Scaling of brain metabolism with a fixed energy budget per neuron: implications for neuronal activity, plasticity and evolution

Machine learning reveals correlations between brain age and mechanics

Our brain undergoes significant micro- and macroscopic changes throughout its life cycle. It is therefore crucial to understand the effect of aging on the mechanical properties of the brain in order to develop accurate personalized simulations and diagnostic tools. Here we systematically probed the mechanical behavior of n=439 brain tissue samples in tension and compression, in different anatomical regions, for different axon orientations, across five age groups. We used Bayesian statistics to characterize the relation between brain age and mechanical properties and quantify uncertainties. Our results, based on our experimental data and material parameters for the isotropic Ogden and the anisotropic Gasser-Ogden-Holzapfel models, reveal a non-linear relationship between age and mechanics across the life cycle of the porcine brain. Both tensile and compressive shear moduli reached peak values ranging from 0.4-1.0 kPa in tension to 0.16-0.32 kPa in compression at three years of age. Anisotropy was most pronounced at six months, and then decreased. These results represent an important step in understanding age-dependent changes in the mechanical properties of brain tissue and provide the scientific basis for more accurate and realistic computational brain simulations. STATEMENT OF SIGNIFICANCE: In this paper, we investigate the age-dependent mechanical properties of brain tissue based on different deformation modes, anatomical regions, and axon orientations. Hierarchical Bayesian modeling was used to identify isotropic and anisotropic material parameters. The study reveals a nonlinear relationship between shear modulus, degree of anisotropy, and tension-compression asymmetry over the life cycle of the brain. By demonstrating the non-linearity of these relationships, the study fills a significant knowledge gap in current research. This work is a fundamental step in accurately characterizing the complex relationship between brain aging and mechanical properties.

Parametric resonance brain model

The paper introduces a parametric resonance model for characterizing some features of the brain's electrical activity. This activity is assumed to be a fundamental aspect of brain functionality underpinning functions from basic sensory processing to complex cognitive operations such as memory, reasoning, and emotion. A pivotal element of the proposed parametric model is neuron synchronization which is crucial for generating detectable brain waves. The analysis of the frequency content of brain waves, categorized as delta (0÷4 Hz), theta (4÷7 Hz), alpha (8÷12 Hz), beta (13÷30 Hz), and gamma (30÷100 Hz) reveals, notably, that the mean frequency of each of these brain wave classes is, in sequence, approximately the double of that of the previous one. Based on this observation, the proposed parametric resonance model suggests a cascade of amplification effects. Following the proposed model, in the transition from wakefulness to sleep, the brain wave bands are energized at double frequency by higher frequency neighboring bands; on the contrary, in the sleep to awake transition, brain waves are energized at a half frequency by their lower frequency neighbor waves. Finally, the trend of increasing amplitude values from higher to lower frequencies lends empirical support to the parametric resonant brain model validity.

Econeurobiology and brain development in children: key factors affecting development, behavioral outcomes, and school interventions

The Econeurobiology of the brain describes the environment in which an individual's brain develops. This paper explores the complex neural mechanisms that support and evaluate enrichment at various stages of development, providing an overview of how they contribute to plasticity and enhancement of both achievement and health. It explores the deep benefits of enrichment and contrasts them with the negative effects of trauma and stress on brain development. In addition, the paper strongly emphasizes the integration of Gardner's intelligence types into the school curriculum environment. It emphasizes the importance of linking various intelligence traits to educational strategies to ensure a holistic approach to cognitive development. In the field of Econeurobiology, this work explains the central role of the environment in shaping the development of the brain. It examines brain connections and plasticity and reveals the impact of certain environmental factors on brain development in early and mid-childhood. In particular, the six key factors highlighted are an environment of support, nutrition, physical activity, music, sleep, and cognitive strategies, highlighting their potential to improve cognitive abilities, memory, learning, self-regulation, and social and emotional development. This paper also investigates the social determinants of health and education in the context of Econeurobiology. It emphasizes the transformative power of education in society, especially in vulnerable communities facing global challenges in accessing quality education.

Sex-specific decline in prefrontal cortex mitochondrial bioenergetics in aging baboons correlates with walking speed

Mitochondria play a crucial role in brain aging due to their involvement in bioenergetics, neuroinflammation and brain steroid synthesis. Mitochondrial dysfunction is linked to age-related neurodegenerative diseases, including Alzheimer's disease and Parkinson's disease. We investigated changes in the activities of the electron transport chain (ETC) complexes in normally aging baboon brains and determined how these changes relate to donor sex, morning cortisol levels, and walking speed. Using a novel approach, we assessed mitochondrial bioenergetics from frozen prefrontal cortex (PFC) tissues from a large cohort (60 individuals) of well-characterized aging baboons (6.6-22.8 years, approximately equivalent to 26.4-91.2 human years). Aging was associated with a decline in mitochondrial ETC complexes in the PFC, which was more pronounced when activities were normalized for citrate synthase activity, suggesting that the decline in respiration is predominantly driven by changes in the specific activity of individual complexes rather than changes in mitochondrial number. Moreover, when donor sex was used as a covariate, we found that mitochondrial respiration was preserved with age in females, whereas males showed significant loss of ETC activity with age. Males had higher activities of each individual ETC complex and greater lactate dehydrogenase activity relative to females. Circulating cortisol levels correlated only with complex II-linked respiration in males. We also observed a robust positive predictive relationship between walking speed and respiration linked to complexes I, III, and IV in males but not in females. This data reveals a previously unknown link between aging and bioenergetics across multiple tissues linking frailty and bioenergetic function. This study highlights a potential molecular mechanism for sexual dimorphism in brain resilience and suggests that in males changes in PFC bioenergetics contribute to reduced motor function with age.

Information Thermodynamics: From Physics to Neuroscience

This paper provides a perspective on applying the concepts of information thermodynamics, developed recently in non-equilibrium statistical physics, to problems in theoretical neuroscience. Historically, information and energy in neuroscience have been treated separately, in contrast to physics approaches, where the relationship of entropy production with heat is a central idea. It is argued here that also in neural systems, information and energy can be considered within the same theoretical framework. Starting from basic ideas of thermodynamics and information theory on a classic Brownian particle, it is shown how noisy neural networks can infer its probabilistic motion. The decoding of the particle motion by neurons is performed with some accuracy, and it has some energy cost, and both can be determined using information thermodynamics. In a similar fashion, we also discuss how neural networks in the brain can learn the particle velocity and maintain that information in the weights of plastic synapses from a physical point of view. Generally, it is shown how the framework of stochastic and information thermodynamics can be used practically to study neural inference, learning, and information storing.

