain of Glires, Primates, Scandentia, Eulipotyphlans, Afrotherians and Artiodactyls, and Their Relationship with Body Mass

Comparative studies amongst extant species are one of the pillars of evolutionary neurobiology. In the 20th century, most comparative studies remained restricted to analyses of brain structure volume and surface areas, besides estimates of neuronal density largely limited to the cerebral cortex. Over the last 10 years, we have amassed data on the numbers of neurons and other cells that compose the entirety of the brain (subdivided into cerebral cortex, cerebellum, and rest of brain) of 39 mammalian species spread over 6 clades, as well as their densities. Here we provide that entire dataset in a format that is readily useful to researchers of any area of interest in the hope that it will foster the advancement of evolutionary and comparative studies well beyond the scope of neuroscience itself. We also reexamine the relationship between numbers of neurons, neuronal densities and body mass, and find that in the rest of brain, but not in the cerebral cortex or cerebellum, there is a single scaling rule that applies to average neuronal cell size, which increases with the linear dimension of the body, even though there is no single scaling rule that relates the number of neurons in the rest of brain to body mass. Thus, larger bodies do not uniformly come with more neurons - but they do fairly uniformly come with larger neurons in the rest of brain, which contains a number of structures directly connected to sources or targets in the body.

All brains are made of this: a fundamental building block of brain matter with matching neuronal and glial masses

How does the size of the glial and neuronal cells that compose brain tissue vary across brain structures and species? Our previous studies indicate that average neuronal size is highly variable, while average glial cell size is more constant. Measuring whole cell sizes in vivo, however, is a daunting task. Here we use chi-square minimization of the relationship between measured neuronal and glial cell densities in the cerebral cortex, cerebellum, and rest of brain in 27 mammalian species to model neuronal and glial cell mass, as well as the neuronal mass fraction of the tissue (the fraction of tissue mass composed by neurons). Our model shows that while average neuronal cell mass varies by over 500-fold across brain structures and species, average glial cell mass varies only 1.4-fold. Neuronal mass fraction varies typically between 0.6 and 0.8 in all structures. Remarkably, we show that two fundamental, universal relationships apply across all brain structures and species: (1) the glia/neuron ratio varies with the total neuronal mass in the tissue (which in turn depends on variations in average neuronal cell mass), and (2) the neuronal mass per glial cell, and with it the neuronal mass fraction and neuron/glia mass ratio, varies with average glial cell mass in the tissue. We propose that there is a fundamental building block of brain tissue: the glial mass that accompanies a unit of neuronal mass. We argue that the scaling of this glial mass is a consequence of a universal mechanism whereby numbers of glial cells are added to the neuronal parenchyma during development, irrespective of whether the neurons composing it are large or small, but depending on the average mass of the glial cells being added. We also show how evolutionary variations in neuronal cell mass, glial cell mass and number of neurons suffice to determine the most basic characteristics of brain structures, such as mass, glia/neuron ratio, neuron/glia mass ratio, and cell densities.

Quantifying white matter tract diffusion parameters in the presence of increased extra-fiber cellularity and vasogenic edema

The effect of extra-fiber structural and pathological components confounding diffusion tensor imaging (DTI) computation was quantitatively investigated using data generated by both Monte-Carlo simulations and tissue phantoms. Increased extent of vasogenic edema, by addition of various amount of gel to fixed normal mouse trigeminal nerves or by increasing non-restricted isotropic diffusion tensor components in Monte-Carlo simulations, significantly decreased fractional anisotropy (FA) and increased radial diffusivity, while less significantly increased axial diffusivity derived by DTI. Increased cellularity, mimicked by graded increase of the restricted isotropic diffusion tensor component in Monte-Carlo simulations, significantly decreased FA and axial diffusivity with limited impact on radial diffusivity derived by DTI. The MC simulation and tissue phantom data were also analyzed by the recently developed diffusion basis spectrum imaging (DBSI) to simultaneously distinguish and quantify the axon/myelin integrity and extra-fiber diffusion components. Results showed that increased cellularity or vasogenic edema did not affect the DBSI-derived fiber FA, axial or radial diffusivity. Importantly, the extent of extra-fiber cellularity and edema estimated by DBSI correlated with experimentally added gel and Monte-Carlo simulations. We also examined the feasibility of applying 25-direction diffusion encoding scheme for DBSI analysis on coherent white matter tracts. Results from both phantom experiments and simulations suggested that the 25-direction diffusion scheme provided comparable DBSI estimation of both fiber diffusion parameters and extra-fiber cellularity/edema extent as those by 99-direction scheme. An in vivo 25-direction DBSI analysis was performed on experimental autoimmune encephalomyelitis (EAE, an animal model of human multiple sclerosis) optic nerve as an example to examine the validity of derived DBSI parameters with post-imaging immunohistochemistry verification. Results support that in vivo DBSI using 25-direction diffusion scheme correctly reflect the underlying axonal injury, demyelination, and inflammation of optic nerves in EAE mice.

