Global and regional brain metabolic scaling and its functional consequences

Profound seasonal changes in brain size and architecture in the common shrew

The seasonal changes in brain size of some shrews represent the most drastic reversible transformation in the mammalian central nervous system known to date. Brain mass decreases 10-26% from summer to winter and regrows 9-16% in spring, but the underlying structural changes at the cellular level are not yet understood. Here, we describe the volumetric differences in brain structures between seasons and sexes of the common shrew (Sorex araneus) in detail, confirming that changes in different brain regions vary in the magnitude of change. Notably, shrews show a decrease in hypothalamus, thalamus, and hippocampal volume and later regrowth in spring, whereas neocortex and striatum volumes decrease in winter and do not recover in size. For some regions, males and females showed different patterns of seasonal change from each other. We also analyzed the underlying changes in neuron morphology. We observed a general decrease in soma size and total dendrite volume in the caudoputamen and anterior cingulate cortex. This neuronal retraction may partially explain the overall tissue shrinkage in winter. While not sufficient to explain the entire seasonal process, it represents a first step toward understanding the mechanisms beneath this remarkable phenomenon.

Evolutionary perspective on sex differences in the expression of neurological diseases

Sex-specific brain and cognitive deficits emerge with malnutrition, some infectious and neurodegenerative diseases, and often with prenatal or postnatal toxin exposure. These deficits are described in disparate literatures and are generally not linked to one another. Sexual selection may provide a unifying framework that integrates our understanding of these deficits and provides direction for future studies of sex-specific vulnerabilities. Sexually selected traits are those that have evolved to facilitate competition for reproductive resources or that influence mate choices, and are often larger and more complex than other traits. Critically, malnutrition, disease, chronic social stress, and exposure to man-made toxins compromise the development and expression of sexually selected traits more strongly than that of other traits. The fundamental mechanism underlying vulnerability might be the efficiency of mitochondrial energy capture and control of oxidative stress that in turn links these traits to current advances in neuroenergetics, stress endocrinology, and toxicology. The key idea is that the elaboration of these cognitive abilities, with more underlying gray matter or more extensive inter-modular white matter connections, makes them particularly sensitive to disruptions in mitochondrial functioning and oxidative stress. A framework of human sexually selected cognitive abilities and underlying brain systems is proposed and used to organize what is currently known about sex-specific vulnerabilities.

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.

Optimal synaptic signaling connectome for locomotory behavior in Caenorhabditis elegans: Design minimizing energy cost

The detailed knowledge of C. elegans connectome for 3 decades has not contributed dramatically to our understanding of worm's behavior. One of main reasons for this situation has been the lack of data on the type of synaptic signaling between particular neurons in the worm's connectome. The aim of this study was to determine synaptic polarities for each connection in a small pre-motor circuit controlling locomotion. Even in this compact network of just 7 neurons the space of all possible patterns of connection types (excitation vs. inhibition) is huge. To deal effectively with this combinatorial problem we devised a novel and relatively fast technique based on genetic algorithms and large-scale parallel computations, which we combined with detailed neurophysiological modeling of interneuron dynamics and compared the theory to the available behavioral data. As a result of these massive computations, we found that the optimal connectivity pattern that matches the best locomotory data is the one in which all interneuron connections are inhibitory, even those terminating on motor neurons. This finding is consistent with recent experimental data on cholinergic signaling in C. elegans, and it suggests that the system controlling locomotion is designed to save metabolic energy. Moreover, this result provides a solid basis for a more realistic modeling of neural control in these worms, and our novel powerful computational technique can in principle be applied (possibly with some modifications) to other small-scale functional circuits in C. elegans.

Scaling of bony canals for encephalic vessels in euarchontans: Implications for the role of the vertebral artery and brain metabolism

Supplying the central nervous system with oxygen and glucose for metabolic activities is a critical function for all animals at physiologic, anatomical, and behavioral levels. A relatively proximate challenge to nourishing the brain is maintaining adequate blood flow. Euarchontans (primates, dermopterans and treeshrews) display a diversity of solutions to this challenge. Although the vertebral artery is a major encephalic vessel, previous research has questioned its importance for irrigating the cerebrum. This presents a puzzling scenario for certain strepsirrhine primates (non-cheirogaleid lemuriforms) that have reduced promontorial branches of the internal carotid artery and no apparent alternative encephalic vascular route except for the vertebral artery. Here, we present results of phylogenetic comparative analyses of data on the cross-sectional area of bony canals that transmit the vertebral artery (transverse foramina). These results show that, across primates (and within major primate subgroups), variation in the transverse foramina helps significantly to explain variation in forebrain mass even when variation in promontorial canal cross-sectional areas are also considered. Furthermore, non-cheirogaleid lemuriforms have larger transverse foramina for their endocranial volume than other euarchontans, suggesting that the vertebral arteries compensate for reduced promontorial artery size. We also find that, among internal carotid-reliant euarchontans, species that are more encephalized tend to have a promontorial canal that is larger relative to the transverse foramina. Tentatively, we consider the correlation between arterial canal diameters (as a proxy for blood flow) and brain metabolic demands. The results of this analysis imply that human investment in brain metabolism (∼27% of basal metabolic rate) may not be exceptional among euarchontans.

Zdhhc13-dependent Drp1 S-palmitoylation impacts brain bioenergetics, anxiety, coordination and motor skills

Protein S-palmitoylation is a reversible post-translational modification mediated by palmitoyl acyltransferase enzymes, a group of Zn²⁺-finger DHHC-domain-containing proteins (ZDHHC). Here, for the first time, we show that Zdhhc13 plays a key role in anxiety-related behaviors and motor function, as well as brain bioenergetics, in a mouse model (luc) carrying a spontaneous Zdhhc13 recessive mutation. At 3 m of age, mutant mice displayed increased sensorimotor gating, anxiety, hypoactivity, and decreased motor coordination, compared to littermate controls. Loss of Zdhhc13 in cortex and cerebellum from 3- and 24 m old hetero- and homozygous male mutant mice resulted in lower levels of Drp1 S-palmitoylation accompanied by altered mitochondrial dynamics, increased glycolysis, glutaminolysis and lactic acidosis, and neurotransmitter imbalances. Employing in vivo and in vitro models, we identified that Zdhhc13-dependent Drp1 S-palmitoylation, which acting alone or in concert, enables the normal occurrence of the fission-fusion process. In vitro and in vivo direct Zdhhc13-Drp1 protein interaction was observed, confirming Drp1 as a substrate of Zdhhc13. Abnormal fission-fusion processes result in disrupted mitochondria morphology and distribution affecting not only mitochondrial ATP output but neurotransmission and integrity of synaptic structures in the brain, setting the basis for the behavioral abnormalities described in the Zdhhc13-deficient mice.

