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Although we have learned much about how the brain fuels its functions over the last decades, there remains much still to discover in an organ that is so complex. This article lays out major gaps in our knowledge of interrelationships between brain metabolism and brain function, including biochemical, cellular, and subcellular aspects of functional metabolism and its imaging in adult brain, as well as during development, aging, and disease. The focus is on unknowns in metabolism of major brain substrates and associated transporters, the roles of insulin and of lipid droplets, the emerging role of metabolism in microglia, mysteries about the major brain cofactor and signaling molecule NAD+ , as well as unsolved problems underlying brain metabolism in pathologies such as traumatic brain injury, epilepsy, and metabolic downregulation during hibernation. It describes our current level of understanding of these facets of brain energy metabolism as well as a roadmap for future research.

Objective: Obesity is associated with alterations in eating behavior and neurocognitive function. In this study, we investigate the effect of obesity on brain energy utilization, including brain glucose transport and metabolism. Methods: A total of 11 lean participants and 7 young healthy participants with obesity (mean age, 27 years) underwent magnetic resonance spectroscopy scanning coupled with a hyperglycemic clamp (target, ~180 mg/dL) using [1‐13C] glucose to measure brain glucose uptake and metabolism, as well as peripheral markers of insulin resistance. Results: Individuals with obesity demonstrated an ~20% lower ratio of brain glucose uptake to cerebral glucose metabolic rate (Tmax/CMRglucose) than lean participants (2.12 ± 0.51 vs. 2.67 ± 0.51; p = 0.04). The cerebral tricarboxylic acid cycle flux (VTCA) was similar between the two groups (p = 0.64). There was a negative correlation between total nonesterified fatty acids and Tmax/CMRglucose (r = −0.477; p = 0.045). Conclusions: We conclude that CMRglucose is unlikely to differ between groups due to similar VTCA, and, therefore, the glucose transport Tmax is lower in individuals with obesity. These human findings suggest that obesity is associated with reduced cerebral glucose transport capacity even at a young age and in the absence of other cardiometabolic comorbidities, which may have implications for long‐term brain function and health. [ABSTRACT FROM AUTHOR]

Because the human brain consumes a disproportionate fraction of the resting body's energy, positron emission tomography (PET) measurements of absolute glucose metabolism (CMRglc) can serve as disease biomarkers. Global mean normalization (GMN) of PET data reveals disease-based differences from healthy individuals as fractional changes across regions relative to a global mean. To assess the impact of GMN applied to metabolic data, we compared CMRglc with and without GMN in healthy awake volunteers with eyes closed (i.e., control) against specific physiological/clinical states, including healthy/awake with eyes open, healthy/awake but congenitally blind, healthy/sedated with anesthetics, and patients with disorders of consciousness. Without GMN, global CMRglc alterations compared to control were detected in all conditions except in congenitally blind where regional CMRglc variations were detected in the visual cortex. However, GMN introduced regional and bidirectional CMRglc changes at smaller fractions of the quantitative delocalized changes. While global information was lost with GMN, the quantitative approach (i.e., a validated method for quantitative baseline metabolic activity without GMN) not only preserved global CMRglc alterations induced by opening eyes, sedation, and varying consciousness but also detected regional CMRglc variations in the congenitally blind. These results caution the use of GMN upon PET-measured CMRglc data in health and disease.

ImportanceDespite strong theoretical rationale and preclinical evidence, several glutamate-targeted treatments for schizophrenia have failed in recent pivotal trials, prompting questions as to target validity, compound inadequacy, or lack of target engagement. A key limitation for glutamate-based treatment development is the lack of functional target-engagement biomarkers for translation between preclinical and early-stage clinical studies. We evaluated the utility of 3 potential biomarkers-ketamine-evoked changes in the functional magnetic imaging (fMRI) blood oxygen level-dependent response (pharmacoBOLD), glutamate proton magnetic resonance spectroscopy (1H MRS), and task-based fMRI-for detecting ketamine-related alterations in brain glutamate.ObjectiveTo identify measures with sufficient effect size and cross-site reliability to serve as glutamatergic target engagement biomarkers within early-phase clinical studies.Design, setting, and participantsThis randomized clinical trial was conducted at an academic research institution between May 2014 and October 2015 as part of the National Institute of Mental Health-funded Fast-Fail Trial for Psychotic Spectrum Disorders project. All raters were blinded to study group. Healthy volunteers aged 18 to 55 years of either sex and free of significant medical or psychiatric history were recruited from 3 sites. Data were analyzed between November 2015 and December 2016.InterventionsVolunteers received either sequential ketamine (0.23 mg/kg infusion over 1 minute followed by 0.58 mg/kg/h infusion over 30 minutes and then 0.29 mg/kg/h infusion over 29 minutes) or placebo infusions.Main outcomes and measuresKetamine-induced changes in pharmacoBOLD, 1H MRS, and task-based fMRI measures, along with symptom ratings. Measures were prespecified prior to data collection.ResultsOf the 65 volunteers, 41 (63%) were male, and the mean (SD) age was 31.1 (9.6) years; 59 (91%) had at least 1 valid scan. A total of 53 volunteers (82%) completed both ketamine infusions. In pharmacoBOLD, a highly robust increase (Cohen d = 5.4; P