The elephant brain in numbers

What explains the superior cognitive abilities of the human brain compared to other, larger brains? Here we investigate the possibility that the human brain has a larger number of neurons than even larger brains by determining the cellular composition of the brain of the African elephant. We find that the African elephant brain, which is about three times larger than the human brain, contains 257 billion (10(9)) neurons, three times more than the average human brain; however, 97.5% of the neurons in the elephant brain (251 billion) are found in the cerebellum. This makes the elephant an outlier in regard to the number of cerebellar neurons compared to other mammals, which might be related to sensorimotor specializations. In contrast, the elephant cerebral cortex, which has twice the mass of the human cerebral cortex, holds only 5.6 billion neurons, about one third of the number of neurons found in the human cerebral cortex. This finding supports the hypothesis that the larger absolute number of neurons in the human cerebral cortex (but not in the whole brain) is correlated with the superior cognitive abilities of humans compared to elephants and other large-brained mammals.

The glia/neuron ratio: how it varies uniformly across brain structures and species and what that means for brain physiology and evolution

It is a widespread notion that the proportion of glial to neuronal cells in the brain increases with brain size, to the point that glial cells represent "about 90% of all cells in the human brain." This notion, however, is wrong on both counts: neither does the glia/neuron ratio increase uniformly with brain size, nor do glial cells represent the majority of cells in the human brain. This review examines the origin of interest in the glia/neuron ratio; the original evidence that led to the notion that it increases with brain size; the extent to which this concept can be applied to white matter and whole brains and the recent supporting evidence that the glia/neuron ratio does not increase with brain size, but rather, and in surprisingly uniform fashion, with decreasing neuronal density due to increasing average neuronal cell size, across brain structures and species. Variations in the glia/neuron ratio are proposed to be related not to the supposed larger metabolic cost of larger neurons (given that this cost is not found to vary with neuronal density), but simply to the large variation in neuronal sizes across brain structures and species in the face of less overall variation in glial cell sizes, with interesting implications for brain physiology. The emerging evidence that the glia/neuron ratio varies uniformly across the different brain structures of mammalian species that diverged as early as 90 million years ago in evolution highlights how fundamental for brain function must be the interaction between glial cells and neurons.

Cellular scaling rules for the brain of afrotherians

Quantitative analysis of the cellular composition of rodent, primate and eulipotyphlan brains has shown that non-neuronal scaling rules are similar across these mammalian orders that diverged about 95 million years ago, and therefore appear to be conserved in evolution, while neuronal scaling rules appear to be free to vary in evolution in a clade-specific manner. Here we analyze the cellular scaling rules that apply to the brain of afrotherians, believed to be the first clade to radiate from the common eutherian ancestor. We find that afrotherians share non-neuronal scaling rules with rodents, primates and eulipotyphlans, as well as the coordinated scaling of numbers of neurons in the cerebral cortex and cerebellum. Afrotherians share with rodents and eulipotyphlans, but not with primates, the scaling of number of neurons in the cortex and in the cerebellum as a function of the number of neurons in the rest of the brain. Afrotheria also share with rodents and eulipotyphlans the neuronal scaling rules that apply to the cerebral cortex. Afrotherians share with rodents, but not with eulipotyphlans nor primates, the neuronal scaling rules that apply to the cerebellum. Importantly, the scaling of the folding index of the cerebral cortex with the number of neurons in the cerebral cortex is not shared by either afrotherians, rodents, or primates. The sharing of some neuronal scaling rules between afrotherians and rodents, and of some additional features with eulipotyphlans and primates, raise the interesting possibility that these shared characteristics applied to the common eutherian ancestor. In turn, the clade-specific characteristics that relate to the distribution of neurons along the surface of the cerebral cortex and to its degree of gyrification suggest that these characteristics compose an evolutionarily plastic suite of features that may have defined and distinguished mammalian groups in evolution.