Why are there so many explanations for primate brain evolution?

The question as to why primates have evolved unusually large brains has received much attention, with many alternative proposals all supported by evidence. We review the main hypotheses, the assumptions they make and the evidence for and against them. Taking as our starting point the fact that every hypothesis has sound empirical evidence to support it, we argue that the hypotheses are best interpreted in terms of a framework of evolutionary causes (selection factors), consequences (evolutionary windows of opportunity) and constraints (usually physiological limitations requiring resolution if large brains are to evolve). Explanations for brain evolution in birds and mammals generally, and primates in particular, have to be seen against the backdrop of the challenges involved with the evolution of coordinated, cohesive, bonded social groups that require novel social behaviours for their resolution, together with the specialized cognition and neural substrates that underpin this. A crucial, but frequently overlooked, issue is that fact that the evolution of large brains required energetic, physiological and time budget constraints to be overcome. In some cases, this was reflected in the evolution of 'smart foraging' and technical intelligence, but in many cases required the evolution of behavioural competences (such as coalition formation) that required novel cognitive skills. These may all have been supported by a domain-general form of cognition that can be used in many different contexts.This article is part of the themed issue 'Physiological determinants of social behaviour in animals'.

Topological length of white matter connections predicts their rate of atrophy in premanifest Huntington's disease

We lack a mechanistic explanation for the stereotyped pattern of white matter loss seen in Huntington’s disease (HD). While the earliest white matter changes are seen around the striatum, within the corpus callosum, and in the posterior white matter tracts, the order in which these changes occur and why these white matter connections are specifically vulnerable is unclear. Here, we use diffusion tractography in a longitudinal cohort of individuals yet to develop clinical symptoms of HD to identify a hierarchy of vulnerability, where the topological length of white matter connections between a brain area and its neighbors predicts the rate of atrophy over 24 months. This demonstrates a new principle underlying neurodegeneration in HD, whereby brain connections with the greatest topological length are the first to suffer damage that can account for the stereotyped pattern of white matter loss observed in premanifest HD.

Diffusion tractography in a longitudinal cohort demonstrates that topological length of white matter connections can account for white matter loss patterns in premanifest Huntington’s disease.

Neurons derived from different brain regions are inherently different in vitro: a novel multiregional brain-on-a-chip

Brain in vitro models are critically important to developing our understanding of basic nervous system cellular physiology, potential neurotoxic effects of chemicals, and specific cellular mechanisms of many disease states. In this study, we sought to address key shortcomings of current brain in vitro models: the scarcity of comparative data for cells originating from distinct brain regions and the lack of multiregional brain in vitro models. We demonstrated that rat neurons from different brain regions exhibit unique profiles regarding their cell composition, protein expression, metabolism, and electrical activity in vitro. In vivo, the brain is unique in its structural and functional organization, and the interactions and communication between different brain areas are essential components of proper brain function. This fact and the observation that neurons from different areas of the brain exhibit unique behaviors in vitro underline the importance of establishing multiregional brain in vitro models. Therefore, we here developed a multiregional brain-on-a-chip and observed a reduction of overall firing activity, as well as altered amounts of astrocytes and specific neuronal cell types compared with separately cultured neurons. Furthermore, this multiregional model was used to study the effects of phencyclidine, a drug known to induce schizophrenia-like symptoms in vivo, on individual brain areas separately while monitoring downstream effects on interconnected regions. Overall, this work provides a comparison of cells from different brain regions in vitro and introduces a multiregional brain-on-a-chip that enables the development of unique disease models incorporating essential in vivo features.NEW & NOTEWORTHY Due to the scarcity of comparative data for cells from different brain regions in vitro, we demonstrated that neurons isolated from distinct brain areas exhibit unique behaviors in vitro. Moreover, in vivo proper brain function is dependent on the connection and communication of several brain regions, underlining the importance of developing multiregional brain in vitro models. We introduced a novel brain-on-a-chip model, implementing essential in vivo features, such as different brain areas and their functional connections.

Fossil skulls reveal that blood flow rate to the brain increased faster than brain volume during human evolution

The evolution of human cognition has been inferred from anthropological discoveries and estimates of brain size from fossil skulls. A more direct measure of cognition would be cerebral metabolic rate, which is proportional to cerebral blood flow rate (perfusion). The hominin cerebrum is supplied almost exclusively by the internal carotid arteries. The sizes of the foramina that transmitted these vessels in life can be measured in hominin fossil skulls and used to calculate cerebral perfusion rate. Perfusion in 11 species of hominin ancestors, from Australopithecus to archaic Homo sapiens, increases disproportionately when scaled against brain volume (the allometric exponent is 1.41). The high exponent indicates an increase in the metabolic intensity of cerebral tissue in later Homo species, rather than remaining constant (1.0) as expected by a linear increase in neuron number, or decreasing according to Kleiber's Law (0.75). During 3 Myr of hominin evolution, cerebral tissue perfusion increased 1.7-fold, which, when multiplied by a 3.5-fold increase in brain size, indicates a 6.0-fold increase in total cerebral blood flow rate. This is probably associated with increased interneuron connectivity, synaptic activity and cognitive function, which all ultimately depend on cerebral metabolic rate.

Reduced cerebrovascular reserve is regionally associated with cortical thickness reductions in children with sickle cell disease

Sickle cell disease (SCD) is a genetic disorder which adversely affects cerebrovascular health. Previous studies have demonstrated regional cortical thinning in SCD. However, the reason behind regional reductions in cortical thickness remains unclear. Therefore, we aimed to explore the possible link between the state of cerebrovascular health and cortical thickness. In this study, we obtained magnetic resonance (MR) based measures of cerebrovascular reactivity (CVR), a measure of vascular health, and cortical thickness in SCD patients (N=60) and controls of similar age and similar gender ratio (N=27). The group comparison analysis revealed significant regionally specific reductions in CVR and cortical thickness in the SCD group compared to the controls. In addition, a regional association analysis was performed between CVR and cortical thickness in the SCD group which revealed a significant regional association in several brain regions with the highest strength of association observed in the left cuneus, right post central gyrus and the right temporal pole. The regional association analysis revealed that significant associations were found in brain regions with high metabolic activity (anterior cingulate, posterior cingulate, occipital gyrus, precuneus) thus demonstrating that these regions could be most vulnerable to structural damage under hypoxic conditions.

