Global and regional brain metabolic scaling and its functional consequences

Long-range connections damage in white matter hyperintensities affects information processing speed

White matter hyperintensities, one of the major markers of cerebral small vessel disease, disrupt the integrity of neuronal networks and ultimately contribute to cognitive dysfunction. However, a deeper understanding of how white matter hyperintensities related to the connectivity patterns of brain hubs at the neural network level could provide valuable insights into the relationship between white matter hyperintensities and cognitive dysfunction. A total of 36 patients with moderate to severe white matter hyperintensities (Fazekas score ≥ 3) and 34 healthy controls underwent comprehensive neuropsychological assessments and resting-state functional MRI scans. The voxel-based graph-theory approach-functional connectivity strength was employed to systematically investigate the topological organization of the whole-brain networks. The white matter hyperintensities patients performed significantly worse than the healthy controls in episodic memory, executive function and information processing speed. Additionally, we found that white matter hyperintensities selectively affected highly connected hub regions, predominantly involving the medial and lateral prefrontal, precuneus, inferior parietal lobule, insula and thalamus. Intriguingly, this impairment was connectivity distance-dependent, with the most prominent disruptions observed in long-range connections (e.g. 100-150 mm). Finally, these disruptions of hub connectivity (e.g. the long-range functional connectivity strength in the left dorsolateral prefrontal cortex) positively correlated with the cognitive performance in white matter hyperintensities patients. Our findings emphasize that the disrupted hub connectivity patterns in white matter hyperintensities are dependent on connection distance, especially longer-distance connections, which in turn predispose white matter hyperintensities patients to worse cognitive function.

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.

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.

Information encoded in volumes and areas of dendritic spines is nearly maximal across mammalian brains

Many experiments suggest that long-term information associated with neuronal memory resides collectively in dendritic spines. However, spines can have a limited size due to metabolic and neuroanatomical constraints, which should effectively limit the amount of encoded information in excitatory synapses. This study investigates how much information can be stored in the population of sizes of dendritic spines, and whether it is optimal in any sense. It is shown here, using empirical data for several mammalian brains across different regions and physiological conditions, that dendritic spines nearly maximize entropy contained in their volumes and surface areas for a given mean size in cortical and hippocampal regions. Although both short- and heavy-tailed fitting distributions approach [Formula: see text] of maximal entropy in the majority of cases, the best maximization is obtained primarily for short-tailed gamma distribution. We find that most empirical ratios of standard deviation to mean for spine volumes and areas are in the range [Formula: see text], which is close to the theoretical optimal ratios coming from entropy maximization for gamma and lognormal distributions. On average, the highest entropy is contained in spine length ([Formula: see text] bits per spine), and the lowest in spine volume and area ([Formula: see text] bits), although the latter two are closer to optimality. In contrast, we find that entropy density (entropy per spine size) is always suboptimal. Our results suggest that spine sizes are almost as random as possible given the constraint on their size, and moreover the general principle of entropy maximization is applicable and potentially useful to information and memory storing in the population of cortical and hippocampal excitatory synapses, and to predicting their morphological properties.

Structural architecture and brain network efficiency link polygenic scores to intelligence

Intelligence is highly heritable. Genome-wide association studies (GWAS) have shown that thousands of alleles contribute to variation in intelligence with small effect sizes. Polygenic scores (PGS), which combine these effects into one genetic summary measure, are increasingly used to investigate polygenic effects in independent samples. Whereas PGS explain a considerable amount of variance in intelligence, it is largely unknown how brain structure and function mediate this relationship. Here, we show that individuals with higher PGS for educational attainment and intelligence had higher scores on cognitive tests, larger surface area, and more efficient fiber connectivity derived by graph theory. Fiber network efficiency as well as the surface of brain areas partly located in parieto-frontal regions were found to mediate the relationship between PGS and cognitive performance. These findings are a crucial step forward in decoding the neurogenetic underpinnings of intelligence, as they identify specific regional networks that link polygenic predisposition to intelligence.

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.

Resilience of compound action potential peaks to high-frequency firing in the mouse optic nerve

Action potential conduction in axons triggers trans-membrane ion movements, where Na⁺ enters and K⁺ leaves axons, leading to disruptions in resting trans-membrane ion gradients that must be restored for optimal axon conduction, an energy dependent process. The higher the stimulus frequency, the greater the ion movements and the resulting energy demand. In the mouse optic nerve (MON), the stimulus evoked compound action potential (CAP) displays a triple peaked profile, consistent with subpopulations of axons classified by size producing the distinct peaks. The three CAP peaks show differential sensitivity to high-frequency firing, with the large axons, which contribute to the 1st peak, more resilient than the small axons, which produce the 3rd peak. Modeling studies predict frequency dependent intra-axonal Na⁺ accumulation at the nodes of Ranvier, sufficient to attenuate the triple peaked CAP. Short bursts of high-frequency stimulus evoke transient elevations in interstitial K⁺ ([K⁺ ]_o ), which peak at about 50 Hz. However, powerful astrocytic buffering limits the [K⁺ ]_o increase to levels insufficient to cause CAP attenuation. A post-stimulus [K⁺ ]_o undershoot below baseline coincides with a transient increase in the amplitudes of all three CAP peaks. The volume specific scaling relating energy expenditure to increasing axon size dictates that large axons are more resilient to high-frequency firing than small axons.

[Chronic sleep restriction in rats leads to a weakening of compensatory reactions in response to acute sleep deprivation]

OBJECTIVE

To identify features in the compensatory mechanisms of sleep regulation in response to acute sleep deprivation after chronic sleep restriction in rats.

MATERIAL AND METHODS

Male Wistar rats 7-8 months old underwent 5-day sleep restriction: 3 h of sleep deprivation and 1 h of sleep opportunity repeating throughout each day. Six-hour acute total sleep deprivation was performed at the beginning of daylight hours on the 3rd day after sleep restriction. Polysomnogramms were recorded throughout the day before chronic sleep restriction, on the 2nd recovery day after chronic sleep restriction and after acute sleep deprivation. The control group was not subjected to chronic sleep restriction.