Distribution of neurons in functional areas of the mouse cerebral cortex reveals quantitatively different cortical zones

How are neurons distributed along the cortical surface and across functional areas? Here we use the isotropic fractionator (Herculano-Houzel and Lent, 2005) to analyze the distribution of neurons across the entire isocortex of the mouse, divided into 18 functional areas defined anatomically. We find that the number of neurons underneath a surface area (the N/A ratio) varies 4.5-fold across functional areas and neuronal density varies 3.2-fold. The face area of S1 contains the most neurons, followed by motor cortex and the primary visual cortex. Remarkably, while the distribution of neurons across functional areas does not accompany the distribution of surface area, it mirrors closely the distribution of cortical volumes—with the exception of the visual areas, which hold more neurons than expected for their volume. Across the non-visual cortex, the volume of individual functional areas is a shared linear function of their number of neurons, while in the visual areas, neuronal densities are much higher than in all other areas. In contrast, the 18 functional areas cluster into three different zones according to the relationship between the N/A ratio and cortical thickness and neuronal density: these three clusters can be called visual, sensory, and, possibly, associative. These findings are remarkably similar to those in the human cerebral cortex (Ribeiro et al., 2013) and suggest that, like the human cerebral cortex, the mouse cerebral cortex comprises two zones that differ in how neurons form the cortical volume, and three zones that differ in how neurons are distributed underneath the cortical surface, possibly in relation to local differences in connectivity through the white matter. Our results suggest that beyond the developmental divide into visual and non-visual cortex, functional areas initially share a common distribution of neurons along the parenchyma that become delimited into functional areas according to the pattern of connectivity established later.

The human cerebral cortex is neither one nor many: neuronal distribution reveals two quantitatively different zones in the gray matter, three in the white matter, and explains local variations in cortical folding

The human prefrontal cortex has been considered different in several aspects and relatively enlarged compared to the rest of the cortical areas. Here we determine whether the white and gray matter of the prefrontal portion of the human cerebral cortex have similar or different cellular compositions relative to the rest of the cortical regions by applying the Isotropic Fractionator to analyze the distribution of neurons along the entire anteroposterior axis of the cortex, and its relationship with the degree of gyrification, number of neurons under the cortical surface, and other parameters. The prefrontal region shares with the remainder of the cerebral cortex (except for occipital cortex) the same relationship between cortical volume and number of neurons. In contrast, both occipital and prefrontal areas vary from other cortical areas in their connectivity through the white matter, with a systematic reduction of cortical connectivity through the white matter and an increase of the mean axon caliber along the anteroposterior axis. These two parameters explain local differences in the distribution of neurons underneath the cortical surface. We also show that local variations in cortical folding are neither a function of local numbers of neurons nor of cortical thickness, but correlate with properties of the white matter, and are best explained by the folding of the white matter surface. Our results suggest that the human cerebral cortex is divided in two zones (occipital and non-occipital) that differ in how neurons are distributed across their gray matter volume and in three zones (prefrontal, occipital, and non-occipital) that differ in how neurons are connected through the white matter. Thus, the human prefrontal cortex has the largest fraction of neuronal connectivity through the white matter and the smallest average axonal caliber in the white matter within the cortex, although its neuronal composition fits the pattern found for other, non-occipital areas.