Analytic Models of Oxygen and Nutrient Diffusion, Metabolism Dynamics, and Architecture Optimization in Three-Dimensional Tissue Constructs with Applications and Insights in Cerebral Organoids

Diffusion models are important in tissue engineering as they enable an understanding of gas, nutrient, and signaling molecule delivery to cells in cell cultures and tissue constructs. As three-dimensional (3D) tissue constructs become larger, more intricate, and more clinically applicable, it will be essential to understand internal dynamics and signaling molecule concentrations throughout the tissue and whether cells are receiving appropriate nutrient delivery. Diffusion characteristics present a significant limitation in many engineered tissues, particularly for avascular tissues and for cells whose viability, differentiation, or function are affected by concentrations of oxygen and nutrients. This article seeks to provide novel analytic solutions for certain cases of steady-state and nonsteady-state diffusion and metabolism in basic 3D construct designs (planar, cylindrical, and spherical forms), solutions that would otherwise require mathematical approximations achieved through numerical methods. This model is applied to cerebral organoids, where it is shown that limitations in diffusion and organoid size can be partially overcome by localizing metabolically active cells to an outer layer in a sphere, a regionalization process that is known to occur through neuroglial precursor migration both in organoids and in early brain development. The given prototypical solutions include a review of metabolic information for many cell types and can be broadly applied to many forms of tissue constructs. This work enables researchers to model oxygen and nutrient delivery to cells, predict cell viability, study dynamics of mass transport in 3D tissue constructs, design constructs with improved diffusion capabilities, and accurately control molecular concentrations in tissue constructs that may be used in studying models of development and disease or for conditioning cells to enhance survival after insults like ischemia or implantation into the body, thereby providing a framework for better understanding and exploring the characteristics and behaviors of engineered tissue constructs.

Cortical Composition Hierarchy Driven by Spine Proportion Economical Maximization or Wire Volume Minimization

The structure and quantitative composition of the cerebral cortex are interrelated with its computational capacity. Empirical data analyzed here indicate a certain hierarchy in local cortical composition. Specifically, neural wire, i.e., axons and dendrites take each about 1/3 of cortical space, spines and glia/astrocytes occupy each about (1/3)², and capillaries around (1/3)⁴. Moreover, data analysis across species reveals that these fractions are roughly brain size independent, which suggests that they could be in some sense optimal and thus important for brain function. Is there any principle that sets them in this invariant way? This study first builds a model of local circuit in which neural wire, spines, astrocytes, and capillaries are mutually coupled elements and are treated within a single mathematical framework. Next, various forms of wire minimization rule (wire length, surface area, volume, or conduction delays) are analyzed, of which, only minimization of wire volume provides realistic results that are very close to the empirical cortical fractions. As an alternative, a new principle called “spine economy maximization” is proposed and investigated, which is associated with maximization of spine proportion in the cortex per spine size that yields equally good but more robust results. Additionally, a combination of wire cost and spine economy notions is considered as a meta-principle, and it is found that this proposition gives only marginally better results than either pure wire volume minimization or pure spine economy maximization, but only if spine economy component dominates. However, such a combined meta-principle yields much better results than the constraints related solely to minimization of wire length, wire surface area, and conduction delays. Interestingly, the type of spine size distribution also plays a role, and better agreement with the data is achieved for distributions with long tails. In sum, these results suggest that for the efficiency of local circuits wire volume may be more primary variable than wire length or temporal delays, and moreover, the new spine economy principle may be important for brain evolutionary design in a broader context.

Cerebral cortex is an outer layer of the brain in mammals, and it plays a critical part in various cognitive processes such as learning, memory, attention, language, and consciousness. The cerebral cortex contains a number of neuroanatomical parameters whose values are essentially conserved across species and brain sizes, which suggests that these particular parameters are somehow important for brain efficient functioning. This study shows that the fractional volumes of five major cortical components both neuronal and non-neuronal (axons, dendrites, spines, glia/astrocytes, capillaries) are also approximately conserved across mammals, and neural wire (axons and dendrites) occupies the most of cortical space. Moreover, the fractional volumes form a special hierarchy of dependencies, being approximately equal to integer powers of 1/3. Is there any evolutionary principle of cortical organization that would explain these properties? This study finds that there are two different theoretical principles that can provide answers: one standard related to minimization of neural wire fractional volume, and a new proposition associated with economical maximization of spine content. However, the latter principle produces more robust results, which suggests that spine economical maximization is potentially an alternative to the more common “wire minimization” in explaining the cortical layout. Therefore, the current study can become an important contribution to our understanding (or debating) of the main factors influencing the evolution of local cortical circuits in the brain.

Cerebral metabolic rate of oxygen (CMRO2) assessed by combined Doppler and spectroscopic OCT

A method of measuring cortical oxygen metabolism in the mouse brain that uses independent quantitative measurements of three key parameters: cerebral blood flow (CBF), arteriovenous oxygen extraction (OE), and hemoglobin concentration ([HbT]) is presented. Measurements were performed using a single visible light spectral/Fourier domain OCT microscope, with Doppler and spectroscopic capabilities, through a thinned-skull cranial window in the mouse brain. Baseline metabolic measurements in mice are shown to be consistent with literature values. Oxygen consumption, as measured by this method, did not change substantially during minor changes either in the fraction of inspired oxygen (FiO2) or in the fraction of inspired carbon dioxide (FiCO2), in spite of larger variations in oxygen saturations. This set of experiments supports, but does not prove, the validity of the proposed method of measuring brain oxygen metabolism.

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.

High-Throughput Tissue Bioenergetics Analysis Reveals Identical Metabolic Allometric Scaling for Teleost Hearts and Whole Organisms

Organismal metabolic rate, a fundamental metric in biology, demonstrates an allometric scaling relationship with body size. Fractal-like vascular distribution networks of biological systems are proposed to underlie metabolic rate allometric scaling laws from individual organisms to cells, mitochondria, and enzymes. Tissue-specific metabolic scaling is notably absent from this paradigm. In the current study, metabolic scaling relationships of hearts and brains with body size were examined by improving on a high-throughput whole-organ oxygen consumption rate (OCR) analysis method in five biomedically and environmentally relevant teleost model species. Tissue-specific metabolic scaling was compared with organismal routine metabolism (RMO₂), which was measured using whole organismal respirometry. Basal heart OCR and organismal RMO₂ scaled identically with body mass in a species-specific fashion across all five species tested. However, organismal maximum metabolic rates (MMO₂) and pharmacologically-induced maximum cardiac metabolic rates in zebrafish Danio rerio did not show a similar relationship with body mass. Brain metabolic rates did not scale with body size. The identical allometric scaling of heart and organismal metabolic rates with body size suggests that hearts, the power generator of an organism’s vascular distribution network, might be crucial in determining teleost metabolic rate scaling under routine conditions. Furthermore, these findings indicate the possibility of measuring heart OCR utilizing the high-throughput approach presented here as a proxy for organismal metabolic rate—a useful metric in characterizing organismal fitness. In addition to heart and brain OCR, the current approach was also used to measure whole liver OCR, partition cardiac mitochondrial bioenergetic parameters using pharmacological agents, and estimate heart and brain glycolytic rates. This high-throughput whole-organ bioenergetic analysis method has important applications in toxicology, evolutionary physiology, and biomedical sciences, particularly in the context of investigating pathogenesis of mitochondrial diseases.

