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Sleep is a universal and evolutionarily conserved behavior among many animal species, yet we do not have a fundamental understanding of why animals need to sleep. What we do know, however, is that sleep is critical for behavioral performance during the waking period and for long-term brain health. Here we provide an overview of some putative mechanisms that mediate the restorative effects of sleep, namely metabolic biosynthesis, fluid perfusion, and synaptic homeostasis. We then review recent experimental findings that advance the possibility of inducing sleep-like slow-wave activity (SWA) during wakefulness or enhance SWA during sleep in a top-down manner using noninvasive brain stimulation. SWA induction and SWA enhancement are believed to recapitulate the beneficial effects of sleep independent of the actual state of the subjects. If confirmed, these observations will change the way in which we investigate the neural correlates of sleep, thus paving the way for comprehending and actively controlling its restorative function.

Following spinal cord injury (SCI) the degree of functional (motor, autonomous, or sensory) loss correlates with the severity of nervous tissue damage. An imaging technique able to capture non-invasively and simultaneously the complex mechanisms of neuronal loss, vascular damage, and peri-lesional tissue reorganization is currently lacking in experimental SCI studies. Synchrotron X-ray phase-contrast tomography (SXPCT) has emerged as a non-destructive three-dimensional (3D) neuroimaging technique with high contrast and spatial resolution. In this framework, we developed a multi-modal approach combining SXPCT, histology and correlative methods to study neurovascular architecture in normal and spinal level C4-contused mouse spinal cords (C57BL/6J mice, age 2-3 months). The evolution of SCI lesion was imaged at the cell resolution level during the acute (30 min) and subacute (7 day) phases. Spared motor neurons (MNs) were segmented and quantified in different volumes localized at and away from the epicenter. SXPCT was able to capture neuronal loss and blood-brain barrier breakdown following SCI. Three-dimensional quantification based on SXPCT acquisitions showed no additional MN loss between 30 min and 7 days post-SCI. In addition, the analysis of hemorrhagic (at 30 min) and lesion (at 7 days) volumes revealed a high similarity in size, suggesting no extension of tissue degeneration between early and later time-points. Moreover, glial scar borders were unevenly distributed, with rostral edges being the most extended. In conclusion, SXPCT capability to image at high resolution cellular changes in 3D enables the understanding of the relationship between hemorrhagic events and nervous structure damage in SCI.

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

Over the last two decades, it has been established that glucose metabolic fluxes in neurons and astrocytes are proportional to the rates of the glutamate/GABA-glutamine neurotransmitter cycles in close to 1:1 stoichiometries across a wide range of functional energy demands. However, there is presently no mechanistic explanation for these relationships. We present here a theoretical meta-analysis that tests whether the brain’s unique compartmentation of glycogen metabolism in the astrocyte and the requirement for neuronal glucose homeostasis lead to the observed stoichiometries. We found that blood-brain barrier glucose transport can be limiting during activation and that the energy demand could only be met if glycogenolysis supports neuronal glucose metabolism by replacing the glucose consumed by astrocytes, a mechanism we call Glucose Sparing by Glycogenolysis (GSG). The predictions of the GSG model are in excellent agreement with a wide range of experimental results from rats, mice, tree shrews, and humans, which were previously unexplained. Glycogenolysis and glucose sparing dictate the energy available to support neuronal activity, thus playing a fundamental role in brain function in health and disease.

Visuospatial attention is strongly lateralized, with the right hemisphere commonly exhibiting stronger activation and connectivity patterns than the left hemisphere during attentive processes. However, whether such asymmetry influences inter-hemispheric information transfer and behavioral performance is not known. Here we used a region of interest (ROI) and network-based approach to determine steady-state fMRI functional connectivity (FC) in the whole cerebral cortex during a leftward/rightward covert visuospatial attention task. We found that the global FC topology between either ROIs or networks was independent on the attended side. The side of attention significantly modulated FC strength between brain networks, with leftward attention primarily involving the connections of the right visual network with dorsal and ventral attention networks in both the left and right hemisphere. High hemispheric functional segregation significantly correlated with faster target detection response times (i.e., better performance). Our findings suggest that the dominance of the right hemisphere in visuospatial attention is associated with an hemispheric functional segregation that is beneficial for behavioral performance.

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

Astrocytic glycogen is the sole glucose reserve of the brain. Both glycogen and glucose are necessary for basic neurophysiology and in turn for higher brain functions. In spite of low concentration, turnover and stimulation-induced degradation, any interference with normal glycogen metabolism in the brain severely affects neuronal excitability and disrupts memory formation. Here, I briefly discuss the glycogenolysis-induced glucose-sparing effect, which involves glucose phosphates as key allosteric effectors in the modulation of astrocytic and neuronal glucose uptake and phosphorylation. I further advance a novel and thus far unexplored effect of glycogenolysis that might be mediated by glucose phosphates.

