Quantitative fMRI and oxidative neuroenergetics

Challenges of Investigating Compartmentalized Brain Energy Metabolism Using Nuclear Magnetic Resonance Spectroscopy in vivo

Brain function requires continuous energy supply. Thus, unraveling brain metabolic regulation is critical not only for our basic understanding of overall brain function, but also for the cellular basis of functional neuroimaging techniques. While it is known that brain energy metabolism is exquisitely compartmentalized between astrocytes and neurons, the metabolic and neuro-energetic basis of brain activity is far from fully understood. 1H nuclear magnetic resonance (NMR) spectroscopy has been widely used to detect variations in metabolite levels, including glutamate and GABA, while 13C NMR spectroscopy has been employed to study metabolic compartmentation and to determine metabolic rates coupled brain activity, focusing mainly on the component corresponding to excitatory glutamatergic neurotransmission. The rates of oxidative metabolism in neurons and astrocytes are both associated with the rate of the glutamate-glutamine cycle between neurons and astrocytes. However, any possible correlation between energy metabolism pathways and the inhibitory GABAergic neurotransmission rate in the living brain remains to be experimentally demonstrated. That is due to low GABA levels, and the consequent challenge of determining GABAergic rates in a non-invasive manner. This brief review surveys the state-of-the-art analyses of energy metabolism in neurons and astrocytes contributing to glutamate and GABA synthesis using 13C NMR spectroscopy in vivo, and identifies limitations that need to be overcome in future studies.

In vivo neuropil density from anatomical MRI and machine learning

Brain energy budgets specify metabolic costs emerging from underlying mechanisms of cellular and synaptic activities. While current bottom-up energy budgets use prototypical values of cellular density and synaptic density, predicting metabolism from a person's individualized neuropil density would be ideal. We hypothesize that in vivo neuropil density can be derived from magnetic resonance imaging (MRI) data, consisting of longitudinal relaxation (T1) MRI for gray/white matter distinction and diffusion MRI for tissue cellularity (apparent diffusion coefficient, ADC) and axon directionality (fractional anisotropy, FA). We present a machine learning algorithm that predicts neuropil density from in vivo MRI scans, where ex vivo Merker staining and in vivo synaptic vesicle glycoprotein 2A Positron Emission Tomography (SV2A-PET) images were reference standards for cellular and synaptic density, respectively. We used Gaussian-smoothed T1/ADC/FA data from 10 healthy subjects to train an artificial neural network, subsequently used to predict cellular and synaptic density for 54 test subjects. While excellent histogram overlaps were observed both for synaptic density (0.93) and cellular density (0.85) maps across all subjects, the lower spatial correlations both for synaptic density (0.89) and cellular density (0.58) maps are suggestive of individualized predictions. This proof-of-concept artificial neural network may pave the way for individualized energy atlas prediction, enabling microscopic interpretations of functional neuroimaging data.

Interictal high-frequency oscillations, spikes, and connectivity profiles: A fingerprint of epileptogenic brain pathologies

OBJECTIVE

Focal cortical dysplasia (FCD), hippocampal sclerosis (HS), nonspecific gliosis (NG), and normal tissue (NT) comprise the majority of histopathological results of surgically treated drug-resistant epilepsy patients. Epileptic spikes, high-frequency oscillations (HFOs), and connectivity measures are valuable biomarkers of epileptogenicity. The question remains whether they could also be utilized for preresective differentiation of the underlying brain pathology. This study explored spikes and HFOs together with functional connectivity in various epileptogenic pathologies.

METHODS

Interictal awake stereoelectroencephalographic recordings of 33 patients with focal drug-resistant epilepsy with seizure-free postoperative outcomes were analyzed (15 FCD, 8 HS, 6 NT, and 4 NG). Interictal spikes and HFOs were automatically identified in the channels contained in the overlap of seizure onset zone and resected tissue. Functional connectivity measures (relative entropy, linear correlation, cross-correlation, and phase consistency) were computed for neighboring electrode pairs.

RESULTS

Statistically significant differences were found between the individual pathologies in HFO rates, spikes, and their characteristics, together with functional connectivity measures, with the highest values in the case of HS and NG/NT. A model to predict brain pathology based on all interictal measures achieved up to 84.0% prediction accuracy.

SIGNIFICANCE

The electrophysiological profile of the various epileptogenic lesions in epilepsy surgery patients was analyzed. Based on this profile, a predictive model was developed. This model offers excellent potential to identify the nature of the underlying lesion prior to resection. If validated, this model may be particularly valuable for counseling patients, as depending on the lesion type, different outcomes are achieved after epilepsy surgery.

Reproducibility of 3D MRSI for imaging human brain glucose metabolism using direct (2H) and indirect (1H) detection of deuterium labeled compounds at 7T and clinical 3T

INTRODUCTION

Deuterium metabolic imaging (DMI) and quantitative exchange label turnover (QELT) are novel MR spectroscopy techniques for non-invasive imaging of human brain glucose and neurotransmitter metabolism with high clinical potential. Following oral or intravenous administration of non-ionizing [6,6'-2H2]-glucose, its uptake and synthesis of downstream metabolites can be mapped via direct or indirect detection of deuterium resonances using 2H MRSI (DMI) and 1H MRSI (QELT), respectively. The purpose of this study was to compare the dynamics of spatially resolved brain glucose metabolism, i.e., estimated concentration enrichment of deuterium labeled Glx (glutamate+glutamine) and Glc (glucose) acquired repeatedly in the same cohort of subjects using DMI at 7T and QELT at clinical 3T.

METHODS

Five volunteers (4 m/1f) were scanned in repeated sessions for 60 min after overnight fasting and 0.8 g/kg oral [6,6'-2H2]-glucose administration using time-resolved 3D 2H FID-MRSI with elliptical phase encoding at 7T and 3D 1H FID-MRSI with a non-Cartesian concentric ring trajectory readout at clinical 3T.

RESULTS

One hour after oral tracer administration regionally averaged deuterium labeled Glx4 concentrations and the dynamics were not significantly different over all participants between 7T 2H DMI and 3T 1H QELT data for GM (1.29±0.15 vs. 1.38±0.26 mM, p=0.65 & 21±3 vs. 26±3 µM/min, p=0.22) and WM (1.10±0.13 vs. 0.91±0.24 mM, p=0.34 & 19±2 vs. 17±3 µM/min, p=0.48). Also, the observed time constants of dynamic Glc6 data in GM (24±14 vs. 19±7 min, p=0.65) and WM (28±19 vs. 18±9 min, p=0.43) dominated regions showed no significant differences. Between individual 2H and 1H data points a weak to moderate negative correlation was observed for Glx4 concentrations in GM (r=-0.52, p<0.001), and WM (r=-0.3, p<0.001) dominated regions, while a strong negative correlation was observed for Glc6 data GM (r=-0.61, p<0.001) and WM (r=-0.70, p<0.001).

CONCLUSION

This study demonstrates that indirect detection of deuterium labeled compounds using 1H QELT MRSI at widely available clinical 3T without additional hardware is able to reproduce absolute concentration estimates of downstream glucose metabolites and the dynamics of glucose uptake compared to 2H DMI data acquired at 7T. This suggests significant potential for widespread application in clinical settings especially in environments with limited access to ultra-high field scanners and dedicated RF hardware.