RESULTS

The animals after chronic sleep restriction had the compensatory increase in total sleep time in response to acute sleep deprivation weaker than in control animals. Animals after sleep restriction had the compensatory increase in the time of slow-wave sleep (SWS) only in the first 6 hours after acute sleep deprivation, whereas in control animals the period of compensation of SWS lasted 12 hours. A compensatory increase in slow-wave activity (SWA) was observed in both groups of animals, but in animals experiencing chronic sleep restriction the amplitude of SWA after acute sleep deprivation was less than in control animals. A compensatory increase in REM sleep in sleep restricted animals occurred immediately after acute sleep deprivation and coincides with a compensatory increase in SWS and SWA, whereas in control conditions these processes are spaced in time.

CONCLUSION

Compensatory reactions in response to acute sleep deprivation (sleep homeostasis) are weakened in animals subjected to chronic sleep restriction, as the reaction time and amplitude are reduced.

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.

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.

White Paper: An Integrated Perspective on the Causes of Hypometric Metabolic Scaling in Animals

Larger animals studied during ontogeny, across populations, or across species, usually have lower mass-specific metabolic rates than smaller animals (hypometric scaling). This pattern is usually observed regardless of physiological state (e.g. basal, resting, field, maximally-active). The scaling of metabolism is usually highly correlated with the scaling of many life history traits, behaviors, physiological variables, and cellular/molecular properties, making determination of the causation of this pattern challenging. For across-species comparisons of resting and locomoting animals (but less so for across populations or during ontogeny), the mechanisms at the physiological and cellular level are becoming clear. Lower mass-specific metabolic rates of larger species at rest are due to a) lower contents of expensive tissues (brains, liver, kidneys), and b) slower ion leak across membranes at least partially due to membrane composition, with lower ion pump ATPase activities. Lower mass-specific costs of larger species during locomotion are due to lower costs for lower-frequency muscle activity, with slower myosin and Ca++ ATPase activities, and likely more elastic energy storage. The evolutionary explanation(s) for hypometric scaling remain(s) highly controversial. One subset of evolutionary hypotheses relies on constraints on larger animals due to changes in geometry with size; for example, lower surface-to-volume ratios of exchange surfaces may constrain nutrient or heat exchange, or lower cross-sectional areas of muscles and tendons relative to body mass ratios would make larger animals more fragile without compensation. Another subset of hypotheses suggests that hypometric scaling arises from biotic interactions and correlated selection, with larger animals experiencing less selection for mass-specific growth or neurolocomotor performance. A additional third type of explanation comes from population genetics. Larger animals with their lower effective population sizes and subsequent less effective selection relative to drift may have more deleterious mutations, reducing maximal performance and metabolic rates. Resolving the evolutionary explanation for the hypometric scaling of metabolism and associated variables is a major challenge for organismal and evolutionary biology. To aid progress, we identify some variation in terminology use that has impeded cross-field conversations on scaling. We also suggest that promising directions for the field to move forward include: 1) studies examining the linkages between ontogenetic, population-level, and cross-species allometries, 2) studies linking scaling to ecological or phylogenetic context, 3) studies that consider multiple, possibly interacting hypotheses, and 4) obtaining better field data for metabolic rates and the life history correlates of metabolic rate such as lifespan, growth rate and reproduction.

Acute stroke-like deficits associated with nonketotic hyperglycemic hyperosmolar state: an illustrative case and systematic review of literature

Introduction

Nonketotic hyperglycemic hyperosmolar state (NKHHS) is associated with a wide spectrum of neurological syndromes including acute stroke-like deficits. Clinical features and etiology have not been established yet.

Methods

Here we provide a case illustration and systematic review on non-epileptic acute neurological deficits in NKHSS. The systematic literature search followed PRISMA guidelines and a predefined protocol, including cases of NKHSS with acute stroke-like presentation.

Results

The database search yielded 18 cases. Hemianopia was the most common clinical presentation (73%), followed by partial or total anterior circulation syndrome (26%). Patients with symptoms of acute anterior circulation infarct were significantly older (69.5 ± 5.1 vs. 52.2 ± 13.9 years; p = 0.03) and showed higher mean glucose levels at the admission vs. those with hemianopia (674.8 ± 197.2 vs. 529.4 ± 190.8 mg/dL; p = 0.16). Brain MRI was performed in 89% of patients, resulting abnormal in 71% of them, especially hemianopic (91%). Subcortical hypointensities in T2-FLAIR MR sequences were present in all the analyzed cases. Cortical DWI hyperintensities were also common (64%). EEG showed diffuse or focal slow wave activity in 68% of patients, especially with visual hallucinations (85%). Neurological symptoms completely resolved in 78% of patients within 6 (IQR 3–10) days, following aggressive treatment and glucose normalization.

Conclusions

Our results suggest neuronal dysfunction on a metabolic basis as the leading cause of acute neurological deficits in NKHHS. Despite the generally favorable prognosis, prompt identification and aggressive treatment are crucial to avoid irreversible damage. Larger cohort studies are needed to confirm our findings.

After 55 Years of Neurorehabilitation, What Is the Plan?

Neurological disorders often cause severe long-term disabilities with substantial activity limitations and participation restrictions such as community integration, family functioning, employment, social interaction and participation. Increasing understanding of brain functioning has opened new perspectives for more integrative interventions, boosting the intrinsic central nervous system neuroplastic capabilities in order to achieve efficient behavioral restitution. Neurorehabilitation must take into account the many aspects of the individual through a comprehensive analysis of actual and potential cognitive, behavioral, emotional and physical skills, while increasing awareness and understanding of the new self of the person being dealt with. The exclusive adoption by the rehabilitator of objective functional measures often overlooks the values and goals of the disabled person. Indeed, each individual has their own rhythm, unique life history and personality construct. In this challenging context, it is essential to deepen the assessment through subjective measures, which more adequately reflect the patient’s perspective in order to shape genuinely tailored instead of standardized neurorehabilitation approaches. In this overly complex panorama, where confounding and prognostic factors also strongly influence potential functional recovery, the healthcare community needs to rethink neurorehabilitation formats.