Altered resting perfusion and functional connectivity of default mode network in youth with autism spectrum disorder

BACKGROUND

Neuroimaging studies can shed light on the neurobiological underpinnings of autism spectrum disorders (ASD). Studies of the resting brain have shown both altered baseline metabolism from PET/SPECT and altered functional connectivity (FC) of intrinsic brain networks based on resting-state fMRI. To date, however, no study has investigated these two physiological parameters of resting brain function jointly, or explored the relationship between these measures and ASD symptom severity.

METHODS

Here, we used pseudo-continuous arterial spin labeling with 3D background-suppressed GRASE to assess resting cerebral blood flow (CBF) and FC in 17 youth with ASD and 22 matched typically developing (TD) children.

RESULTS

A pattern of altered resting perfusion was found in ASD versus TD children including frontotemporal hyperperfusion and hypoperfusion in the dorsal anterior cingulate cortex. We found increased local FC in the anterior module of the default mode network (DMN) accompanied by decreased CBF in the same area. In our cohort, both alterations were associated with greater social impairments as assessed with the Social Responsiveness Scale (SRS-total T scores). While FC was correlated with CBF in TD children, this association between FC and baseline perfusion was disrupted in children with ASD. Furthermore, there was reduced long-range FC between anterior and posterior modules of the DMN in children with ASD.

CONCLUSION

Taken together, the findings of this study--the first to jointly assess resting CBF and FC in ASD--highlight new avenues for identifying novel imaging markers of ASD symptomatology.

Metabolism of dinosaurs as determined from their growth

A model based on cellular properties is used to analyze the mass growth curves of 20 dinosaurs. This analysis yields the first measurement of the average cellular metabolism of dinosaurs. The organismal metabolism is also determined. The cellular metabolism of dinosaurs is found to decrease with mass at a slower rate than is observed in extant animals. The organismal metabolism increases with the mass of the dinosaur. These results come from both the Saurischia and Ornithischia branches of Dinosauria, suggesting that the observed metabolic features were common to all dinosaurs. The results from dinosaurs are compared to data from extant placental and marsupial mammals, a monotreme, and altricial and precocial birds, reptiles, and fish. Dinosaurs had cellular and organismal metabolisms in the range observed in extant mesotherms.

A cellular perspective on brain energy metabolism and functional imaging

The energy demands of the brain are high: they account for at least 20% of the body's energy consumption. Evolutionary studies indicate that the emergence of higher cognitive functions in humans is associated with an increased glucose utilization and expression of energy metabolism genes. Functional brain imaging techniques such as fMRI and PET, which are widely used in human neuroscience studies, detect signals that monitor energy delivery and use in register with neuronal activity. Recent technological advances in metabolic studies with cellular resolution have afforded decisive insights into the understanding of the cellular and molecular bases of the coupling between neuronal activity and energy metabolism and point at a key role of neuron-astrocyte metabolic interactions. This article reviews some of the most salient features emerging from recent studies and aims at providing an integration of brain energy metabolism across resolution scales.

Scaling of cerebral blood perfusion in primates and marsupials

The evolution of primates involved increasing body size, brain size and presumably cognitive ability. Cognition is related to neural activity, metabolic rate and rate of blood flow to the cerebral cortex. These parameters are difficult to quantify in living animals. This study shows that it is possible to determine the rate of cortical brain perfusion from the size of the internal carotid artery foramina in skulls of certain mammals, including haplorrhine primates and diprotodont marsupials. We quantify combined blood flow rate in both internal carotid arteries as a proxy of brain metabolism in 34 species of haplorrhine primates (0.116-145 kg body mass) and compare it to the same analysis for 19 species of diprotodont marsupials (0.014-46 kg). Brain volume is related to body mass by essentially the same exponent of 0.70 in both groups. Flow rate increases with haplorrhine brain volume to the 0.95 power, which is significantly higher than the exponent (0.75) expected for most organs according to 'Kleiber's Law'. By comparison, the exponent is 0.73 in marsupials. Thus, the brain perfusion rate increases with body size and brain size much faster in primates than in marsupials. The trajectory of cerebral perfusion in primates is set by the phylogenetically older groups (New and Old World monkeys, lesser apes) and the phylogenetically younger groups (great apes, including humans) fall near the line, with the highest perfusion. This may be associated with disproportionate increases in cortical surface area and mental capacity in the highly social, larger primates.

NSF workshop report: discovering general principles of nervous system organization by comparing brain maps across species

Efforts to understand nervous system structure and function have received new impetus from the federal Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative. Comparative analyses can contribute to this effort by leading to the discovery of general principles of neural circuit design, information processing, and gene-structure-function relationships that are not apparent from studies on single species. We here propose to extend the comparative approach to nervous system 'maps' comprising molecular, anatomical, and physiological data. This research will identify which neural features are likely to generalize across species, and which are unlikely to be broadly conserved. It will also suggest causal relationships between genes, development, adult anatomy, physiology, and, ultimately, behavior. These causal hypotheses can then be tested experimentally. Finally, insights from comparative research can inspire and guide technological development. To promote this research agenda, we recommend that teams of investigators coalesce around specific research questions and select a set of 'reference species' to anchor their comparative analyses. These reference species should be chosen not just for practical advantages, but also with regard for their phylogenetic position, behavioral repertoire, well-annotated genome, or other strategic reasons. We envision that the nervous systems of these reference species will be mapped in more detail than those of other species. The collected data may range from the molecular to the behavioral, depending on the research question. To integrate across levels of analysis and across species, standards for data collection, annotation, archiving, and distribution must be developed and respected. To that end, it will help to form networks or consortia of researchers and centers for science, technology, and education that focus on organized data collection, distribution, and training. These activities could be supported, at least in part, through existing mechanisms at NSF, NIH, and other agencies. It will also be important to develop new integrated software and database systems for cross-species data analyses. Multidisciplinary efforts to develop such analytical tools should be supported financially. Finally, training opportunities should be created to stimulate multidisciplinary, integrative research into brain structure, function, and evolution.