1H magnetic resonance spectroscopic imaging of deuterated glucose and of neurotransmitter metabolism at 7 T in the human brain

Impaired glucose metabolism in the brain has been linked to several neurological disorders. Positron emission tomography and carbon-13 magnetic resonance spectroscopic imaging (MRSI) can be used to quantify the metabolism of glucose, but these methods involve exposure to radiation, cannot quantify downstream metabolism, or have poor spatial resolution. Deuterium MRSI (2H-MRSI) is a non-invasive and safe alternative for the quantification of the metabolism of 2H-labelled substrates such as glucose and their downstream metabolic products, yet it can only measure a limited number of deuterated compounds and requires specialized hardware. Here we show that proton MRSI (1H-MRSI) at 7 T has higher sensitivity, chemical specificity and spatiotemporal resolution than 2H-MRSI. We used 1H-MRSI in five volunteers to differentiate glutamate, glutamine, γ-aminobutyric acid and glucose deuterated at specific molecular positions, and to simultaneously map deuterated and non-deuterated metabolites. 1H-MRSI, which is amenable to clinically available magnetic-resonance hardware, may facilitate the study of glucose metabolism in the brain and its potential roles in neurological disorders.

Noninvasive 3-Dimensional 1 H-Magnetic Resonance Spectroscopic Imaging of Human Brain Glucose and Neurotransmitter Metabolism Using Deuterium Labeling at 3T : Feasibility and Interscanner Reproducibility

OBJECTIVES

Noninvasive, affordable, and reliable mapping of brain glucose metabolism is of critical interest for clinical research and routine application as metabolic impairment is linked to numerous pathologies, for example, cancer, dementia, and depression. A novel approach to map glucose metabolism noninvasively in the human brain has been presented recently on ultrahigh-field magnetic resonance (MR) scanners (≥7T) using indirect detection of deuterium-labeled glucose and downstream metabolites such as glutamate, glutamine, and lactate. The aim of this study was to demonstrate the feasibility to noninvasively detect deuterium-labeled downstream glucose metabolites indirectly in the human brain via 3-dimensional (3D) proton ( 1 H) MR spectroscopic imaging on a clinical 3T MR scanner without additional hardware.

MATERIALS AND METHODS

This prospective, institutional review board-approved study was performed in 7 healthy volunteers (mean age, 31 ± 4 years, 5 men/2 women) after obtaining written informed consent. After overnight fasting and oral deuterium-labeled glucose administration, 3D metabolic maps were acquired every ∼4 minutes with ∼0.24 mL isotropic spatial resolution using real-time motion-, shim-, and frequency-corrected echo-less 3D 1 H-MR spectroscopic Imaging on a clinical routine 3T MR system. To test the interscanner reproducibility of the method, subjects were remeasured on a similar 3T MR system. Time courses were analyzed using linear regression and nonparametric statistical tests. Deuterium-labeled glucose and downstream metabolites were detected indirectly via their respective signal decrease in dynamic 1 H MR spectra due to exchange of labeled and unlabeled molecules.

RESULTS

Sixty-five minutes after deuterium-labeled glucose administration, glutamate + glutamine (Glx) signal intensities decreased in gray/white matter (GM/WM) by -1.63 ± 0.3/-1.0 ± 0.3 mM (-13% ± 3%, P = 0.02/-11% ± 3%, P = 0.02), respectively. A moderate to strong negative correlation between Glx and time was observed in GM/WM ( r = -0.64, P < 0.001/ r = -0.54, P < 0.001), with 60% ± 18% ( P = 0.02) steeper slopes in GM versus WM, indicating faster metabolic activity. Other nonlabeled metabolites showed no significant changes. Excellent intrasubject repeatability was observed across scanners for static results at the beginning of the measurement (coefficient of variation 4% ± 4%), whereas differences were observed in individual Glx dynamics, presumably owing to physiological variation of glucose metabolism.

CONCLUSION

Our approach translates deuterium metabolic imaging to widely available clinical routine MR scanners without specialized hardware, offering a safe, affordable, and versatile (other substances than glucose can be labeled) approach for noninvasive imaging of glucose and neurotransmitter metabolism in the human brain.

Reproducibility of 3D MRSI for imaging human brain glucose metabolism using direct ( 2 H) and indirect ( 1 H) detection of deuterium labeled compounds at 7T and clinical 3T

Introduction

Deuterium metabolic imaging (DMI) and quantitative exchange label turnover (QELT) are novel MR spectroscopy techniques for non-invasive imaging of human brain glucose and neurotransmitter metabolism with high clinical potential. Following oral or intravenous administration of non-ionizing [6,6'- 2 H 2 ]-glucose, its uptake and synthesis of downstream metabolites can be mapped via direct or indirect detection of deuterium resonances using 2 H MRSI (DMI) and 1 H MRSI (QELT), respectively. The purpose of this study was to compare the dynamics of spatially resolved brain glucose metabolism, i.e., estimated concentration enrichment of deuterium labeled Glx (glutamate+glutamine) and Glc (glucose) acquired repeatedly in the same cohort of subjects using DMI at 7T and QELT at clinical 3T.

Methods

Five volunteers (4m/1f) were scanned in repeated sessions for 60 min after overnight fasting and 0.8g/kg oral [6,6'- 2 H 2 ]-glucose administration using time-resolved 3D 2 H FID-MRSI with elliptical phase encoding at 7T and 3D 1 H FID-MRSI with a non-Cartesian concentric ring trajectory readout at clinical 3T.

Results

One hour after oral tracer administration regionally averaged deuterium labeled Glx 4 concentrations and the dynamics were not significantly different over all participants between 7T 2 H DMI and 3T 1 H QELT data for GM (1.29±0.15 vs. 1.38±0.26 mM, p=0.65 & 21±3 vs. 26±3 µM/min, p=0.22) and WM (1.10±0.13 vs. 0.91±0.24 mM, p=0.34 & 19±2 vs. 17±3 µM/min, p=0.48). Also, the observed time constants of dynamic Glc 6 data in GM (24±14 vs. 19±7 min, p=0.65) and WM (28±19 vs. 18±9 min, p=0.43) dominated regions showed no significant differences. Between individual 2 H and 1 H data points a weak to moderate negative correlation was observed for Glx 4 concentrations in GM (r=-0.52, p<0.001), and WM (r=-0.3, p<0.001) dominated regions, while a strong negative correlation was observed for Glc 6 data GM (r=- 0.61, p<0.001) and WM (r=-0.70, p<0.001).

Conclusion

This study demonstrates that indirect detection of deuterium labeled compounds using 1 H QELT MRSI at widely available clinical 3T without additional hardware is able to reproduce absolute concentration estimates of downstream glucose metabolites and the dynamics of glucose uptake compared to 2 H DMI data acquired at 7T. This suggests significant potential for widespread application in clinical settings especially in environments with limited access to ultra-high field scanners and dedicated RF hardware.