Percolation may explain efficiency, robustness, and economy of the brain

The brain consists of billions of neurons connected by ultra-dense synapses, showing remarkable efficiency, robust flexibility, and economy in information processing. It is generally believed that these advantageous properties are rooted in brain connectivity; however, direct evidence remains absent owing to technical limitations or theoretical vacancy. This research explores the origins of these properties in the largest yet brain connectome of the fruit fly. We reveal that functional connectivity formation in the brain can be explained by a percolation process controlled by synaptic excitation-inhibition (E/I) balance. By increasing the E/I balance gradually, we discover the emergence of these properties as byproducts of percolation transition when the E/I balance arrives at 3:7. As the E/I balance keeps increase, an optimal E/I balance 1:1 is unveiled to ensure these three properties simultaneously, consistent with previous in vitro experimental predictions. Once the E/I balance reaches over 3:2, an intrinsic limitation of these properties determined by static (anatomical) brain connectivity can be observed. Our work demonstrates that percolation, a universal characterization of critical phenomena and phase transitions, may serve as a window toward understanding the emergence of various brain properties.

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.

Interactions Between Intestinal Microbiota and Neural Mitochondria: A New Perspective on Communicating Pathway From Gut to Brain

Many studies shown that neurological diseases are associated with neural mitochondrial dysfunctions and microbiome composition alterations. Since mitochondria emerged from bacterial ancestors during endosymbiosis, mitochondria, and bacteria had analogous genomic characteristics, similar bioactive compounds and comparable energy metabolism pathways. Therefore, it is necessary to rationalize the interactions of intestinal microbiota with neural mitochondria. Recent studies have identified neural mitochondrial dysfunction as a critical pathogenic factor for the onset and progress of multiple neurological disorders, in which the non-negligible role of altered gut flora composition was increasingly noticed. Here, we proposed a new perspective of intestinal microbiota – neural mitochondria interaction as a communicating channel from gut to brain, which could help to extend the vision of gut-brain axis regulation and provide additional research directions on treatment and prevention of responsive neurological disorders.

Altered Structural and Functional MRI Connectivity in Type 2 Diabetes Mellitus Related Cognitive Impairment: A Review

Type 2 diabetes mellitus (T2DM) is associated with cognitive impairment in many domains. There are several pieces of evidence that changes in neuronal neuropathies and metabolism have been observed in T2DM. Structural and functional MRI shows that abnormal connections and synchronization occur in T2DM brain circuits and related networks. Neuroplasticity and energy metabolism appear to be principal effector systems, which may be related to amyloid beta (Aβ) deposition, although there is no unified explanation that includes the complex etiology of T2DM with cognitive impairment. Herein, we assume that cognitive impairment in diabetes may lead to abnormalities in neuroplasticity and energy metabolism in the brain, and those reflected to MRI structural connectivity and functional connectivity, respectively.

Redundant functions of the SLC5A transporters Rumpel, Bumpel, and Kumpel in ensheathing glial cells

Neuronal processing is energy demanding, and relies on sugar metabolism. To nurture the Drosophila nervous system, the blood-brain barrier forming glial cells take up trehalose from the hemolymph and then distribute the metabolic products further to all neurons. This function is provided by glucose and lactate transporters of the solute carrier (SLC) 5A family. Here we identified three SLC5A genes that are specifically expressed in overlapping sets of CNS glial cells, rumpel, bumpel and kumpel. We generated mutants in all genes and all mutants are viable and fertile, lacking discernible phenotypes. Loss of rumpel causes subtle locomotor phenotypes and flies display increased daytime sleep. In addition, in bumpel kumpel double mutants, and to an even greater extent in rumpel bumpel kumpel triple mutants, oogenesis is disrupted at the onset of the vitollegenic phase. This indicates a partially redundant functions between these genes. Rescue experiments exploring this effect indicate that oogenesis can be affected by CNS glial cells. Moreover, expression of heterologous mammalian SLC5A transporters, with known transport properties, suggest that Bumpel and/or Kumpel transport glucose or lactate. Overall, our results imply a redundancy in SLC5A nutrient sensing functions in Drosophila glial cells, affecting ovarian development and behavior.

Visceral adiposity, inflammation, and hippocampal function in obesity

The 'apple-shaped' anatomical pattern that accompanies visceral adiposity increases risk for multiple chronic diseases, including conditions that impact the brain, such as diabetes and hypertension. However, distinguishing between the consequences of visceral obesity, as opposed to visceral adiposity-associated metabolic and cardiovascular pathologies, presents certain challenges. This review summarizes current literature on relationships between adipose tissue distribution and cognition in preclinical models and highlights unanswered questions surrounding the potential role of tissue- and cell type-specific insulin resistance in these effects. While gaps in knowledge persist related to insulin insensitivity and cognitive impairment in obesity, several recent studies suggest that cells of the neurovascular unit contribute to hippocampal synaptic dysfunction, and this review interprets those findings in the context of progressive metabolic dysfunction in the CNS. Signalling between cerebrovascular endothelial cells, astrocytes, microglia, and neurons has been linked with memory deficits in visceral obesity, and this article describes the cellular changes in each of these populations with respect to their role in amplification or diminution of peripheral signals. The picture emerging from these studies, while incomplete, implicates pro-inflammatory cytokines, insulin resistance, and hyperglycemia in various stages of obesity-induced hippocampal dysfunction. As in the parable of the five blind wanderers holding different parts of an elephant, considerable work remains in order to assemble a model for the underlying mechanisms linking visceral adiposity with age-related cognitive decline.