In‐scanner head motion represents a major confounding factor in functional connectivity studies and it raises particular concerns when motion correlates with the effect of interest. One such instance regards research focused on functional connectivity modulations induced by sustained cognitively demanding tasks. Indeed, cognitive engagement is generally associated with substantially lower in‐scanner movement compared with unconstrained, or minimally constrained, conditions. Consequently, the reliability of condition‐dependent changes in functional connectivity relies on effective denoising strategies. In this study, we evaluated the ability of common denoising pipelines to minimize and balance residual motion‐related artifacts between resting‐state and task conditions. Denoising pipelines—including realignment/tissue‐based regression, PCA/ICA‐based methods (aCompCor and ICA‐AROMA, respectively), global signal regression, and censoring of motion‐contaminated volumes—were evaluated according to a set of benchmarks designed to assess either residual artifacts or network identifiability. We found a marked heterogeneity in pipeline performance, with many approaches showing a differential efficacy between rest and task conditions. The most effective approaches included aCompCor, optimized to increase the noise prediction power of the extracted confounding signals, and global signal regression, although both strategies performed poorly in mitigating the spurious distance‐dependent association between motion and connectivity. Censoring was the only approach that substantially reduced distance‐dependent artifacts, yet this came at the great cost of reduced network identifiability. The implications of these findings for best practice in denoising task‐based functional connectivity data, and more generally for resting‐state data, are discussed., We showed the inefficacy of many denoising strategies in balancing motion‐related artifacts between functional conditions that are differently prone to motion, such as rest and cognitively demanding conditions. While no pipeline was able to completely suppress motion artifacts and simultaneously maximize network identifiability, we found that strategies exploiting an optimized aCompCor yielded the best results. Importantly, we advocate the use of censoring with caution, since we found the method to be cost ineffective, prone to introduce biases and to reduce network identifiability.

Subtle semantic deficits can be observed in Alzheimer's disease (AD) patients even in the early stages of the illness. In this work, we tested the hypothesis that the semantic control network is deregulated in mild AD patients. We assessed the integrity of the semantic control system using resting-state functional magnetic resonance imaging in a cohort of patients with mild AD (n = 38; mean mini-mental state examination = 20.5) and in a group of age-matched healthy controls (n = 19). Voxel-wise analysis spatially constrained in the left fronto-temporal semantic control network identified two regions with altered functional connectivity (FC) in AD patients, specifically in the pars opercularis (POp, BA44) and in the posterior middle temporal gyrus (pMTG, BA21). Using whole-brain seed-based analysis, we demonstrated that these two regions have altered FC even beyond the semantic control network. In particular, the pMTG displayed a wide-distributed pattern of lower connectivity to several brain regions involved in language-semantic processing, along with a possibly compensatory higher connectivity to the Wernicke's area. We conclude that in mild AD brain regions belonging to the semantic control network are abnormally connected not only within the network, but also to other areas known to be critical for language processing.

A fundamental understanding of glycogen structure, concentration, polydispersity and turnover is critical to qualify the role of glycogen in the brain. These molecular and metabolic features are under the control of neuronal activity through the interdependent action of neuromodulatory tone, ionic homeostasis and availability of metabolic substrates, all variables that concur to define the state of the system. In this chapter, we briefly describe how glycogen responds to selected behavioral, nutritional, environmental, hormonal, developmental and pathological conditions. We argue that interpreting glycogen metabolism through the lens of brain state is an effective approach to establish the relevance of energetics in connecting molecular and cellular neurophysiology to behavior.

A fundamental understanding of glycogen structure, concentration, polydispersity and turnover is critical to qualify the role of glycogen in the brain. These molecular and metabolic features are under the control of neuronal activity through the interdependent action of neuromodulatory tone, ionic homeostasis and availability of metabolic substrates, all variables that concur to define the state of the system. In this chapter, we briefly describe how glycogen responds to selected behavioral, nutritional, environmental, hormonal, developmental and pathological conditions. We argue that interpreting glycogen metabolism through the lens of brain state is an effective approach to establish the relevance of energetics in connecting molecular and cellular neurophysiology to behavior.

