An energy budget for signaling in the grey matter of the brain

Biomolecular Markers of Brain Aging

Characterized by the gradual loss of physiological integrity, impaired function, and increased susceptibility to death, aging is considered the primary risk factor for major human diseases, such as cancer, diabetes, cardiovascular disorders, and neurodegenerative diseases. The time-dependent accumulation of cellular damage is widely considered the general cause of aging. While the mechanism of normal aging is still unresolved, researchers have identified different markers of aging, including genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient-sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication. Theories of aging can be divided into two categories: (1) aging is a genetically programmed process, and (2) aging is a random process caused by gradual damage to the organism over time as a result of its vital activities. Aging affects the entire human body, and aging of the brain is undoubtedly different from all other organs, as neurons are highly differentiated postmitotic cells, and the lifespan of most neurons in the postnatal period is equal to the lifespan of the brain. In this chapter, we discuss the conserved mechanisms of aging that may underlie the changes observed in the aging brain, with a focus on mitochondrial function and oxidative stress, autophagy and protein turnover, insulin/IGF signaling, target of rapamycin (TOR) signaling, and sirtuin function.

Pathogenesis of Dementia

According to Alzheimer's Disease International, 55 million people worldwide are living with dementia. Dementia is a disorder that manifests as a set of related symptoms, which usually result from the brain being damaged by injury or disease. The symptoms involve progressive impairments in memory, thinking, and behavior, usually accompanied by emotional problems, difficulties with language, and decreased motivation. The most common variant of dementia is Alzheimer's disease with symptoms dominated by cognitive disorders, particularly memory loss, impaired personality, and judgmental disorders. So far, all attempts to treat dementias by removing their symptoms rather than their causes have failed. Therefore, in the presented narrative review, I will attempt to explain the etiology of dementia and Alzheimer's disease from the perspective of energy and cognitive metabolism dysfunction in an aging brain. I hope that this perspective, though perhaps too simplified, will bring us closer to the essence of aging-related neurodegenerative disorders and will soon allow us to develop new preventive/therapeutic strategies in our struggle with dementia, Alzheimer's disease, and Parkinson's disease.

Brain capillary pericytes are metabolic sentinels that control blood flow through a KATP channel-dependent energy switch

Despite the abundance of capillary thin-strand pericytes and their proximity to neurons and glia, little is known of the contributions of these cells to the control of brain hemodynamics. We demonstrate that the pharmacological activation of thin-strand pericyte KATP channels profoundly hyperpolarizes these cells, dilates upstream penetrating arterioles and arteriole-proximate capillaries, and increases capillary blood flow. Focal stimulation of pericytes with a KATP channel agonist is sufficient to evoke this response, mediated via KIR2.1 channel-dependent retrograde propagation of hyperpolarizing signals, whereas genetic inactivation of pericyte KATP channels eliminates these effects. Critically, we show that decreasing extracellular glucose to less than 1 mM or inhibiting glucose uptake by blocking GLUT1 transporters in vivo flips a mechanistic energy switch driving rapid KATP-mediated pericyte hyperpolarization to increase local blood flow. Together, our findings recast capillary pericytes as metabolic sentinels that respond to local energy deficits by increasing blood flow to neurons to prevent energetic shortfalls.

Astrocyte L-Lactate Signaling in the ACC Regulates Visceral Pain Aversive Memory in Rats

Pain involves both sensory and affective elements. An aspect of the affective dimension of pain is its sustained unpleasantness, characterized by emotional feelings. Pain results from interactions between memory, attentional, and affective brain circuitry, and it has attracted enormous interest in pain research. However, the brain targets and signaling mechanism involved in pain remain elusive. Using a conditioned place avoidance (CPA) paradigm, we show that colorectal distention (CRD magnitude ≤ 35 mmHg, a subthreshold for pain) paired with a distinct environment can cause significant aversion to a location associated with pain-related insults in rats. We show a substantial increase in the L-lactate concentration in the anterior cingulate cortex (ACC) following CPA training. Local exogenous infusion of lactate into the ACC enhances aversive memory and induces the expression of the memory-related plasticity genes pCREB, CREB, and Erk1/2. The pharmacological experiments revealed that the glycogen phosphorylation inhibitor 1,4-dideoxy-1,4-imino-D-arabinitol (DAB) impairs memory consolidation. Furthermore, short-term Gi pathway activation of ACC astrocytes before CPA training significantly decreases the lactate level and suppresses pain-related aversive learning. The effects were reversed by the local infusion of lactate into the ACC. Our study demonstrates that lactate is released from astrocytes in vivo following visceral pain-related aversive learning and memory retrieval and induces the expression of the plasticity-related immediate early genes CREB, pCREB, and Erk1/2 in the ACC. Chronic visceral pain is an important factor in the pathophysiology of irritable bowel syndrome (IBS). The current study provides evidence that astrocytic activity in the ACC is required for visceral pain-related aversive learning and memory.

Synapse integrity and function: Dependence on protein synthesis and identification of potential failure points

Synaptic integrity and function depend on myriad proteins - labile molecules with finite lifetimes that need to be continually replaced with freshly synthesized copies. Here we describe experiments designed to expose synaptic (and neuronal) properties and functions that are particularly sensitive to disruptions in protein supply, identify proteins lost early upon such disruptions, and uncover potential, yet currently underappreciated failure points. We report here that acute suppressions of protein synthesis are followed within hours by reductions in spontaneous network activity levels, impaired oxidative phosphorylation and mitochondrial function, and, importantly, destabilization and loss of both excitatory and inhibitory postsynaptic specializations. Conversely, gross impairments in presynaptic vesicle recycling occur over longer time scales (days), as does overt cell death. Proteomic analysis identified groups of potentially essential 'early-lost' proteins including regulators of synapse stability, proteins related to bioenergetics, fatty acid and lipid metabolism, and, unexpectedly, numerous proteins involved in Alzheimer's disease pathology and amyloid beta processing. Collectively, these findings point to neuronal excitability, energy supply and synaptic stability as early-occurring failure points under conditions of compromised supply of newly synthesized protein copies.

Artificial neural network applied to fragile X-associated tremor/ataxia syndrome stage diagnosis based on peripheral mitochondrial bioenergetics and brain imaging outcomes

No proven prognosis is available for the neurodegenerative disorder fragile X-associated tremor/ataxia syndrome (FXTAS). Artificial neural network analyses (ANN) were used to predict FXTAS progression using data from 127 adults (noncarriers and FMR1 premutation carriers with and without FXTAS) with five outcomes from brain MRI imaging and 22 peripheral bioenergetic outcomes from two cell types. Diagnosis accuracy by ANN predictions ranged from 41.7 to 86.3% (depending on the algorithm used), and those misclassified usually presented a higher FXTAS stage. ANN prediction of FXTAS stages was based on a combination of two imaging findings (white matter hyperintensity and whole-brain volumes adjusted for intracranial volume) and four bioenergetic outcomes. Those at Stage 3 vs. 0-2 showed lower mitochondrial mass, higher oxidative stress, and an altered electron transfer consistent with mitochondrial unfolded protein response activation. Those at Stages 4-5 vs. 3 had higher oxidative stress and glycerol-3-phosphate-linked ATP production, suggesting that targeting mGPDH activity may prevent a worse prognosis. This was confirmed by the bioenergetic improvement of inhibiting mGPDH with metformin in affected fibroblasts. ANN supports the prospect of an unbiased molecular definition in diagnosing FXTAS stages while identifying potential targets for personalized medicine.

