Folding of the cerebellar cortex is clade-specific in form but universal in degree.

Like the cerebralcortex, the surface of the cerebellum is repeatedly folded. Unlike the cerebralcortex, however, cerebellar folds are much thinner and more numerous; repeatthemselves largely along a single direction, forming accordion-like folds transverseto the mid-sagittal plane; and occur in all but the smallest cerebella. We haveshown previously that while the location of folds in mammalian cerebral cortex isclade-specific, the overall degree of folding strictly follows a universalpower law relating cortical thickness and the exposed and total surface areas predictedfrom the minimization of the effective free energy of an expanding, self-avoidingsurface of a certain thickness. Here we show that this scaling law extends tothe folding of the mid-sagittal sections of the cerebellum of 53 speciesbelonging to six mammalian clades. Simultaneously, we show that each clade hasa previously unsuspected distinctive spatial pattern of folding evident at themid-sagittal surface of the cerebellum. We note, however, that the mammaliancerebellum folds as a multi-fractal object, because of the difference betweenthe outside-in development of the cerebellar cortex around a preexisting coreof already connected white matter, compared to the inside-out development ofthe cerebral cortex with a white matter volume that develops as the cerebralcortex itself gains neurons. We conclude that repeated folding, one of the mostrecognizable features of biology, can arise simply from the interplay betweenthe universal applicability of the physics of self-organization and biological,phylogenetical clade-specific contingency, without the need for invokingselective pressures in evolution.

Neurovascular coupling is optimized to compensate for the increase in proton production from nonoxidative glycolysis and glycogenolysis during brain activation and maintain homeostasis of pH, pCO2 , and pO2.

During transient brain activation cerebral blood flow (CBF) increases substantially more than cerebral metabolic rate of oxygen consumption (CMRO2 ) resulting in blood hyperoxygenation, the basis of BOLD fMRI contrast. Explanations for the high CBF vs. CMRO2 slope, termed neurovascular coupling (NVC) constant, focused on maintainenance of tissue oxygenation to support mitochondrial ATP production. However, paradoxically the brain has a 3-fold lower oxygen extraction fraction (OEF) than other organs with high energy requirements, like heart and muscle during exercise. Here, we hypothesize that the NVC constant and the capillary oxygen mass transfer coefficient (which in combination determine OEF) are co-regulated during activation to maintain simultaneous homeostasis of pH and partial pressure of CO2 and O2 (pCO2 and pO2 ). To test our hypothesis, we developed an arteriovenous flux balance model for calculating blood and brain pH, pCO2 , and pO2 as a function of baseline OEF (OEF0 ), CBF, CMRO2 , and proton production by nonoxidative metabolism coupled to ATP hydrolysis. Our model was validated against published brain arteriovenous difference studies and then used to calculate pH, pCO2, and pO2 in activated human cortex from published calibrated fMRI and PET measurements. In agreement with our hypothesis, calculated pH, pCO2, and pO2 remained close to constant independently of CMRO2 in correspondence to experimental measurements of NVC and OEF0 . We also found that the optimum values of the NVC constant and OEF0 that ensure simultaneous homeostasis of pH, pCO2, and pO2 were remarkably similar to their experimental values. Thus, the high NVC constant is overall determined by proton removal by CBF due to increases in nonoxidative glycolysis and glycogenolysis. These findings resolve the paradox of the brain's high CBF yet low OEF during activation, and may contribute to explaining the vulnerability of brain function to reductions in blood flow and capillary density with aging and neurovascular disease.

Theropod dinosaurs had primate-like numbers of telencephalic neurons.

Understanding the neuronal composition of the brains of dinosaurs and other fossil amniotes would offer fundamental insight into their behavioral and cognitive capabilities, but brain tissue is only rarely fossilized. However, when the bony brain case is preserved, the volume and therefore mass of the brain can be estimated with computer tomography; and if the scaling relationship between brain mass and numbers of neurons for the clade is known, that relationship can be applied to estimate the neuronal composition of the brain. Using a recently published database of numbers of neurons in the telencephalon of extant sauropsids (birds, squamates, and testudines), here I show that the neuronal scaling rules that apply to these animals can be used to infer the numbers of neurons that composed the telencephalon of dinosaur, pterosaur, and other fossil sauropsid species. The key to inferring numbers of telencephalic neurons in these species is first using the relationship between their estimated brain and body mass to determine whether bird-like (endothermic) or squamate-like (ectothermic) rules apply to each fossil sauropsid species. This procedure shows that the notion of "mesothermy" in dinosaurs is an artifact due to the mixing of animals with bird-like and squamate-like scaling, and indicates that theropods such as Tyrannosaurus and Allosaurus were endotherms with baboon- and monkey-like numbers of telencephalic neurons, respectively, which would make these animals not only giant but also long-lived and endowed with flexible cognition, and thus even more magnificent predators than previously thought.