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

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

The immune-stress/endocrine-redox-metabolic nature of psychosis' etiopathology; focus on the intersystemic pathways interactions

The evidence supporting the involvement of a number of systems in the neurobiological etiopathology of psychosis has recently grown exponentially. Indeed, the focus of research has changed from measuring solely neurotransmitters to estimating parameters from fields like immunity, stress/endocrine, redox, and metabolism. Yet, little is known regarding the exact role of each one of these fields on the formation of not only the brain neuropathological substrate in psychosis but also the associated general systemic pathology, in terms of causality directions. Research has shown deviations in the levels and/or function of basic effector molecules of the aforementioned fields namely cytokines, pro-/anti- oxidants, glucocorticoids, catecholamines, glucose, and lipids metabolites as well as kynurenines, in psychosis. Yet the evidence regarding their impact on neurotransmitters is minimal and the findings concerning these systems' interactions in the psychotic context are even more dispersed. The present review aims to draw holistically the frame of the hitherto known "players" in the field of psychosis' cellular pathobiology, with a particular focus on their in-between interactions.

Decreased but diverse activity of cortical and thalamic neurons in consciousness-impairing rodent absence seizures

Absence seizures are brief episodes of impaired consciousness, behavioral arrest, and unresponsiveness, with yet-unknown neuronal mechanisms. Here we report that an awake female rat model recapitulates the behavioral, electroencephalographic, and cortical functional magnetic resonance imaging characteristics of human absence seizures. Neuronally, seizures feature overall decreased but rhythmic firing of neurons in cortex and thalamus. Individual cortical and thalamic neurons express one of four distinct patterns of seizure-associated activity, one of which causes a transient initial peak in overall firing at seizure onset, and another which drives sustained decreases in overall firing. 40-60 s before seizure onset there begins a decline in low frequency electroencephalographic activity, neuronal firing, and behavior, but an increase in higher frequency electroencephalography and rhythmicity of neuronal firing. Our findings demonstrate that prolonged brain state changes precede consciousness-impairing seizures, and that during seizures distinct functional groups of cortical and thalamic neurons produce an overall transient firing increase followed by a sustained firing decrease, and increased rhythmicity.

Glutamatergic dysfunction in Schizophrenia

The NMDA-R hypofunction model of schizophrenia started with the clinical observation of the precipitation of psychotic symptoms in patients with schizophrenia exposed to PCP or ketamine. Healthy volunteers exposed to acute low doses of ketamine experienced mild psychosis but also negative and cognitive type symptoms reminiscent of the full clinical picture of schizophrenia. In rodents, acute systemic ketamine resulted in a paradoxical increase in extracellular frontal glutamate as well as of dopamine. Similar increase in prefrontal glutamate was documented with acute ketamine in healthy volunteers with 1H-MRS. Furthermore, sub-chronic low dose PCP lead to reductions in frontal dendritic tree density in rodents. In post-mortem ultrastructural studies in schizophrenia, a broad reduction in dendritic complexity and somal volume of pyramidal cells has been repeatedly described. This most likely accounts for the broad, subtle progressive cortical thinning described with MRI in- vivo. Additionally, prefrontal reductions in the obligatory GluN1 subunit of the NMDA-R has been repeatedly found in post-mortem tissue. The vast 1H-MRS literature in schizophrenia has documented trait-like small increases in glutamate concentrations in striatum very early in the illness, before antipsychotic treatment (the same structure where increased pre-synaptic release of dopamine has been reported with PET). The more recent genetic literature has reliably detected very small risk effects for common variants involving several glutamate-related genes. The pharmacological literature has followed two main tracks, directly informed by the NMDA-R hypo model: agonism at the glycine site (as mostly add-on studies targeting negative and cognitive symptoms); and pre-synaptic modulation of glutamatergic release (as single agents for acute psychosis). Unfortunately, both approaches have failed so far. There is little doubt that brain glutamatergic abnormalities are present in schizophrenia and that some of these are related to the etiology of the illness. The genetic literature directly supports a non- specific etiological role for glutamatergic dysfunction. Whether NMDA-R hypofunction as a specific mechanism accounts for any important component of the illness is still not evident. However, a glutamatergic model still has heuristic value to guide future research in schizophrenia. New tools to jointly examine brain glutamatergic, GABA-ergic and dopaminergic systems in-vivo, early in the illness, may lay the ground for a next generation of clinical trials that go beyond dopamine D2 blockade.

Mapping oxidative metabolism in the human brain with calibrated fMRI in health and disease

Conventional functional MRI (fMRI) with blood-oxygenation level dependent (BOLD) contrast is an important tool for mapping human brain activity non-invasively. Recent interest in quantitative fMRI has renewed the importance of oxidative neuroenergetics as reflected by cerebral metabolic rate of oxygen consumption (CMR_O2) to support brain function. Dynamic CMR_O2 mapping by calibrated fMRI require multi-modal measurements of BOLD signal along with cerebral blood flow (CBF) and/or volume (CBV). In human subjects this "calibration" is typically performed using a gas mixture containing small amounts of carbon dioxide and/or oxygen-enriched medical air, which are thought to produce changes in CBF (and CBV) and BOLD signal with minimal or no CMR_O2 changes. However non-human studies have demonstrated that the "calibration" can also be achieved without gases, revealing good agreement between CMR_O2 changes and underlying neuronal activity (e.g., multi-unit activity and local field potential). Given the simpler set-up of gas-free calibrated fMRI, there is evidence of recent clinical applications for this less intrusive direction. This up-to-date review emphasizes technological advances for such translational gas-free calibrated fMRI experiments, also covering historical progression of the calibrated fMRI field that is impacting neurological and neurodegenerative investigations of the human brain.

Current Status of Our Understanding for Brain Integrated Functions and its Energetics

Human/animal brain is a unique organ with substantially high metabolism but it contains no energy reserve that is the reason it requires continuous supply of O₂ and energy fluxes through CBF. The main source of energy remains glucose as the other biomolecules do not able to cross the blood-brain barrier. The speed of glucose metabolism is heterogeneous throughout the brain. One of the major flux consumption is Neuron-astrocyte cycling of glutamate and glutamine in glutamatergic neurons (approximately 80% of glucose metabolism in brain). The quantification of cellular glucose and other related substrate in resting, activated state can be analyzed through [¹⁸ F]FDG -positron-emission tomography (studying CMRglc) and [¹³ C/³¹P -MRS: for neuroenergetics & neurotransmitter cycling &³¹P-MRS: for energy induction & redox state). Merging basic in vitro studies with these techniques will help to develop new treatment paradigms for human brain diseased conditions.

Human brain functional MRS reveals interplay of metabolites implicated in neurotransmission and neuroenergetics

While functional MRI (fMRI) localizes brain activation and deactivation, functional MRS (fMRS) provides insights into the underlying metabolic conditions. There is much interest in measuring task-induced and resting levels of metabolites implicated in neuroenergetics (e.g., lactate, glucose, or β-hydroxybutyrate (BHB)) and neurotransmission (e.g., γ-aminobutyric acid (GABA) or pooled glutamate and glutamine (Glx)). Ultra-high magnetic field (e.g., 7T) has boosted the fMRS quantification precision, reliability, and stability of spectroscopic observations using short echo-time (TE) 1H-MRS techniques. While short TE 1H-MRS lacks sensitivity and specificity for fMRS at lower magnetic fields (e.g., 3T or 4T), most of these metabolites can also be detected by J-difference editing (JDE) 1H-MRS with longer TE to filter overlapping resonances. The 1H-MRS studies show that JDE can detect GABA, Glx, lactate, and BHB at 3T, 4T and 7T. Most recently, it has also been demonstrated that JDE 1H-MRS is capable of reliable detection of metabolic changes in different brain areas at various magnetic fields. Combining fMRS measurements with fMRI is important for understanding normal brain function, but also clinically relevant for mechanisms and/or biomarkers of neurological and neuropsychiatric disorders. We provide an up-to-date overview of fMRS research in the last three decades, both in terms of applications and technological advances. Overall the emerging fMRS techniques can be expected to contribute substantially to our understanding of metabolism for brain function and dysfunction.