Since the introduction of functional magnetic resonance imaging (fMRI), several computational approaches have been developed to examine the effect of the morphology and arrangement of blood vessels on the blood oxygenation-level dependent (BOLD) signal in the brain. In the present work, we implemented the original Ogawa's model using a numerical simulation based on the finite element method (FEM) instead of the analytical models. In literature, there are different works using analytical methods to analyse the transverse relaxation rate ( R 2 ∗ ), which BOLD signal is related to, modelling the vascular system with simple and canonical geometries such as an infinite cylinder model (ICM) or a set of cylinders. We applied the numerical simulation to the extravascular BOLD signal as a function of angular vessel distribution (perpendicular vs parallel to the static magnetic field) relevant for anatomical districts characterized by geometrical symmetries, such as spinal cord. Numerical simulations confirmed analytical results for the canonical ICM. Moreover, the perturbation to the magnetic field induced by blood deoxyhaemoglobin, as quantified assuming Brownian diffusion of water molecules around the vessel, revealed that vessels contribute the most to the variation of the R 2 ∗ when they are preferentially perpendicular to the external magnetic field, regardless of their size. Our results indicate that the numerical simulation method is sensitive to the effects of different vascular geometry. This work highlights the opportunity to extend R 2 ∗ simulations to realistic models of vasculature based on high-resolution anatomical images.

Supercompensated brain glycogen levels may contribute to the development of hypoglycemia-associated autonomic failure (HAAF) following recurrent hypoglycemia (RH) by providing energy for the brain during subsequent periods of hypoglycemia. To assess the role of glycogen supercompensation in the generation of HAAF, we estimated the level of brain glycogen following RH and acute hypoglycemia (AH). After undergoing 3 hyperinsulinemic, euglycemic and 3 hyperinsulinemic, hypoglycemic clamps (RH) on separate occasions at least 1 month apart, five healthy volunteers received [1-13C]glucose intravenously over 80+ h while maintaining euglycemia. 13C-glycogen levels in the occipital lobe were measured by 13C magnetic resonance spectroscopy at ∼8, 20, 32, 44, 56, 68 and 80 h at 4 T and glycogen levels estimated by fitting the data with a biophysical model that takes into account the tiered glycogen structure. Similarly, prior 13C-glycogen data obtained following a single hypoglycemic episode (AH) were fitted with the same model. Glycogen levels did not significantly increase after RH relative to after euglycemia, while they increased by ∼16% after AH relative to after euglycemia. These data suggest that glycogen supercompensation may be blunted with repeated hypoglycemic episodes. A causal relationship between glycogen supercompensation and generation of HAAF remains to be established.

PURPOSE OF REVIEW: The goal of the present paper is to review current literature supporting the occurrence of fundamental changes in brain energy metabolism during the transition from wakefulness to sleep. RECENT FINDINGS: Latest research in the field indicates that glucose utilization and the concentrations of several brain metabolites consistently change across the sleep-wake cycle. Lactate, a product of glycolysis that is involved in synaptic plasticity, has emerged as a good biomarker of brain state. Sleep-induced changes in cerebral metabolite levels result from a shift in oxidative metabolism, which alters the reliance of brain metabolism upon carbohydrates. SUMMARY: We found wide support for the notion that brain energetics is state-dependent. In particular, oxidation of fatty acids and ketone bodies partly replace glucose as cerebral energy source during sleep. This mechanism plausibly accounts for increases in biosynthetic pathways and functional alterations in neuronal activity associated with sleep. A better account of brain energy metabolism during sleep might help elucidate the long mysterious restorative effects of sleep for the whole organism.

Brain activity at rest is characterized by widely distributed and spatially specific patterns of synchronized low-frequency blood-oxygenation level-dependent (BOLD) fluctuations, which correspond to physiologically relevant brain networks. This network behaviour is known to persist also during task execution, yet the details underlying task-associated modulations of within- and between-network connectivity are largely unknown. In this study we exploited a multi-parametric and multi-scale approach to investigate how low-frequency fluctuations adapt to a sustained n-back working memory task. We found that the transition from the resting state to the task state involves a behaviourally relevant and scale-invariant modulation of synchronization patterns within both task-positive and default mode networks. Specifically, decreases of connectivity within networks are accompanied by increases of connectivity between networks. In spite of large and widespread changes of connectivity strength, the overall topology of brain networks is remarkably preserved. We show that these findings are strongly influenced by connectivity at rest, suggesting that the absolute change of connectivity (i.e., disregarding the baseline) may be not the most suitable metric to study dynamic modulations of functional connectivity. Our results indicate that a task can evoke scale-invariant, distributed changes of BOLD fluctuations, further confirming that low frequency BOLD oscillations show a specialized response and are tightly bound to task-evoked activation. The human brain is organized in functional networks, characterized by long range functional connections between brain areas. This network behavior is modulated by the execution of tasks. In our work, we show that modulations associated to a task are massive and widespread, but changes are scale invariant and the overall topology of the networks is well preserved under stimulation, confirming that the functional networks are intrinsic features of the human brain function. We found also that the amplitude of the massive change we observed is heavily influenced by the degree of connectivity at rest, indicating that the magnitude of connectivity change is not an independent metric for the assessment of functional network dynamics.