Efficient processing of natural scenes in visual cortex

Neural circuits in the periphery of the visual, auditory, and olfactory systems are believed to use limited resources efficiently to represent sensory information by adapting to the statistical structure of the natural environment. This "efficient coding" principle has been used to explain many aspects of early visual circuits including the distribution of photoreceptors, the mosaic geometry and center-surround structure of retinal receptive fields, the excess OFF pathways relative to ON pathways, saccade statistics, and the structure of simple cell receptive fields in V1. We know less about the extent to which such adaptations may occur in deeper areas of cortex beyond V1. We thus review recent developments showing that the perception of visual textures, which depends on processing in V2 and beyond in mammals, is adapted in rats and humans to the multi-point statistics of luminance in natural scenes. These results suggest that central circuits in the visual brain are adapted for seeing key aspects of natural scenes. We conclude by discussing how adaptation to natural temporal statistics may aid in learning and representing visual objects, and propose two challenges for the future: (1) explaining the distribution of shape sensitivity in the ventral visual stream from the statistics of object shape in natural images, and (2) explaining cell types of the vertebrate retina in terms of feature detectors that are adapted to the spatio-temporal structures of natural stimuli. We also discuss how new methods based on machine learning may complement the normative, principles-based approach to theoretical neuroscience.

How axon and dendrite branching are guided by time, energy, and spatial constraints

Neurons are connected by complex branching processes-axons and dendrites-that process information for organisms to respond to their environment. Classifying neurons according to differences in structure or function is a fundamental part of neuroscience. Here, by constructing biophysical theory and testing against empirical measures of branching structure, we develop a general model that establishes a correspondence between neuron structure and function as mediated by principles such as time or power minimization for information processing as well as spatial constraints for forming connections. We test our predictions for radius scale factors against those extracted from neuronal images, measured for species that range from insects to whales, including data from light and electron microscopy studies. Notably, our findings reveal that the branching of axons and peripheral nervous system neurons is mainly determined by time minimization, while dendritic branching is determined by power minimization. Our model also predicts a quarter-power scaling relationship between conduction time delay and body size.

Different Features of a Metabolic Connectivity Map and the Granger Causality Method in Revealing Directed Dopamine Pathways: A Study Based on Integrated PET/MR Imaging

BACKGROUND AND PURPOSE

Exploring the directionality of neural information in the brain is important for understanding brain mechanisms and neurodisease development. Granger causality analysis and the metabolic connectivity map can be used to investigate directional transmission of information between brain regions, but their differences in depicting functional effective connectivity are not clear.

MATERIALS AND METHODS

Using the Monash rs-PET/MR imaging data set, we conducted Granger causality and metabolic connectivity map analyses of the dopamine reward circuit in the brain. The dopamine reward circuit is a well-known system consisting primarily of the bilateral orbital frontal cortex, caudate, nucleus accumbens, thalamus, and substantia nigra. We validated these circuit pathways using Granger causality and the metabolic connectivity map for identifying effective connectivities against a priori knowledge by testing the significance of directed pathways (P < .05, false discovery rate-corrected).

RESULTS

We found 3 types of effective connectivities in the dopamine reward circuit: long-range, neighborhood, and symmetric. Granger causality analysis revealed long-range connections in the orbital frontal cortex-caudate and orbital frontal cortex-nucleus accumbens regions. Metabolic connectivity map analysis revealed neighborhood connections in the nucleus accumbens-caudate, substantia nigra-thalamus, and thalamus-caudate regions. Metabolic connectivity map analysis also found symmetric connections in each of the bilateral nucleus accumbens, caudate, thalamus, and orbital frontal cortex-caudate regions. Different patterns in directional networks of the dopamine reward circuit were revealed by Granger causality and metabolic connectivity map analyses.

CONCLUSIONS

Granger causality analysis primarily identified bidirectional cortico-nucleus connections, while the metabolic connectivity map primarily identified direct connections among neighborhood and symmetric regions. The results of this study indicated that investigations of effective connectivities should use an appropriate analysis method depending on the purpose of the study.

A dynamic spike threshold with correlated noise predicts observed patterns of negative interval correlations in neuronal spike trains

Negative correlations in the sequential evolution of interspike intervals (ISIs) are a signature of memory in neuronal spike-trains. They provide coding benefits including firing-rate stabilization, improved detectability of weak sensory signals, and enhanced transmission of information by improving signal-to-noise ratio. Primary electrosensory afferent spike-trains in weakly electric fish fall into two categories based on the pattern of ISI correlations: non-bursting units have negative correlations which remain negative but decay to zero with increasing lags (Type I ISI correlations), and bursting units have oscillatory (alternating sign) correlation which damp to zero with increasing lags (Type II ISI correlations). Here, we predict and match observed ISI correlations in these afferents using a stochastic dynamic threshold model. We determine the ISI correlation function as a function of an arbitrary discrete noise correlation function [Formula: see text], where k is a multiple of the mean ISI. The function permits forward and inverse calculations of the correlation function. Both types of correlation functions can be generated by adding colored noise to the spike threshold with Type I correlations generated with slow noise and Type II correlations generated with fast noise. A first-order autoregressive (AR) process with a single parameter is sufficient to predict and accurately match both types of afferent ISI correlation functions, with the type being determined by the sign of the AR parameter. The predicted and experimentally observed correlations are in geometric progression. The theory predicts that the limiting sum of ISI correlations is [Formula: see text] yielding a perfect DC-block in the power spectrum of the spike train. Observed ISI correlations from afferents have a limiting sum that is slightly larger at [Formula: see text] ([Formula: see text]). We conclude that the underlying process for generating ISIs may be a simple combination of low-order AR and moving average processes and discuss the results from the perspective of optimal coding.

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

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

Predictive coding is a consequence of energy efficiency in recurrent neural networks

Predictive coding is a promising framework for understanding brain function. It postulates that the brain continuously inhibits predictable sensory input, ensuring preferential processing of surprising elements. A central aspect of this view is its hierarchical connectivity, involving recurrent message passing between excitatory bottom-up signals and inhibitory top-down feedback. Here we use computational modeling to demonstrate that such architectural hardwiring is not necessary. Rather, predictive coding is shown to emerge as a consequence of energy efficiency. When training recurrent neural networks to minimize their energy consumption while operating in predictive environments, the networks self-organize into prediction and error units with appropriate inhibitory and excitatory interconnections and learn to inhibit predictable sensory input. Moving beyond the view of purely top-down-driven predictions, we demonstrate, via virtual lesioning experiments, that networks perform predictions on two timescales: fast lateral predictions among sensory units and slower prediction cycles that integrate evidence over time.