Energy supply per neuron is constrained by capillary density in the mouse brain.

Neuronal densities vary enormously across sites within a brain. Does the density of the capillary bed vary accompanying the presumably larger energy requirement of sites with more neurons, or with larger neurons, or is energy supply constrained by a mostly homogeneous capillary bed? Here we find evidence for the latter, with a capillary bed that represents typically between 0.7 and 1.5% of the volume of the parenchyma across various sites in the mouse brain, whereas neuronal densities vary by at least 100-fold. As a result, the ratio of capillary cells per neuron decreases uniformly with increasing neuronal density and therefore with smaller average neuronal size across sites. Thus, given the relatively constant capillary density compared to neuronal density in the brain, blood and energy availability per neuron is presumably dependent on how many neurons compete for the limited supply provided by a mostly homogeneous capillary bed. Additionally, we find that local capillary density is not correlated with local synapse densities, although there is a small but significant correlation between lower neuronal density (and therefore larger neuronal size) and more synapses per neuron within the restricted range of 6,500-9,500 across cortical sites. Further, local variations in the glial/neuron ratio are not correlated with local variations in the number of synapses per neuron or local synaptic densities. These findings suggest that it is not that larger neurons, neurons with more synapses, or even sites with more synapses demand more energy, but simply that larger neurons (in low density sites) have more energy available per cell and for the totality of its synapses than smaller neurons (in high density sites) due to competition for limited resources supplied by a capillary bed of fairly homogeneous density throughout the brain.

Resting Rates of Blood Flow and Glucose Use per Neuron Are Proportional to Number of Endothelial Cells Available per Neuron Across Sites in the Rat Brain.

We report in a companion paper that in the mouse brain, in contrast to the 1,000-fold variation in local neuronal densities across sites, capillary density (measured both as capillary volume fraction and as density of endothelial cells) show very little variation, of the order of only fourfold. Here we confirm that finding in the rat brain and, using published rates of local blood flow and glucose use at rest, proceed to show that what small variation exists in capillary density across sites in the rat brain is strongly and linearly correlated to variations in local rates of brain metabolism at rest. Crucially, we show that such variations in local capillary density and brain metabolism are not correlated with local variations in neuronal density, which contradicts expectations that use-dependent self-organization would cause brain sites with more neurons to have higher capillary densities due to higher energetic demands. In fact, we show that the ratio of endothelial cells per neuron serves as a linear indicator of average blood flow and glucose use per neuron at rest, and both increase as neuronal density decreases across sites. In other words, because of the relatively tiny variation in capillary densities compared to the large variation in neuronal densities, the anatomical infrastructure of the brain is such that those sites with fewer neurons have more energy supplied per neuron, which matches a higher average rate of energy use per neuron, compared to sites with more neurons. Taken together, our data support the interpretation that resting brain metabolism is not demand-based, but rather limited by its capillary supply, and raise multiple implications for the differential vulnerability of diverse brain areas to disease and aging.

From a Demand-Based to a Supply-Limited Framework of Brain Metabolism.

What defines the rate of energy use by the brain, as well as per neurons of different sizes in different structures and animals, is one fundamental aspect of neuroscience for which much has been theorized, but very little data are available. The prevalent theories and models consider that energy supply from the vascular system to different brain regions is adjusted both dynamically and in the course of development and evolution to meet the demands of neuronal activity. In this perspective, we offer an alternative view: that regional rates of energy use might be mostly constrained by supply, given the properties of the brain capillary network, the highly stable rate of oxygen delivery to the whole brain under physiological conditions, and homeostatic constraints. We present evidence that these constraints, based on capillary density and tissue oxygen homeostasis, are similar between brain regions and mammalian species, suggesting they derive from fundamental biophysical limitations. The same constraints also determine the relationship between regional rates of brain oxygen supply and usage over the full physiological range of brain activity, from deep sleep to intense sensory stimulation, during which the apparent uncoupling of blood flow and oxygen use is still a predicted consequence of supply limitation. By carefully separating "energy cost" into energy supply and energy use, and doing away with the problematic concept of energetic "demands," our new framework should help shine a new light on the neurovascular bases of metabolic support of brain function and brain functional imaging. We speculate that the trade-offs between functional systems and even the limitation to a single attentional spot at a time might be consequences of a strongly supply-limited brain economy. We propose that a deeper understanding of brain energy supply constraints will provide a new evolutionary understanding of constraints on brain function due to energetics; offer new diagnostic insight to disturbances of brain metabolism; lead to clear, testable predictions on the scaling of brain metabolic cost and the evolution of brains of different sizes; and open new lines of investigation into the microvascular bases of progressive cognitive loss in normal aging as well as metabolic diseases.