Brain activity during wakefulness is associated with high metabolic rates that are believed to support information processing and memory encoding. In spite of loss of consciousness, sleep still carries a substantial energy cost. Experimental evidence supports a cerebral metabolic shift taking place during sleep that suppresses aerobic glycolysis, a hallmark of environment-oriented waking behavior and synaptic plasticity. Recent studies reveal that glial astrocytes respond to the reduction of wake-promoting neuromodulators by regulating volume, composition and glymphatic drainage of interstitial fluid. These events are accompanied by changes in neuronal discharge patterns, astrocyte-neuron interactions, synaptic transactions and underlying metabolic features. Internally-generated neuronal activity and network homeostasis are proposed to account for the high sleep-related energy demand.

Functional magnetic resonance imaging (fMRI) is a fundamental tool to investigate human brain networks. However, the cellular mechanisms underlying fMRI signals are not fully understood. One hypothetical mechanism is the putative vascular control exerted by cytosolic calcium in perivascular astrocytes. We have performed combined fMRI-electrophysiology experiments in mice lacking the inositol 1,4,5-triphosphate-type-2 receptor, with the primary pathway of cytosolic calcium increase eliminated into astrocytes. Our results show that evoked electrophysiologic activity and fMRI signals acquired during either transient or sustained neuronal activations occur independently of these large calcium signals. This result challenges the suggested intermediary role of astrocytic calcium surges in fMRI-signal generation.

Glycogen provides an important glucose reservoir in the brain since the concentration of glucosyl units stored in glycogen is several fold higher than free glucose available in brain tissue. We have previously reported 3-4 µmol/g brain glycogen content using in vivo (13)C magnetic resonance spectroscopy (MRS) in conjunction with [1-(13)C]glucose administration in healthy humans, while higher levels were reported in the rodent brain. Due to the slow turnover of bulk brain glycogen in humans, complete turnover of the glycogen pool, estimated to take 3-5 days, was not observed in these prior studies. In an attempt to reach complete turnover and thereby steady state (13)C labeling in glycogen, here we administered [1-(13)C]glucose to healthy volunteers for 80 h. To eliminate any net glycogen synthesis during this period and thereby achieve an accurate estimate of glycogen concentration, volunteers were maintained at euglycemic blood glucose levels during [1-(13)C]glucose administration and (13)C-glycogen levels in the occipital lobe were measured by (13)C MRS approximately every 12 h. Finally, we fitted the data with a biophysical model that was recently developed to take into account the tiered structure of the glycogen molecule and additionally incorporated blood glucose levels and isotopic enrichments as input function in the model. We obtained excellent fits of the model to the (13)C-glycogen data, and glycogen content in the healthy human brain tissue was found to be 7.8 ± 0.3 µmol/g, a value substantially higher than previous estimates of glycogen content in the human brain.

Time-domain analysis of blood-oxygenation level-dependent (BOLD) signals allows the identification of clusters of voxels responding to photic stimulation in primary visual cortex (V1). However, the characterization of information encoding into temporal properties of the BOLD signals of an activated cluster is poorly investigated. Here, we used Shannon entropy to determine spatial and temporal information encoding in the BOLD signal within the most strongly activated area of the human visual cortex during a hemifield photic stimulation. We determined the distribution profile of BOLD signals during epochs at rest and under stimulation within small (19-121 voxels) clusters designed to include only voxels driven by the stimulus as highly and uniformly as possible. We found consistent and significant increases (2-4% on average) in temporal information entropy during activation in contralateral but not ipsilateral V1, which was mirrored by an expected loss of spatial information entropy. These opposite changes coexisted with increases in both spatial and temporal mutual information (i.e., dependence) in contralateral V1. Thus, we showed that the first cortical stage of visual processing is characterized by a specific spatiotemporal rearrangement of intracluster BOLD responses. Our results indicate that while in the space domain BOLD maps may be incapable of capturing the functional specialization of small neuronal populations due to relatively low spatial resolution, some information encoding may still be revealed in the temporal domain by an increase of temporal information entropy.

Epilepsy is a heterogeneous family of neurological disorders that manifest as seizures, i.e. the hypersynchronous activity of large population of neurons. About 30% of epileptic patients do not respond to currently available antiepileptic drugs. Decades of intense research have elucidated the involvement of a number of possible signaling pathways, however, at present we do not have a fundamental understanding of epileptogenesis. In this paper, we review the literature on epilepsy under a wide-angle perspective, a mandatory choice that responds to the recurrent and unanswered question about what is epiphenomenal and what is causal to the disease. While focusing on the involvement of K+ and glutamate/GABA in determining neuronal hyperexcitability, emphasis is given to astrocytic contribution to epileptogenesis, and especially to loss-of-function of astrocytic glutamine synthetase following reactive astrogliosis, a hallmark of epileptic syndromes. We finally introduce the potential involvement of abnormal glycogen synthesis induced by excess glutamate in increasing susceptibility to seizures.