How cytoskeletal proteins regulate mitochondrial energetics in cell physiology and diseases

Mitochondria are ubiquitous organelles that play a pivotal role in the supply of energy through the production of adenosine triphosphate in all eukaryotic cells. The importance of mitochondria in cells is demonstrated in the poor survival outcomes observed in patients with defects in mitochondrial gene or RNA expression. Studies have identified that mitochondria are influenced by the cell's cytoskeletal environment. This is evident in pathological conditions such as cardiomyopathy where the cytoskeleton is in disarray and leads to alterations in mitochondrial oxygen consumption and electron transport. In cancer, reorganization of the actin cytoskeleton is critical for trans-differentiation of epithelial-like cells into motile mesenchymal-like cells that promotes cancer progression. The cytoskeleton is critical to the shape and elongation of neurons, facilitating communication during development and nerve signalling. Although it is recognized that cytoskeletal proteins physically tether mitochondria, it is not well understood how cytoskeletal proteins alter mitochondrial function. Since end-stage disease frequently involves poor energy production, understanding the role of the cytoskeleton in the progression of chronic pathology may enable the development of therapeutics to improve energy production and consumption and slow disease progression.

This article is part of the theme issue ‘The cardiomyocyte: new revelations on the interplay between architecture and function in growth, health, and disease’.

Inhibition of microRNA-200c preserves astrocyte sirtuin-1 and mitofusin-2, and protects against hippocampal neurodegeneration following global cerebral ischemia in mice

Memory impairment remains a leading disability in survivors of global cerebral ischemia, occurring secondary to delayed neurodegeneration of hippocampal cornu ammonis-1 (CA1) neurons. MicroRNA-200c (miR-200c) is induced following ischemic stress and we have previously demonstrated that pre-treatment with anti-miR-200c is protective against embolic stroke in mice. In the present study we assessed the role of miR-200c on CA1 neurodegeneration, sirtuin-1 (SIRT1), and mitochondrial dynamic protein expression in a mouse model of transient global cerebral ischemia and in vitro in primary mouse astrocyte cultures after simulated ischemia. Mice were subjected to 10 min bilateral common carotid artery occlusion plus hypotension with 5% isoflurane. After 2 h recovery mice were treated with intravenous injection of either anti-miR-200c or mismatch control. Memory function was assessed by Barnes maze at post-injury days 3 and 7. Mice were sacrificed at post-injury day 7 for assessment of brain cell-type specific expression of miR-200c, SIRT1, and the mitochondrial fusion proteins mitofusin-2 (MFN2) and OPA1 via complexed fluorescent in situ hybridization and fluorescent immunohistochemistry. Global cerebral ischemia induced significant loss of CA1 neurons, impaired memory performance and decreased expression of CA1 SIRT1, MFN2, and OPA1. Post-injury treatment with anti-miR-200c significantly improved survival, prevented CA1 neuronal loss, improved post-injury performance in Barnes maze, and was associated with increased post-injury expression of CA1 SIRT1 and MFN2 in astrocytes. In vitro, primary mouse astrocyte cultures pre-treated with miR-200c inhibitor prior to oxygen/glucose deprivation preserved expression of SIRT1 and MFN2, and decreased reactive oxygen species generation, whereas pre-treatment with miR-200c mimic had opposite effects that could be reversed by co-treatment with SIRT1 activator. These results suggest that miR-200c regulates astrocyte mitochondrial homeostasis via targeting SIRT1, and that CA1 astrocyte mitochondria and SIRT1 represent potential post-injury therapeutic targets to preserve cognitive function in survivors of global cerebral ischemia.

Longitudinal Changes in Global Cerebral Blood Flow in Cognitively Normal Older Adults: A Phase-Contrast MRI Study

BACKGROUND

Characterization of blood supply changes in older individuals is important in understanding brain aging and diseases. However, prior studies largely focused on cross-sectional design, thus change in cerebral blood flow (CBF) could not be assessed on an individual level.

PURPOSE

To evaluate longitudinal short-term changes in global CBF in cognitively normal older adults.

STUDY TYPE

Prospective, longitudinal, and cohort.

POPULATION

One-hundred twenty-seven cognitive-normal participants (mean age 69 ± 7 years, 47 males) underwent serial MRI with an average follow-up time of 2.1 years.

FIELD STRENGTH/SEQUENCE

3 T phase-contrast (PC), three-dimensional magnetization-prepared-rapid-acquisition-of-gradient-echo (MPRAGE) and fluid-attenuated inversion recovery (FLAIR) MRI.

ASSESSMENT

Total CBF was measured with PC MRI allowing assessment of quantitative flow in four major feeding arteries by a trained radiologist with >3 years' experience (O.K.). Brain volume was obtained from MPRAGE MRI and measured by T1-MultiAtlas MRICloud tool. The ratio between total CBF and brain volume yielded global CBF in mL/100 g/min. White matter hyperintensity (WMH) was measured automatically using a Bayesian probability approach on FLAIR.

STATISTICAL TESTS

Linear mixed effect model was used to simultaneously assess cross-sectional age-differences and longitudinal age-changes in CBF. Spearman rank correlation was used to evaluate the relationship between CBF change and WMH progression. A P-value of <0.05 (two-tailed) was considered significant.

RESULTS

Global CBF decreased with age at a longitudinal rate of -0.56 mL/100 g/min/year (95% confidence interval [CI]: -1.09, -0.03), compared to a cross-sectional rate of -0.26 mL/100 g/min/year (95% CI: -0.41, -0.11). Changes in CBF were significantly associated with progression of WMH (Spearman rank correlation r = -0.25), as those participants who had a more rapid CBF reduction had greater increases in WMH volumes and the relationship remained significant when adjusting for baseline vascular risk scores. Additionally, age-related changes in whole-brain volume were found to be -0.151%/year (95% CI: -0.186, -0.116).

DATA CONCLUSION

These findings suggest that brain aging in older adults is accompanied by a rapid longitudinal reduction in CBF, the rate of which is associated with white matter damage.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 2.

Energy-efficient network activity from disparate circuit parameters

Neural circuits can produce similar activity patterns from vastly different combinations of channel and synaptic conductances. These conductances are tuned for specific activity patterns but might also reflect additional constraints, such as metabolic cost or robustness to perturbations. How do such constraints influence the range of permissible conductances? Here we investigate how metabolic cost affects the parameters of neural circuits with similar activity in a model of the pyloric network of the crab Cancer borealis . We present a machine learning method that can identify a range of network models that generate activity patterns matching experimental data and find that neural circuits can consume largely different amounts of energy despite similar circuit activity. Furthermore, a reduced but still significant range of circuit parameters gives rise to energy-efficient circuits. We then examine the space of parameters of energy-efficient circuits and identify potential tuning strategies for low metabolic cost. Finally, we investigate the interaction between metabolic cost and temperature robustness. We show that metabolic cost can vary across temperatures but that robustness to temperature changes does not necessarily incur an increased metabolic cost. Our analyses show that despite metabolic efficiency and temperature robustness constraining circuit parameters, neural systems can generate functional, efficient, and robust network activity with widely disparate sets of conductances.