Structural uniformity of neocortex, revisited

The number of neurons under a square millimeter of cortical surface has been reported to be the same across five cortical areas and five species [Rockel et al. (1980) Brain 103(2):221-244] despite differences in cortical thickness between the areas. Although the accuracy of this result has been the subject of sharp debate since its publication approximately 30 y ago, the experiments of Rockel et al. have never been directly replicated with modern stereological methods. We have replicated these experiments and confirm the accuracy of the original report. In addition, we have observed that the number of glial cells under a square millimeter of cortical surface depends on cortical thickness, but not on cortical area or species.

Cytoarchitecture, areas, and neuron numbers of the Etruscan shrew cortex

The Etruscan shrew, Suncus etruscus, is one of the smallest mammals. Etruscan shrews can recognize prey shape with amazing speed and accuracy, based on whisker-mediated tactile cues. Because of its small size, quantitative analysis of the Etruscan shrew cortex is more tractable than in other animals. To quantitatively assess the anatomy of the Etruscan shrew's brain, we sectioned brains and applied Nissl staining and NeuN (neuronal nuclei) antibody staining. On the basis of these stains, we estimated the number of neurons of 10 cortical hemispheres by using Stereoinvestigator and Neurolucida (MBF Bioscience) software. On average, the neuron number per hemisphere was found to be ~1 million. We also measured cortical surface area and found an average of 11.1 mm² (n = 7) and an average volume of 5.3 mm³ (n = 10) per hemisphere. We identified 13 cortical regions by cytoarchitectonic boundaries in coronal, sagittal, and tangential sections processed for Nissl substance, myelin, cytochrome oxidase, ionic zinc, neurofilaments, and vesicular glutamate transporter 2 (VGluT2). The Etruscan shrew is a highly tactile animal with a large somatosensory cortex, which contains a barrel field, but the barrels are much less clearly defined than in rodents. The anatomically derived cortical partitioning scheme roughly corresponds to physiologically derived maps of neocortical sensory areas.

Positive selection on NIN, a gene involved in neurogenesis, and primate brain evolution

A long-held dogma in comparative neurobiology has been that the number of neurons under a given area of cortical surface is constant. As such, the attention of those seeking to understand the genetic basis of brain evolution has focused on genes with functions in the lateral expansion of the developing cerebral cortex. However, new data suggest that cortical cytoarchitecture is not constant across primates, raising the possibility that changes in radial cortical development played a role in primate brain evolution. We present the first analysis of a gene with functions relevant to this dimension of brain evolution. We show that NIN, a gene necessary for maintaining asymmetric, neurogenic divisions of radial glial cells (RGCs), evolved adaptively during anthropoid evolution. We explored how this selection relates to neural phenotypes and find a significant association between selection on NIN and neonatal brain size in catarrhines. Our analyses suggest a relationship with prenatal neurogenesis and identify the human data point as an outlier, possibly explained by postnatal changes in development on the human lineage. A similar pattern is found in platyrrhines, but the highly encephalized genus Cebus departs from the general trend. We further show that the evolution of NIN may be associated with variation in neuron number not explained by increases in surface area, a result consistent with NIN's role in neurogenic divisions of RGCs. Our combined results suggest a role for NIN in the evolution of cortical development.

How many neurons do you have? Some dogmas of quantitative neuroscience under revision

Owing to methodological shortcomings and a certain conservatism that consolidates wrong assumptions in the literature, some dogmas have become established and reproduced in papers and textbooks, derived from quantitative features of the brain. The first dogma states that the cerebral cortex is the pinnacle of brain evolution - based on the observations that its volume is greater in more 'intelligent' species, and that cortical surface area grows more than any other brain region, to reach the largest proportion in higher primates and humans. The second dogma claims that the human brain contains 100 billion neurons, plus 10-fold more glial cells. These round numbers have become widely adopted, although data provided by different authors have led to a broad range of 75-125 billion neurons in the whole brain. The third dogma derives from the second, and states that our brain is structurally special, an outlier as compared with other primates. Being so large and convoluted, it is a special construct of nature, unrelated to evolutionary scaling. Finally, the fourth dogma appeared as a tentative explanation for the considerable growth of the brain throughout development and evolution - being modular in structure, the brain (and particularly the cerebral cortex) grows by tangential addition of modules that are uniform in neuronal composition. In this review, we sought to examine and challenge these four dogmas, and propose other interpretations or simply their replacement with alternative views.