Effect of temperature and glia in brain size enlargement and origin of allometric body-brain size scaling in vertebrates

Background

Brain signaling requires energy. The cost of maintaining and supporting energetically demanding neurons is the key constraint on brain size. The dramatic increase in brain size among mammals and birds cannot be understood without solving this conundrum: larger brains, with more neurons, consume more energy.

Results

Here we examined the intrinsic relationships between metabolism, body-brain size ratios and neuronal densities of both endothermic and ectothermic animals. We formulated a general model to elucidate the key factors that correlate with brain enlargement, and the origin of allometric body-brain size scaling. This framework identified temperature as a critical factor in brain enlargement via temperature-regulated changes in metabolism. Our framework predicts that ectothermic animals living in tropical climates should have brain sizes that are several times larger than those of ectothermic animals living in cold climates. This prediction was confirmed by data from experiments in fish brains. Our framework also suggests that a rapid increase in the number of less energy-demanding glial cells may be another important factor contributing to the ten-fold increase in the brain sizes of endotherms compared with ectotherms.

Conclusions

This study thus provides a quantitative theory that predicts the brain sizes of all the major types of animals and quantifies the contributions of temperature-dependent metabolism, body size and neuronal density.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-014-0178-z) contains supplementary material, which is available to authorized users.

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

Enough species have now been subject to systematic quantitative analysis of the relationship between the morphology and cellular composition of their brain that patterns begin to emerge and shed light on the evolutionary path that led to mammalian brain diversity. Based on an analysis of the shared and clade-specific characteristics of 41 modern mammalian species in 6 clades, and in light of the phylogenetic relationships among them, here we propose that ancestral mammal brains were composed and scaled in their cellular composition like modern afrotherian and glire brains: with an addition of neurons that is accompanied by a decrease in neuronal density and very little modification in glial cell density, implying a significant increase in average neuronal cell size in larger brains, and the allocation of approximately 2 neurons in the cerebral cortex and 8 neurons in the cerebellum for every neuron allocated to the rest of brain. We also propose that in some clades the scaling of different brain structures has diverged away from the common ancestral layout through clade-specific (or clade-defining) changes in how average neuronal cell mass relates to numbers of neurons in each structure, and how numbers of neurons are differentially allocated to each structure relative to the number of neurons in the rest of brain. Thus, the evolutionary expansion of mammalian brains has involved both concerted and mosaic patterns of scaling across structures. This is, to our knowledge, the first mechanistic model that explains the generation of brains large and small in mammalian evolution, and it opens up new horizons for seeking the cellular pathways and genes involved in brain evolution.

Diabetes mellitus and disturbances in brain connectivity: a bidirectional relationship?

Diabetes mellitus (DM) is associated with deficits across multiple cognitive domains. The observed impairments in cognitive function are hypothesized to be subserved by alterations in brain structure and function. Several lines of evidence indicate that alterations in glial integrity and function, as well as abnormal synchrony within brain circuits and associated networks, are observed in adults with DM. Microangiopathy and alterations in insulin homeostasis appear to be principal effector systems, although a unitary explanation subsuming the complex etiopathology of white matter in DM is unavailable. A contemporary model of disease pathophysiology for several mental disorders, including but not limited to mood disorders, posits abnormalities in the synchronization of cellular systems in circuits. The observation that similar abnormalities occur in diabetic populations provides the basis for hypothesizing the convergence of pathoetiological factors. Herein, we propose that abnormal structure, function and chemical composition as well as synchrony within and between circuits is an accompaniment of DM and is shared in common with several mental disorders.

What can volumes reveal about human brain evolution? A framework for bridging behavioral, histometric, and volumetric perspectives

An overall relationship between brain size and cognitive ability exists across primates. Can more specific information about neural function be gleaned from cortical area volumes? Numerous studies have found significant relationships between brain structures and behaviors. However, few studies have speculated about brain structure-function relationships from the microanatomical to the macroanatomical level. Here we address this problem in comparative neuroanatomy, where the functional relevance of overall brain size and the sizes of cortical regions have been poorly understood, by considering comparative psychology, with measures of visual acuity and the perception of visual illusions. We outline a model where the macroscopic size (volume or surface area) of a cortical region (such as the primary visual cortex, V1) is related to the microstructure of discrete brain regions. The hypothesis developed here is that an absolutely larger V1 can process more information with greater fidelity due to having more neurons to represent a field of space. This is the first time that the necessary comparative neuroanatomical research at the microstructural level has been brought to bear on the issue. The evidence suggests that as the size of V1 increases: the number of neurons increases, the neuron density decreases, and the density of neuronal connections increases. Thus, we describe how information about gross neuromorphology, using V1 as a model for the study of other cortical areas, may permit interpretations of cortical function.

The natural science underlying big history

Nature's many varied complex systems—including galaxies, stars, planets, life, and society—are islands of order within the increasingly disordered Universe. All organized systems are subject to physical, biological, or cultural evolution, which together comprise the grander interdisciplinary subject of cosmic evolution. A wealth of observational data supports the hypothesis that increasingly complex systems evolve unceasingly, uncaringly, and unpredictably from big bang to humankind. These are global history greatly extended, big history with a scientific basis, and natural history broadly portrayed across ∼14 billion years of time. Human beings and our cultural inventions are not special, unique, or apart from Nature; rather, we are an integral part of a universal evolutionary process connecting all such complex systems throughout space and time. Such evolution writ large has significant potential to unify the natural sciences into a holistic understanding of who we are and whence we came. No new science (beyond frontier, nonequilibrium thermodynamics) is needed to describe cosmic evolution's major milestones at a deep and empirical level. Quantitative models and experimental tests imply that a remarkable simplicity underlies the emergence and growth of complexity for a wide spectrum of known and diverse systems. Energy is a principal facilitator of the rising complexity of ordered systems within the expanding Universe; energy flows are as central to life and society as they are to stars and galaxies. In particular, energy rate density—contrasting with information content or entropy production—is an objective metric suitable to gauge relative degrees of complexity among a hierarchy of widely assorted systems observed throughout the material Universe. Operationally, those systems capable of utilizing optimum amounts of energy tend to survive, and those that cannot are nonrandomly eliminated.

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.

Functional craniology and brain evolution: from paleontology to biomedicine

Anatomical systems are organized through a network of structural and functional relationships among their elements. This network of relationships is the result of evolution, it represents the actual target of selection, and it generates the set of rules orienting and constraining the morphogenetic processes. Understanding the relationship among cranial and cerebral components is necessary to investigate the factors that have influenced and characterized our neuroanatomy, and possible drawbacks associated with the evolution of large brains. The study of the spatial relationships between skull and brain in the human genus has direct relevance in cranial surgery. Geometrical modeling can provide functional perspectives in evolution and brain physiology, like in simulations to investigate metabolic heat production and dissipation in the endocranial form. Analysis of the evolutionary constraints between facial and neural blocks can provide new information on visual impairment. The study of brain form variation in fossil humans can supply a different perspective for interpreting the processes behind neurodegeneration and Alzheimer’s disease. Following these examples, it is apparent that paleontology and biomedicine can exchange relevant information and contribute at the same time to the development of robust evolutionary hypotheses on brain evolution, while offering more comprehensive biological perspectives with regard to the interpretation of pathological processes.