Epilepsy is a family of brain disorders with a largely unknown etiology and high percentage of pharmacoresistance. The clinical manifestations of epilepsy are seizures, which originate from aberrant neuronal synchronization and hyperexcitability. Reactive astrocytosis, a hallmark of the epileptic tissue, develops into loss-of-function of glutamine synthetase, impairment of glutamate-glutamine cycle and increase in extracellular and astrocytic glutamate concentration. Here, we argue that chronically elevated intracellular glutamate level in astrocytes is instrumental to alterations in the metabolism of glycogen and leads to the synthesis of polyglucosans. Unaccessibility of glycogen-degrading enzymes to these insoluble molecules compromises the glycogenolysis-dependent reuptake of extracellular K(+) by astrocytes, thereby leading to increased extracellular K(+) and associated membrane depolarization. Based on current knowledge, we propose that the deterioration in structural homogeneity of glycogen particles is relevant to disruption of brain K(+) homeostasis and increased susceptibility to seizures in epilepsy.

Fractal analysis is a powerful method for the morphological study of complex systems that is increasingly applied to biomedical images. Spatial resolution and image segmentation are crucial for the discrimination of tissue structures at the multiscale level. In this work, we have applied fractal analysis to high-resolution X-ray phase contrast micro-tomography (XrPC&mu, T) images in both uninjured and injured tissue of a mouse spinal cord. We estimated the fractal dimension (FD) using the box-counting method on tomographic slices segmented at different threshold levels. We observed an increased FD in the ipsilateral injured hemicord compared with the contralateral uninjured tissue, which was almost independent of the chosen threshold. Moreover, we found that images exhibited the highest fractality close to the global histogram threshold level. Finally, we showed that the FD estimate largely depends on the image histogram regardless of tissue appearance. Our results demonstrate that the pre-processing of XrPC&mu, T images is critical to fractal analysis and the estimation of FD.

A biophysical model of the glycogen molecule is developed, which takes into account the points of attack of synthase and phosphorylase at the level of the individual glucose chain. Under the sole assumption of steric effects governing enzyme accessibility to glucosyl residues, the model reproduces the known equilibrium structure of cellular glycogen at steady state. In particular, experimental data are reproduced assuming that synthase (1) operates preferentially on inner chains of the molecule and (2) exhibits a faster mobility than phosphorylase in translocating from an attacked chain to another. The model is then used to examine the turnover of outer versus inner tiers during the labeling process of isotopic enrichment (IE) experiments. Simulated data are fitted to in vivo13C nuclear magnetic resonance spectroscopy measurements obtained in the human brain under resting conditions. Within this experimental set-up, analysis of simulated label incorporation and retention shows that 7% to 35% of labeled glucose is lost from the rapidly turning-over surface of the glycogen molecule when stimulation onset is delayed by 7 to 11.5 hours after the end of [1-13C]glucose infusion as done in actual procedures. The substantial label washout before stimulation suggests that much of the subsequent activation-induced glycogenolysis could remain undetected. Overall, these results show that the molecular structure significantly affects the patterns of synthesis and degradation of glycogen, which is relevant for appropriate design of labeling experiments aiming at investigating the functional roles of this glucose reserve.

Biology is full of instances of exaptation, the functional shift or co-optation of a trait during evolution (Gould and Vrba, 1982). Exaptation played a critical role in human brain evolution. For example, hominin brain expansion is thought to have happened opportunistically upon food resources rich in brain-selective nutrients (Tattersall, 2010). Prehensile hands and bipedalism were other enabling factors in this process, as both features preceded the expansion of the brain, and notably, the development and utilization of tools (Wood, 2010). Similarly, central and peripheral vocal structures, initially used for a variety of non-linguistic reasons (chewing, larynx protection, size exaggeration), were pre-existing conditions to, and provided the anatomical basis for, the evolution of language (e.g., MacNeilage, 2010). The very emergence of abstract cognitive abilities in humans are hypothesized to have evolved from faculties originally developed for other purposes (Pinker, 2010).

The available estimate of the energy expended for signaling in rat neocortex is refined to examine the separate contribution of spiking and synaptic activity as a function of average neuronal firing rate. By taking into account a phenomenological model of short-term synaptic plasticity, we show that the transition from low to high cortical activity is accompanied by a substantial increase in relative energy consumed by action potentials vs. synaptic potentials. This consideration might be important for a deeper understanding of how information is represented in the cortex and which metabolic pathways are upregulated to sustain cortical activity.