The neurobiology of Etruscan shrew active touch

The Etruscan shrew, Suncus etruscus, is not only the smallest terrestrial mammal, but also one of the fastest and most tactile hunters described to date. The shrew's skeletal muscle consists entirely of fast-twitch types and lacks slow fibres. Etruscan shrews detect, overwhelm, and kill insect prey in large numbers in darkness. The cricket prey is exquisitely mechanosensitive and fast-moving, and is as big as the shrew itself. Experiments with prey replica show that shape cues are both necessary and sufficient for evoking attacks. Shrew attacks are whisker guided by motion- and size-invariant Gestalt-like prey representations. Shrews often attack their prey prior to any signs of evasive manoeuvres. Shrews whisk at frequencies of approximately 14 Hz and can react with latencies as short as 25-30 ms to prey movement. The speed of attacks suggests that shrews identify and classify prey with a single touch. Large parts of the shrew's brain respond to vibrissal touch, which is represented in at least four cortical areas comprising collectively about a third of the cortical volume. Etruscan shrews can enter a torpid state and reduce their body temperature; we observed that cortical response latencies become two to three times longer when body temperature drops from 36°C to 24°C, suggesting that endothermy contributes to the animal's high-speed sensorimotor performance. We argue that small size, high-speed behaviour and extreme dependence on touch are not coincidental, but reflect an evolutionary strategy, in which the metabolic costs of small body size are outweighed by the advantages of being a short-range high-speed touch and kill predator.

Updated neuronal scaling rules for the brains of Glires (rodents/lagomorphs)

Brain size scales as different functions of its number of neurons across mammalian orders such as rodents, primates, and insectivores. In rodents, we have previously shown that, across a sample of 6 species, from mouse to capybara, the cerebral cortex, cerebellum and the remaining brain structures increase in size faster than they gain neurons, with an accompanying decrease in neuronal density in these structures [Herculano-Houzel et al.: Proc Natl Acad Sci USA 2006;103:12138-12143]. Important remaining questions are whether such neuronal scaling rules within an order apply equally to all pertaining species, and whether they extend to closely related taxa. Here, we examine whether 4 other species of Rodentia, as well as the closely related rabbit (Lagomorpha), conform to the scaling rules identified previously for rodents. We report the updated neuronal scaling rules obtained for the average values of each species in a way that is directly comparable to the scaling rules that apply to primates [Gabi et al.: Brain Behav Evol 2010;76:32-44], and examine whether the scaling relationships are affected when phylogenetic relatedness in the dataset is accounted for. We have found that the brains of the spiny rat, squirrel, prairie dog and rabbit conform to the neuronal scaling rules that apply to the previous sample of rodents. The conformity to the previous rules of the new set of species, which includes the rabbit, suggests that the cellular scaling rules we have identified apply to rodents in general, and probably to Glires as a whole (rodents/lagomorphs), with one notable exception: the naked mole-rat brain is apparently an outlier, with only about half of the neurons expected from its brain size in its cerebral cortex and cerebellum.

The evolution of the brain, the human nature of cortical circuits, and intellectual creativity

The tremendous expansion and the differentiation of the neocortex constitute two major events in the evolution of the mammalian brain. The increase in size and complexity of our brains opened the way to a spectacular development of cognitive and mental skills. This expansion during evolution facilitated the addition of microcircuits with a similar basic structure, which increased the complexity of the human brain and contributed to its uniqueness. However, fundamental differences even exist between distinct mammalian species. Here, we shall discuss the issue of our humanity from a neurobiological and historical perspective.