Differential role of neuronal glucose and PFKFB3 in memory formation during development

The consumption of glucose in the brain peaks during late childhood; yet, whether and how glucose metabolism is differentially regulated in the brain during childhood compared to adulthood remains to be understood. In particular, it remains to be determined how glucose metabolism is involved in behavioral activations such as learning. Here we show that, compared to adult, the juvenile rat hippocampus has significantly higher mRNA levels of several glucose metabolism enzymes belonging to all glucose metabolism pathways, as well as higher levels of the monocarboxylate transporters MCT1 and MCT4 and the glucose transporters endothelial-GLUT1 and GLUT3 proteins. Furthermore, relative to adults, long-term episodic memory formation in juvenile animals requires significantly higher rates of aerobic glycolysis and astrocytic-neuronal lactate coupling in the hippocampus. Only juvenile but not adult long-term memory formation recruits GLUT3, neuronal 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) and more efficiently engages glucose in the hippocampus. Hence, compared to adult, the juvenile hippocampus distinctively regulates glucose metabolism pathways, and formation of long-term memory in juveniles involves differential neuronal glucose metabolism mechanisms.

Contrast polarity-specific mapping improves efficiency of neuronal computation for collision detection

Neurons receive information through their synaptic inputs, but the functional significance of how those inputs are mapped on to a cell's dendrites remains unclear. We studied this question in a grasshopper visual neuron that tracks approaching objects and triggers escape behavior before an impending collision. In response to black approaching objects, the neuron receives OFF excitatory inputs that form a retinotopic map of the visual field onto compartmentalized, distal dendrites. Subsequent processing of these OFF inputs by active membrane conductances allows the neuron to discriminate the spatial coherence of such stimuli. In contrast, we show that ON excitatory synaptic inputs activated by white approaching objects map in a random manner onto a more proximal dendritic field of the same neuron. The lack of retinotopic synaptic arrangement results in the neuron's inability to discriminate the coherence of white approaching stimuli. Yet, the neuron retains the ability to discriminate stimulus coherence for checkered stimuli of mixed ON/OFF polarity. The coarser mapping and processing of ON stimuli thus has a minimal impact, while reducing the total energetic cost of the circuit. Further, we show that these differences in ON/OFF neuronal processing are behaviorally relevant, being tightly correlated with the animal's escape behavior to light and dark stimuli of variable coherence. Our results show that the synaptic mapping of excitatory inputs affects the fine stimulus discrimination ability of single neurons and document the resulting functional impact on behavior.

Baseline oxygen consumption decreases with cortical depth

The cerebral cortex is organized in cortical layers that differ in their cellular density, composition, and wiring. Cortical laminar architecture is also readily revealed by staining for cytochrome oxidase-the last enzyme in the respiratory electron transport chain located in the inner mitochondrial membrane. It has been hypothesized that a high-density band of cytochrome oxidase in cortical layer IV reflects higher oxygen consumption under baseline (unstimulated) conditions. Here, we tested the above hypothesis using direct measurements of the partial pressure of O2 (pO2) in cortical tissue by means of 2-photon phosphorescence lifetime microscopy (2PLM). We revisited our previously developed method for extraction of the cerebral metabolic rate of O2 (CMRO2) based on 2-photon pO2 measurements around diving arterioles and applied this method to estimate baseline CMRO2 in awake mice across cortical layers. To our surprise, our results revealed a decrease in baseline CMRO2 from layer I to layer IV. This decrease of CMRO2 with cortical depth was paralleled by an increase in tissue oxygenation. Higher baseline oxygenation and cytochrome density in layer IV may serve as an O2 reserve during surges of neuronal activity or certain metabolically active brain states rather than reflecting baseline energy needs. Our study provides to our knowledge the first quantification of microscopically resolved CMRO2 across cortical layers as a step towards better understanding of brain energy metabolism.

Low-Consumption Synaptic Devices Based on Gate-All-Around InAs Nanowire Field-Effect Transistors

In this work, an artificial electronic synaptic device based on gate-all-around InAs nanowire field-effect transistor is proposed and analyzed. The deposited oxide layer (In₂O₃) on the InAs nanowire surface serves as a charge trapping layer for information storage. The gate voltage pulse serves as stimuli of the presynaptic membrane, and the drain current and channel conductance are treated as post-synaptic current and weights of the postsynaptic membrane, respectively. At low gate voltages, the device simulates synaptic behaviors including short-term depression and long-term depression. By increasing the amplitude and quantity of gate voltage pulses, the transition from short-term depression to long-term potentiation can be achieved. The device exhibits a large memory window of over 1 V and a minimal energy consumption of 12.5 pJ per synaptic event. This work may pave the way for the development of miniaturized low-consumption synaptic devices and related neuromorphic systems.

Review of the Research Progress of Human Brain Oxygen Extraction Fraction by Magnetic Resonance Imaging

In recent years, the incidence of cerebrovascular diseases (CVD) is increasing, which seriously endangers human health. The study on hemodynamics of cerebrovascular disease can help us to understand, prevent, and treat the disease. As one of the important parameters of human cerebral hemodynamics and tissue metabolism, OEF (oxygen extraction fraction) is of great value in central nervous system diseases. The use of BOLD (blood oxygen level dependent) effect offers the possibility to study cerebral hemodynamic and metabolic characteristics by MRI (magnetic resonance imaging) measurements. Therefore, this paper reviews the hemodynamic parameters of brain tissue, discusses the principles and methods of quantitative BOLD-based MRI measurements of OEF, and discusses the advantages and disadvantages of each method.

Optimal noise level for coding with tightly balanced networks of spiking neurons in the presence of transmission delays

Neural circuits consist of many noisy, slow components, with individual neurons subject to ion channel noise, axonal propagation delays, and unreliable and slow synaptic transmission. This raises a fundamental question: how can reliable computation emerge from such unreliable components? A classic strategy is to simply average over a population of N weakly-coupled neurons to achieve errors that scale as [Formula: see text]. But more interestingly, recent work has introduced networks of leaky integrate-and-fire (LIF) neurons that achieve coding errors that scale superclassically as 1/N by combining the principles of predictive coding and fast and tight inhibitory-excitatory balance. However, spike transmission delays preclude such fast inhibition, and computational studies have observed that such delays can cause pathological synchronization that in turn destroys superclassical coding performance. Intriguingly, it has also been observed in simulations that noise can actually improve coding performance, and that there exists some optimal level of noise that minimizes coding error. However, we lack a quantitative theory that describes this fascinating interplay between delays, noise and neural coding performance in spiking networks. In this work, we elucidate the mechanisms underpinning this beneficial role of noise by deriving analytical expressions for coding error as a function of spike propagation delay and noise levels in predictive coding tight-balance networks of LIF neurons. Furthermore, we compute the minimal coding error and the associated optimal noise level, finding that they grow as power-laws with the delay. Our analysis reveals quantitatively how optimal levels of noise can rescue neural coding performance in spiking neural networks with delays by preventing the build up of pathological synchrony without overwhelming the overall spiking dynamics. This analysis can serve as a foundation for the further study of precise computation in the presence of noise and delays in efficient spiking neural circuits.