Abnormal Large-Scale Neuronal Network in High Myopia

Aim

Resting state functional magnetic resonance imaging (rs-fMRI) was used to analyze changes in functional connectivity (FC) within various brain networks and functional network connectivity (FNC) among various brain regions in patients with high myopia (HM).

Methods

rs-fMRI was used to scan 82 patients with HM (HM group) and 59 healthy control volunteers (HC group) matched for age, sex, and education level. Fourteen resting state networks (RSNs) were extracted, of which 11 were positive. Then, the FCs and FNCs of RSNs in HM patients were examined by independent component analysis (ICA).

Results

Compared with the HC group, FC in visual network 1 (VN1), dorsal attention network (DAN), auditory network 2 (AN2), visual network 3 (VN3), and sensorimotor network (SMN) significantly increased in the HM group. FC in default mode network 1 (DMN1) significantly decreased. Furthermore, some brain regions in default mode network 2 (DMN2), default mode network 3 (DMN3), auditory network 1 (AN1), executive control network (ECN), and significance network (SN) increased while others decreased. FNC analysis also showed that the network connection between the default mode network (DMN) and cerebellar network (CER) was enhanced in the HM group.

Conclusion

Compared with HCs, HM patients showed neural activity dysfunction within and between specific brain networks, particularly in the DMN and CER. Thus, HM patients may have deficits in visual, cognitive, and motor balance functions.

Differences in the Level of Functional Fitness and Precise Hand Movements of People with and without Cognitive Disorders

OBJECTIVES

to assess and compare the gross and fine motor skills in people with identified cognitive impairment and in people from the control group.

METHOD

The research was conducted at the Center of Dementia-Related Diseases, involved participants with (n = 39) and without (n = 29) cognitive disorders. Fast, precise hand movements were measured via Vienna System Test. The up-and-go, chair-stand, 6-minute walk tests were used to assess functional fitness. The results for participants with and without cognitive disorders were compared.

RESULTS

People from both groups do not differ significantly in terms of the level of condition-based functional fitness. Participants with cognitive disorders achieve worse results in hand coordination tests which are more complex and require both speed and accuracy of hand movements.

DISCUSSION

The deterioration of precise hand movements with the correct functional efficiency may indicate degenerative changes in brain areas associated with complex thought processes, conceptual thinking, and may lead to dementia.

Metabolic underpinnings of activated and deactivated cortical areas in human brain

Neuroimaging with functional MRI (fMRI) identifies activated and deactivated brain regions in task-based paradigms. These patterns of (de)activation are altered in diseases, motivating research to understand their underlying biochemical/biophysical mechanisms. Essentially, it remains unknown how aerobic metabolism of glucose to lactate (aerobic glycolysis) and excitatory-inhibitory balance of glutamatergic and GABAergic neuronal activities vary in these areas. In healthy volunteers, we investigated metabolic distinctions of activating visual cortex (VC, a task-positive area) using a visual task and deactivating posterior cingulate cortex (PCC, a task-negative area) using a cognitive task. We used fMRI-guided J-edited functional MRS (fMRS) to measure lactate, glutamate plus glutamine (Glx) and γ-aminobutyric acid (GABA), as indicators of aerobic glycolysis and excitatory-inhibitory balance, respectively. Both lactate and Glx increased upon activating VC, but did not change upon deactivating PCC. Basal GABA was negatively correlated with BOLD responses in both brain areas, but during functional tasks GABA decreased in VC upon activation and GABA increased in PCC upon deactivation, suggesting BOLD responses in relation to baseline are impacted oppositely by task-induced inhibition. In summary, opposite relations between BOLD response and GABAergic inhibition, and increases in aerobic glycolysis and glutamatergic activity distinguish the BOLD response in (de)activated areas.

Midlife Chronological and Endocrinological Transitions in Brain Metabolism: System Biology Basis for Increased Alzheimer's Risk in Female Brain

Decline in brain glucose metabolism is a hallmark of late-onset Alzheimer’s disease (LOAD). Comprehensive understanding of the dynamic metabolic aging process in brain can provide insights into windows of opportunities to promote healthy brain aging. Chronological and endocrinological aging are associated with brain glucose hypometabolism and mitochondrial adaptations in female brain. Using a rat model recapitulating fundamental features of the human menopausal transition, results of transcriptomic analysis revealed stage-specific shifts in bioenergetic systems of biology that were paralleled by bioenergetic dysregulation in midlife aging female brain. Transcriptomic profiles were predictive of outcomes from unbiased, discovery-based metabolomic and lipidomic analyses, which revealed a dynamic adaptation of the aging female brain from glucose centric to utilization of auxiliary fuel sources that included amino acids, fatty acids, lipids, and ketone bodies. Coupling between brain and peripheral metabolic systems was dynamic and shifted from uncoupled to coupled under metabolic stress. Collectively, these data provide a detailed profile across transcriptomic and metabolomic systems underlying bioenergetic function in brain and its relationship to peripheral metabolic responses. Mechanistically, these data provide insights into the complex dynamics of chronological and endocrinological bioenergetic aging in female brain. Translationally, these findings are predictive of initiation of the prodromal / preclinical phase of LOAD for women in midlife and highlight therapeutic windows of opportunity to reduce the risk of late-onset Alzheimer’s disease.

Pioglitazone improves working memory performance when administered in chronic TBI

Traumatic brain injury (TBI) is a leading cause of long-term disability in the United States. Even in comparatively mild injuries, cognitive and behavioral symptoms can persist for years, and there are currently no established strategies for mitigating symptoms in chronic injury. A key feature of TBI-induced damage in acute and chronic injury is disruption of metabolic pathways. As neurotransmission, and therefore cognition, are highly dependent on the supply of energy, we hypothesized that modulating metabolic activity could help restore behavioral performance even when treatment was initiated weeks after TBI. We treated rats with pioglitazone, a FDA-approved drug for diabetes, beginning 46 days after lateral fluid percussion injury and tested working memory performance in the radial arm maze (RAM) after 14 days of treatment. Pioglitazone treated TBI rats performed significantly better in the RAM test than untreated TBI rats, and similarly to control animals. While hexokinase activity in hippocampus was increased by pioglitazone treatment, there was no upregulation of either the neuronal glucose transporter or hexokinase enzyme expression. Expression of glial markers GFAP and Iba-1 were also not influenced by pioglitazone treatment. These studies suggest that targeting brain metabolism, in particular hippocampal metabolism, may be effective in alleviating cognitive symptoms in chronic TBI.