Cellular scaling rules for the brains of an extended number of primate species

What are the rules relating the size of the brain and its structures to the number of cells that compose them and their average sizes? We have shown previously that the cerebral cortex, cerebellum and the remaining brain structures increase in size as a linear function of their numbers of neurons and non-neuronal cells across 6 species of primates. Here we describe that the cellular composition of the same brain structures of 5 other primate species, as well as humans, conform to the scaling rules identified previously, and that the updated power functions for the extended sample are similar to those determined earlier. Accounting for phylogenetic relatedness in the combined dataset does not affect the scaling slopes that apply to the cerebral cortex and cerebellum, but alters the slope for the remaining brain structures to a value that is similar to that observed in rodents, which raises the possibility that the neuronal scaling rules for these structures are shared among rodents and primates. The conformity of the new set of primate species to the previous rules strongly suggests that the cellular scaling rules we have identified apply to primates in general, including humans, and not only to particular subgroups of primate species. In contrast, the allometric rules relating body and brain size are highly sensitive to the particular species sampled, suggesting that brain size is neither determined by body size nor together with it, but is rather only loosely correlated with body size.

The human brain in numbers: a linearly scaled-up primate brain

The human brain has often been viewed as outstanding among mammalian brains: the most cognitively able, the largest-than-expected from body size, endowed with an overdeveloped cerebral cortex that represents over 80% of brain mass, and purportedly containing 100 billion neurons and 10x more glial cells. Such uniqueness was seemingly necessary to justify the superior cognitive abilities of humans over larger-brained mammals such as elephants and whales. However, our recent studies using a novel method to determine the cellular composition of the brain of humans and other primates as well as of rodents and insectivores show that, since different cellular scaling rules apply to the brains within these orders, brain size can no longer be considered a proxy for the number of neurons in the brain. These studies also showed that the human brain is not exceptional in its cellular composition, as it was found to contain as many neuronal and non-neuronal cells as would be expected of a primate brain of its size. Additionally, the so-called overdeveloped human cerebral cortex holds only 19% of all brain neurons, a fraction that is similar to that found in other mammals. In what regards absolute numbers of neurons, however, the human brain does have two advantages compared to other mammalian brains: compared to rodents, and probably to whales and elephants as well, it is built according to the very economical, space-saving scaling rules that apply to other primates; and, among economically built primate brains, it is the largest, hence containing the most neurons. These findings argue in favor of a view of cognitive abilities that is centered on absolute numbers of neurons, rather than on body size or encephalization, and call for a re-examination of several concepts related to the exceptionality of the human brain.

Cellular scaling rules of insectivore brains

Insectivores represent extremes in mammalian body size and brain size, retaining various “primitive” morphological characteristics, and some species of Insectivora are thought to share similarities with small-bodied ancestral eutherians. This raises the possibility that insectivore brains differ from other taxa, including rodents and primates, in cellular scaling properties. Here we examine the cellular scaling rules for insectivore brains and demonstrate that insectivore scaling rules overlap somewhat with those for rodents and primates such that the insectivore cortex shares scaling rules with rodents (increasing faster in size than in numbers of neurons), but the insectivore cerebellum shares scaling rules with primates (increasing isometrically). Brain structures pooled as “remaining areas” appear to scale similarly across all three mammalian orders with respect to numbers of neurons, and the numbers of non-neurons appear to scale similarly across all brain structures for all three orders. Therefore, common scaling rules exist, to different extents, between insectivore, rodent, and primate brain regions, and it is hypothesized that insectivores represent the common aspects of each order. The olfactory bulbs of insectivores, however, offer a noteworthy exception in that neuronal density increases linearly with increasing structure mass. This implies that the average neuronal cell size decreases with increasing olfactory bulb mass in order to accommodate greater neuronal density, and represents the first documentation of a brain structure gaining neurons at a greater rate than mass. This might allow insectivore brains to concentrate more neurons within the olfactory bulbs without a prohibitively large and metabolically costly increase in structure mass.

A claim in search of evidence: reply to Manger's thermogenesis hypothesis of cetacean brain structure

In a recent publication in Biological Reviews, Manger (2006) made the controversial claim that the large brains of cetaceans evolved to generate heat during oceanic cooling in the Oligocene epoch and not, as is the currently accepted view, as a basis for an increase in cognitive or information-processing capabilities in response to ecological or social pressures. Manger further argued that dolphins and other cetaceans are considerably less intelligent than generally thought. In this review we challenge Manger's arguments and provide abundant evidence that modern cetacean brains are large in order to support complex cognitive abilities driven by social and ecological forces.