The Na+/K+ pump dominates control of glycolysis in hippocampal dentate granule cells

Cellular ATP that is consumed to perform energetically expensive tasks must be replenished by new ATP through the activation of metabolism. Neuronal stimulation, an energetically demanding process, transiently activates aerobic glycolysis, but the precise mechanism underlying this glycolysis activation has not been determined. We previously showed that neuronal glycolysis is correlated with Ca2+ influx, but is not activated by feedforward Ca2+ signaling (Díaz-García et al., 2021a). Since ATP-powered Na+ and Ca2+ pumping activities are increased following stimulation to restore ion gradients and are estimated to consume most neuronal ATP, we aimed to determine if they are coupled to neuronal glycolysis activation. By using two-photon imaging of fluorescent biosensors and dyes in dentate granule cell somas of acute mouse hippocampal slices, we observed that production of cytoplasmic NADH, a byproduct of glycolysis, is strongly coupled to changes in intracellular Na+, while intracellular Ca2+ could only increase NADH production if both forward Na+/Ca2+ exchange and Na+/K+ pump activity were intact. Additionally, antidromic stimulation-induced intracellular [Na+] increases were reduced >50% by blocking Ca2+ entry. These results indicate that neuronal glycolysis activation is predominantly a response to an increase in activity of the Na+/K+ pump, which is strongly potentiated by Na+ influx through the Na+/Ca2+ exchanger during extrusion of Ca2+ following stimulation.

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.

Physiology of PNS axons relies on glycolytic metabolism in myelinating Schwann cells

While lactate shuttle theory states that glial cells metabolize glucose into lactate to shuttle it to neurons, how glial cells support axonal metabolism and function remains unclear. Lactate production is a common occurrence following anaerobic glycolysis in muscles. However, several other cell types, including some stem cells, activated macrophages and tumor cells, can produce lactate in presence of oxygen and cellular respiration, using Pyruvate Kinase 2 (PKM2) to divert pyruvate to lactate dehydrogenase. We show here that PKM2 is also upregulated in myelinating Schwann cells (mSC) of mature mouse sciatic nerve versus postnatal immature nerve. Deletion of this isoform in PLP-expressing cells in mice leads to a deficit of lactate in mSC and in peripheral nerves. While the structure of myelin sheath was preserved, mutant mice developed a peripheral neuropathy. Peripheral nerve axons of mutant mice failed to maintain lactate homeostasis upon activity, resulting in an impaired production of mitochondrial ATP. Action potential propagation was not altered but axonal mitochondria transport was slowed down, muscle axon terminals retracted and motor neurons displayed cellular stress. Additional reduction of lactate availability through dichloroacetate treatment, which diverts pyruvate to mitochondrial oxidative phosphorylation, further aggravated motor dysfunction in mutant mice. Thus, lactate production through PKM2 enzyme and aerobic glycolysis is essential in mSC for the long-term maintenance of peripheral nerve axon physiology and function.

Modeling Reactive Oxygen Species-Induced Axonal Loss in Leber Hereditary Optic Neuropathy

Leber hereditary optic neuropathy (LHON) is a rare syndrome that results in vision loss. A necessary but not sufficient condition for its onset is the existence of known mitochondrial DNA mutations that affect complex I biomolecular structure. Cybrids with LHON mutations generate higher rates of reactive oxygen species (ROS). This study models how ROS, particularly H₂O₂, could signal and execute the axonal degeneration process that underlies LHON. We modeled and explored several hypotheses regarding the influence of H₂O₂ on the dynamics of propagation of axonal degeneration in LHON. Zonal oxidative stress, corresponding to H₂O₂ gradients, correlated with the morphology of injury exhibited in the LHON pathology. If the axonal membrane is highly permeable to H₂O₂ and oxidative stress induces larger production of H₂O₂, small injuries could trigger cascading failures of neighboring axons. The cellular interdependence created by H₂O₂ diffusion, and the gradients created by tissue variations in H₂O₂ production and scavenging, result in injury patterns and surviving axonal loss distributions similar to LHON tissue samples. Specifically, axonal degeneration starts in the temporal optic nerve, where larger groups of small diameter fibers are located and propagates from that region. These findings correlate well with clinical observations of central loss of visual field, visual acuity, and color vision in LHON, and may serve as an in silico platform for modeling the mechanism of action for new therapeutics.

Nanodiamond-Quantum Sensors Reveal Temperature Variation Associated to Hippocampal Neurons Firing

Temperature is one of the most relevant parameters for the regulation of intracellular processes. Measuring localized subcellular temperature gradients is fundamental for a deeper understanding of cell function, such as the genesis of action potentials, and cell metabolism. Notwithstanding several proposed techniques, at the moment detection of temperature fluctuations at the subcellular level still represents an ongoing challenge. Here, for the first time, temperature variations (1 °C) associated with potentiation and inhibition of neuronal firing is detected, by exploiting a nanoscale thermometer based on optically detected magnetic resonance in nanodiamonds. The results demonstrate that nitrogen-vacancy centers in nanodiamonds provide a tool for assessing various levels of neuronal spiking activity, since they are suitable for monitoring different temperature variations, respectively, associated with the spontaneous firing of hippocampal neurons, the disinhibition of GABAergic transmission and the silencing of the network. Conjugated with the high sensitivity of this technique (in perspective sensitive to &lt; 0.1 °C variations), nanodiamonds pave the way to a systematic study of the generation of localized temperature gradients under physiological and pathological conditions. Furthermore, they prompt further studies explaining in detail the physiological mechanism originating this effect.

A Survey of the Metabolic Landscape of the Developing Cerebellum at Single-Cell Resolution

The use of cell-culture models to investigate development and disease of the cerebellum is a recent advance, facilitated by the discovery that patterning of precursors is capable of giving rise to cells with specific neuronal identity. Pluripotent stem cell-derived organoids, which exhibit self-organisational characteristics reminiscent of early cerebellar tissue, present a number of challenges including recapitulation of conditions resembling the mature brain. An understanding of the processes driving fetal and postnatal maturation is required to reproduce these conditions in vitro and advance the capability of the system to model adult-onset disease. A key tool for achieving this is single-cell RNA sequencing, which enables visualisation of key transcriptional features of subpopulations comprising tissues. Here, we explore and compare available single-cell RNA sequencing data derived from the developing human cerebellum and its synthetic, in vitro counterpart (stem cell-derived cerebellar organoids). We focus on performing a qualitative assessment of the expression of key metabolic pathway genes, given recent findings exemplifying tissue-specific metabolic activity, including hypoxia and metabolic shifts associated with neuronal expansion. Signatures indicative of known cell type-specific metabolic differences, such as the astrocyte-neuron lactate shuttle and glutamate-glutamine cycle were evident at a transcriptional level. Cerebellar tissue and cerebellar organoids showed a number of behavioural similarities, including HIF1 signalling, which may serve to drive expansion of granule cell progenitors in both settings. We further highlight numerous differences between cultured organoids and native tissue which may provide clarity on the state of metabolic state following differentiation of organoids, providing the future framework to test and further hypotheses regarding promoting maturation. Overall, this analysis provides insight into understanding the state of in vitro models of the cerebellum, a critical factor required for modelling susceptibility of various cell types to cerebellar disease.