NSF workshop report: discovering general principles of nervous system organization by comparing brain maps across species

Efforts to understand nervous system structure and function have received new impetus from the federal Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative. Comparative analyses can contribute to this effort by leading to the discovery of general principles of neural circuit design, information processing, and gene-structure-function relationships that are not apparent from studies on single species. We here propose to extend the comparative approach to nervous system 'maps' comprising molecular, anatomical, and physiological data. This research will identify which neural features are likely to generalize across species, and which are unlikely to be broadly conserved. It will also suggest causal relationships between genes, development, adult anatomy, physiology, and, ultimately, behavior. These causal hypotheses can then be tested experimentally. Finally, insights from comparative research can inspire and guide technological development. To promote this research agenda, we recommend that teams of investigators coalesce around specific research questions and select a set of 'reference species' to anchor their comparative analyses. These reference species should be chosen not just for practical advantages, but also with regard for their phylogenetic position, behavioral repertoire, well-annotated genome, or other strategic reasons. We envision that the nervous systems of these reference species will be mapped in more detail than those of other species. The collected data may range from the molecular to the behavioral, depending on the research question. To integrate across levels of analysis and across species, standards for data collection, annotation, archiving, and distribution must be developed and respected. To that end, it will help to form networks or consortia of researchers and centers for science, technology, and education that focus on organized data collection, distribution, and training. These activities could be supported, at least in part, through existing mechanisms at NSF, NIH, and other agencies. It will also be important to develop new integrated software and database systems for cross-species data analyses. Multidisciplinary efforts to develop such analytical tools should be supported financially. Finally, training opportunities should be created to stimulate multidisciplinary, integrative research into brain structure, function, and evolution.

Constancy and trade-offs in the neuroanatomical and metabolic design of the cerebral cortex

Mammalian brains span about four orders of magnitude in cortical volume and have to operate in different environments that require diverse behavioral skills. Despite these geometric and behavioral diversities, the examination of cerebral cortex across species reveals that it contains a substantial number of conserved characteristics that are associated with neuroanatomy and metabolism, i.e., with neuronal connectivity and function. Some of these cortical constants or invariants have been known for a long time but not sufficiently appreciated, and others were only recently discovered. The focus of this review is to present the cortical invariants and discuss their role in the efficient information processing. Global conservation in neuroanatomy and metabolism, as well as their correlated regional and developmental variability suggest that these two parallel systems are mutually coupled. It is argued that energetic constraint on cortical organization can be strong if cerebral blood supplied is either below or above a certain level, and it is rather soft otherwise. Moreover, because maximization or minimization of parameters associated with cortical connectivity, function and cost often leads to conflicts in design, it is argued that the architecture of the cerebral cortex is a result of structural and functional compromises.

Scaling and systems biology for integrating multiple organs-on-a-chip

Coupled systems of in vitro microfabricated organs-on-a-chip containing small populations of human cells are being developed to address the formidable pharmacological and physiological gaps between monolayer cell cultures, animal models, and humans that severely limit the speed and efficiency of drug development. These gaps present challenges not only in tissue and microfluidic engineering, but also in systems biology: how does one model, test, and learn about the communication and control of biological systems with individual organs-on-chips that are one-thousandth or one-millionth of the size of adult organs, or even smaller, i.e., organs for a milliHuman (mHu) or microHuman (μHu)? Allometric scaling that describes inter-species variation of organ size and properties provides some guidance, but given the desire to utilize these systems to extend and validate human pharmacokinetic and pharmacodynamic (PK/PD) models in support of drug discovery and development, it is more appropriate to scale each organ functionally to ensure that it makes the suitable physiological contribution to the coupled system. The desire to recapitulate the complex organ-organ interactions that result from factors in the blood and lymph places a severe constraint on the total circulating fluid (~5 mL for a mHu and ~5 μL for a μHu) and hence on the pumps, valves, and analytical instruments required to maintain and study these systems. Scaling arguments also provide guidance on the design of a universal cell-culture medium, typically without red blood cells. This review presents several examples of scaling arguments and discusses steps that should ensure the success of this endeavour.

The blood-brain barrier: an engineering perspective

It has been more than 100 years since Paul Ehrlich reported that various water-soluble dyes injected into the circulation did not enter the brain. Since Ehrlich's first experiments, only a small number of molecules, such as alcohol and caffeine have been found to cross the blood-brain barrier, and this selective permeability remains the major roadblock to treatment of many central nervous system diseases. At the same time, many central nervous system diseases are associated with disruption of the blood-brain barrier that can lead to changes in permeability, modulation of immune cell transport, and trafficking of pathogens into the brain. Therefore, advances in our understanding of the structure and function of the blood-brain barrier are key to developing effective treatments for a wide range of central nervous system diseases. Over the past 10 years it has become recognized that the blood-brain barrier is a complex, dynamic system that involves biomechanical and biochemical signaling between the vascular system and the brain. Here we reconstruct the structure, function, and transport properties of the blood-brain barrier from an engineering perspective. New insight into the physics of the blood-brain barrier could ultimately lead to clinical advances in the treatment of central nervous system diseases.

Shape, connectedness and dynamics in neuronal networks

The morphology of neurons is directly related to several aspects of the nervous system, including its connectedness, health, development, evolution, dynamics and, ultimately, behavior. Such interplays of the neuronal morphology can be understood within the more general shape-function paradigm. The current article reviews, in an introductory way, some key issues regarding the role of neuronal morphology in the nervous system, with emphasis on works developed in the authors' group. The following topics are addressed: (a) characterization of neuronal shape; (b) stochastic synthesis of neurons and neuronal systems; (c) characterization of the connectivity of neuronal networks by using complex networks concepts; and (d) investigations of influences of neuronal shape on network dynamics. The presented concepts and methods are useful also for several other multiple object systems, such as protein-protein interaction, tissues, aggregates and polymers.