Mammalian neurobiology: The elephant (brain) in the room.

Neuroscience research is understandably focused on highly tractable and lab-friendly mice and rats, but that emphasis obfuscates the biological beauty and intellectual richness that lies in animal diversity. The benefits of venturing further into that phylogenetic diversity are nicely illustrated by a new study on the elephant brain.

High associative neuron numbers could drive cognitive performance in corvid species.

Corvids possess cognitive skills, matching those of nonhuman primates. However, how these species with their small brains achieve such feats remains elusive. Recent studies suggest that cognitive capabilities could be based on the total numbers of telencephalic neurons. Here we extend this hypothesis further and posit that especially high neuron counts in associative pallial areas drive flexible, complex cognition. If true, avian species like corvids should specifically accumulate neurons in the avian associative areas meso- and nidopallium. To test the hypothesis, we analyzed the neuronal composition of telencephalic areas in corvids and noncorvids (chicken, pigeons, and ostriches-the species with the largest bird brain). The overall number of pallial neurons in corvids was much higher than in chicken and pigeons and comparable to those of ostriches. However, neuron numbers in the associative mesopallium and nidopallium were twice as high in corvids and, in correlation with these associative areas, the corvid subpallium also contained high neuron numbers. These findings support our hypothesis that large absolute numbers of associative pallial neurons contribute to cognitive flexibility and complexity and are key to explain why crows are smart. Since meso-/nidopallial and subpallial areas scale jointly, it is conceivable that associative pallio-striatal loops play a similar role in executive decision making as described in primates.

Cytoarchitectural characteristics associated with cognitive flexibility in raccoons.

With rates of psychiatric illnesses such as depression continuing to rise, additional preclinical models are needed to facilitate translational neuroscience research. In the current study, the raccoon (Procyon lotor) was investigated due to its similarities with primate brains, including comparable proportional neuronal densities, cortical magnification of the forepaw area, and cortical gyrification. Specifically, we report on the cytoarchitectural characteristics of raccoons profiled as high, intermediate, or low solvers in a multiaccess problem-solving task. Isotropic fractionation indicated that high-solvers had significantly more cells in the hippocampus (HC) than the other solving groups; further, a nonsignificant trend suggested that this increase in cell profile density was due to increased nonneuronal (e.g., glial) cells. Group differences were not observed in the cellular density of the somatosensory cortex. Thionin-based staining confirmed the presence of von Economo neurons (VENs) in the frontoinsular cortex, although no impact of solving ability on VEN cell profile density levels was observed. Elongated fusiform cells were quantified in the HC dentate gyrus where high-solvers were observed to have higher levels of this cell type than the other solving groups. In sum, the current findings suggest that varying cytoarchitectural phenotypes contribute to cognitive flexibility. Additional research is necessary to determine the translational value of cytoarchitectural distribution patterns on adaptive behavioral outcomes associated with cognitive performance and mental health.

Are ectotherm brains vulnerable to global warming?

Elevated temperatures during development affect a wide range of traits in ectotherms. Less well understood is the impact of global warming on brain development, which has only rarely been studied experimentally. Here, we evaluate current progress in the field and search for common response patterns among ectotherm groups. Evidence suggests that temperature may have a positive effect on neuronal activity and growth in developing brains, but only up to a threshold, above which temperature is detrimental to neuron development. These responses appear to be taxon dependent but this assumption may be due to a paucity of data for some taxonomic groups. We provide a framework with which to advance this highly promising field in the future.

Amplification of potential thermogenetic mechanisms in cetacean brains compared to artiodactyl brains.

To elucidate factors underlying the evolution of large brains in cetaceans, we examined 16 brains from 14 cetartiodactyl species, with immunohistochemical techniques, for evidence of non-shivering thermogenesis. We show that, in comparison to the 11 artiodactyl brains studied (from 11 species), the 5 cetacean brains (from 3 species), exhibit an expanded expression of uncoupling protein 1 (UCP1, UCPs being mitochondrial inner membrane proteins that dissipate the proton gradient to generate heat) in cortical neurons, immunolocalization of UCP4 within a substantial proportion of glia throughout the brain, and an increased density of noradrenergic axonal boutons (noradrenaline functioning to control concentrations of and activate UCPs). Thus, cetacean brains studied possess multiple characteristics indicative of intensified thermogenetic functionality that can be related to their current and historical obligatory aquatic niche. These findings necessitate reassessment of our concepts regarding the reasons for large brain evolution and associated functional capacities in cetaceans.