The global neuronal workspace as a broadcasting network

A new strategy for moving forward in the characterization of the global neuronal workspace (GNW) is proposed. According to Dehaene, Changeux, and colleagues (Dehaene, 2014, pp. 304, 312; Dehaene & Changeux, 2004, 2005), broadcasting is the main function of the GNW. However, the dynamic network properties described by recent graph theoretic GNW models are consistent with many large-scale communication processes that are different from broadcasting. We propose to apply a different graph theoretic approach, originally developed for optimizing information dissemination in communication networks, which can be used to identify the pattern of frequency and phase-specific directed functional connections that the GNW would exhibit only if it were a broadcasting network.

Cross-attractor repertoire provides new perspective on structure-function relationship in the brain

The brain exhibits complex intrinsic dynamics, i.e., spontaneously arising activity patterns without any external inputs or tasks. Such intrinsic dynamics and their alteration are thought to play crucial roles in typical as well as atypical cognitive functioning. Linking the ever-changing intrinsic dynamics to the rather static anatomy is a challenging endeavor. Dynamical systems models are important tools for understanding how structure and function are linked in the brain. Here, we provide a novel modeling framework to examine how functional connectivity depends on structural connectivity in the brain. Existing modeling frameworks typically focus on noise-driven (or stochastic) dynamics near a single attractor. Complementing existing approaches, we examine deterministic features of the distribution of attractors, in particular, how regional states are correlated across all attractors - cross-attractor coordination. We found that cross-attractor coordination between brain regions better predicts human functional connectivity than noise-driven single-attractor dynamics. Importantly, cross-attractor coordination better accounts for the nonlinear dependency of functional connectivity on structural connectivity. Our findings suggest that functional connectivity patterns in the brain may reflect transitions between attractors, which impose an energy cost. The framework may be used to predict transitions and energy costs associated with experimental or clinical interventions.

Ca2+ channels couple spiking to mitochondrial metabolism in substantia nigra dopaminergic neurons

How do neurons match generation of adenosine triphosphate by mitochondria to the bioenergetic demands of regenerative activity? Although the subject of speculation, this coupling is still poorly understood, particularly in neurons that are tonically active. To help fill this gap, pacemaking substantia nigra dopaminergic neurons were studied using a combination of optical, electrophysiological, and molecular approaches. In these neurons, spike-activated calcium (Ca2+) entry through Cav1 channels triggered Ca2+ release from the endoplasmic reticulum, which stimulated mitochondrial oxidative phosphorylation through two complementary Ca2+-dependent mechanisms: one mediated by the mitochondrial uniporter and another by the malate-aspartate shuttle. Disrupting either mechanism impaired the ability of dopaminergic neurons to sustain spike activity. While this feedforward control helps dopaminergic neurons meet the bioenergetic demands associated with sustained spiking, it is also responsible for their elevated oxidant stress and possibly to their decline with aging and disease.

Active neural coordination of motor behaviors with internal states

The brain continuously coordinates skeletomuscular movements with internal physiological states like arousal, but how is this coordination achieved? One possibility is that the brain simply reacts to changes in external and/or internal signals. Another possibility is that it is actively coordinating both external and internal activities. We used functional ultrasound imaging to capture a large medial section of the brain, including multiple cortical and subcortical areas, in marmoset monkeys while monitoring their spontaneous movements and cardiac activity. By analyzing the causal ordering of these different time series, we found that information flowing from the brain to movements and heart-rate fluctuations were significantly greater than in the opposite direction. The brain areas involved in this external versus internal coordination were spatially distinct, but also extensively interconnected. Temporally, the brain alternated between network states for this regulation. These findings suggest that the brain's dynamics actively and efficiently coordinate motor behavior with internal physiology.

NLRP3 inflammasomes: A potential target to improve mitochondrial biogenesis in Parkinson's disease

Parkinson's disease (PD) is a common neurodegenerative condition for which no approved treatment exists to prevent collective neuronal death. There is ample evidence that mitochondrial dysfunction, reactive oxygen species (ROS), and associated caspase activity underlie the pathology observed. Neurons rely on mitochondrial activity since they have such high energy consumption. Therefore, it is not surprising that mitochondrial alterations favour neuronal degeneration. In particular, mitochondrial dysregulation contributes to PD, based on the observation that mitochondrial toxins can cause parkinsonism in humans and animal models. Also, it is known that inflammatory cytokine-mediated neuroinflammation is the key pathogenic mechanism in neuronal loss. In recent years, the research has focussed on mitochondria being the platform for nucleotide-binding oligomerization domain-like receptors 3 (NLRP3) inflammasome activation. Mitochondrial dysfunction and NLRP3 activation are emerging as critical players in inducing and sustaining neuroinflammation. Moreover, mitochondrial-derived ROS and mitochondrial DNA (mtDNA) could serve as the priming signal for forming inflammasome complexes responsible for the activation, maturation, and release of pro-inflammatory cytokines, including interleukin-1(IL-1) and interleukin-18 (IL-18). The current review takes a more comprehensive approach to elucidating the link between mitochondrial dysfunction and aberrant NLRP3 activation in PD. In addition, we focus on some inhibitors of NLRP3 inflammatory pathways to alleviate the progression of PD.

Mitochondrial Alterations in Neurons Derived from the Murine AppNL-F Knock-In Model of Alzheimer’s Disease

Background: Alzheimer’s disease (AD) research has relied on mouse models overexpressing human mutant A βPP; however, newer generation knock-in models allow for physiological expression of amyloid-β protein precursor (AβPP) containing familial AD mutations where murine AβPP is edited with a humanized amyloid-β (Aβ) sequence. The AppNL-F mouse model has shown substantial similarities to AD brains developing late onset cognitive impairment. Objective: In this study, we aimed to characterize mature primary cortical neurons derived from homozygous AppNL-F embryos, especially to identify early mitochondrial alterations in this model. Methods: Primary cultures of AppNL-F neurons kept in culture for 12–15 days were used to measure Aβ levels, secretase activity, mitochondrial functions, mitochondrial-ER contacts, synaptic function, and cell death. Results: We detected higher levels of Aβ42 released from AppNL-F neurons as compared to wild-type neurons. AppNL-F neurons, also displayed an increased Aβ42/Aβ40 ratio, similar to adult AppNL-F mouse brain. Interestingly, we found an upregulation in mitochondrial oxygen consumption with concomitant downregulation in glycolytic reserve. Furthermore, AppNL-F neurons were more susceptible to cell death triggered by mitochondrial electron transport chain inhibition. Juxtaposition between ER and mitochondria was found to be substantially upregulated, which may account for upregulated mitochondrial-derived ATP production. However, anterograde mitochondrial movement was severely impaired in this model along with loss in synaptic vesicle protein and impairment in pre- and post-synaptic function. Conclusion: We show that widespread mitochondrial alterations can be detected in AppNL-F neurons in vitro, where amyloid plaque deposition does not occur, suggesting soluble and oligomeric Aβ-species being responsible for these alterations.