Scaling Principles of White Matter Connectivity in the Human and Nonhuman Primate Brain

Brains come in many shapes and sizes. Nature has endowed big-brained primate species like humans with a proportionally large cerebral cortex. Comparative studies have suggested, however, that the total volume allocated to white matter connectivity-the brain's infrastructure for long-range interregional communication-does not keep pace with the cortex. We investigated the consequences of this allometric scaling on brain connectivity and network organization. We collated structural and diffusion magnetic resonance imaging data across 14 primate species, describing a comprehensive 350-fold range in brain size across species. We show volumetric scaling relationships that indeed point toward a restriction of macroscale connectivity in bigger brains. We report cortical surface area to outpace white matter volume, with larger brains showing lower levels of overall connectedness particularly through sparser long-range connectivity. We show that these constraints on white matter connectivity are associated with longer communication paths, higher local network clustering, and higher levels of asymmetry in connectivity patterns between homologous areas across the left and right hemispheres. Our findings reveal conserved scaling relationships of major brain components and show consequences for macroscale brain circuitry, providing insights into the connectome architecture that could be expected in larger brains such as the human brain.

Gill surface area provides a clue for the respiratory basis of brain size in the blacktip shark (Carcharhinus limbatus)

Brain size varies dramatically, both within and across species, and this variation is often believed to be the result of trade-offs between the cognitive benefits of having a large brain for a given body size and the energetic cost of sustaining neural tissue. One potential consequence of having a large brain is that organisms must also meet the associated high energetic demands. Thus, a key question is whether metabolic rate correlates with brain size. However, using metabolic rate to measure energetic demand yields a relatively instantaneous and dynamic measure of energy turnover, which is incompatible with the longer evolutionary timescale of changes in brain size within and across species. Morphological traits associated with oxygen consumption, specifically gill surface area, have been shown to be correlates of oxygen demand and energy use, and thus may serve as integrated correlates of these processes, allowing us to assess whether evolutionary changes in brain size correlate with changes in longer-term oxygen demand and energy use. We tested how brain size relates to gill surface area in the blacktip shark Carcharhinus limbatus. First, we examined whether the allometric slope of brain mass (i.e., the rate that brain mass changes with body mass) is lower than the allometric slope of gill surface area across ontogeny. Second, we tested whether gill surface area explains variation in brain mass, after accounting for the effects of body mass on brain mass. We found that brain mass and gill surface area both had positive allometric slopes, with larger individuals having both larger brains and larger gill surface areas compared to smaller individuals. However, the allometric slope of brain mass was lower than the allometric slope of gill surface area, consistent with our prediction that the allometric slope of gill surface area could pose an upper limit to the allometric slope of brain mass. Finally, after accounting for body mass, individuals with larger brains tended to have larger gill surface areas. Together, our results provide clues as to how fishes may evolve and maintain large brains despite their high energetic cost, suggesting that C. limbatus individuals with a large gill surface area for their body mass may be able to support a higher energetic turnover, and, in turn, a larger brain for their body mass.

Functional Weight of Somatic and Cognitive Networks and Asymmetry of Compensatory Mechanisms: Collaboration or Divergency among Hemispheres after Cerebrovascular Accident?

The human brain holds highly sophisticated compensatory mechanisms relying on neuroplasticity. Neuronal degeneracy, redundancy, and brain network organization make the human nervous system more robust and evolvable to continuously guarantee an optimal environmental-related homeostasis. Nevertheless, after injury, restitution processes appear dissimilar, depending on the pathology. Following a cerebrovascular accident, asymmetry, within- and across-network compensation and interhemispheric inhibition are key features to functional recovery. In moderate-to-severe stroke, neurological outcome is often poor, and little is known about the paths that enable either an efficient collaboration among hemispheres or, on the contrary, an antagonism of adaptative responses. In this review, we aim to decipher key issues of ipsilesional and contralesional hemispheric functioning allowing the foundations of effective neurorehabilitation strategies.

Energetics of stochastic BCM type synaptic plasticity and storing of accurate information

Excitatory synaptic signaling in cortical circuits is thought to be metabolically expensive. Two fundamental brain functions, learning and memory, are associated with long-term synaptic plasticity, but we know very little about energetics of these slow biophysical processes. This study investigates the energy requirement of information storing in plastic synapses for an extended version of BCM plasticity with a decay term, stochastic noise, and nonlinear dependence of neuron’s firing rate on synaptic current (adaptation). It is shown that synaptic weights in this model exhibit bistability. In order to analyze the system analytically, it is reduced to a simple dynamic mean-field for a population averaged plastic synaptic current. Next, using the concepts of nonequilibrium thermodynamics, we derive the energy rate (entropy production rate) for plastic synapses and a corresponding Fisher information for coding presynaptic input. That energy, which is of chemical origin, is primarily used for battling fluctuations in the synaptic weights and presynaptic firing rates, and it increases steeply with synaptic weights, and more uniformly though nonlinearly with presynaptic firing. At the onset of synaptic bistability, Fisher information and memory lifetime both increase sharply, by a few orders of magnitude, but the plasticity energy rate changes only mildly. This implies that a huge gain in the precision of stored information does not have to cost large amounts of metabolic energy, which suggests that synaptic information is not directly limited by energy consumption. Interestingly, for very weak synaptic noise, such a limit on synaptic coding accuracy is imposed instead by a derivative of the plasticity energy rate with respect to the mean presynaptic firing, and this relationship has a general character that is independent of the plasticity type. An estimate for primate neocortex reveals that a relative metabolic cost of BCM type synaptic plasticity, as a fraction of neuronal cost related to fast synaptic transmission and spiking, can vary from negligible to substantial, depending on the synaptic noise level and presynaptic firing.