Invariance of Mitochondria and Synapses in the Primary Visual Cortex of Mammals Provides Insight Into Energetics and Function

The cerebral cortex accounts for substantial energy expenditure, primarily driven by the metabolic demands of synaptic signaling. Mitochondria, the organelles responsible for generating cellular energy, play a crucial role in this process. We investigated ultrastructural characteristics of the primary visual cortex in 18 phylogenetically diverse mammals, spanning a broad range of brain sizes from mouse to elephant. Our findings reveal remarkable uniformity in synapse density, postsynaptic density (PSD) length, and mitochondria density, indicating functional and metabolic constraints that maintain these fundamental features. Notably, we observed an average of 1.9 mitochondria per synapse across mammalian species. When considered together with the trend of decreasing neuron density with larger brain size, we find that brain enlargement in mammals is characterized by increasing proportions of synapses and mitochondria per cortical neuron. These results shed light on the adaptive mechanisms and metabolic dynamics that govern cortical ultrastructure across mammals.

Brain energy metabolism as an underlying basis of slow and fast cognitive phenotypes in honeybees

In the context of slow-fast behavioral variation, fast individuals are hypothesized to be those who prioritize speed over accuracy while slow individuals are those which do the opposite. Since energy metabolism is a critical component of neural and cognitive functioning, this predicts such differences in cognitive style to be reflected at the level of the brain. We tested this idea in honeybees by first classifying individuals into slow and fast cognitive phenotypes based on a learning assay and then measuring their brain respiration with high-resolution respirometry. Our results broadly show that inter-individual differences in cognition are reflected in differences in brain mass and accompanying energy use at the level of the brain and the whole animal. Larger brains had lower mass-specific energy usage and bees with larger brains had a higher metabolic rate. These differences in brain respiration and brain mass were, in turn, associated with cognitive differences, such that bees with larger brains were fast cognitive phenotypes whereas those with smaller brains were slow cognitive phenotypes. We discuss these results in the context of the role of energy in brain functioning and slow-fast decision making and speed accuracy trade-off.

Sex-specific resilience of neocortex to food restriction

Mammals have evolved sex-specific adaptations to reduce energy usage in times of food scarcity. These adaptations are well described for peripheral tissue, though much less is known about how the energy-expensive brain adapts to food restriction, and how such adaptations differ across the sexes. Here, we examined how food restriction impacts energy usage and function in the primary visual cortex (V1) of adult male and female mice. Molecular analysis and RNA sequencing in V1 revealed that in males, but not in females, food restriction significantly modulated canonical, energy-regulating pathways, including pathways associated waith AMP-activated protein kinase, peroxisome proliferator-activated receptor alpha, mammalian target of rapamycin, and oxidative phosphorylation. Moreover, we found that in contrast to males, food restriction in females did not significantly affect V1 ATP usage or visual coding precision (assessed by orientation selectivity). Decreased serum leptin is known to be necessary for triggering energy-saving changes in V1 during food restriction. Consistent with this, we found significantly decreased serum leptin in food-restricted males but no significant change in food-restricted females. Collectively, our findings demonstrate that cortical function and energy usage in female mice are more resilient to food restriction than in males. The neocortex, therefore, contributes to sex-specific, energy-saving adaptations in response to food restriction.

Caste-biased patterns of brain investment in the subterranean termite Reticulitermes flavipes

Investment into neural tissue is expected to reflect the specific sensory and behavioral capabilities of a particular organism. Termites are eusocial insects that exhibit a caste system in which individuals can develop into one of several morphologically and behaviorally distinct castes. However, it is unclear to what extent these differences between castes are reflected in the anatomy of the brain. To address this question, we used deformation-based morphometry to conduct pairwise comparisons between the brains of different castes in the eastern subterranean termite, Reticulitermes flavipes. Workers exhibited enlargement in the antennal lobes and mushroom bodies, while reproductives showed increased investment into the optic lobes and central body. In addition, caste-specific enlargement was observed in regions that could not be mapped to distinct neuropils, most notably in soldiers. These findings demonstrate a significant influence of caste development on brain anatomy in termites alongside convergence with eusocial hymenopteran systems.

Healthy diets positively associated with health-related quality of life in children and adolescents from low socioeconomic areas: Findings from the Greek Food Aid Program, DIATROFI

OBJECTIVES

To assess the relationship of diet with health-related quality of life (HRQoL) in vulnerable children and adolescents.

METHODS

Data included 6583 children and adolescents (aged 3-18 years old) from the Greek Food-Aid DIATROFI Program in the 2015 to 2016 and 2017 to 2018 school years. HRQoL was measured with the Pediatric Quality of Life Inventory questionnaire and diet with food frequency questionnaires. The healthy plant-based diet index (hPDI), animal score, and dietary patterns were investigated.

RESULTS

The hPDI and animal score were associated with good HRQoL (odds ratio [OR] [95% confidence interval], 10-unit increase: ORhPDI = 1.28 [1.05, 1.57], ORanimal = 1.51 [1.14, 2.00]) and physical (ORanimal = 1.62 [1.23, 2.13]), emotional (ORhPDI = 1.30 [1.07, 1.58], ORanimal = 1.41 [1.08, 1.85]) and school function (ORhPDI = 1.32 [1.09, 1.59], ORanimal = 1.46 [1.12, 1.89]). Dietary patterns of fruits, raw vegetables, and cheese were associated with good HRQoL (OR of 1-unit increase: 1.22 [1.13, 1.32]), and physical OR = 1.18 [1.09, 1.27]) and emotional function (OR = 1.09 [1.02, 1.18]). Starchy foods and sweetened beverages were associated with poor HRQoL (OR = 0.75 [0.63, 0.90]), and emotional (OR = 0.80 [0.68, 0.95]) and school function (OR = 0.72 [0.61, 0.85]).

CONCLUSION

Healthy diets and dietary patterns were positively associated with the HRQoL of vulnerable children and adolescents, which may offer opportunities for prevention.