Energetic cost of brain functional connectivity

The brain's functional connectivity is complex, has high energetic cost, and requires efficient use of glucose, the brain's main energy source. It has been proposed that regions with a high degree of functional connectivity are energy efficient and can minimize consumption of glucose. However, the relationship between functional connectivity and energy consumption in the brain is poorly understood. To address this neglect, here we propose a simple model for the energy demands of brain functional connectivity, which we tested with positron emission tomography and MRI in 54 healthy volunteers at rest. Higher glucose metabolism was associated with proportionally larger MRI signal amplitudes, and a higher degree of connectivity was associated with nonlinear increases in metabolism, supporting our hypothesis for the energy efficiency of the connectivity hubs. Basal metabolism (in the absence of connectivity) accounted for 30% of brain glucose utilization, which suggests that the spontaneous brain activity accounts for 70% of the energy consumed by the brain. The energy efficiency of the connectivity hubs was higher for ventral precuneus, cerebellum, and subcortical hubs than for cortical hubs. The higher energy demands of brain communication that hinges upon higher connectivity could render brain hubs more vulnerable to deficits in energy delivery or utilization and help explain their sensitivity to neurodegenerative conditions, such as Alzheimer's disease.

Networks of anatomical covariance

Functional imaging or diffusion-weighted imaging techniques are widely used to understand brain connectivity at the systems level and its relation to normal neurodevelopment, cognition or brain disorders. It is also possible to extract information about brain connectivity from the covariance of morphological metrics derived from anatomical MRI. These covariance patterns may arise from genetic influences on normal development and aging, from mutual trophic reinforcement as well as from experience-related plasticity. This review describes the basic methodological strategies, the biological basis of the observed covariance as well as applications in normal brain and brain disease before a final review of future prospects for the technique.

A comparative analysis of biclustering algorithms for gene expression data

The need to analyze high-dimension biological data is driving the development of new data mining methods. Biclustering algorithms have been successfully applied to gene expression data to discover local patterns, in which a subset of genes exhibit similar expression levels over a subset of conditions. However, it is not clear which algorithms are best suited for this task. Many algorithms have been published in the past decade, most of which have been compared only to a small number of algorithms. Surveys and comparisons exist in the literature, but because of the large number and variety of biclustering algorithms, they are quickly outdated. In this article we partially address this problem of evaluating the strengths and weaknesses of existing biclustering methods. We used the BiBench package to compare 12 algorithms, many of which were recently published or have not been extensively studied. The algorithms were tested on a suite of synthetic data sets to measure their performance on data with varying conditions, such as different bicluster models, varying noise, varying numbers of biclusters and overlapping biclusters. The algorithms were also tested on eight large gene expression data sets obtained from the Gene Expression Omnibus. Gene Ontology enrichment analysis was performed on the resulting biclusters, and the best enrichment terms are reported. Our analyses show that the biclustering method and its parameters should be selected based on the desired model, whether that model allows overlapping biclusters, and its robustness to noise. In addition, we observe that the biclustering algorithms capable of finding more than one model are more successful at capturing biologically relevant clusters.

Human brain evolution: transcripts, metabolites and their regulators

What evolutionary events led to the emergence of human cognition? Although the genetic differences separating modern humans from both non-human primates (for example, chimpanzees) and archaic hominins (Neanderthals and Denisovans) are known, linking human-specific mutations to the cognitive phenotype remains a challenge. One strategy is to focus on human-specific changes at the level of intermediate phenotypes, such as gene expression and metabolism, in conjunction with evolutionary changes in gene regulation involving transcription factors, microRNA and proximal regulatory elements. In this Review we show how this strategy has yielded some of the first hints about the mechanisms of human cognition.

Cortical energy demands of signaling and nonsignaling components in brain are conserved across mammalian species and activity levels

The continuous need for ion gradient restoration across the cell membrane, a prerequisite for synaptic transmission and conduction, is believed to be a major factor for brain's high oxidative demand. However, do energy requirements of signaling and nonsignaling components of cortical neurons and astrocytes vary with activity levels and across species? We derived oxidative ATP demand associated with signaling (P(s)) and nonsignaling (P(ns)) components in the cerebral cortex using species-specific physiologic and anatomic data. In rat, we calculated glucose oxidation rates from layer-specific neuronal activity measured across different states, spanning from isoelectricity to awake and sensory stimulation. We then compared these calculated glucose oxidation rates with measured glucose metabolic data for the same states as reported by 2-deoxy-glucose autoradiography. Fixed values for P(s) and P(ns) were able to predict the entire range of states in the rat. We then calculated glucose oxidation rates from human EEG data acquired under various conditions using fixed P(s) and P(ns) values derived for the rat. These calculated metabolic data in human cerebral cortex compared well with glucose metabolism measured by PET. Independent of species, linear relationship was established between neuronal activity and neuronal oxidative demand beyond isoelectricity. Cortical signaling requirements dominated energy demand in the awake state, whereas nonsignaling requirements were ∼20% of awake value. These predictions are supported by (13)C magnetic resonance spectroscopy results. We conclude that mitochondrial energy support for signaling and nonsignaling components in cerebral cortex are conserved across activity levels in mammalian species.

Dissipation of 'dark energy' by cortex in knowledge retrieval

We have devised a thermodynamic model of cortical neurodynamics expressed at the classical level by neural networks and at the quantum level by dissipative quantum field theory. Our model is based on features in the spatial images of cortical activity newly revealed by high-density electrode arrays. We have incorporated the mechanism and necessity for so-called dark energy in knowledge retrieval. We have extended the model first using the Carnot cycle to define our measures for energy, entropy and temperature, and then using the Rankine cycle to incorporate criticality and phase transitions. We describe the dynamics of two interactive fields of neural activity that express knowledge, one at high and the other at low energy density, and the two operators that create and annihilate the fields. We postulate that the extremely high density of energy sequestered briefly in cortical activity patterns can account for the vividness, richness of associations, and emotional intensity of memories recalled by stimuli.

Metabolic constraint imposes tradeoff between body size and number of brain neurons in human evolution

Despite a general trend for larger mammals to have larger brains, humans are the primates with the largest brain and number of neurons, but not the largest body mass. Why are great apes, the largest primates, not also those endowed with the largest brains? Recently, we showed that the energetic cost of the brain is a linear function of its numbers of neurons. Here we show that metabolic limitations that result from the number of hours available for feeding and the low caloric yield of raw foods impose a tradeoff between body size and number of brain neurons, which explains the small brain size of great apes compared with their large body size. This limitation was probably overcome in Homo erectus with the shift to a cooked diet. Absent the requirement to spend most available hours of the day feeding, the combination of newly freed time and a large number of brain neurons affordable on a cooked diet may thus have been a major positive driving force to the rapid increased in brain size in human evolution.