The role of brain size on mammalian population densities

The local abundance or population density of different organisms often varies widely. Understanding what determines this variation is an important, but not yet fully resolved question in ecology. Differences in population density are partly driven by variation in body size and diet among organisms. Here we propose that the size of an organism' brain could be an additional, overlooked, driver of mammalian population densities. We explore two possible contrasting mechanisms by which brain size, measured by its mass, could affect population density. First, because of the energetic demands of larger brains and their influence on life history, we predict mammals with larger relative brain masses would occur at lower population densities. Alternatively, larger brains are generally associated with a greater ability to exploit new resources, which would provide a competitive advantage leading to higher population densities among large-brained mammals. We tested these predictions using phylogenetic path analysis, modelling hypothesized direct and indirect relationships between diet, body mass, brain mass and population density for 656 non-volant terrestrial mammalian species. We analysed all data together and separately for marsupials and the four taxonomic orders with most species in the dataset (Carnivora, Cetartiodactyla, Primates, Rodentia). For all species combined, a single model was supported showing lower population density associated with larger brains, larger bodies and more specialized diets. The negative effect of brain mass was also supported for separate analyses in Primates and Carnivora. In other groups (Rodentia, Cetartiodactyla and marsupials) the relationship was less clear: supported models included a direct link from brain mass to population density but 95% confidence intervals of the path coefficients overlapped zero. Results support our hypothesis that brain mass can explain variation in species' average population density, with large-brained species having greater area requirements, although the relationship may vary across taxonomic groups. Future research is needed to clarify whether the role of brain mass on population density varies as a function of environmental (e.g. environmental stability) and biotic conditions (e.g. level of competition).

Scaling of organ masses in mammals and birds: phylogenetic signal and implications for metabolic rate scaling

The persistent enigma of why the whole-body metabolic rate increases hypoallometrically with body mass should be solved on both the ultimate and proximate levels. The proximate mechanism may involve hyperallometric scaling of metabolically inert tissue/organ masses, hypoallometric scaling of metabolically expensive organ masses, a decrease in mass-specific metabolic rates of organs or a combination of these three factors. Although there are literature data on the tissue/organ masses scaling, they do not consider phylogenetic information. Here, we analyse the scaling of tissue/organ masses in a sample of 100 mammalian and 22 bird species with a phylogenetically informed method (PGLS) to address two questions: the role of phylogenetic differences in organ/tissue size scaling and the potential role of organ/tissue mass scaling in interspecific metabolic rate scaling. Strong phylogenetic signal was found for the brain, kidney, spleen and stomach mass in mammals but only for the brain and leg muscle in birds. Metabolically relatively inert adipose tissue scales isometrically in both groups. The masses of energetically expensive visceral organs scale hypoallometrically in mammals, with the exception of lungs, with the lowest exponent for the brain. In contrast, only brain mass scales hypoallometrically in birds, whereas other tissues and organs scale isometrically or almost isometrically. Considering that the whole-body metabolic rate scales more steeply in mammals than in birds, the mass-specific metabolic rate of visceral organs must decrease with body mass much faster in birds than in mammals. In general, studying whole-body metabolic rate is not adequate for explaining its scaling, and measuring metabolic rates of organs, together with their contribution to body mass, is urgently required.

Coevolution of body size and metabolic rate in vertebrates: a life-history perspective

Despite many decades of research, the allometric scaling of metabolic rates (MRs) remains poorly understood. Here, we argue that scaling exponents of these allometries do not themselves mirror one universal law of nature but instead statistically approximate the non-linearity of the relationship between MR and body mass. This 'statistical' view must be replaced with the life-history perspective that 'allows' organisms to evolve myriad different life strategies with distinct physiological features. We posit that the hypoallometric allometry of MRs (mass scaling with an exponent smaller than 1) is an indirect outcome of the selective pressure of ecological mortality on allocation 'decisions' that divide resources among growth, reproduction, and the basic metabolic costs of repair and maintenance reflected in the standard or basal metabolic rate (SMR or BMR), which are customarily subjected to allometric analyses. Those 'decisions' form a wealth of life-history variation that can be defined based on the axis dictated by ecological mortality and the axis governed by the efficiency of energy use. We link this variation as well as hypoallometric scaling to the mechanistic determinants of MR, such as metabolically inert component proportions, internal organ relative size and activity, cell size and cell membrane composition, and muscle contributions to dramatic metabolic shifts between the resting and active states. The multitude of mechanisms determining MR leads us to conclude that the quest for a single-cause explanation of the mass scaling of MRs is futile. We argue that an explanation based on the theory of life-history evolution is the best way forward.

An integrative understanding of comparative cognition: lessons from human brain evolution

A comprehensive understanding of animal cognition requires the integration of studies on behavior, electrophysiology, neuroanatomy, development, and genomics. Although studies of comparative cognition are receiving increasing attention from organismal biologists, most current studies focus on the comparison of behaviors and anatomical structures to understand their adaptative values. However, to understand the most potentially complex cognitive program of the human brain a greater synthesis of a multitude of disciplines is needed. In this review, we start with extensive neuroanatomic comparisons between humans and other primates. One likely specialization of the human brain is the expansion of neocortex, especially in regions for high-order cognition (e.g., prefrontal cortex). We then discuss how such an expansion can be linked to heterochrony of the brain developmental program, resulting in a greater number of neurons and enhanced computational capacity. Furthermore, alteration of gene expression in the human brain has been associated with positive selection in DNA sequences of gene regulatory regions. These results not only imply that genes associated with brain development are a major factor in the evolution of cognition, but also that high-quality whole-genome sequencing and gene manipulation techniques are needed for an integrative and functional understanding of comparative cognition in non-model organisms.