Mitochondrial Dysfunction in Spinal Muscular Atrophy

Spinal muscular atrophy (SMA) is a devastating neuromuscular disorder caused by recessive mutations in the SMN1 gene, globally affecting ~8-14 newborns per 100,000. The severity of the disease depends on the residual levels of functional survival of motor neuron protein, SMN. SMN is a ubiquitously expressed RNA binding protein involved in a plethora of cellular processes. In this review, we discuss the effects of SMN loss on mitochondrial functions in the neuronal and muscular systems that are the most affected in patients with spinal muscular atrophy. Our aim is to highlight how mitochondrial defects may contribute to disease progression and how restoring mitochondrial functionality may be a promising approach to develop new therapies. We also collected from previous studies a list of transcripts encoding mitochondrial proteins affected in various SMA models. Moreover, we speculate that in adulthood, when motor neurons require only very low SMN levels, the natural deterioration of mitochondria associated with aging may be a crucial triggering factor for adult spinal muscular atrophy, and this requires particular attention for therapeutic strategies.

Physical exercise and mitochondrial function: New therapeutic interventions for psychiatric and neurodegenerative disorders

Psychiatric and neurodegenerative diseases, including major depression disorder (MDD), bipolar disorder, and Alzheimer's disease, are a burden to society. Deficits of adult hippocampal neurogenesis (AHN) have been widely considered the main hallmark of psychiatric diseases as well as neurodegeneration. Herein, exploring applicable targets for improving hippocampal neural plasticity could provide a breakthrough for the development of new treatments. Emerging evidence indicates the broad functions of mitochondria in regulating cellular behaviors of neural stem cells, neural progenitors, and mature neurons in adulthood could offer multiple neural plasticities for behavioral modulation. Normalizing mitochondrial functions could be a new direction for neural plasticity enhancement. Exercise, a highly encouraged integrative method for preventing disease, has been indicated to be an effective pathway to improving both mitochondrial functions and AHN. Herein, the relative mechanisms of mitochondria in regulating neurogenesis and its effects in linking the effects of exercise to neurological diseases requires a systematic summary. In this review, we have assessed the relationship between mitochondrial functions and AHN to see whether mitochondria can be potential targets for treating neurological diseases. Moreover, as for one of well-established alternative therapeutic approaches, we summarized the evidence to show the underlying mechanisms of exercise to improve mitochondrial functions and AHN.

Mitochondrial Ca2+ uptake by the MCU facilitates pyramidal neuron excitability and metabolism during action potential firing

Neuronal activation is fundamental to information processing by the brain and requires mitochondrial energy metabolism. Mitochondrial Ca²⁺ uptake by the mitochondrial Ca²⁺ uniporter (MCU) has long been implicated in the control of energy metabolism and intracellular Ca²⁺ signalling, but its importance to neuronal function in the brain remains unclear. Here, we used in situ electrophysiology and two-photon imaging of mitochondrial Ca²⁺, cytosolic Ca²⁺, and NAD(P)H to test the relevance of MCU activation to pyramidal neuron Ca²⁺ signalling and energy metabolism during action potential firing. We demonstrate that mitochondrial Ca²⁺ uptake by the MCU is tuned to enhanced firing rate and the strength of this relationship varied between neurons of discrete brain regions. MCU activation promoted electron transport chain activity and chemical reduction of NAD⁺ to NADH. Moreover, Ca²⁺ buffering by mitochondria attenuated cytosolic Ca²⁺ signals and thereby reduced the coupling between activity and the slow afterhyperpolarization, a ubiquitous regulator of excitability. Collectively, we demonstrate that the MCU is engaged by accelerated spike frequency to facilitate neuronal activity through simultaneous control of energy metabolism and excitability. As such, the MCU is situated to promote brain functions associated with high frequency signalling and may represent a target for controlling excessive neuronal activity.

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.

Neural consequences of chronic sleep disruption

Recent studies in both humans and animal models call into question the completeness of recovery after chronic sleep disruption. Studies in humans have identified cognitive domains particularly vulnerable to delayed or incomplete recovery after chronic sleep disruption, including sustained vigilance and episodic memory. These findings, in turn, provide a focus for animal model studies to critically test the lasting impact of sleep loss on the brain. Here, we summarize the human response to sleep disruption and then discuss recent findings in animal models examining recovery responses in circuits pertinent to vigilance and memory. We then propose pathways of injury common to various forms of sleep disruption and consider the implications of this injury in aging and in neurodegenerative 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.

Abnormal brain oxygen homeostasis in an animal model of liver disease

Background & Aims

Increased plasma ammonia concentration and consequent disruption of brain energy metabolism could underpin the pathogenesis of hepatic encephalopathy (HE). Brain energy homeostasis relies on effective maintenance of brain oxygenation, and dysregulation impairs neuronal function leading to cognitive impairment. We hypothesised that HE is associated with reduced brain oxygenation and we explored the potential role of ammonia as an underlying pathophysiological factor.

Methods

In a rat model of chronic liver disease with minimal HE (mHE; bile duct ligation [BDL]), brain tissue oxygen measurement, and proton magnetic resonance spectroscopy were used to investigate how hyperammonaemia impacts oxygenation and metabolic substrate availability in the central nervous system. Ornithine phenylacetate (OP, OCR-002; Ocera Therapeutics, CA, USA) was used as an experimental treatment to reduce plasma ammonia concentration.

Results

In BDL animals, glucose, lactate, and tissue oxygen concentration in the cerebral cortex were significantly lower than those in sham-operated controls. OP treatment corrected the hyperammonaemia and restored brain tissue oxygen. Although BDL animals were hypotensive, cortical tissue oxygen concentration was significantly improved by treatments that increased arterial blood pressure. Cerebrovascular reactivity to exogenously applied CO2 was found to be normal in BDL animals.

Conclusions

These data suggest that hyperammonaemia significantly decreases cortical oxygenation, potentially compromising brain energy metabolism. These findings have potential clinical implications for the treatment of patients with mHE.

Lay summary

Brain dysfunction is a serious complication of cirrhosis and affects approximately 30% of these patients; however, its treatment continues to be an unmet clinical need. This study shows that oxygen concentration in the brain of an animal model of cirrhosis is markedly reduced. Low arterial blood pressure and increased ammonia (a neurotoxin that accumulates in patients with liver failure) are shown to be the main underlying causes. Experimental correction of these abnormalities restored oxygen concentration in the brain, suggesting potential therapeutic avenues to explore.

Chronic AMPK Activation Reduces the Expression and Alters Distribution of Synaptic Proteins in Neuronal SH-SY5Y Cells

Neuronal growth and synaptic function are dependent on precise protein production and turnover at the synapse. AMPK-activated protein kinase (AMPK) represents a metabolic node involved in energy sensing and in regulating synaptic protein homeostasis. However, there is ambiguity surrounding the role of AMPK in regulating neuronal growth and health. This study examined the effect of chronic AMPK activation on markers of synaptic function and growth. Retinoic-acid-differentiated SH-SY5Y human neuroblastoma cells were treated with A-769662 (100 nM) or Compound C (30 nM) for 1, 3, or 5 days before AMPK, mTORC1, and markers for synapse function were examined. Cell morphology, neuronal marker content, and location were quantified after 5 days of treatment. AMPK phosphorylation was maintained throughout all 5 days of treatment with A-769662 and resulted in chronic mTORC1 inhibition. Lower total, soma, and neuritic neuronal marker contents were observed following 5 d of AMPK activation. Neurite protein abundance and distribution was lower following 5 days of A-769662 treatment. Our data suggest that chronic AMPK activation impacts synaptic protein content and reduces neurite protein abundance and distribution. These results highlight a distinct role that metabolism plays on markers of synapse health and function.