Social cognition on the Internet: testing constraints on social network size

The social brain hypothesis (an explanation for the evolution of brain size in primates) predicts that humans typically cannot maintain more than 150 relationships at any one time. The constraint is partly cognitive (ultimately determined by some aspect of brain volume) and partly one of time. Friendships (but not necessarily kin relationships) are maintained by investing time in them, and failure to do so results in an inexorable deterioration in the quality of a relationship. The Internet, and in particular the rise of social networking sites (SNSs), raises the possibility that digital media might allow us to circumvent some or all of these constraints. This allows us to test the importance of these constraints in limiting human sociality. Although the recency of SNSs means that there have been relatively few studies, those that are available suggest that, in general, the ability to broadcast to many individuals at once, and the possibilities this provides in terms of continuously updating our understanding of network members' behaviour and thoughts, do not allow larger networks to be maintained. This may be because only relatively weak quality relationships can be maintained without face-to-face interaction.

The remarkable, yet not extraordinary, human brain as a scaled-up primate brain and its associated cost

Neuroscientists have become used to a number of "facts" about the human brain: It has 100 billion neurons and 10- to 50-fold more glial cells; it is the largest-than-expected for its body among primates and mammals in general, and therefore the most cognitively able; it consumes an outstanding 20% of the total body energy budget despite representing only 2% of body mass because of an increased metabolic need of its neurons; and it is endowed with an overdeveloped cerebral cortex, the largest compared with brain size. These facts led to the widespread notion that the human brain is literally extraordinary: an outlier among mammalian brains, defying evolutionary rules that apply to other species, with a uniqueness seemingly necessary to justify the superior cognitive abilities of humans over mammals with even larger brains. These facts, with deep implications for neurophysiology and evolutionary biology, are not grounded on solid evidence or sound assumptions, however. Our recent development of a method that allows rapid and reliable quantification of the numbers of cells that compose the whole brain has provided a means to verify these facts. Here, I review this recent evidence and argue that, with 86 billion neurons and just as many nonneuronal cells, the human brain is a scaled-up primate brain in its cellular composition and metabolic cost, with a relatively enlarged cerebral cortex that does not have a relatively larger number of brain neurons yet is remarkable in its cognitive abilities and metabolism simply because of its extremely large number of neurons.

Approximate invariance of metabolic energy per synapse during development in mammalian brains

During mammalian development the cerebral metabolic rate correlates qualitatively with synaptogenesis, and both often exhibit bimodal temporal profiles. Despite these non-monotonic dependencies, it is found based on empirical data for different mammals that regional metabolic rate per synapse is approximately conserved from birth to adulthood for a given species (with a slight deviation from this constancy for human visual and temporal cortices during adolescence). A typical synapse uses about glucose molecules per second in primate cerebral cortex, and about five times of that amount in cat and rat visual cortices. A theoretical model for brain metabolic expenditure is used to estimate synaptic signaling and neural spiking activity during development. It is found that synaptic efficacy is generally inversely correlated with average firing rate, and, additionally, synapses consume a bulk of metabolic energy, roughly during most of the developmental process (except human temporal cortex ). Overall, these results suggest a tight regulation of brain electrical and chemical activities during the formation and consolidation of neural connections. This presumably reflects strong energetic constraints on brain development.

Callosal fiber length and interhemispheric connectivity in adults with autism: brain overgrowth and underconnectivity

Typical adults show an inverse relation between callosal fiber length and degree of interhemispheric connectivity. This has been hypothesized to be a consequence of the influence of conduction delays and cellular costs during development on axonal pruning, both of which increase with fiber length. Autism spectrum disorder (ASD) provides a test of this hypothesis: Children with ASD are known to have enlarged brains; thus, adults with ASD should show reductions in interhemispheric connectivity proportional to their degree of brain overgrowth during development. This prediction was tested by assessing the relation between both the size and structure of the corpus callosum and callosal fiber length, adjusting for intracranial volume, which is thought to reflect maximum brain size achieved during development. Using tractography to estimate the length of callosal fibers emanating from all areas of cortex, and through which region of the corpus callosum they pass, we show that adults with ASD show an inverse relation between callosal fiber length, adjusted for intracranial volume, and callosum size, and a positive relation between adjusted callosal fiber length and radial diffusivity. The results provide support for the hypothesized impact of fiber length during development.

Scaling of brain metabolism and blood flow in relation to capillary and neural scaling

Brain is one of the most energy demanding organs in mammals, and its total metabolic rate scales with brain volume raised to a power of around 5/6. This value is significantly higher than the more common exponent 3/4 relating whole body resting metabolism with body mass and several other physiological variables in animals and plants. This article investigates the reasons for brain allometric distinction on a level of its microvessels. Based on collected empirical data it is found that regional cerebral blood flow CBF across gray matter scales with cortical volume as , brain capillary diameter increases as , and density of capillary length decreases as . It is predicted that velocity of capillary blood is almost invariant (), capillary transit time scales as , capillary length increases as , and capillary number as , where is typically a small correction for medium and large brains, due to blood viscosity dependence on capillary radius. It is shown that the amount of capillary length and blood flow per cortical neuron are essentially conserved across mammals. These results indicate that geometry and dynamics of global neuro-vascular coupling have a proportionate character. Moreover, cerebral metabolic, hemodynamic, and microvascular variables scale with allometric exponents that are simple multiples of 1/6, rather than 1/4, which suggests that brain metabolism is more similar to the metabolism of aerobic than resting body. Relation of these findings to brain functional imaging studies involving the link between cerebral metabolism and blood flow is also discussed.

Expensive Brains: "Brainy" Rodents have Higher Metabolic Rate

Brains are the centers of the nervous system of animals, controlling the organ systems of the body and coordinating responses to changes in the ecological and social environment. The evolution of traits that correlate with cognitive ability, such as relative brain size is thus of broad interest. Brain mass relative to body mass (BM) varies among mammals, and diverse factors have been proposed to explain this variation. A recent study provided evidence that energetics play an important role in brain evolution (Isler and van Schaik, 2006). Using composite phylogenies and data drawn from multiple sources, these authors showed that basal metabolic rate (BMR) correlates with brain mass across mammals. However, no such relationship was found within rodents. Here we re-examined the relationship between BMR and brain mass within Rodentia using a novel species-level phylogeny. Our results are sensitive to parameter evaluation; in particular how species mass is estimated. We detect no pattern when applying an approach used by previous studies, where each species BM is represented by two different numbers, one being the individual that happened to be used for BMR estimates of that species. However, this approach may compromise the analysis. When using a single value of BM for each species, whether representing a single individual, or available species mean, our findings provide evidence that brain mass (independent of BM) and BMR are correlated. These findings are thus consistent with the hypothesis that large brains evolve when the payoff for increased brain mass is greater than the energetic cost they incur.