Persistent changes in extracellular lactate dynamics following synaptic potentiation

A diverse array of neurometabolic coupling mechanisms exist within the brain to ensure that sufficient metabolite availability is present to meet both acute and chronic energetic demands. Excitatory synaptic activity, which produces the majority of the brain's energetic demands, triggers a rapid metabolic response including a characteristic shift towards aerobic glycolysis. Herein, astrocytically derived lactate appears to serve as an important metabolite to meet the extensive metabolic needs of activated neurons. Despite a wealth of literature characterizing lactate's role in mediating these acute metabolic needs, the extent to which lactate supports chronic energetic demands of neurons remains unclear. We hypothesized that synaptic potentiation, a ubiquitous brain phenomenon that can produce chronic alterations in synaptic activity, could necessitate persistent alterations in brain energetics. In freely-behaving rats, we induced long-term potentiation (LTP) of synapses within the dentate gyrus through high-frequency electrical stimulation (HFS) of the medial perforant pathway. Before, during, and after LTP induction, we continuously recorded extracellular lactate concentrations within the dentate gyrus to assess how changes in synaptic strength alter local glycolytic activity. Synaptic potentiation 1) altered the acute response of extracellular lactate to transient neuronal activation as evident by a larger initial dip and subsequent overshoot and 2) chronically increased local lactate availability. Although synapses were potentiated immediately following HFS, observed changes in lactate dynamics were only evident beginning ~24 h later. Once observed, however, both synaptic potentiation and altered lactate dynamics persisted for the duration of the experiment (~72 h). Persistent alterations in synaptic strength, therefore, appear to be associated with metabolic plasticity in the form of persistent augmentation of glycolytic activity.

Age-Related Alterations in Brain Perfusion, Venous Oxygenation, and Oxygen Metabolic Rate of Mice: A 17-Month Longitudinal MRI Study

Background: Characterization of physiological parameters of the aging brain, such as perfusion and brain metabolism, is important for understanding brain function and diseases. Aging studies on human brain have mostly been based on the cross-sectional design, while the few longitudinal studies used relatively short follow-up time compared to the lifespan. Objectives: To determine the longitudinal time courses of cerebral physiological parameters across the adult lifespan in mice. Methods: The present work examined longitudinal changes in cerebral blood flow (CBF), cerebral venous oxygenation (Yv), and cerebral metabolic rate of oxygen (CMRO2) using MRI in healthy C57BL/6 mice from 3 to 20 months of age. Each mouse received 16 imaging sessions at an ~1-month interval. Results: Significant increases with age were observed in CBF (p = 0.017) and CMRO2 (p < 0.001). Meanwhile, Yv revealed a significant decrease (p = 0.002) with a non-linear pattern (p = 0.013). The rate of change was 0.87, 2.26, and -0.24% per month for CBF, CMRO2, and Yv, respectively. On the other hand, systemic parameters such as heart rate did not show a significant age dependence (p = 0.47). No white-matter-hyperintensities (WMH) were observed on the T2-weighted image at any age of the mice. Conclusion: With age, the mouse brain revealed an increase in oxygen consumption. This observation is consistent with previous findings in humans using a cross-sectional design and suggests a degradation of the brain's energy production or utilization machinery. Cerebral perfusion remains relatively intact in aged mice, at least until 20 months of age, consistent with the absence of WMH in mice.

What is bipolar disorder? A disease model of dysregulated energy expenditure

Advances in the understanding and management of bipolar disorder (BD) have been slow to emerge. Despite notable recent developments in neurosciences, our conceptualization of the nature of this mental disorder has not meaningfully progressed. One of the key reasons for this scenario is the continuing lack of a comprehensive disease model. Within the increasing complexity of modern research methods, there is a clear need for an overarching theoretical framework, in which findings are assimilated and predictions are generated. In this review and hypothesis article, we propose such a framework, one in which dysregulated energy expenditure is a primary, sufficient cause for BD. Our proposed model is centered on the disruption of the molecular and cellular network regulating energy production and expenditure, as well its potential secondary adaptations and compensatory mechanisms. We also focus on the putative longitudinal progression of this pathological process, considering its most likely periods for onset, such as critical periods that challenges energy homeostasis (e.g. neurodevelopment, social isolation), and the resulting short and long-term phenotypical manifestations.

Therapeutic alternative of the ketogenic Mediterranean diet to improve mitochondrial activity in Amyotrophic Lateral Sclerosis (ALS): A Comprehensive Review

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease which is pathogenically based on the mitochondrial alteration of motor neurons, causing progressive neuron death. While ALS is characterized by enormous oxidative stress, the Mediterranean diet has been seen to have high antioxidant power. Therefore, the aim of this study is to determine how the Mediterranean diet can improve mitochondrial activity, establishing the specific nutrients and, in addition, observing the pathogenic mechanisms related to the disease that would achieve this improvement. To this end, a comprehensive review of the literature was performed using PubMed. KBs have been observed to have a neuroprotective effect to improve energy balance, increasing survival and the number of motor neurons. This ketogenesis can be achieved after following a Mediterranean diet which is associated with great benefits in other neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and ALS. These benefits are due to the high antioxidant power especially based on polyphenols contained mainly in olive oil, wine, nuts, or berries. In short, KBs could be considered as a promising option to treat ALS, representing an alternative source to glucose in motor neurons by providing neuroprotection. In addition, treatment results can be improved as ketogenesis can be achieved (increase in KBs) by following a Mediterranean diet, thanks to the high antioxidant properties which, at the same time, would improve the high oxidative stress that characterizes the disease.

Is There a Contribution of Structural Brain Phenotypes to the Variance in Resting Energy Expenditure before and after Weight Loss in Overweight Females?

Brain gray (GM) and white matter (WM) are associated with resting energy expenditure (REE). The impact of weight loss on GM and WM masses, as well as on their associations with REE and the ratio between body and brain metabolism, i.e., encephalic measure (EM)), are unknown. Longitudinal data of 69 female Caucasian subjects (age range 19–69 years) with detailed information on fat mass (FM), fat free mas (FFM), GM, WM and REE. Mean weight loss was 14.5 ± 11.9 kg with changes in FM (−12.9 ± 9.8 kg), FFM (−1.7 ± 4.8 kg) and REE (−159 ± 191 kcal/24 h) (all p < 0.05). With weight loss, there were no changes in GM and WM. Before and after weight loss, FFM was the main determinant of REE (r² = 0.483 and 0.413; p < 0.05). After weight loss, GM added to the variances in REE (3.6%), REE_adjFFM (6.1%) and the REE on FFM residuals (6.6%). In addition, before and after weight loss GM explained 25.0% and 10.0% of the variances in EM (p < 0.05). Weight loss had no effect on volumes of GM and WM. After weight loss, both, GM added to the variances of REE, REE on FFM residuals and EM.