Oxygen and the Spark of Human Brain Evolution: Complex Interactions of Metabolism and Cortical Expansion across Development and Evolution

Scientific theories on the functioning and dysfunction of the human brain require an understanding of its development-before and after birth and through maturation to adulthood-and its evolution. Here we bring together several accounts of human brain evolution by focusing on the central role of oxygen and brain metabolism. We argue that evolutionary expansion of human transmodal association cortices exceeded the capacity of oxygen delivery by the vascular system, which led these brain tissues to rely on nonoxidative glycolysis for additional energy supply. We draw a link between the resulting lower oxygen tension and its effect on cytoarchitecture, which we posit as a key driver of genetic developmental programs for the human brain-favoring lower intracortical myelination and the presence of biosynthetic materials for synapse turnover. Across biological and temporal scales, this protracted capacity for neural plasticity sets the conditions for cognitive flexibility and ongoing learning, supporting complex group dynamics and intergenerational learning that in turn enabled improved nutrition to fuel the metabolic costs of further cortical expansion. Our proposed model delineates explicit mechanistic links among metabolism, molecular and cellular brain heterogeneity, and behavior, which may lead toward a clearer understanding of brain development and its disorders.

Resource allocation in mammalian systems

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

Metabolic dynamics in astrocytes and microglia during post-natal development and their implications for autism spectrum disorders

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by elusive underlying mechanisms. Recent attention has focused on the involvement of astrocytes and microglia in ASD pathology. These glial cells play pivotal roles in maintaining neuronal homeostasis, including the regulation of metabolism. Emerging evidence suggests a potential association between ASD and inborn errors of metabolism. Therefore, gaining a comprehensive understanding of the functions of microglia and astrocytes in ASD is crucial for the development of effective therapeutic interventions. This review aims to provide a summary of the metabolism of astrocytes and microglia during post-natal development and the evidence of disrupted metabolic pathways in ASD, with particular emphasis on those potentially important for the regulation of neuronal post-natal maturation by astrocytes and microglia.

A mitochondrial nexus in major depressive disorder: Integration with the psycho-immune-neuroendocrine network

Nervous system processes, including cognition and affective state, fundamentally rely on mitochondria. Impaired mitochondrial function is evident in major depressive disorder (MDD), reflecting cumulative detrimental influences of both extrinsic and intrinsic stressors, genetic predisposition, and mutation. Glucocorticoid 'stress' pathways converge on mitochondria; oxidative and nitrosative stresses in MDD are largely mitochondrial in origin; both initiate cascades promoting mitochondrial DNA (mtDNA) damage with disruptions to mitochondrial biogenesis and tryptophan catabolism. Mitochondrial dysfunction facilitates proinflammatory dysbiosis while directly triggering immuno-inflammatory activation via released mtDNA, mitochondrial lipids and mitochondria associated membranes (MAMs), further disrupting mitochondrial function and mitochondrial quality control, promoting the accumulation of abnormal mitochondria (confirmed in autopsy studies). Established and putative mechanisms highlight a mitochondrial nexus within the psycho-immune neuroendocrine (PINE) network implicated in MDD. Whether lowering neuronal resilience and thresholds for disease, or linking mechanistic nodes within the MDD pathogenic network, impaired mitochondrial function emerges as an important risk, a functional biomarker, providing a therapeutic target in MDD. Several treatment modalities have been demonstrated to reset mitochondrial function, which could benefit those with MDD.

Amyloid Pathology Impairs Experience-Dependent Inhibitory Synaptic Plasticity

Alzheimer's disease patients and mouse models exhibit aberrant neuronal activity and altered excitatory-to-inhibitory synaptic ratio. Using multicolor two-photon microscopy, we test how amyloid pathology alters the structural dynamics of excitatory and inhibitory synapses and their adaptation to altered visual experience in vivo in the visual cortex. We show that the baseline dynamics of mature excitatory synapses and their adaptation to visual deprivation are not altered in amyloidosis. Likewise, the baseline dynamics of inhibitory synapses are not affected. In contrast, visual deprivation fails to induce inhibitory synapse loss in amyloidosis, a phenomenon observed in nonpathological conditions. Intriguingly, inhibitory synapse loss associated with visual deprivation in nonpathological mice is accompanied by subtle broadening of spontaneous but not visually evoked calcium transients. However, such broadening does not manifest in the context of amyloidosis. We also show that excitatory and inhibitory synapse loss is locally clustered under the nonpathological state. In contrast, a fraction of synapse loss is not locally clustered in amyloidosis, indicating an impairment in inhibitory synapse adaptation to changes in excitatory synaptic activity.

Tempo and mode of gene expression evolution in the brain across primates

Primate evolution has led to a remarkable diversity of behavioral specializations and pronounced brain size variation among species (Barton, 2012; DeCasien and Higham, 2019; Powell et al., 2017). Gene expression provides a promising opportunity for studying the molecular basis of brain evolution, but it has been explored in very few primate species to date (e.g. Khaitovich et al., 2005; Khrameeva et al., 2020; Ma et al., 2022; Somel et al., 2009). To understand the landscape of gene expression evolution across the primate lineage, we generated and analyzed RNA-seq data from four brain regions in an unprecedented eighteen species. Here, we show a remarkable level of variation in gene expression among hominid species, including humans and chimpanzees, despite their relatively recent divergence time from other primates. We found that individual genes display a wide range of expression dynamics across evolutionary time reflective of the diverse selection pressures acting on genes within primate brain tissue. Using our samples that represent a 190-fold difference in primate brain size, we identified genes with variation in expression most correlated with brain size. Our study extensively broadens the phylogenetic context of what is known about the molecular evolution of the brain across primates and identifies novel candidate genes for the study of genetic regulation of brain evolution.

Astrocytes Drive Divergent Metabolic Gene Expression in Humans and Chimpanzees

The human brain utilizes ∼20% of all of the body's metabolic resources, while chimpanzee brains use <10%. Although previous work shows significant differences in metabolic gene expression between the brains of primates, we have yet to fully resolve the contribution of distinct brain cell types. To investigate cell type-specific interspecies differences in brain gene expression, we conducted RNA-seq on neural progenitor cells, neurons, and astrocytes generated from induced pluripotent stem cells from humans and chimpanzees. Interspecies differential expression analyses revealed that twice as many genes exhibit differential expression in astrocytes (12.2% of all genes expressed) than neurons (5.8%). Pathway enrichment analyses determined that astrocytes, rather than neurons, diverged in expression of glucose and lactate transmembrane transport, as well as pyruvate processing and oxidative phosphorylation. These findings suggest that astrocytes may have contributed significantly to the evolution of greater brain glucose metabolism with proximity to humans.