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.

Astrocyte energy and neurotransmitter metabolism in Alzheimer's disease: integration of the glutamate/GABA-glutamine cycle

Astrocytes contribute to the complex cellular pathology of Alzheimer's disease (AD). Neurons and astrocytes function in close collaboration through neurotransmitter recycling, collectively known as the glutamate/GABA-glutamine cycle, which is essential to sustain neurotransmission. Neurotransmitter recycling is intimately linked to astrocyte energy metabolism. In the course of AD, astrocytes undergo extensive metabolic remodeling, which may profoundly affect the glutamate/GABA-glutamine cycle. The consequences of altered astrocyte function and metabolism in relation to neurotransmitter recycling are yet to be comprehended. Metabolic alterations of astrocytes in AD deprive neurons of metabolic support, thereby contributing to synaptic dysfunction and neurodegeneration. In addition, several astrocyte-specific components of the glutamate/GABA-glutamine cycle, including glutamine synthesis and synaptic neurotransmitter uptake, are perturbed in AD. Integration of the complex astrocyte biology within the context of AD is essential for understanding the fundamental mechanisms of the disease, while restoring astrocyte metabolism may serve as an approach to arrest or even revert clinical progression of AD.

Early alterations in brain glucose metabolism and vascular function in a transgenic rat model of Alzheimer's disease

Alteration in brain metabolism predates clinical onset of Alzheimer's Disease (AD). Realizing its potential as an early diagnostic marker, however, requires understanding how early AD metabolic dysregulation manifests on non-invasive brain imaging. We presently utilized magnetic resonance imaging and spectroscopy to map glucose and ketone metabolic profiles and image cerebrovascular function in a rat model of early stage AD - 9-month-old TgF344-AD (TgAD) rats - and their age-matched non-transgenic (nTg) littermates. Compared to the nTg rats, TgAD rats displayed attenuation in global cerebral and hippocampal vasoreactivity to hypercapnia, by 49±17% and 58±19%, respectively, while their functional hyperemia to somatosensory stimulation diminished by 69±5%. To assess brain glucose uptake, rats were fasted overnight and then challenged with an intravenous infusion of 2-deoxy-D-glucose (2DG). Compared to their non-transgenic littermates, TgAD rats exhibited 99±10% and 52±5% smaller glucose uptake in the entorhinal cortex and the hippocampus, respectively. Moreover, hippocampal glucose uptake reduction in male TgAD rats compared to the nTg was 54±36% greater than the reduction seen in female TgAD rats. TgAD rats also showed a 59±42% increase in total choline level in the hippocampus, suggesting increased membrane turnover. In combination with our earlier findings of impaired electrophysiological metrics at this early stage of AD pathology progression, our findings suggest that subtle neuronal function alterations that would be difficult to assess in a clinical population may be accompanied by MRI-detectable changes in brain glucose metabolism and cerebrovascular function.

Supplementation of Regular Diet With Medium-Chain Triglycerides for Procognitive Effects: A Narrative Review

It is now widely accepted that ketosis (a physiological state characterized by elevated plasma ketone body levels) possesses a wide range of neuroprotective effects. There is a growing interest in the use of ketogenic supplements, including medium-chain triglycerides (MCT), to achieve intermittent ketosis without adhering to a strict ketogenic diet. MCT supplementation is an inexpensive and simple ketogenic intervention, proven to benefit both individuals with normal cognition and those suffering from mild cognitive impairment, Alzheimer's disease, and other cognitive disorders. The commonly accepted paradigm underlying MCT supplementation trials is that the benefits stem from ketogenesis and that MCT supplementation is safe. However, medium-chain fatty acids (MCFAs) may also exert effects in the brain directly. Moreover, MCFAs, long-chain fatty acids, and glucose participate in mutually intertwined metabolic pathways. Therefore, the metabolic effects must be considered if the desired procognitive effects require administering MCT in doses larger than 1 g/kg. This review summarizes currently available research on the procognitive effects of using MCTs as a supplement to regular feed/diet without concomitant reduction of carbohydrate intake and focuses on the revealed mechanisms linked to particular MCT metabolites (ketone bodies, MCFAs), highlighting open questions and potential considerations.

Critical Role of Neuronal Vps35 in Blood Vessel Branching and Maturation in Developing Mouse Brain

Vps35 (vacuolar protein sorting 35), a key component of retromer, plays a crucial role in selective retrieval of transmembrane proteins from endosomes to trans-Golgi networks. Dysfunctional Vps35/retromer is a risk factor for the development of neurodegenerative diseases. Vps35 is highly expressed in developing pyramidal neurons, both in the mouse neocortex and hippocampus, Although embryonic neuronal Vps35’s function in promoting neuronal terminal differentiation and survival is evident, it remains unclear whether and how neuronal Vps35 communicates with other types of brain cells, such as blood vessels (BVs), which are essential for supplying nutrients to neurons. Dysfunctional BVs contribute to the pathogenesis of various neurodegenerative disorders. Here, we provide evidence for embryonic neuronal Vps35 as critical for BV branching and maturation in the developing mouse brain. Selectively knocking out (KO) Vps35 in mouse embryonic, not postnatal, neurons results in reductions in BV branching and density, arteriole diameter, and BV-associated pericytes and microglia but an increase in BV-associated reactive astrocytes. Deletion of microglia by PLX3397 enhances these BV deficits in mutant mice. These results reveal the function of neuronal Vps35 in neurovascular coupling in the developing mouse brain and implicate BV-associated microglia as underlying this event.

Efficient Temporal Coding in the Early Visual System: Existing Evidence and Future Directions

While it is universally accepted that the brain makes predictions, there is little agreement about how this is accomplished and under which conditions. Accurate prediction requires neural circuits to learn and store spatiotemporal patterns observed in the natural environment, but it is not obvious how such information should be stored, or encoded. Information theory provides a mathematical formalism that can be used to measure the efficiency and utility of different coding schemes for data transfer and storage. This theory shows that codes become efficient when they remove predictable, redundant spatial and temporal information. Efficient coding has been used to understand retinal computations and may also be relevant to understanding more complicated temporal processing in visual cortex. However, the literature on efficient coding in cortex is varied and can be confusing since the same terms are used to mean different things in different experimental and theoretical contexts. In this work, we attempt to provide a clear summary of the theoretical relationship between efficient coding and temporal prediction, and review evidence that efficient coding principles explain computations in the retina. We then apply the same framework to computations occurring in early visuocortical areas, arguing that data from rodents is largely consistent with the predictions of this model. Finally, we review and respond to criticisms of efficient coding and suggest ways that this theory might be used to design future experiments, with particular focus on understanding the extent to which neural circuits make predictions from efficient representations of environmental statistics.