A community-based transcriptomics classification and nomenclature of neocortical cell types.

To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.

Microchiropterans have a diminutive cerebral cortex, not an enlarged cerebellum, compared to megachiropterans and other mammals.

Small echolocating bats are set apart from most other mammals by their relatively large cerebellum, a feature that has been associated to echolocation, as it is presumed to indicate a relatively enlarged number of neurons in the cerebellum in comparison to other brain structures. Here we quantify the neuronal composition of the cerebral cortex, cerebellum and remaining brain structures of seven species of large Pteropodid bats (formerly classified as megachiropterans), one of which echolocates, and six species of small bats (formerly classified as microchiropterans), all of which echolocate. This chiropteran data is compared to 60 mammalian species in our dataset to determine whether the relatively large cerebellum of the small echolocating bats, and possibly that of the echolocating Pteropodid, contains a relatively enlarged number of neurons. We find no evidence that the distribution of neurons differs between microchiropterans and megachiropterans, but our data indicate that microchiropterans, like the smallest shrew in our dataset, have diminutive cerebral cortices, which makes the cerebellum appear relatively large. We propose that, in agreement with the diminutive brain size of the earliest fossil mammals, this is a plesiomorphic, not a derived, feature of microchiropteran brains. The results of this study also reveal important neural characteristics related to the phylogenetic affinities and relationships of the chiropterans.

The relationship between the number of neurons and behavioral performance in Swiss mice.

Neuronal number varies by several orders of magnitude across species, and has been proposed to predict cognitive capability across species. Remarkably, numbers of neurons vary across individual mice by a factor of 2 or more. We directly addressed the question of whether there is a relationship between performance in behavioral tests and the number of neurons in functionally relevant structures in the mouse brain. Naïve Swiss mice went through a battery of behavioral tasks designed to measure cognitive, motor and olfactory skills. We estimated the number of neurons in different brain regions (cerebral cortex, hippocampus, olfactory bulb, cerebellum and remaining areas) and crossed the two datasets to test the a priori hypothesis of correlation between cognitive abilities and numbers of neurons. Surprisingly, performance in the behavioral tasks did not correlate strongly with number of neurons in any of the brain regions studied. Our results show that whereas neuronal number is a predictor of cognitive skills across species, it is not a good predictor of cognitive, sensory or motor ability across individuals within a species, which suggests that other factors are more relevant for explaining cognitive differences between individuals of the same species.

Similar Microglial Cell Densities across Brain Structures and Mammalian Species: Implications for Brain Tissue Function.

Microglial cells play essential volume-related actions in the brain that contribute to the maturation and plasticity of neural circuits that ultimately shape behavior. Microglia can thus be expected to have similar cell sizes and even distribution both across brain structures and across species with different brain sizes. To test this hypothesis, we determined microglial cell densities (the inverse of cell size) using immunocytochemistry to Iba1 in samples of free cell nuclei prepared with the isotropic fractionator from brain structures of 33 mammalian species belonging to males and females of five different clades. We found that microglial cells constitute ∼7% of non-neuronal cells in different brain structures as well as in the whole brain of all mammalian species examined. Further, they vary little in cell density compared with neuronal cell densities within the cerebral cortex, across brain structures, across species within the same clade, and across mammalian clades. As a consequence, we find that one microglial cell services as few as one and as many as 100 neurons in different brain regions and species, depending on the local neuronal density. We thus conclude that the addition of microglial cells to mammalian brains is governed by mechanisms that constrain the size of these cells and have remained conserved over 200 million years of mammalian evolution. We discuss the probable consequences of such constrained size for brain function in health and disease.SIGNIFICANCE STATEMENT Microglial cells are resident macrophages of the CNS, with key functions in recycling synapses and maintaining the local environment in health and disease. We find that microglial cells occur in similar densities in the brains of different species and in the different structures of each individual brain, which indicates that these cells maintain a similar average size in mammalian evolution, suggesting in turn that the volume monitored by each microglial cell remains constant across mammals. Because the density of neurons is highly variable across the same brain structures and species, our finding implies that microglia-dependent functional recovery may be particularly difficult in those brain structures and species with high neuronal densities and therefore fewer microglial cells per neuron.

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.