For many years, a tenet of cerebral metabolism held that glucose was the obligate energy substrate of the mammalian brain and that neuronal oxidative metabolism represented the majority of this glucose utilization. In 1994, Pellerin and Magistretti formulated the astrocyte-neuron lactate shuttle (ANLS) hypothesis, in which astrocytes, not neurons, metabolized glucose, with subsequent transport of the glycolytically derived lactate to fuel the energy needs of the neuron during neurotransmission. By considering the concentrations and kinetic characteristics of the nutrient transporter proteins, Simpson et al later supported the opposite view, in which lactate flows from neurons to astrocytes, thus leading to the neuron-astrocyte lactate shuttle (NALS). Most recently, a commentary was published in this journal attempting to discredit the NALS. This challenge has stimulated the present response in which we detail the inaccuracies of the commentary and further model several different possibilities. Although our simulations continue to support the predominance of neuronal glucose utilization during activation and neuronal to astrocytic lactate flow, the most important result is that, regardless of the direction of the flow, the overall contribution of lactate to cerebral glucose metabolism is found to be so small as to make this ongoing debate ‘much ado about nothing'.

In this paper, we combined several mathematical models of cerebral metabolism and nutrient transport to investigate the energetic significance of metabolite trafficking within the brain parenchyma during a 360-secs activation. Glycolytic and oxidative cellular metabolism were homogeneously modeled between neurons and astrocytes, and the stimulation-induced neuronal versus astrocytic Na+ inflow was set to 3:1. These assumptions resemble physiologic conditions and are supported by current literature. Simulations showed that glucose diffusion to the interstitium through basal lamina dominates the provision of the sugar to both neurons and astrocytes, whereas astrocytic endfeet transfer less than 4% of the total glucose supplied to the tissue. Neuronal access to paracellularly diffused glucose prevails even after halving (doubling) the ratio of neuronal versus astrocytic glycolytic (oxidative) metabolism, as well as after reducing the neuronal versus astrocytic Na+ inflow to a nonphysiologic value of 1:1. Noticeably, displaced glucose equivalents as intercellularly shuttled lactate account for ∼6% to 7% of total brain glucose uptake, an amount comparable with the concomitant drainage of the monocarboxylate by the bloodstream. Overall, our results suggest that the control of carbon recruitment for neurons and astrocytes is exerted at the level of glucose uptake rather than that of lactate shuttle.

Brainstem nuclei are the principal sites of monoamine (MA) innervation to major forebrain structures. In the cortical grey matter, increased secretion of MA neuromodulators occurs in response to a wealth of environmental and homeostatic challenges, whose onset is associated with rapid, preparatory changes in neural activity as well as with increases in energy metabolism. Blood-borne glucose is the main substrate for energy production in the brain. Once entered the tissue, interstitial glucose is equally accessible to neurons and astrocytes, the two cell types accounting for most of cellular volume and energy metabolism in neocortex and hippocampus. Astrocytes also store substantial amounts of glycogen, but non-stimulated glycogen turnover is very small. The rate of cellular glucose utilization in the brain is largely determined by hexokinase, which under basal conditions is more than 90 % inhibited by its product glucose-6-phosphate (Glc-6-P). During rapid increases in energy demand, glycogen is a primary candidate in modulating the intracellular level of Glc-6-P, which can occur only in astrocytes. Glycogenolysis can produce Glc-6-P at a rate higher than uptake and phosphorylation of glucose. MA neurotransmitter are released extrasinaptically by brainstem neurons projecting to neocortex and hippocampus, thus activating MA receptors located on both neuronal and astrocytic plasma membrane. Importantly, MAs are glycogenolytic agents and thus they are exquisitely suitable for regulation of astrocytic Glc-6-P concentration, upstream substrate flow through hexokinase and hence cellular glucose uptake. Conforming to such mechanism, Gerald A. Dienel and Nancy F. Cruz recently suggested that activation of noradrenergic locus coeruleus might reversibly block astrocytic glucose uptake by stimulating glycogenolysis in these cells, thereby anticipating the rise in glucose need by active neurons. In this paper, we further develop the idea that the whole monoaminergic system modulates both function and metabolism of forebrain regions in a manner mediated by glycogen mobilization in astrocytes.

Several laboratories have consistently reported small concentration changes in lactate, glutamate, aspartate, and glucose in the human cortex during prolonged stimuli. However, whether such changes correlate with blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI) signals have not been determined. The present study aimed at characterizing the relationship between metabolite concentrations and BOLD-fMRI signals during a block-designed paradigm of visual stimulation. Functional magnetic resonance spectroscopy (fMRS) and fMRI data were acquired from 12 volunteers. A short echo-time semi-LASER localization sequence optimized for 7 Tesla was used to achieve full signal-intensity MRS data. The group analysis confirmed that during stimulation lactate and glutamate increased by 0.26±0.06 μmol/g (~30%) and 0.28±0.03 μmol/g (~3%), respectively, while aspartate and glucose decreased by 0.20±0.04 μmol/g (~5%) and 0.19±0.03 μmol/g (~16%), respectively. The single-subject analysis revealed that BOLD-fMRI signals were positively correlated with glutamate and lactate concentration changes. The results show a linear relationship between metabolic and BOLD responses in the presence of strong excitatory sensory inputs, and support the notion that increased functional energy demands are sustained by oxidative metabolism. In addition, BOLD signals were inversely correlated with baseline ã-aminobutyric acid concentration. Finally, we discussed the critical importance of taking into account linewidth effects on metabolite quantification in fMRS paradigms.Journal of Cerebral Blood Flow and Metabolism advance online publication, 7 January 2015; doi:10.1038/jcbfm.2014.233.