Functional genomics and small molecules in mitochondrial neurodevelopmental disorders

Mitochondria are critical for brain development and homeostasis. Therefore, pathogenic variation in the mitochondrial or nuclear genome which disrupts mitochondrial function frequently results in developmental disorders and neurodegeneration at the organismal level. Large-scale application of genome-wide technologies to individuals with mitochondrial diseases has dramatically accelerated identification of mitochondrial disease-gene associations in humans. Multi-omic and high-throughput studies involving transcriptomics, proteomics, metabolomics, and saturation genome editing are providing deeper insights into the functional consequence of mitochondrial genomic variation. Integration of deep phenotypic and genomic data through allelic series continues to uncover novel mitochondrial functions and permit mitochondrial gene function dissection on an unprecedented scale. Finally, mitochondrial disease-gene associations illuminate disease mechanisms and thereby direct therapeutic strategies involving small molecules and RNA-DNA therapeutics. This review summarizes progress in functional genomics and small molecule therapeutics in mitochondrial neurodevelopmental disorders.

Metabolic energetics underlying attractors in neural models

Neural population modeling, including the role of neural attractors, is a promising tool for understanding many aspects of brain function. We propose a modeling framework to connect the abstract variables used in modeling to recent cellular-level estimates of the bioenergetic costs of different aspects of neural activity, measured in ATP consumed per second per neuron. Based on recent work, an empirical reference for brain ATP use for the awake resting brain was estimated as ∼2 × 109 ATP/s-neuron across several mammalian species. The energetics framework was applied to the Wilson-Cowan (WC) model of two interacting populations of neurons, one excitatory (E) and one inhibitory (I). Attractors were considered to exhibit steady-state behavior and limit cycle behavior, both of which end when the excitatory stimulus ends, and sustained activity that persists after the stimulus ends. The energy cost of limit cycles, with oscillations much faster than the average neuronal firing rate of the population, is tracked more closely with the firing rate than the limit cycle frequency. Self-sustained firing driven by recurrent excitation, though, involves higher firing rates and a higher energy cost. As an example of a simple network in which each node is a WC model, a combination of three nodes can serve as a flexible circuit element that turns on with an oscillating output when input passes a threshold and then persists after the input ends (an "on-switch"), with moderate overall ATP use. The proposed framework can serve as a guide for anchoring neural population models to plausible bioenergetics requirements.NEW & NOTEWORTHY This work bridges two approaches for understanding brain function: cellular-level studies of the metabolic energy costs of different aspects of neural activity and neural population modeling, including the role of neural attractors. The proposed modeling framework connects energetic costs, in ATP consumed per second per neuron, to the more abstract variables used in neural population modeling. In particular, this work anchors potential neural attractors to physiologically plausible bioenergetics requirements.

An energy costly architecture of neuromodulators for human brain evolution and cognition

In comparison to other species, the human brain exhibits one of the highest energy demands relative to body metabolism. It remains unclear whether this heightened energy demand uniformly supports an enlarged brain or if specific signaling mechanisms necessitate greater energy. We hypothesized that the regional distribution of energy demands will reveal signaling strategies that have contributed to human cognitive development. We measured the energy distribution within the brain functional connectome using multimodal brain imaging and found that signaling pathways in evolutionarily expanded regions have up to 67% higher energetic costs than those in sensory-motor regions. Additionally, histology, transcriptomic data, and molecular imaging independently reveal an up-regulation of signaling at G-protein-coupled receptors in energy-demanding regions. Our findings indicate that neuromodulator activity is predominantly involved in cognitive functions, such as reading or memory processing. This study suggests that an up-regulation of neuromodulator activity, alongside increased brain size, is a crucial aspect of human brain evolution.

Mathematical modelling with Bayesian inference to quantitatively characterize therapeutic cell behaviour in nerve tissue engineering

Cellular engineered neural tissues have significant potential to improve peripheral nerve repair strategies. Traditional approaches depend on quantifying tissue behaviours using experiments in isolation, presenting a challenge for an overarching framework for tissue design. By comparison, mathematical cell-solute models benchmarked against experimental data enable computational experiments to be performed to test the role of biological/biophysical mechanisms, as well as to explore the impact of different design scenarios and thus accelerate the development of new treatment strategies. Such models generally consist of a set of continuous, coupled, partial differential equations relying on a number of parameters and functional forms. They necessitate dedicated in vitro experiments to be informed, which are seldom available and often involve small datasets with limited spatio-temporal resolution, generating uncertainties. We address this issue and propose a pipeline based on Bayesian inference enabling the derivation of experimentally informed cell-solute models describing therapeutic cell behaviour in nerve tissue engineering. We apply our pipeline to three relevant cell types and obtain models that can readily be used to simulate nerve repair scenarios and quantitatively compare therapeutic cells. Beyond parameter estimation, the proposed pipeline enables model selection as well as experiment utility quantification, aimed at improving both model formulation and experimental design.

Brain-computer interface: trend, challenges, and threats

Brain-computer interface (BCI), an emerging technology that facilitates communication between brain and computer, has attracted a great deal of research in recent years. Researchers provide experimental results demonstrating that BCI can restore the capabilities of physically challenged people, hence improving the quality of their lives. BCI has revolutionized and positively impacted several industries, including entertainment and gaming, automation and control, education, neuromarketing, and neuroergonomics. Notwithstanding its broad range of applications, the global trend of BCI remains lightly discussed in the literature. Understanding the trend may inform researchers and practitioners on the direction of the field, and on where they should invest their efforts more. Noting this significance, we have analyzed 25,336 metadata of BCI publications from Scopus to determine advancement of the field. The analysis shows an exponential growth of BCI publications in China from 2019 onwards, exceeding those from the United States that started to decline during the same period. Implications and reasons for this trend are discussed. Furthermore, we have extensively discussed challenges and threats limiting exploitation of BCI capabilities. A typical BCI architecture is hypothesized to address two prominent BCI threats, privacy and security, as an attempt to make the technology commercially viable to the society.