Mitochondria, Metabolism, and Redox Mechanisms in Psychiatric Disorders

Significance: Our current knowledge of the pathophysiology and molecular mechanisms causing psychiatric disorders is modest, but genetic susceptibility and environmental factors are central to the etiology of these conditions. Autism, schizophrenia, bipolar disorder and major depressive disorder show genetic gene risk overlap and share symptoms and metabolic comorbidities. The identification of such common features may provide insights into the development of these disorders. Recent Advances: Multiple pieces of evidence suggest that brain energy metabolism, mitochondrial functions and redox balance are impaired to various degrees in psychiatric disorders. Since mitochondrial metabolism and redox signaling can integrate genetic and environmental environmental factors affecting the brain, it is possible that they are implicated in the etiology and progression of psychiatric disorders. Critical Issue: Evidence for direct links between cellular mitochondrial dysfunction and disease features are missing. Future Directions: A better understanding of the mitochondrial biology and its intracellular connections to the nuclear genome, the endoplasmic reticulum and signaling pathways, as well as its role in intercellular communication in the organism, is still needed. This review focuses on the findings that implicate mitochondrial dysfunction, the resultant metabolic changes and oxidative stress as important etiological factors in the context of psychiatric disorders. We also propose a model where specific pathophysiologies of psychiatric disorders depend on circuit-specific impairments of mitochondrial dysfunction and redox signaling at specific developmental stages.

Selected Topics Relating to Functional MRI Study of the Brain

The authors selected some interesting current topics among many in the field of functional MRI (fMRI) of the brain. The selection was based on authours' immediate interests in exploring these aspects further; the topics are presented and discussed along with their perspectives. If progress can be made in these areas, it would be very advantageous to the field of brain research. The topics are (I) Detectable MRI signals in response to functional activity of the brain, including the current status of neurocurrent MRI; (II) Vascular-dependent and vascular-independent MRI signals, leading to the distinction of functional and structural MRI; (III) Functional specificity and functional connectivity of local sites, including differences between task-fMRI and resting state fMRI; (IV) Functional networks: an example of application to assessing the vocational aptitude test by fMRI; (V) Neural oscillation relevant to the formation of fMRI signals and of networks; (VI) Upgrading fMRI to "information-content-reflecting" fMRI, discussed as one of the prospects of near-future fMRI.

A Non-cognitive Behavioral Model for Interpreting Functional Neuroimaging Studies

The dominant model for interpreting brain imaging experiments, which we refer to as the Standard Cognitive Model (SCM), assumes that the brain is organized in support of mental processes that control behavior. However, functional neuroimaging experiments of cognitive tasks have not shown clear anatomic segregation between mental processes originally proposed by this model. This failing has been blamed on limitations in imaging technology and non-linearity in the brain's implementation of these processes. However, the validity of the underlying cognitive models used to describe the brain has rarely been questioned or directly tested against imaging results. We propose an alternative model of brain function, that we term the Non-cognitive Behavioral Model (NBM), which correlates observed human behavior directly with measured brain activity without making assumptions about intervening cognitive processes. Our model derives from behavioral psychology but is extended to include brain activity, in addition to behavior, as observables. A further extension is the role of neuroplasticity, as opposed to innate cognitive processes, in developing the brain's support of cognitive behavior. We present the theoretical basis with which the SCM maps cognitive processes onto functional magnetic resonance and positron emission tomography images and compare and contrast with the NBM. We also describe how the NBM can be used experimentally to study how the brain supports behavior. Two applications are presented that support the usefulness of the NBM. In one, the NBM use of the total functional imaging signal (not just the differences between states) provides a stronger correlation of neural activity with the behavioral state of consciousness than the SCM approach in both anesthesia and coma. The second example reviews studies of facial and object recognition that provide evidence for the NBM proposal that neuroplasticity and experience play key roles in the brain's support of recognition and other behaviors. The conclusions regarding neuroplasticity are then generalized to explain the incomplete functional segregation observed in the application of the SCM to neuroimaging.

A Revised Mental Energy Hypothesis of the g Factor in Light of Recent Neuroscience

The article proposes a revised mental energy hypothesis for the emergence of the g factor. Charles E. Spearman interpreted the g factor as a kind of domain-general mental energy. Nowadays, it is known that the energy currency of organisms is the chemical energy transporter adenosine triphosphate (ATP). ATP is produced by complex metabolic processes (mainly by glucose oxidation), and most of it in the human brain is used for neural signaling. There are substantial individual differences in the metabolic properties of the brain, which lead to different levels of energy production. It is thereby proposed to place more emphasis on individual differences of metabolic functions in intelligence research. Neuroscientific findings suggest that increased brain metabolism and, therefore, higher energy-production levels facilitate better performance on different cognitive tasks. These findings are not in conflict with the refined neural efficiency hypothesis. In addition, building on Dennis Garlick’s proposal that neural plasticity is the core process underlying the development of the g factor, it is illustrated why ATP is crucial for neural plasticity. Taken together, the direct effects of level of energy production on cognitive performance and the relations with neural plasticity suggest an important role in the emergence of the g factor.

A Longitudinal Multimodal Neuroimaging Study to Examine Relationships Between Resting State Glutamate and Task Related BOLD Response in Schizophrenia

Previous studies have observed impairments in both brain function and neurometabolite levels in schizophrenia. In this study, we investigated the relationship between brain activity and neurochemistry in off-medication patients with schizophrenia and if this relationship is altered following antipsychotic medication by combining proton magnetic resonance spectroscopy (1H-MRS) with functional magnetic resonance imaging (fMRI). We used single voxel MRS acquired in the bilateral dorsal anterior cingulate cortex (ACC) and fMRI during performance of a Stroop color-naming task in 22 patients with schizophrenia (SZ), initially off-medication and after a 6-week course of risperidone, and 20 matched healthy controls (HC) twice, 6 weeks apart. We observed a significant decrease in ACC glutamate + glutamine (Glx)/Creatine (Cr) levels in medicated SZ patients compared to HC but not compared to their off-medication baseline. In off-medication SZ, the relationship between ACC Glx/Cr levels and the blood oxygen level-dependent (BOLD) response in regions of the salience network (SN) and posterior default mode network (DMN) was opposite than of HC. After 6 weeks, the relationship between Glx and the BOLD response was still opposite between the groups; however for both groups the direction of the relationship changed from baseline to week 6. These results suggest a mechanism whereby alterations in the relationship between cortical glutamate and BOLD response is disrupting the modulation of major neural networks subserving cognitive processes, potentially affecting cognition. While these relationships appear to normalize with treatment in patients, the interpretations of the results are confounded by significant group differences in Glx levels, as well as the variability of the relationship between Glx and BOLD response in HC over time, which may be driven by factors including habituation to task or scanner environment.