Recent advances in brain energy metabolism support the notion that glycogen in astrocytes is necessary for the clearance of neuronally-released K(+) from the extracellular space. However, how the multiple metabolic pathways involved in K(+)-induced increase in glycogen turnover are regulated is only partly understood. Here we summarize the current knowledge about the mechanisms that control glycogen metabolism during enhanced K(+) uptake. We also describe the action of the ubiquitous Na(+)/K(+) ATPase for both ion transport and intracellular signaling cascades, and emphasize its importance in understanding the complex relation between glycogenolysis and K(+) uptake.

The results of the study of Xu and colleagues in this issue constitute a critical new piece of information on the functional specialization of astrocytes for K(+) homeostasis in the brain. The relationship between astrocytes and potassium has been long recognized in half a century of research. Now this relation appears to have found its metabolic correlate in astrocytic glycogen. Xu et al. showed that glycogen is committed to fuel astrocytic K(+) uptake, as this process is abolished when glycogenolysis is inhibited even in the presence of glucose. They went further by showing that the cellular mechanisms which selectively mobilize glycogen involve the participation of several intracellular signaling cascades. As with all good science, these findings generate a number of fundamental questions that are open for experimental research.

The non-metabolizable fluorescent glucose analogue 6-(N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-2-deoxyglucose (6-NBDG) is increasingly used to study cellular transport of glucose. Intracellular accumulation of exogenously applied 6-NBDG is assumed to reflect concurrent gradient-driven glucose uptake by glucose transporters (GLUTs). Here theoretical considerations are provided that put this assumption into question. In particular, depending on the microscopic parameters of the carrier proteins, theory proves that changes in glucose transport can be accompanied by opposite changes in flow of 6-NBDG. Simulations were carried out applying the symmetric four-state carrier model on the GLUT1 isoform, which is the only isoform whose kinetic parameters are presently available. Results show that cellular 6-NBDG uptake decreases with increasing rate of glucose utilization under core-model conditions supported by literature, namely where the transporter is assumed to work in regime of slow reorientation of the free-carrier compared to the ligand-carrier complex. In order to observe an increase of 6-NBDG uptake with increasing rate of glucose utilization, and thus interpret 6-NBDG increase as surrogate of glucose uptake, the transporter must be assumed to operate in regime of slow ligand-carrier binding, a condition that is currently not supported by literature. Our findings suggest that the interpretation of data obtained with NBDG derivatives is presently ambiguous and should be cautious because the underlying transport kinetics are not adequately established.

The energetics of cerebral activity critically relies on the functional and metabolic interactions between neurons and astrocytes. Important open questions include the relation between neuronal versus astrocytic energy demand, glucose uptake and intercellular lactate transfer, as well as their dependence on the level of activity. We have developed a large-scale, constraint-based network model of the metabolic partnership between astrocytes and glutamatergic neurons that allows for a quantitative appraisal of the extent to which stoichiometry alone drives the energetics of the system. We find that the velocity of the glutamate-glutamine cycle ($V_{cyc}$) explains part of the uncoupling between glucose and oxygen utilization at increasing $V_{cyc}$ levels. Thus, we are able to characterize different activation states in terms of the tissue oxygen-glucose index (OGI). Calculations show that glucose is taken up and metabolized according to cellular energy requirements, and that partitioning of the sugar between different cell types is not significantly affected by $V_{cyc}$. Furthermore, both the direction and magnitude of the lactate shuttle between neurons and astrocytes turn out to depend on the relative cell glucose uptake while being roughly independent of $V_{cyc}$. These findings suggest that, in absence of ad hoc activity-related constraints on neuronal and astrocytic metabolism, the glutamate-glutamine cycle does not control the relative energy demand of neurons and astrocytes, and hence their glucose uptake and lactate exchange., Comment: 21 pages, incl. supporting text and tables

Several brain regions exhibit a sustained negative BOLD response (NBR) during specific tasks, as assessed with functional magnetic resonance imaging. The origin of the NBR and the relationships between the vascular/metabolic dynamics and the underlying neural activity are highly debated. Converging evidence indicates that NBR, in human and non-human primates, can be interpreted in terms of decrease in neuronal activity under its basal level, rather than a purely vascular phenomenon. However, the scarcity of direct experimental evidence suggests caution and encourages the ongoing utilization of multimodal approaches in the investigation of this effect.