A 3D atlas of functional human brain energetic connectome based on neuropil distribution

The human brain is energetically expensive, yet the key factors governing its heterogeneous energy distributions across cortical regions to support its diversity of functions remain unexplored. Here, we built up a 3D digital cortical energy atlas based on the energetic costs of all neuropil activities into a high-resolution stereological map of the human cortex with cellular and synaptic densities derived, respectively, from ex vivo histological staining and in vivo PET imaging. The atlas was validated with PET-measured glucose oxidation at the voxel level. A 3D cortical activity map was calculated to predict the heterogeneous activity rates across all cortical regions, which revealed that resting brain is indeed active with heterogeneous neuronal activity rates averaging around 1.2 Hz, comprising around 70% of the glucose oxidation of the cortex. Additionally, synaptic density dominates spatial patterns of energetics, suggesting that the cortical energetics rely heavily on the distribution of synaptic connections. Recent evidence from functional imaging studies suggests that some cortical areas act as hubs (i.e., interconnecting distinct and functionally active regions). An inverse allometric relationship was observed between hub metabolic rates versus hub volumes. Hubs with smaller volumes have higher synapse density, metabolic rate, and activity rates compared to nonhubs. The open-source BrainEnergyAtlas provides a granular framework for exploring revealing design principles in energy-constrained human cortical circuits across multiple spatial scales.

Astrocyte strategies in the energy-efficient brain

Astrocytes generate ATP through glycolysis and mitochondrion respiration, using glucose, lactate, fatty acids, amino acids, and ketone bodies as metabolic fuels. Astrocytic mitochondria also participate in neuronal redox homeostasis and neurotransmitter recycling. In this essay, we aim to integrate the multifaceted evidence about astrocyte bioenergetics at the cellular and systems levels, with a focus on mitochondrial oxidation. At the cellular level, the use of fatty acid β-oxidation and the existence of molecular switches for the selection of metabolic mode and fuels are examined. At the systems level, we discuss energy audits of astrocytes and how astrocytic Ca2+ signaling might contribute to the higher performance and lower energy consumption of the brain as compared to engineered circuits. We finish by examining the neural-circuit dysregulation and behavior impairment associated with alterations of astrocytic mitochondria. We conclude that astrocytes may contribute to brain energy efficiency by coupling energy, redox, and computational homeostasis in neural circuits.

α1-Adrenergic Receptors: Insights into Potential Therapeutic Opportunities for COVID-19, Heart Failure, and Alzheimer's Disease

α1-Adrenergic receptors (ARs) are members of the G-Protein Coupled Receptor superfamily and with other related receptors (β and α2), they are involved in regulating the sympathetic nervous system through binding and activation by norepinephrine and epinephrine. Traditionally, α1-AR antagonists were first used as anti-hypertensives, as α1-AR activation increases vasoconstriction, but they are not a first-line use at present. The current usage of α1-AR antagonists increases urinary flow in benign prostatic hyperplasia. α1-AR agonists are used in septic shock, but the increased blood pressure response limits use for other conditions. However, with the advent of genetic-based animal models of the subtypes, drug design of highly selective ligands, scientists have discovered potentially newer uses for both agonists and antagonists of the α1-AR. In this review, we highlight newer treatment potential for α1A-AR agonists (heart failure, ischemia, and Alzheimer's disease) and non-selective α1-AR antagonists (COVID-19/SARS, Parkinson's disease, and posttraumatic stress disorder). While the studies reviewed here are still preclinical in cell lines and rodent disease models or have undergone initial clinical trials, potential therapeutics discussed here should not be used for non-approved conditions.

Paying the brain's energy bill

How have animals managed to maintain metabolically expensive brains given the volatile and fleeting availability of calories in the natural world? Here we review studies in support of three strategies that involve: 1) a reallocation of energy from peripheral tissues and functions to cover the costs of the brain, 2) an implementation of energy-efficient neural coding, enabling the brain to operate at reduced energy costs, and 3) efficient use of costly neural resources during food scarcity. Collectively, these studies reveal a heterogeneous set of energy-saving mechanisms that make energy-costly brains fit for survival.

[Oxidative stress in the pathogenesis of stroke and its correction]

We reviewed the role of oxidative stress (OS) in the pathogenesis of ischemic (IS) and hemorrhagic stroke (HS). OS plays a major role in programmed cell death, increased permeability of the blood-brain barrier, astroglial and microglial activation, and local inflammatory response. We also reviewed the current state of neuro- and cytoprotection studies and their translation in clinical practice. With respect to experimental and clinical data the efficacy of long term administration of multimodal cytoprotective drug with antioxidant effect - ethylmethylhydroxypyridine succinate (Mexidol) is discussed during the acute and early recovery period after stroke.

Age-Related Decline in Nrf2/ARE Signaling Is Associated with the Mitochondrial DNA Damage and Cognitive Impairments

In this research, we compared the cognitive parameters of 2-, 7-, and 15-month-old mice, changes in mitochondrial DNA (mtDNA) integrity and expression of genes involved in the nuclear erythroid 2-related factor 2/antioxidant response element (Nrf2/ARE) signaling pathway. We showed an age-related decrease in the Nfe2l2 expression in the cerebral cortex, not in the hippocampus. At the same time, we find an increase in the mtDNA copy number in the cerebral cortex, despite the lack of an increase in gene expression, which is involved in the mitochondrial biogenesis regulation. We suppose that increase in mtDNA content is associated with mitophagy downregulation. We supposed that mitophagy downregulation may be associated with an age-related increase in the mtDNA damage. In the hippocampus, we found a decrease in the Bdnf expression, which is involved in the pathways, which play an essential role in regulating long-term memory formation. We showed a deficit of working and reference memory in 15-month-old-mice in the water Morris maze, and a decrease in the exploratory behavior in the open field test. Cognitive impairments in 15-month-old mice correlated with a decrease in Bdnf expression in the hippocampus, Nfe2l2 expression, and an increase in the number of mtDNA damage in the cerebral cortex. Thus, these signaling pathways may be perspective targets for pharmacological intervention to maintain mitochondrial quality control, neuronal plasticity, and prevent the development of age-related cognitive impairment.

Forgetful, sad and old: Do vascular cognitive impairment and depression share a common pre-disease network and how is it impacted by ageing?