Functional MRS with J-edited lactate in human motor cortex at 4 T

While functional MRI (fMRI) localizes regions of brain activation, functional MRS (fMRS) provides insights into metabolic underpinnings. Previous fMRS studies detected task-induced lactate increase using short echo-time non-edited ¹H-MRS protocols, where lactate changes depended on accurate exclusion of overlapping lactate and lipid/macromolecule signals. Because long echo-time J-difference ¹H-MRS detection of lactate is less susceptible to this shortcoming, we posited if J-edited fMRS protocol could reliably detect metabolic changes in the human motor cortex during a finger-tapping paradigm in relation to a reliable measure of basal lactate. Our J-edited fMRS protocol at 4T was guided by an fMRI pre-scan to determine the ¹H-MRS voxel placement in the motor cortex. Because lactate and β-hydroxybutyrate (BHB) follow similar J-evolution profiles we observed both metabolites in all spectra, but only lactate showed reproducible task-induced modulation by 0.07 mM from a basal value of 0.82 mM. These J-edited fMRS results demonstrate good sensitivity and specificity for task-induced lactate modulation, suggesting that J-edited fMRS studies can be used to investigate the metabolic underpinning of human cognition by measuring lactate dynamics associated with activation and deactivation fMRI paradigms across brain regions at magnetic field lower than 7T.

Evaluating the gray and white matter energy budgets of human brain function

The insatiable appetite for energy to support human brain function is mainly supplied by glucose oxidation (CMR_glc(ox)). But how much energy is consumed for signaling and nonsignaling processes in gray/white matter is highly debated. We examined this issue by combining metabolic measurements of gray/white matter and a theoretical calculation of bottom-up energy budget using biophysical properties of neuronal/glial cells in conjunction with species-exclusive electrophysiological and morphological data. We calculated a CMR_glc(ox)-derived budget and confirmed it with experimental results measured by PET, autoradiography, ¹³C-MRS, and electrophysiology. Several conserved principles were observed regarding the energy costs for brain's signaling and nonsignaling components in both human and rat. The awake resting cortical signaling processes and mass-dependent nonsignaling processes, respectively, demand ∼70% and ∼30% of CMR_glc(ox). Inhibitory neurons and glia need 15-20% of CMR_glc(ox), with the rest demanded by excitatory neurons. Nonsignaling demands dominate in white matter, in near opposite contrast to gray matter demands. Comparison between ¹³C-MRS data and calculations suggests ∼1.2 Hz glutamatergic signaling rate in the awake human cortex, which is ∼4 times lower than signaling in the rat cortex. Top-down validated bottom-up budgets could allow computation of anatomy-based CMR_glc(ox) maps and accurate cellular level interpretation of brain metabolic imaging.

Impact of Global Mean Normalization on Regional Glucose Metabolism in the Human Brain

Because the human brain consumes a disproportionate fraction of the resting body's energy, positron emission tomography (PET) measurements of absolute glucose metabolism (CMR_glc) 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 CMR_glc 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 CMR_glc alterations compared to control were detected in all conditions except in congenitally blind where regional CMR_glc variations were detected in the visual cortex. However, GMN introduced regional and bidirectional CMR_glc 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 CMR_glc alterations induced by opening eyes, sedation, and varying consciousness but also detected regional CMR_glc variations in the congenitally blind. These results caution the use of GMN upon PET-measured CMR_glc data in health and disease.

Advances in Imaging Brain Metabolism

Metabolism is central to neuroimaging because it can reveal pathways by which neuronal and glial cells use nutrients to fuel their growth and function. We focus on advanced magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) methods used in brain metabolic studies. ¹⁷O-MRS and ³¹P-MRS, respectively, provide rates of oxygen use and ATP synthesis inside mitochondria, whereas ¹⁹F-MRS enables measurement of cytosolic glucose metabolism. Calibrated functional MRI (fMRI), an advanced form of fMRI that uses contrast generated by deoxyhemoglobin, provides maps of oxygen use that track neuronal firing across brain regions. ¹³C-MRS is the only noninvasive method of measuring both glutamatergic neurotransmission and cell-specific energetics with signaling and nonsignaling purposes. Novel MRI contrasts, arising from endogenous diamagnetic agents and exogenous paramagnetic agents, permit pH imaging of glioma. Overall, these magnetic resonance methods for imaging brain metabolism demonstrate translational potential to better understand brain disorders and guide diagnosis and treatment.

Cerebral Angioplasticity: The Anatomical Contribution to Ensuring Appropriate Oxygen Transport to Brain

In order to maintain proper function, mammalian brain requires a significant fraction of the energy provided through whole body oxygen consumption and oxidative phosphorylation. This has been fairly well known for a long time. More recently there has been an increased appreciation that, while whole brain blood flow remains fairly constant, there are large regional changes in local blood flow to account for spatial and temporal heterogeneity of neuronal activity. This latter phenomenon requires an extensive regulatory system for local oxygen delivery that involves arteriolar and capillary control mechanisms. The ISOTT has been a major contributor to the study of oxygen supply and demand through studies of the mechanisms of vascular dilation and constriction in response to energy expenditure and availability of substrate and oxygen. Nevertheless, it has become clear in the past few decades that in addition to acute, physiological responses to energy demand and oxygen/substrate availability, there are regulatory mechanisms that are continuously operating to control the capillary distribution over a time course of weeks. This process of "angioplasticity" results in the gradual acclimatization of the brain capillary bed to prolonged changes in oxygen/substrate availability and/or neuronal activity patterns. Angioplasticity is primarily regulated through the hypoxia inducible transcription factor, acting as a detector of the balance between oxygen delivery and energy demand at the level of the cell redox state, controlling vascular endothelial growth factor production which helps determine capillary density in consort with the cyclooxygenase-2/angiopoietin-2 pathway that controls endothelial cell junction mechanical stability. We can conclude that the structure-function of brain capillaries is regulated during prolonged challenges to energy supply-demand balance within the physiological range. We can conclude that over the physiological range of ambient oxygen, brain capillary density is proportional to fraction inspired oxygen. The primary mechanisms for regulation of brain capillary density are HIF-1/VEGF and COX-2/PGE2/ang-2 pathways of angiogenesis and angiolysis.

Metabolic drift in the aging brain

Brain function is highly dependent upon controlled energy metabolism whose loss heralds cognitive impairments. This is particularly notable in the aged individuals and in age-related neurodegenerative diseases. However, how metabolic homeostasis is disrupted in the aging brain is still poorly understood. Here we performed global, metabolomic and proteomic analyses across different anatomical regions of mouse brain at different stages of its adult lifespan. Interestingly, while severe proteomic imbalance was absent, global-untargeted metabolomics revealed an energy metabolic drift or significant imbalance in core metabolite levels in aged mouse brains. Metabolic imbalance was characterized by compromised cellular energy status (NAD decline, increased AMP/ATP, purine/pyrimidine accumulation) and significantly altered oxidative phosphorylation and nucleotide biosynthesis and degradation. The central energy metabolic drift suggests a failure of the cellular machinery to restore metabostasis (metabolite homeostasis) in the aged brain and therefore an inability to respond properly to external stimuli, likely driving the alterations in signaling activity and thus in neuronal function and communication.