Cerebral blood flow rates in recent great apes are greater than in Australopithecus species that had equal or larger brains

Brain metabolic rate (MR) is linked mainly to the cost of synaptic activity, so may be a better correlate of cognitive ability than brain size alone. Among primates, the sizes of arterial foramina in recent and fossil skulls can be used to evaluate brain blood flow rate, which is proportional to brain MR. We use this approach to calculate flow rate in the internal carotid arteries (Q˙ICA), which supply most of the primate cerebrum. Q˙ICA is up to two times higher in recent gorillas, chimpanzees and orangutans compared with 3-million-year-old australopithecine human relatives, which had equal or larger brains. The scaling relationships between Q˙ICA and brain volume (V_br) show exponents of 1.03 across 44 species of living haplorhine primates and 1.41 across 12 species of fossil hominins. Thus, the evolutionary trajectory for brain perfusion is much steeper among ancestral hominins than would be predicted from living primates. Between 4.4-million-year-old Ardipithecus and Homo sapiens, V_br increased 4.7-fold, but Q˙ICA increased 9.3-fold, indicating an approximate doubling of metabolic intensity of brain tissue. By contrast, Q˙ICA is proportional to V_br among haplorhine primates, suggesting a constant volume-specific brain MR.

Quantitative analysis of arterial supply to the developing brain in tetrapod vertebrates

Understanding the metabolic cost of building developing tetrapod brains is critically important to explaining the more than 10-fold differences in encephalization of adult tetrapods that have emerged during evolution. The exact metabolic costs of developing the variety of tetrapod brains are impossible to determine, but one can compare cerebral artery caliber (internal radius raised to the fourth power-r⁴ ) across developing tetrapod vertebrate groups as a proxy of cerebral arterial flow, the delivery of nutrients during embryogenesis and early postnatal development, and hence the metabolic costs of brain development. In this study, r⁴ of aortic outflow and cerebral inflow arteries, as well as aortic wall thickness as a proxy of arterial pressure, were measured and compared between developing representatives of all four tetrapod classes (mammals, birds, reptiles, and amphibians). We found a clear endotherm/ectotherm dichotomy in aortic outflow and cerebral inflow between developing mammals and birds on the one hand, and developing reptiles and amphibians on the other. We did not find strong evidence for functionally significant differences in cerebral arterial caliber between groups at the order level (i.e., within birds, reptiles or amphibians). In particular, we did not find evidence in favor of increased blood supply to the brain for more behaviorally complex and encephalized avian species.

Region-specific changes in Mus musculus brain size and cell composition under chronic nutrient restriction

Nutrition is one of the most influential environmental factors affecting the development of different tissues and organs. It is suggested that under nutrient restriction the growth of the brain is spared as a result of the differential allocation of resources from other organs. However, it is not clear whether this sparing occurs brain-wide. Here, we analyzed morphological changes and cell composition in different regions of the offspring mouse brain after maternal exposure to nutrient restriction during pregnancy and lactation. Using high-resolution magnetic resonance imaging, we found that brain regions were differentially sensitive to maternal protein restriction and exhibited particular patterns of volume reduction. The cerebellum was reduced in absolute and relative volume, while cortex volume was relatively preserved. Alterations in cell composition (examined by the isotropic fractionator method) and organization of white matter (measured by diffusor tensor images) were also region specific. These changes were not related to the metabolic rate of the regions and were only partially explained by their specific growth trajectories. This study is a first step towards understanding the mechanisms of regional brain sparing at microstructural and macrostructural levels resulting from undernutrition.

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

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

Metabolic constraints on synaptic learning and memory

Dendritic spines, the carriers of long-term memory, occupy a small fraction of cortical space, and yet they are the major consumers of brain metabolic energy. What fraction of this energy goes for synaptic plasticity, correlated with learning and memory? It is estimated here based on neurophysiological and proteomic data for rat brain that, depending on the level of protein phosphorylation, the energy cost of synaptic plasticity constitutes a small fraction of the energy used for fast excitatory synaptic transmission, typically 4.0-11.2%. Next, this study analyzes a metabolic cost of new learning and its memory trace in relation to the cost of prior memories, using a class of cascade models of synaptic plasticity. It is argued that these models must contain bidirectional cyclic motifs, related to protein phosphorylation, to be compatible with basic thermodynamic principles. For most investigated parameters longer memories generally require proportionally more energy to store. The exceptions are the parameters controlling the speed of molecular transitions (e.g., ATP-driven phosphorylation rate), for which memory lifetime per invested energy can increase progressively for longer memories. Furthermore, in general, a memory trace decouples dynamically from a corresponding synaptic metabolic rate such that the energy expended on new learning and its memory trace constitutes in most cases only a small fraction of the baseline energy associated with prior memories. Taken together, these empirical and theoretical results suggest a metabolic efficiency of synaptically stored information.NEW & NOTEWORTHY Learning and memory involve a sequence of molecular events in dendritic spines called synaptic plasticity. These events are physical in nature and require energy, which has to be supplied by ATP molecules. However, our knowledge of the energetics of these processes is very poor. This study estimates the empirical energy cost of synaptic plasticity and considers theoretically a metabolic rate of learning and its memory trace in a class of cascade models of synaptic plasticity.

Astrocyte dysfunction and neurovascular impairment in neurological disorders: Correlation or causation?