The olfactory bulb (OB) plays a fundamental role in the sense of smell and has been implicated in several pathologies, including Alzheimer's disease. Despite its importance, high metabolic activity and unique laminar architecture, the OB is not frequently studied using MRS methods, likely due to the small size and challenging location. Here we present a detailed metabolic characterization of OB metabolism, in terms of both static metabolite concentrations using 1H MRS and metabolic fluxes associated with neuro‐energetics and neurotransmission by tracing the dynamic 13C flow from intravenously administered [1,6‐13C2]‐glucose, [2‐13C]‐glucose and [2‐13C]‐acetate to downstream metabolites, including [4‐13C]‐glutamate, [4‐13C]‐glutamine and [2‐13C]‐GABA. The unique laminar architecture and associated metabolism of the OB, distinctly different from that of the cerebral cortex, is characterized by elevated GABA and glutamine levels, as well as increased GABAergic and astroglial energy metabolism and neurotransmission. The results show that, despite the technical challenges, high‐quality 1H and 1H–[13C] MR spectra can be obtained from the rat OB in vivo. The derived metabolite concentrations and metabolic rates demonstrate a unique metabolic profile for the OB. The metabolic model provides a solid basis for future OB studies on functional activation or pathological conditions. [ABSTRACT FROM AUTHOR]

Isotopic assays of brain glucose utilization rates have been used for more than four decades to establish relationships between energetics, functional activity, and neurotransmitter cycling. Limitations of these methods include the relatively long time (1–60 min) for the determination of labeled metabolite levels and the lack of cellular resolution. Identification and quantification of fuels for neurons and astrocytes that support activation and higher brain functions are a major, unresolved issues. Glycolysis is preferentially up-regulated during activation even though oxygen level and supply are adequate, causing lactate concentrations to quickly rise during alerting, sensory processing, cognitive tasks, and memory consolidation. However, the fate of lactate (rapid release from brain or cell–cell shuttling coupled with local oxidation) is long disputed. Genetically encoded biosensors can determine intracellular metabolite concentrations and report real-time lactate level responses to sensory, behavioral, and biochemical challenges at the cellular level. Kinetics and time courses of cellular lactate concentration changes are informative, but accurate biosensor calibration is required for quantitative comparisons of lactate levels in astrocytes and neurons. An in vivo calibration procedure for the Laconic lactate biosensor involves intracellular lactate depletion by intravenous pyruvate-mediated trans-acceleration of lactate efflux followed by sensor saturation by intravenous infusion of high doses of lactate plus ammonium chloride. In the present paper, the validity of this procedure is questioned because rapid lactate–pyruvate interconversion in blood, preferential neuronal oxidation of both monocarboxylates, on-going glycolytic metabolism, and cellular volumes were not taken into account. Calibration pitfalls for the Laconic lactate biosensor also apply to other metabolite biosensors that are standardized in vivo by infusion of substrates that can be metabolized in peripheral tissues. We discuss how technical shortcomings negate the conclusion that Laconic sensor calibrations support the existence of an in vivo astrocyte–neuron lactate concentration gradient linked to lactate shuttling from astrocytes to neurons to fuel neuronal activity. [ABSTRACT FROM AUTHOR]