Neural and metabolic basis of dynamic resting state fMRI

Resting state fMRI (rsfMRI) as a technique showed much initial promise for use in psychiatric and neurological diseases where diagnosis and treatment were difficult. To realize this promise, many groups have moved towards examining "dynamic rsfMRI," which relies on the assumption that rsfMRI measurements on short time scales remain relevant to the underlying neural and metabolic activity. Many dynamic rsfMRI studies have demonstrated differences between clinical or behavioral groups beyond what static rsfMRI measured, suggesting a neurometabolic basis. Correlative studies combining dynamic rsfMRI and other physiological measurements have supported this. However, they also indicate multiple mechanisms and, if using correlation alone, it is difficult to separate cause and effect. Hypothesis-driven studies are needed, a few of which have begun to illuminate the underlying neurometabolic mechanisms that shape observed differences in dynamic rsfMRI. While the number of potential noise sources, potential actual neurometabolic sources, and methodological considerations can seem overwhelming, dynamic rsfMRI provides a rich opportunity in systems neuroscience. Even an incrementally better understanding of the neurometabolic basis of dynamic rsfMRI would expand rsfMRI's research and clinical utility, and the studies described herein take the first steps on that path forward.

Age-related changes in hand dominance and functional asymmetry in older adults

The aim of the study was to investigate fine motor performance and ascertain age-related changes in laterality between the dominant and non-dominant hand. A representative sample of 635 adults (144 males and 491 females) aged 50 years and over completed a test battery MLS (Motor Performance Series) to assess a broad range of hand functions. Functional asymmetry was observed in all four motor tests (postural tremor, aiming, tapping, and inserting long pins). Significant differences between the dominant and non-dominant hand were obtained in both sexes across all age groups, except in the oldest female group (age >70) for the aiming (number of hits and errors) and postural tremor (number of errors) tasks. These differences in age-related changes may be attributed to hemispheric asymmetry, environmental factors, or use-dependent plasticity. Conflicting evidence in the literature warrants additional research to better explain age-related alterations of hand dominance and manual performance in old age.

Energy metabolism in the rat cortex under thiopental anaesthesia measured In Vivo by 13 C MRS

Barbiturates, commonly used as general anaesthetics, depress neuronal activity and thus cerebral metabolism. Moreover, they are likely to disrupt the metabolic support of astrocytes to neurons, as well as the uptake of nutrients from circulation. By employing ¹³ C magnetic resonance spectroscopy (MRS) in vivo at high magnetic field, we characterized neuronal and astrocytic pathways of energy metabolism in the rat cortex under thiopental anaesthesia. The neuronal tricarboxylic acid (TCA) cycle rate was 0.46 ± 0.02 µmol/g/min, and the rate of the glutamate-glutamine cycle was 0.09 ± 0.02 µmol/g/min. In astrocytes, the TCA cycle rate was 0.16 ± 0.02 µmol/g/min, accounting for a quarter of whole brain glucose oxidation, pyruvate carboxylase rate was 0.02 ± 0.01 µmol/g/min, and glutamine synthetase was 0.12 ± 0.01 µmol/g/min. Relative to previous experiments under light α-chloralose anaesthesia, thiopental reduced oxidative metabolism in neurons and even more so in astrocytes. Interestingly, total oxidative metabolism in the cortex under thiopental anaesthesia surpassed the rate of pyruvate production by glycolysis, indicating substantial utilisation of substrates other than glucose, likely plasma lactate. © 2017 Wiley Periodicals, Inc.

Lactate and glutamate dynamics during prolonged stimulation of the rat barrel cortex suggest adaptation of cerebral glucose and oxygen metabolism

A better understanding of BOLD responses stems from a better characterization of the brain's ability to metabolize glucose and oxygen. Non-invasive techniques such as functional magnetic resonance spectroscopy (fMRS) have thus been developed allowing for the reproducible assessment of metabolic changes during barrel cortex (S1BF) activations in rats. The present study aimed at further exploring the role of neurotransmitters on local and temporal changes in vascular and metabolic function in S1BF. fMRS and fMRI data were acquired sequentially in α-chloralose anesthetized rats during 32-min rest and trigeminal nerve stimulation periods. During stimulation, concentrations of lactate (Lac) and glutamate (Glu) increased in S1BF by 0.23±0.05 and 0.34±0.05μmol/g respectively in S1BF. Dynamic analysis of metabolite concentrations allowed estimating changes in cerebral metabolic rates of glucose (ΔCMR_Glc) and oxygen (ΔCMR_O2). Findings confirmed a prevalence of oxidative metabolism during prolonged S1BF activation. Habituation led to a significant BOLD magnitude decline as a function of time while both total ΔCMR_Glc and ΔCMR_O2 remained constant revealing adaptation of glucose and oxygen metabolisms to support ongoing trigeminal nerve stimulation.

Adaptations of Prefrontal Brain Activity, Executive Functions, and Gait in Healthy Elderly Following Exergame and Balance Training: A Randomized-Controlled Study

During aging, the prefrontal cortex (PFC) undergoes age-dependent neuronal changes influencing cognitive and motor functions. Motor-learning interventions are hypothesized to ameliorate motor and cognitive deficits in older adults. Especially, video game-based physical exercise might have the potential to train motor in combination with cognitive abilities in older adults. The aim of this study was to compare conventional balance training with video game-based physical exercise, a so-called exergame, on the relative power (RP) of electroencephalographic (EEG) frequencies over the PFC, executive function (EF), and gait performance. Twenty-seven participants (mean age 79.2 ± 7.3 years) were randomly assigned to one of two groups. All participants completed 24 trainings including three times a 30 min session/week. The EEG measurements showed that theta RP significantly decreased in favor of the exergame group [L₍₁₄₎ = 6.23, p = 0.007]. Comparing pre- vs. post-test, EFs improved both within the exergame (working memory: z = -2.28, p = 0.021; divided attention auditory: z = -2.51, p = 0.009; divided attention visual: z = -2.06, p = 0.040; go/no-go: z = -2.55, p = 0.008; set-shifting: z = -2.90, p = 0.002) and within the balance group (set-shifting: z = -2.04, p = 0.042). Moreover, spatio-temporal gait parameters primarily improved within the exergame group under dual-task conditions (speed normal walking: z = -2.90, p = 0.002; speed fast walking: z = -2.97, p = 0.001; cadence normal walking: z = -2.97, p = 0.001; stride length fast walking: z = -2.69, p = 0.005) and within the balance group under single-task conditions (speed normal walking: z = -2.54, p = 0.009; speed fast walking: z = -1.98, p = 0.049; cadence normal walking: z = -2.79, p = 0.003). These results indicate that exergame training as well as balance training positively influence prefrontal cortex activity and/or function in varying proportion.

Molecular fMRI

Comprehensive analysis of brain function depends on understanding the dynamics of diverse neural signaling processes over large tissue volumes in intact animals and humans. Most existing approaches to measuring brain signaling suffer from limited tissue penetration, poor resolution, or lack of specificity for well-defined neural events. Here we discuss a new brain activity mapping method that overcomes some of these problems by combining MRI with contrast agents sensitive to neural signaling. The goal of this "molecular fMRI" approach is to permit noninvasive whole-brain neuroimaging with specificity and resolution approaching current optical neuroimaging methods. In this article, we describe the context and need for molecular fMRI as well as the state of the technology today. We explain how major types of MRI probes work and how they can be sensitized to neurobiological processes, such as neurotransmitter release, calcium signaling, and gene expression changes. We comment both on past work in the field and on challenges and promising avenues for future development.