Energy homeostasis in the brain is maintained by oxidative metabolism of glucose, primarily to fulfil the energy demand associated with ionic movements in neurons and astrocytes. In this contribution we review the experimental evidence that grounds a specific role of glycogen metabolism in supporting the functional energetic needs of astrocytes during the removal of extracellular potassium. Based on theoretical considerations, we further discuss the hypothesis that the mobilization of glycogen in astrocytes serves the purpose to enhance the availability of glucose for neuronal glycolytic and oxidative metabolism at the onset of stimulation. Finally, we provide an evolutionary perspective for explaining the selection of glycogen as carbohydrate reserve in the energy-sensing machinery of cell metabolism.

Glutamate is one of the most versatile molecules present in the human brain, involved in protein synthesis, energy production, ammonia detoxification, and transport of reducing equivalents. Aside from these critical metabolic roles, glutamate plays a major part in brain function, being not only the most abundant excitatory neurotransmitter, but also the precursor for γ-aminobutyric acid (GABA), the predominant inhibitory neurotransmitter. Regulation of glutamate levels is pivotal for normal brain function, as abnormal extracellular concentration of glutamate can lead to impaired neurotransmission, neurodegeneration and even neuronal death. Understanding how the neuron-astrocyte functional and metabolic interactions modulate glutamate concentration during different activation status and under physiological and pathological conditions is a challenging task, and can only be tentatively estimated from current literature. In this paper, we focus on describing the various metabolic pathways which potentially affect glutamate concentration in the brain, and emphasize which ones are likely to produce the variations in glutamate concentration observed during enhanced neuronal activity in human studies.

A consistent and prominent feature of brain functional magnetic resonance imaging (fMRI) data is the presence of low-frequency (2+ signaling. Specifically, neurotransmission induces pulses of Ca2+ concentration in astrocytes, resulting in increased cerebral perfusion and neuroactive transmitter release by these cells (i.e., gliotransmission), which in turn stimulates neuronal activity. Noticeably, the level of neuron-astrocyte cross talk regulates the periodic behavior of the Ca2+ wave-induced BOLD fluctuations. Our results suggest that the spontaneous ongoing activity of neuroglial networks is a potential source of the observed slow fMRI signal oscillations.

In this article, we examined theoretically the role of human cerebral glycogen in buffering the metabolic requirement of a 360-second brain stimulation, expanding our previous modeling study of neurometabolic coupling. We found that glycogen synthesis and degradation affects the relative amount of glucose taken up by neurons versus astrocytes. Under conditions of 175:115 mmol/L (∼1.5:1) neuronal versus astrocytic activation-induced Na+ influx ratio, ∼12% of astrocytic glycogen is mobilized. This results in the rapid increase of intracellular glucose-6-phosphate level on stimulation and nearly 40% mean decrease of glucose flow through hexokinase (HK) in astrocytes via product inhibition. The suppression of astrocytic glucose phosphorylation, in turn, favors the channeling of glucose from interstitium to nearby activated neurons, without a critical effect on the concurrent intercellular lactate trafficking. Under conditions of increased neuronal versus astrocytic activation-induced Na+ influx ratio to 190:65 mmol/L (∼3:1), glycogen is not significantly degraded and blood glucose is primarily taken up by neurons. These results support a role for astrocytic glycogen in preserving extracellular glucose for neuronal utilization, rather than providing lactate to neurons as is commonly accepted by the current ‘thinking paradigm’. This might be critical in subcellular domains during functional conditions associated with fast energetic demands.

Low frequency fluctuations (LFFs) of the BOLD signal are a major discovery in the study of the resting brain with functional magnetic resonance imaging (fMRI). Two fMRI-based measures, functional connectivity (FC), a measure of signal synchronicity, and the amplitude of LFFs (ALFF), a measure of signal periodicity, have been proved to be sensitive to changes induced by several neurological diseases, including degenerative dementia. In spite of the increasing use of these measures, whether and how they are related to each other remains to be elucidated. In this work we used voxel-wise FC and ALFF computed in different frequency bands (slow-5: 0.01-0.027 Hz; slow-4: 0.027-0.073 Hz; and full-band: 0.01-0.073 Hz), in order to assess their relationship in healthy elderly as well as the relevant changes induced by Alzheimer's Disease (AD) and Mild Cognitive Impairment (MCI). We found that in healthy elderly subjects FC and ALFF are positively correlated in anterior and posterior cingulate cortex (full-band, slow-4 and slow-5), temporal cortex (full-band and slow-5), and in a set of subcortical regions (full-band and slow-4). These correlation patterns between FC and ALFF were absent in either AD or MCI patients. Notably, the loss of correlation between FC and ALFF in the AD group was primarily due to changes in FC rather than in ALFF. Our results indicate that degenerative dementia is characterized by a loss of global connection rather than by a decrease of fluctuation amplitude.