The ~1:1 stoichiometry between the rates of neuronal glucose oxidation (CMRglc-ox–N) and glutamate (Glu)/γ-aminobutyric acid (GABA)-glutamine (Gln) neurotransmitter (NT) cycling between neurons and astrocytes (VNTcycle) has been firmly established. However, the mechanistic basis for this relationship is not fully understood, and this knowledge is critical for the interpretation of metabolic and brain imaging studies in normal and diseased brain. The pseudo-malate-aspartate shuttle (pseudo-MAS) model established the requirement for glycolytic metabolism in cultured glutamatergic neurons to produce NADH that is shuttled into mitochondria to support conversion of extracellular Gln (i.e., astrocyte-derived Gln in vivo) into vesicular neurotransmitter Glu. The evaluation of this model revealed that it could explain half of the 1:1 stoichiometry and it has limitations. Modifications of the pseudo-MAS model were, therefore, devised to address major knowledge gaps, that is, submitochondrial glutaminase location, identities of mitochondrial carriers for Gln and other model components, alternative mechanisms to transaminate α-ketoglutarate to form Glu and shuttle glutamine-derived ammonia while maintaining mass balance. All modified models had a similar 0.5 to 1.0 predicted mechanistic stoichiometry between VNTcycle and the rate of glucose oxidation. Based on studies of brain β-hydroxybutyrate oxidation, about half of CMRglc-ox–N may be linked to glutamatergic neurotransmission and localized in pre-synaptic structures that use pseudo-MAS type mechanisms for Glu-Gln cycling. In contrast, neuronal compartments that do not participate in transmitter cycling may use the MAS to sustain glucose oxidation. The evaluation of subcellular compartmentation of neuronal glucose metabolism in vivo is a critically important topic for future studies to understand glutamatergic and GABAergic neurotransmission. [ABSTRACT FROM AUTHOR]

During transient brain activation cerebral blood flow (CBF) increases substantially more than cerebral metabolic rate of oxygen consumption (CMRO2) resulting in blood hyperoxygenation, the basis of BOLD-fMRI contrast. Explanations for the high CBF versus CMRO2 slope, termed neurovascular coupling (NVC) constant, focused on maintenance of tissue oxygenation to support mitochondrial ATP production. However, paradoxically the brain has a 3-fold lower oxygen extraction fraction (OEF) than other organs with high energy requirements, like heart and muscle during exercise. Here, we hypothesize that the NVC constant and the capillary oxygen mass transfer coefficient (which in combination determine OEF) are co-regulated during activation to maintain simultaneous homeostasis of pH and partial pressure of CO2 and O2 (pCO2 and pO2). To test our hypothesis, we developed an arteriovenous flux balance model for calculating blood and brain pH, pCO2, and pO2 as a function of baseline OEF (OEF0), CBF, CMRO2, and proton production by nonoxidative metabolism coupled to ATP hydrolysis. Our model was validated against published brain arteriovenous difference studies and then used to calculate pH, pCO2, and pO2 in activated human cortex from published calibrated fMRI and PET measurements. In agreement with our hypothesis, calculated pH, pCO2, and pO2 remained close to constant independently of CMRO2 in correspondence to experimental measurements of NVC and OEF0. We also found that the optimum values of the NVC constant and OEF0 that ensure simultaneous homeostasis of pH, pCO2, and pO2 were remarkably similar to their experimental values. Thus, the high NVC constant is overall determined by proton removal by CBF due to increases in nonoxidative glycolysis and glycogenolysis. These findings resolve the paradox of the brain's high CBF yet low OEF during activation, and may contribute to explaining the vulnerability of brain function to reductions in blood flow and capillary density with aging and neurovascular disease. [ABSTRACT FROM AUTHOR]

Leif Hertz, M.D., D.Sc. (honōris causā) (1930–2018), was one of the original and noteworthy participants in the International Conference on Brain Energy Metabolism (ICBEM) series since its inception in 1993. The biennial ICBEM conferences are organized by neuroscientists interested in energetics and metabolism underlying neural functions; they have had a high impact on conceptual and experimental advances in these fields and on promoting collaborative interactions among neuroscientists. Leif made major contributions to ICBEM discussions and understanding of metabolic and signaling characteristics of astrocytes and their roles in brain function. His studies ranged from uptake of K+ from extracellular fluid and its stimulation of astrocytic respiration, identification, and regulation of enzymes specifically or preferentially expressed in astrocytes in the glutamate–glutamine cycle of excitatory neurotransmission, a requirement for astrocytic glycogenolysis for fueling K+ uptake, involvement of glycogen in memory consolidation in the chick, and pharmacology of astrocytes. This tribute to Leif Hertz highlights his major discoveries, the high impact of his work on astrocyte–neuron interactions, and his unparalleled influence on understanding the cellular basis of brain energy metabolism. His work over six decades has helped integrate the roles of astrocytes into neurotransmission where oxidative and glycogenolytic metabolism during neurotransmitter glutamate turnover are key aspects of astrocytic energetics. Leif recognized that brain astrocytic metabolism is greatly underestimated unless the volume fraction of astrocytes is taken into account. Adjustment for pathway rates expressed per gram tissue for volume fraction indicates that astrocytes have much higher oxidative rates than neurons and astrocytic glycogen concentrations and glycogenolytic rates during sensory stimulation in vivo are similar to those in resting and exercising muscle, respectively. These novel insights are typical of Leif's astute contributions to the energy metabolism field, and his publications have identified unresolved topics that provide the neuroscience community with challenges and opportunities for future research. [ABSTRACT FROM AUTHOR]