The basic nonuniformity of the cerebral cortex

Evolutionary changes in the size of the cerebral cortex, a columnar structure, often occur through the addition or subtraction of columnar modules with the same number of neurons underneath a unit area of cortical surface. This view is based on the work of Rockel et al. [Rockel AJ, Hiorns RW, Powell TP (1980) The basic uniformity in structure of the neocortex. Brain 103:221-244], who found a steady number of approximately 110 neurons underneath a surface area of 750 microm(2) (147,000 underneath 1 mm(2)) of the cerebral cortex of five species from different mammalian orders. These results have since been either corroborated or disputed by different groups. Here, we show that the number of neurons underneath 1 mm(2) of the cerebral cortical surface of nine primate species and the closely related Tupaia sp. is not constant and varies by three times across species. We found that cortical thickness is not inversely proportional to neuronal density across species and that total cortical surface area increases more slowly than, rather than linearly with, the number of neurons underneath it. The number of neurons beneath a unit area of cortical surface varies linearly with neuronal density, a parameter that is neither related to cortical size nor total number of neurons. Our finding of a variable number of neurons underneath a unit area of the cerebral cortex across primate species indicates that models of cortical organization cannot assume that cortical columns in different primates consist of invariant numbers of neurons.

The scalable mammalian brain: emergent distributions of glia and neurons

In this paper, we demonstrate that two characteristic properties of mammalian brains emerge when scaling-up modular, cortical structures. Firstly, the glia-to-neuron ratio is not constant across brains of different sizes: large mammalian brains have more glia per neuron than smaller brains. Our analyses suggest that if one assumes that glia number is proportional to wiring, a particular quantitative relationship emerges between brain size and glia-to-neuron ratio that fits the empirical data. Secondly, many authors have reported that the number of neurons underlying one mm(2) of mammalian cortex is remarkably constant, across both areas and species. Here, we will show that such a constancy emerges when enlarging modular, cortical brain structures. Our analyses thus corroborate recent studies on the mammalian brain as a scalable architecture, providing a possible mechanism to explain some of the principles, constancies and rules that hold across brains of different size.

Cellular scaling rules for primate brains

Primates are usually found to have richer behavioral repertoires and better cognitive abilities than rodents of similar brain size. This finding raises the possibility that primate brains differ from rodent brains in their cellular composition. Here we examine the cellular scaling rules for primate brains and show that brain size increases approximately isometrically as a function of cell numbers, such that an 11x larger brain is built with 10x more neurons and approximately 12x more nonneuronal cells of relatively constant average size. This isometric function is in contrast to rodent brains, which increase faster in size than in numbers of neurons. As a consequence of the linear cellular scaling rules, primate brains have a larger number of neurons than rodent brains of similar size, presumably endowing them with greater computational power and cognitive abilities.

Cellular scaling rules for rodent brains

How do cell number and size determine brain size? Here, we show that, in the order Rodentia, increased size of the cerebral cortex, cerebellum, and remaining areas across six species is achieved through greater numbers of neurons of larger size, and much greater numbers of nonneuronal cells of roughly invariant size, such that the ratio between total neuronal and nonneuronal mass remains constant across species. Although relative cerebellar size remains stable among rodents, the number of cerebellar neurons increases with brain size more rapidly than in the cortex, such that the cerebellar fraction of total brain neurons increases with brain size. In contrast, although the relative cortical size increases with total brain size, the cortical fraction of total brain neurons remains constant. We propose that the faster increase in average neuronal size in the cerebral cortex than in the cerebellum as these structures gain neurons and the rapidly increasing glial numbers that generate glial mass to match total neuronal mass at a fixed glia/neuron total mass ratio are fundamental cellular constraints that lead to the relative expansion of cerebral cortical volume across species.