Vascular cognitive impairment (VCI) and depression frequently coexist in geriatric populations and reciprocally increase disease risks. We assert that a shared pre-disease state of the psycho-immune-neuroendocrine (PINE) network model mechanistically explains bidirectional associations between VCI and depression. Five pathophysiological sub-networks are identified that are shared by VCI and depression: neuroinflammation, kynurenine pathway imbalance, hypothalamic-pituitary-adrenal (HPA) axis overactivity, impaired neurotrophic support and cerebrovascular dysfunction. These do not act independently, and their complex interactions necessitate a systems biology approach to better define disease pathogenesis. The PINE network is already established in the context of non-communicable diseases (NCDs) such as depression, hypertension, atherosclerosis, coronary heart disease and type 2 diabetes mellitus. We build on previous literature to specifically explore mechanistic links between MDD and VCI in the context of PINE pathways and discuss key mechanistic commonalities linking these comorbid conditions and identify a common pre-disease state which precedes transition to VCI and MDD. We expand the model to incorporate bidirectional interactions with biological ageing. Diathesis factors for both VCI and depression feed into this network and the culmination of shared mechanisms (on an ageing substrate) lead to a critical network transition to one or both disease states. A common pre-disease state underlying VCI and depression can provide clinicians a unique opportunity for early risk assessment and intervention in disease development. Establishing the mechanistic elements and systems biology of this network can reveal early warning or predictive biomarkers together with novel therapeutic targets. Integrative studies are recommended to elucidate the dynamic networked biology of VCI and depression over time.

Neuronal and non-neuronal scaling across brain regions within an intercross of domestic and wild chickens

The allometric scaling of the brain size and neuron number across species has been extensively studied in recent years. With the exception of primates, parrots, and songbirds, larger brains have more neurons but relatively lower neuronal densities than smaller brains. Conversely, when considering within-population variability, it has been shown that mice with larger brains do not necessarily have more neurons but rather more neurons in the brain reflect higher neuronal density. To what extent this intraspecific allometric scaling pattern of the brain applies to individuals from other species remains to be explored. Here, we investigate the allometric relationships among the sizes of the body, brain, telencephalon, cerebellum, and optic tectum, and the numbers of neurons and non-neuronal cells of the telencephalon, cerebellum, and optic tectum across 66 individuals originated from an intercross between wild and domestic chickens. Our intercross of chickens generates a population with high variation in brain size, making it an excellent model to determine the allometric scaling of the brain within population. Our results show that larger chickens have larger brains with moderately more neurons and non-neuronal cells. Yet, absolute number of neurons and non-neuronal cells correlated strongly and positively with the density of neurons and non-neuronal cells, respectively. As previously shown in mice, this scaling pattern is in stark contrast with what has been found across different species. Our findings suggest that neuronal scaling rules across species are not a simple extension of the neuronal scaling rules that apply within a species, with important implications for the evolutionary developmental origins of brain diversity.

Avian neurons consume three times less glucose than mammalian neurons

Brains are among the most energetically costly tissues in the mammalian body.¹ This is predominantly caused by expensive neurons with high glucose demands.² Across mammals, the neuronal energy budget appears to be fixed, possibly posing an evolutionary constraint on brain growth.^3-6 Compared to similarly sized mammals, birds have higher numbers of neurons, and this advantage conceivably contributes to their cognitive prowess.⁷ We set out to determine the neuronal energy budget of birds to elucidate how they can metabolically support such high numbers of neurons. We estimated glucose metabolism using positron emission tomography (PET) and 2-[¹⁸F]fluoro-2-deoxyglucose ([¹⁸F]FDG) as the radiotracer in awake and anesthetized pigeons. Combined with kinetic modeling, this is the gold standard to quantify cerebral metabolic rate of glucose consumption (CMR_glc).⁸ We found that neural tissue in the pigeon consumes 27.29 ± 1.57 μmol glucose per 100 g per min in an awake state, which translates into a surprisingly low neuronal energy budget of 1.86 × 10^-9 ± 0.2 × 10^-9 μmol glucose per neuron per minute. This is approximately 3 times lower than the rate in the average mammalian neuron.³ The remarkably low neuronal energy budget explains how pigeons, and possibly other avian species, can support such high numbers of neurons without associated metabolic costs or compromising neuronal signaling. The advantage in neuronal processing of information at a higher efficiency possibly emerged during the distinct evolution of the avian brain.

Divergent Cellular Energetics, Glutamate Metabolism, and Mitochondrial Function Between Human and Mouse Cerebral Cortex

Disruptions of brain energy and neurotransmitter metabolism are associated with several pathological conditions including neurodegenerative diseases such as Alzheimer's disease. Transgenic rodent models, and in vitro preparations hereof, are often applied for studying pathological aspects of brain metabolism. However, despite the conserved cerebral development across mammalian species, distinct differences in cellular composition and structure may influence metabolism of the rodent and human brain. To address this, we investigated the metabolic function of acutely isolated brain slices and non-synaptic mitochondria obtained from the cerebral cortex of mice and neurosurgically resected neocortical tissue of humans. Utilizing dynamic isotope labeling with ¹³C-enriched metabolic substrates, we show that metabolism of glucose, acetate, β-hydroxybutyrate, and glutamine operates at lower rates in human cerebral cortical slices when compared to mouse slices. In contrast, human cerebral cortical slices display a higher capacity for converting exogenous glutamate into glutamine, which subsequently supports neuronal GABA synthesis, whereas mouse slices primarily convert glutamate into aspartate. In line with the reduced metabolic rate of the human brain slices, isolated non-synaptic mitochondria of the human cerebral cortex have a lower oxygen consumption rate when provided succinate as substrate. However, when provided pyruvate and malate, human mitochondria display a higher coupled respiration and lower proton leak, signifying a more efficient mitochondrial coupling compared to mouse mitochondria. This study reveals key differences between mouse and human brain metabolism concerning both neurons and astrocytes, which must be taken into account when applying in vitro rodent preparations as a model system of the human brain.

Blind cavefish retain functional connectivity in the tectum despite loss of retinal input

Sensory systems display remarkable plasticity and are under strong evolutionary selection. The Mexican cavefish, Astyanax mexicanus, consists of eyed river-dwelling surface populations and multiple independent cave populations that have converged on eye loss, providing the opportunity to examine the evolution of sensory circuits in response to environmental perturbation. Functional analysis across multiple transgenic populations expressing GCaMP6s showed that functional connectivity of the optic tectum largely did not differ between populations, except for the selective loss of negatively correlated activity within the cavefish tectum, suggesting positively correlated neural activity is resistant to an evolved loss of input from the retina. Furthermore, analysis of surface-cave hybrid fish reveals that changes in the tectum are genetically distinct from those encoding eye loss. Together, these findings uncover the independent evolution of multiple components of the visual system and establish the use of functional imaging in A. mexicanus to study neural circuit evolution.