The neurovascular unit, consisting of neurons, astrocytes, and vascular cells, has become the focus of much discussion in the last two decades and emerging literature now suggests an association between neurovascular dysfunction and neurological disorders. In this review, we synthesize the known and suspected contributions of astrocytes to neurovascular dysfunction in disease. Throughout the brain, astrocytes are centrally positioned to dynamically mediate interactions between neurons and the cerebral vasculature, and play key roles in blood-brain barrier maintenance and neurovascular coupling. It is increasingly apparent that the changes in astrocytes in response to a variety of insults to brain tissue -collectively referred to as "reactive astrogliosis" - are not just an epiphenomenon restricted to morphological alterations, but comprise functional changes in astrocytes that contribute to the phenotype of neurological diseases with both beneficial and detrimental effects. In the context of the neurovascular unit, astrocyte dysfunction accompanies, and may contribute to, blood-brain barrier impairment and neurovascular dysregulation, highlighting the need to determine the exact nature of the relationship between astrocyte dysfunction and neurovascular impairments. Targeting astrocytes may represent a new strategy in combinatorial therapeutics for preventing the mismatch of energy supply and demand that often accompanies neurological disorders.

Carotid foramen size in the human skull tracks developmental changes in cerebral blood flow and brain metabolism

OBJECTIVES

In humans, neuronal processes related to brain development elevate the metabolic rate of brain tissue relative to the body during early childhood. This phenomenon has been hypothesized to contribute to slow somatic growth in preadolescent Homo sapiens. The uncoupling of the brain's metabolic rate from brain size during development complicates the study of the evolutionary emergence of these traits in the fossil record. Here, we extend a method previously developed to predict interspecific differences in cerebral blood flow (a correlate of cerebral glucose use) to predict ontogenetic changes in human brain metabolism.

MATERIALS AND METHODS

Radii of the carotid foramen from an ontogenetic series of modern human crania were used to predict blood flow rates through the internal carotid arteries (ICA), which were compared to empirically measured ICA flow and brain metabolism values.

RESULTS

Predictions of both absolute ICA blood flow rates and perfusion (ICA blood flow rates relative to brain size) generally match measured values in infancy and childhood. Maximum predicted ICA blood flow rates and perfusion were found to occur between ages 5 and 8, which roughly correspond to the age of maximum measured ICA blood flow rate and absolute and brain mass-specific rate of whole brain glucose uptake.

DISCUSSION

These findings suggest that, during human growth and development, the size of the carotid foramen corresponds well to blood flow requirements through the ICA, and the method tested here may provide new opportunities for studying developmental changes in brain metabolism using osteological samples, including fossil hominins.

Metabolism of Glycogen in Brain White Matter

Brain glycogen is a specialized energy buffer, rather than a conventional reserve. In the rodent optic nerve, a central white matter tract, it is located in astrocytes, where it is converted to lactate, which is then shuttled intercellularly from the astrocyte to the axon. This basic pathway was elucidated from non-physiological experiments in which the nerve was deprived of exogenous glucose. However, this shuttling also occurs under physiological conditions, when tissue energy demand is increased above baseline levels in the presence of normoglycemic concentrations of glucose. The signaling mechanism by which axons alert astrocytes to their increased energy requirement is likely to be elevated interstitial K⁺, the inevitable consequence of increased neuronal activity.

Approaches for testing hypotheses for the hypometric scaling of aerobic metabolic rate in animals

Hypometric scaling of aerobic metabolism [larger organisms have lower mass-specific metabolic rates (MR/g)] is nearly universal for interspecific comparisons among animals, yet we lack an agreed upon explanation for this pattern. If physiological constraints on the function of larger animals occur and limit MR/g, these should be observable as direct constraints on animals of extant species and/or as evolved responses to compensate for the proposed constraint. There is evidence for direct constraints and compensatory responses to O2 supply constraint in skin-breathing animals, but not in vertebrates with gas-exchange organs. The duration of food retention in the gut is longer for larger birds and mammals, consistent with a direct constraint on nutrient uptake across the gut wall, but there is little evidence for evolving compensatory responses to gut transport constraints in larger animals. Larger placental mammals (but not marsupials or birds) show evidence of greater challenges with heat dissipation, but there is little evidence for compensatory adaptations to enhance heat loss in larger endotherms, suggesting that metabolic rate (MR) more generally balances heat loss for thermoregulation in endotherms. Size-dependent patterns in many molecular, physiological, and morphological properties are consistent with size-dependent natural selection, such as stronger selection for neurolocomotor performance and growth rate in smaller animals and stronger selection for safety and longevity in larger animals. Hypometric scaling of MR very likely arises from different mechanisms in different taxa and conditions, consistent with the diversity of scaling slopes for MR.

6-Hydroxydopamine induces different mitochondrial bioenergetics response in brain regions of rat

Mitochondrial dysfunction has been demonstrated to have a central role in Parkinson Disease (PD) pathophysiology. Some studies have indicated that PD causes an impairment in mitochondrial bioenergetics; however, the effects of PD on brain-region specific bioenergetics was never investigated before. This study aimed to evaluate mitochondrial bioenergetics in different rat brain structures in an in vitro model of PD using 6-OHDA. Rat brain slices of hippocampus, striatum, and cortex were exposed to 6-OHDA (100 μM) for 1 h and mitochondrial bioenergetic parameters, peroxide production, lactate dehydrogenase (LDH) and citrate synthase (CS) activities were analyzed. Hippocampus slices exposed to 6-OHDA presented increased peroxide production but, no mitochondrial adaptive response against 6-OHDA damage. Cortex slices exposed to 6-OHDA presented increased oxygen flux related to oxidative phosphorylation and energetic pathways exchange demonstrated by the increase in LDH activity, suggesting a mitochondrial compensatory response. Striatum slices exposed to 6-OHDA presented a decrease of oxidative phosphorylation and decrease of oxygen flux related to ATP-synthase indicating an impairment in the respiratory chain. The co-incubation of 6-OHDA with n-acetylcysteine (NAC) abolished the effects of 6-OHDA on mitochondrial function in all brain regions tested, indicating that the increased reactive oxygen species (ROS) production is responsible for the alterations observed in mitochondrial bioenergetics. The present results indicate a brain-region specific response against 6-OHDA, providing new insights into brain mitochondrial bioenergetic function in PD. These findings may contribute to the development of future therapies with a target on energy metabolism.

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.