Heterogeneity in the columnar number of neurons in different neocortical areas in the rat

We have investigated the number of neurons in three neocortical areas of the rat brain. Our results challenge the uniformity concept proposed by Rockel et al. [Brain, 103 (1980) 221-244]. Area Fr1, HL and Oc2 (primary motor, primary somatosensory and secondary visual cortex) from Sprague-Dawley rats were examined. The brains were glutaraldehyde fixed, sectioned in 50 mu m thick sagittal slices and stained in Richardson's solution. The counting was carried out using a computerized system based on the optical disector. The cortical thickness was measured to be 1.9 mm, 1.9 mm, and 1.4 mm in area Fr1, HL, and Oc2, respectively. The number of neurons under 1 mm2 cortical surface was calculated to be 91 100 in Fr1, 133 500 in HL and 106 100 in Oc2. The number of neurons in a volume of tissue 30 x 25 mu m through the depth of the cortex was calculated to be 68 in Fr1, 100 in HL and 80 in Oc2. The density of neurons was calculated to be 48 500 neurons/mm3 in Fr1, 69 400 neurons/mm3 in HL and 76,900 neurons/mm3 in Oc2. There were significant (P < 0.01) differences between all areas regarding both the number of neurons under a certain area of surface as well as the neuron density. The results indicate that there is no basic uniformity in the number of neurons under a certain area of cortical surface.

The CBF threshold and dynamics for focal cerebral infarction in spontaneously hypertensive rats

Two strategies were used to estimate the blood flow threshold for focal cerebral infarction in spontaneously hypertensive rats (SHRs) subjected to permanent middle cerebral artery and common carotid artery occlusion (MCA/CCAO). The first compared the volume of cortical infarction (24 h after ischemia onset) to the volumes of ischemic cortex (image analysis of [14C]iodoantipyrine CBF autoradiographs) perfused below CBF values less than 50 (VIC50) and less than 25 ml 100 g-1 min-1 (VIC25) at serial intervals during the first 3 h of ischemia. The infarct process becomes irreversible within 3 h in this model. In the second, measurements of CBF at the border separating normal from infarcted cortex at 24 h after ischemia onset were used as an index of the threshold. During the first 3 h of ischemia, VIC50 increased slightly to reach a maximum size at 3 h that closely matched the 24 h infarct volume. VIC25, in contrast, consistently underestimated the infarct volume by a factor of 2-3. CBF at the 24 h infarct border averaged 50 ml 100 g-1 min -1. Taken together, the results indicate that the CBF threshold for infarction in SHRs approaches 50 ml 100 g-1 min-1 when ischemia persists for greater than or equal to 3 h. This threshold value is approximately three times higher than in primates. Since cortical neuronal density is also threefold greater in rats than in primates, the higher injury threshold in the rat may reflect a neuronal primacy in determining the brain's susceptibility to partial ischemia.

Comparative morphometry of Bergmann glial (Golgi epithelial) cells. A Golgi study

Bergmann glial (Golgi epithelial) cells were Golgi-impregnated in the cerebella of species with great differences in the thickness of the molecular layer, in small African native mouse, rat, rhesus monkey, and man. The thickness of the molecular layer determines the length of the radial Bergmann cell processes. Whereas the overall morphology of the cells was found to be strikingly similar in all species studied, there were great quantitative differences in length and diameter of the stem processes. Species with thick molecular layers (man, monkey) have thicker stem processes than species with short distances between Bergmann glial cell soma and pial surface (rat, mouse). This could mean that larger animals with longer gestation periods allow for prolonged growth of cell volumes. On the other hand, an increase in the diameter of long processes should reduce the cytoplasmic resistance against ionic currents; this would be important when Bergmann glial cells--like retinal Müller cells--would act as "cables" for spatial buffering of potassium ions released by electrically active neurons. By contrast, the fractal dimension--i.e., a quantitative measure of the complexity of the cell's border--of the cell processes was lower in species with long processes. In an age series of rat cells, the fractal dimension is shown to increase slightly up to a very old age.

Glia:neuron index: review and hypothesis to account for different values in various mammals

The present paper proposes a hypothesis to account for different values of the glia:neuron index in comparable central nervous system tissues of various mammals. This hypothesis assumes that K+ ions released by active neurons are a mitogenic signal for glial cells. The thicker the tissue (for example, the brain wall), the more difficult is efficient K+ clearance, and more perinatal glial cell proliferation should occur. Thus, this hypothesis accounts for higher glia:neuron indices in mammals with thicker brain walls.