Mitochondrial protein synthesis and the bioenergetic cost of neurodevelopment

The human brain consumes five orders of magnitude more energy than the sun by unit of mass and time. This staggering bioenergetic cost serves mostly synaptic transmission and actin cytoskeleton dynamics. The peak of both brain bioenergetic demands and the age of onset for neurodevelopmental disorders is approximately 5 years of age. This correlation suggests that defects in the machinery that provides cellular energy would be causative and/or consequence of neurodevelopmental disorders. We explore this hypothesis from the perspective of the machinery required for the synthesis of the electron transport chain, an ATP-producing and NADH-consuming enzymatic cascade. The electron transport chain is constituted by nuclear- and mitochondrial-genome-encoded subunits. These subunits are synthesized by the 80S and the 55S ribosomes, which are segregated to the cytoplasm and the mitochondrial matrix, correspondingly. Mitochondrial protein synthesis by the 55S ribosome is the rate-limiting step in the synthesis of electron transport chain components, suggesting that mitochondrial protein synthesis is a bottleneck for tissues with high bionergetic demands. We discuss genetic defects in the human nuclear and mitochondrial genomes that affect these protein synthesis machineries and cause a phenotypic spectrum spanning autism spectrum disorders to neurodegeneration during neurodevelopment. We propose that dysregulated mitochondrial protein synthesis is a chief, yet understudied, causative mechanism of neurodevelopmental and behavioral disorders.

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.

Quantitative relationship between cerebrovascular network and neuronal cell types in mice

The cerebrovasculature and its mural cells must meet brain regional energy demands, but how their spatial relationship with different neuronal cell types varies across the brain remains largely unknown. Here we apply brain-wide mapping methods to comprehensively define the quantitative relationships between the cerebrovasculature, capillary pericytes, and glutamatergic and GABAergic neurons, including neuronal nitric oxide synthase-positive (nNOS+) neurons and their subtypes in adult mice. Our results show high densities of vasculature with high fluid conductance and capillary pericytes in primary motor sensory cortices compared with association cortices that show significant positive and negative correlations with energy-demanding parvalbumin+ and vasomotor nNOS+ neurons, respectively. Thalamo-striatal areas that are connected to primary motor sensory cortices also show high densities of vasculature and pericytes, suggesting dense energy support for motor sensory processing areas. Our cellular-resolution resource offers opportunities to examine spatial relationships between the cerebrovascular network and neuronal cell composition in largely understudied subcortical areas.

ALS/FTD: Evolution, Aging, and Cellular Metabolic Exhaustion

Amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD) are neurodegenerations with evolutionary underpinnings, expansive clinical presentations, and multiple genetic risk factors involving a complex network of pathways. This perspective considers the complex cellular pathology of aging motoneuronal and frontal/prefrontal cortical networks in the context of evolutionary, clinical, and biochemical features of the disease. We emphasize the importance of evolution in the development of the higher cortical function, within the influence of increasing lifespan. Particularly, the role of aging on the metabolic competence of delicately optimized neurons, age-related increased proteostatic costs, and specific genetic risk factors that gradually reduce the energy available for neuronal function leading to neuronal failure and disease.

Progressive Mitochondrial Dysfunction of Striatal Synapses in R6/2 Mouse Model of Huntington's Disease

BACKGROUND

Huntington's disease (HD) is a neurodegenerative disorder characterized by synaptic dysfunction and loss of white matter volume especially in the striatum of the basal ganglia and to a lesser extent in the cerebral cortex. Studies investigating heterogeneity between synaptic and non-synaptic mitochondria have revealed a pronounced vulnerability of synaptic mitochondria, which may lead to synaptic dysfunction and loss.

OBJECTIVE

As mitochondrial dysfunction is a hallmark of HD pathogenesis, we investigated synaptic mitochondrial function from striatum and cortex of the transgenic R6/2 mouse model of HD.

METHODS

We assessed mitochondrial volume, ROS production, and antioxidant levels as well as mitochondrial respiration at different pathological stages.

RESULTS

Our results reveal that striatal synaptic mitochondria are more severely affected by HD pathology than those of the cortex. Striatal synaptosomes of R6/2 mice displayed a reduction in mitochondrial mass coinciding with increased ROS production and antioxidants levels indicating prolonged oxidative stress. Furthermore, synaptosomal oxygen consumption rates were significantly increased during depolarizing conditions, which was accompanied by a marked increase in mitochondrial proton leak of the striatal synaptosomes, indicating synaptic mitochondrial stress.

CONCLUSION

Overall, our study provides new insight into the gradual changes of synaptic mitochondrial function in HD and suggests compensatory mitochondrial actions to maintain energy production in the HD brain, thereby supporting that mitochondrial dysfunction do indeed play a central role in early disease progression of HD.

Neurons as hierarchies of quantum reference frames

Conceptual and mathematical models of neurons have lagged behind empirical understanding for decades. Here we extend previous work in modeling biological systems with fully scale-independent quantum information-theoretic tools to develop a uniform, scalable representation of synapses, dendritic and axonal processes, neurons, and local networks of neurons. In this representation, hierarchies of quantum reference frames act as hierarchical active-inference systems. The resulting model enables specific predictions of correlations between synaptic activity, dendritic remodeling, and trophic reward. We summarize how the model may be generalized to nonneural cells and tissues in developmental and regenerative contexts.

Neuroprotection in aortic arch surgery: untold flaws and future directions

The current paradigm of brain protection in aortic surgery falls short of delivering good outcomes with minimal complications. A renewed understanding of neuroprotective methods and biomarkers to predict brain injury and aortic disease are crucial towards the development of more effective clinical management strategies. A review of current literature was carried out to identify current flaws in our approach to neuroprotection in aortic surgery. Emerging evidence surrounding neuroprotective strategies, biomarkers for brain injury, and biomarkers for predicting aortic disease are evaluated in terms of their impact for future therapeutic approaches. Current literature suggests that the prevailing methods of neuroprotection need renewal. Clinical outcomes associated with deep hypothermic circulatory arrest remain varied. Branch-first and endovascular approaches to aortic repair are particularly promising alternatives. The use of biomarkers to identify and manage brain injury, as well as to diagnose aortic disease in the nonacute and acute settings, would further help to improve our overall paradigm of neuroprotection in aortic surgery. Though much prospective research is still required, the outlook for neuroprotection in aortic surgery is promising. Adopting alternative surgical techniques and exploiting predictive novel biomarkers will help us to gradually eliminate the risk of brain damage in aortic surgery.