Reading disability is a brain-based difficulty in acquiring fluent reading skills that affects significant numbers of children. Although neuroanatomical and neurofunctional networks involved in typical and atypical reading are increasingly well characterized, the underlying neurochemical bases of individual differences in reading development are virtually unknown. The current study is the first to examine neurochemistry in children during the critical period in which the neurocircuits that support skilled reading are still developing. In a longitudinal pediatric sample of emergent readers whose reading indicators range on a continuum from impaired to superior, we examined the relationship between individual differences in reading and reading-related skills and concentrations of neurometabolites measured using magnetic resonance spectroscopy. Both continuous and group analyses revealed that choline and glutamate concentrations were negatively correlated with reading and related linguistic measures in phonology and vocabulary (such that higher concentrations were associated with poorer performance). Correlations with behavioral scores obtained 24 months later reveal stability for the relationship between glutamate and reading performance. Implications for neurodevelopmental models of reading and reading disability are discussed, including possible links of choline and glutamate to white matter anomalies and hyperexcitability. These findings point to new directions for research on gene-brain-behavior pathways in human studies of reading disability.

Background: Deep learning‐based methods have been successfully applied to MRI image registration. However, there is a lack of deep learning‐based registration methods for magnetic resonance spectroscopy (MRS) spectral registration (SR). Purpose: To investigate a convolutional neural network‐based SR (CNN‐SR) approach for simultaneous frequency‐and‐phase correction (FPC) of single‐voxel Meshcher–Garwood point‐resolved spectroscopy (MEGA‐PRESS) MRS data. Study Type: Retrospective. Subjects: Forty thousand simulated MEGA‐PRESS datasets generated from FID Appliance (FID‐A) were used and split into the following: 32,000/4000/4000 for training/validation/testing. A 101 MEGA‐PRESS medial parietal lobe data retrieved from the Big GABA were used as the in vivo datasets. Field Strength/Sequence: 3T, MEGA‐PRESS. Assessment: Evaluation of frequency and phase offsets mean absolute errors were performed for the simulation dataset. Evaluation of the choline interval variance was performed for the in vivo dataset. The magnitudes of the offsets introduced were −20 to 20 Hz and −90° to 90° and were uniformly distributed for the simulation dataset at different signal‐to‐noise ratio (SNR) levels. For the in vivo dataset, different additional magnitudes of offsets were introduced: small offsets (0–5 Hz; 0–20°), medium offsets (5–10 Hz; 20–45°), and large offsets (10–20 Hz; 45–90°). Statistical Tests: Two‐tailed paired t‐tests for model performances in the simulation and in vivo datasets were used and a P‐value <0.05 was considered statistically significant. Results: CNN‐SR model was capable of correcting frequency offsets (0.014 ± 0.010 Hz at SNR 20 and 0.058 ± 0.050 Hz at SNR 2.5 with line broadening) and phase offsets (0.104 ± 0.076° at SNR 20 and 0.416 ± 0.317° at SNR 2.5 with line broadening). Using in vivo datasets, CNN‐SR achieved the best performance without (0.000055 ± 0.000054) and with different magnitudes of additional frequency and phase offsets (i.e., 0.000062 ± 0.000068 at small, −0.000033 ± 0.000023 at medium, 0.000067 ± 0.000102 at large) applied. Data Conclusion: The proposed CNN‐SR method is an efficient and accurate approach for simultaneous FPC of single‐voxel MEGA‐PRESS MRS data. Evidence Level: 4 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]