A combined experimental and computational framework to evaluate the behavior of therapeutic cells for peripheral nerve regeneration

Recent studies have explored the potential of tissue‐mimetic scaffolds in encouraging nerve regeneration. One of the major determinants of the regenerative success of cellular nerve repair constructs (NRCs) is the local microenvironment, particularly native low oxygen conditions which can affect implanted cell survival and functional performance. In vivo, cells reside in a range of environmental conditions due to the spatial gradients of nutrient concentrations that are established. Here we evaluate in vitro the differences in cellular behavior that such conditions induce, including key biological features such as oxygen metabolism, glucose consumption, cell death, and vascular endothelial growth factor secretion. Experimental measurements are used to devise and parameterize a mathematical model that describes the behavior of the cells. The proposed model effectively describes the interactions between cells and their microenvironment and could in the future be extended, allowing researchers to compare the behavior of different therapeutic cells. Such a combinatorial approach could be used to accelerate the clinical translation of NRCs by identifying which critical design features should be optimized when fabricating engineered nerve repair conduits.

Brain size, gut size and cognitive abilities: the energy trade-offs tested in artificial selection experiment

The enlarged brains of homeotherms bring behavioural advantages, but also incur high energy expenditures. The ‘expensive brain’ (EB) hypothesis posits that the energetic costs of the enlarged brain and the resulting increased cognitive abilities (CA) were met by either increased energy turnover or reduced allocation to other expensive organs, such as the gut. We tested the EB hypothesis by analysing correlated responses to selection in an experimental evolution model system, which comprises line types of laboratory mice selected for high or low basal metabolic rate (BMR), maximum (VO_2max) metabolic rates and random-bred (unselected) lines. The traits are implicated in the evolution of homeothermy, having been pre-requisites for the encephalization and exceptional CA of mammals, including humans. High-BMR mice had bigger guts, but not brains, than mice of other line types. Yet, they were superior in the cognitive tasks carried out in both reward and avoidance learning contexts and had higher neuronal plasticity (indexed as the long-term potentiation) than their counterparts. Our data indicate that the evolutionary increase of CA in mammals was initially associated with increased BMR and brain plasticity. It was also fuelled by an enlarged gut, which was not traded off for brain size.

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.

The evolution of brain neuron numbers in amniotes

The evolution of brain processing capacity has traditionally been inferred from data on brain size. However, similarly sized brains of distantly related species can differ in the number and distribution of neurons, their basic computational units. Therefore, a finer-grained approach is needed to reveal the evolutionary paths to increased cognitive capacity. Using a new, comprehensive dataset, we analyzed brain cellular composition across amniotes. Compared to reptiles, mammals and birds have dramatically increased neuron numbers in the telencephalon and cerebellum, which are brain parts associated with higher cognition. Astoundingly, a phylogenetic analysis suggests that as few as four major changes in neuron–brain scaling in over 300 million years of evolution pave the way to intelligence in endothermic land vertebrates.

Reconstructing the evolution of brain information-processing capacity is paramount for understanding the rise of complex cognition. Comparative studies of brain evolution typically use brain size as a proxy. However, to get a less biased picture of the evolutionary paths leading to high cognitive power, we need to compare brains not by mass but by numbers of neurons, which are their basic computational units. This study reconstructs the evolution of brains across amniotes by directly analyzing neuron numbers by using the largest dataset of its kind and including essential data on reptiles. We show that reptiles have not only small brains relative to body size but also low neuronal densities, resulting in average neuron numbers over 20 times lower than those in birds and mammals of similar body size. Amniote brain evolution is characterized by the following four major shifts in neuron–brain scaling. The most dramatic increases in brain neurons occurred independently with the appearance of birds and mammals, resulting in convergent neuron scaling in the two endotherm lineages. The other two major increases in the number of neurons happened in core land birds and anthropoid primates, which are two groups known for their cognitive prowess. Interestingly, relative brain size is associated with relative neuronal cell density in reptiles, birds, and primates but not in other mammals. This has important implications for studies using relative brain size as a proxy when looking for evolutionary drivers of animal cognition.

Perception is associated with the brain's metabolic response to sensory stimulation

Processing of incoming sensory stimulation triggers an increase of cerebral perfusion and blood oxygenation (neurovascular response) as well as an alteration of the metabolic neurochemical profile (neurometabolic response). Here we show in human primary visual cortex (V1) that perceived and unperceived isoluminant chromatic flickering stimuli designed to have similar neurovascular responses as measured by blood oxygenation level dependent functional MRI (BOLD-fMRI) have markedly different neurometabolic responses as measured by functional MRS. In particular, a significant regional buildup of lactate, an index of aerobic glycolysis, and glutamate, an index of malate-aspartate shuttle, occurred in V1 only when the flickering was perceived, without any relation with behavioral or physiological variables. Whereas the BOLD-fMRI signal in V1, a proxy for input to V1, was insensitive to flickering perception by design, the BOLD-fMRI signal in secondary visual areas was larger during perceived than unperceived flickering, indicating increased output from V1. These results demonstrate that the upregulation of energy metabolism induced by visual stimulation depends on the type of information processing taking place in V1, and that 1H-fMRS provides unique information about local input/output balance that is not measured by BOLD fMRI.

Frontotemporal Dementia and Glucose Metabolism

Frontotemporal dementia (FTD), hallmarked by antero-temporal degeneration in the human brain, is the second most common early onset dementia. FTD is a diverse disease with three main clinical presentations, four different identified proteinopathies and many disease-associated genes. The exact pathophysiology of FTD remains to be elucidated. One common characteristic all forms of FTD share is the dysregulation of glucose metabolism in patients’ brains. The brain consumes around 20% of the body’s energy supply and predominantly utilizes glucose as a fuel. Glucose metabolism dysregulation could therefore be extremely detrimental for neuronal health. Research into the association between glucose metabolism and dementias has recently gained interest in Alzheimer’s disease. FTD also presents with glucose metabolism dysregulation, however, this remains largely an unexplored area. A better understanding of the link between FTD and glucose metabolism may yield further insight into FTD pathophysiology and aid the development of novel therapeutics. Here we review our current understanding of FTD and glucose metabolism in the brain and discuss the evidence of impaired glucose metabolism in FTD. Lastly, we review research potentially suggesting a causal relationship between FTD proteinopathies and impaired glucose metabolism in FTD.