SIGNIFICANCE STATEMENT

Brain researchers currently have a choice between measuring neural activity using cellular-level recording techniques, such as electrophysiology and optical imaging, or whole-brain imaging methods, such as fMRI. Cellular level methods are precise but only address a small portion of mammalian brains; on the other hand, whole-brain neuroimaging techniques provide very little specificity for neural pathways or signaling components of interest. The molecular fMRI techniques we discuss have particular potential to combine the specificity of cellular-level measurements with the noninvasive whole-brain coverage of fMRI. On the other hand, molecular fMRI is only just getting off the ground. This article aims to offer a snapshot of the status and future prospects for development of molecular fMRI techniques.

Physiological characterization of a robust survival rodent fMRI method

Anesthetics are commonly used in preclinical functional MRI studies. It is well-appreciated that proper choice of anesthetics is of critical importance for maintaining a physiologically normal range of autonomic functioning. A recent study, using a low dose of dexmedetomidine (active isomer of medetomidine) in combination with a low dose of isoflurane, suggested stable measurements across repeated fMRI experiments in individual animals with each session lasting up to several hours. The rat default mode network has been successfully identified using this preparation, indicating that this protocol minimally disturbs brain network functions. However, medetomidine is known to cause peripheral vasoconstriction, respiratory suppression, and bradycardia, each of which could independently confound the BOLD signal. The goal of this study was to systematically characterize physiological conditions for fMRI experiments under this anesthetic regimen. To this end, we acquired somatosensory stimulation "task-evoked" and resting-state fMRI to evaluate the integrity of neurovascular coupling and brain network function during three time windows (0-30min, 30-90min, and 90-150min) following dexmedetomidine initiation. Results demonstrate that both evoked BOLD response and resting-state fMRI signal remained stable during the 90-150min time window, while autonomic physiological parameters maintained near-normal conditions during this period. Our data suggest that using a spontaneously-inhaled, low dose of isoflurane in combination with a continuous low dose of dexmedetomidine is a viable option for longitudinal imaging studies in rats.

Compartmentalised energy metabolism supporting glutamatergic neurotransmission in response to increased activity in the rat cerebral cortex: A 13C MRS study in vivo at 14.1 T

Many tissues exhibit metabolic compartmentation. In the brain, while there is no doubt on the importance of functional compartmentation between neurons and glial cells, there is still debate on the specific regulation of pathways of energy metabolism at different activity levels. Using (13)C magnetic resonance spectroscopy (MRS) in vivo, we determined fluxes of energy metabolism in the rat cortex under α-chloralose anaesthesia at rest and during electrical stimulation of the paws. Compared to resting metabolism, the stimulated rat cortex exhibited increased glutamate-glutamine cycle (+67 nmol/g/min, +95%, P < 0.001) and tricarboxylic (TCA) cycle rate in both neurons (+62 nmol/g/min, +12%, P < 0.001) and astrocytes (+68 nmol/g/min, +22%, P = 0.072). A minor, non-significant modification of the flux through pyruvate carboxylase was observed during stimulation (+5 nmol/g/min, +8%). Altogether, this increase in metabolism amounted to a 15% (67 nmol/g/min, P < 0.001) increase in CMRglc(ox), i.e. the oxidative fraction of the cerebral metabolic rate of glucose. In conclusion, stimulation of the glutamate-glutamine cycle under α-chloralose anaesthesia is associated to similar enhancement of neuronal and glial oxidative metabolism.

New horizons in neurometabolic and neurovascular coupling from calibrated fMRI

Neurovascular coupling relates changes in neuronal activity to constriction/dilation of microvessels. However neurometabolic coupling, which is less well known, relates alterations in neuronal activity with metabolic demands. The link between the blood oxygenation level dependent (BOLD) signal and neural activity opened doors for functional MRI (fMRI) to be a powerful neuroimaging tool in the neurosciences. But due to the complex makeup of BOLD contrast, researchers began to investigate the relationship between BOLD signal and blood flow and/or volume changes during functional brain activation, which together provided the tools to measure oxygen consumption on the basis of the biophysical model of BOLD. This field is called calibrated fMRI, thereby allowed probing of both neurometabolic and neurovascular couplings for a variety of health conditions in animals and humans. Calibrated fMRI may provide brain disorder biomarkers that could be used for monitoring effective therapies.

Cortical Network Models of Firing Rates in the Resting and Active States Predict BOLD Responses

Measurements of blood oxygenation level dependent (BOLD) signals have produced some surprising observations. One is that their amplitude is proportional to the entire activity in a region of interest and not just the fluctuations in this activity. Another is that during sleep and anesthesia the average BOLD correlations between regions of interest decline as the activity declines. Mechanistic explanations of these phenomena are described here using a cortical network model consisting of modules with excitatory and inhibitory neurons, taken as regions of cortical interest, each receiving excitatory inputs from outside the network, taken as subcortical driving inputs in addition to extrinsic (intermodular) connections, such as provided by associational fibers. The model shows that the standard deviation of the firing rate is proportional to the mean frequency of the firing when the extrinsic connections are decreased, so that the mean BOLD signal is proportional to both as is observed experimentally. The model also shows that if these extrinsic connections are decreased or the frequency of firing reaching the network from the subcortical driving inputs is decreased, or both decline, there is a decrease in the mean firing rate in the modules accompanied by decreases in the mean BOLD correlations between the modules, consistent with the observed changes during NREM sleep and under anesthesia. Finally, the model explains why a transient increase in the BOLD signal in a cortical area, due to a transient subcortical input, gives rises to responses throughout the cortex as observed, with these responses mediated by the extrinsic (intermodular) connections.

Comparison of glomerular activity patterns by fMRI and wide-field calcium imaging: Implications for principles underlying odor mapping

Functional imaging signals arise from distinct metabolic and hemodynamic events at the neuropil, but how these processes are influenced by pre- and post-synaptic activities need to be understood for quantitative interpretation of stimulus-evoked mapping data. The olfactory bulb (OB) glomeruli, spherical neuropil regions with well-defined neuronal circuitry, can provide insights into this issue. Optical calcium-sensitive fluorescent dye imaging (OICa(2+)) reflects dynamics of pre-synaptic input to glomeruli, whereas high-resolution functional magnetic resonance imaging (fMRI) using deoxyhemoglobin contrast reveals neuropil function within the glomerular layer where both pre- and post-synaptic activities contribute. We imaged odor-specific activity patterns of the dorsal OB in the same anesthetized rats with fMRI and OICa(2+) and then co-registered the respective maps to compare patterns in the same space. Maps by each modality were very reproducible as trial-to-trial patterns for a given odor, overlapping by ~80%. Maps evoked by ethyl butyrate and methyl valerate for a given modality overlapped by ~80%, suggesting activation of similar dorsal glomerular networks by these odors. Comparison of maps generated by both methods for a given odor showed ~70% overlap, indicating similar odor-specific maps by each method. These results suggest that odor-specific glomerular patterns by high-resolution fMRI primarily tracks pre-synaptic input to the OB. Thus combining OICa(2+) and fMRI lays the framework for studies of OB processing over a range of spatiotemporal scales, where OICa(2+) can feature the fast dynamics of dorsal glomerular clusters and fMRI can map the entire glomerular sheet in the OB.

Quantitative β mapping for calibrated fMRI

The metabolic and hemodynamic dependencies of the blood oxygenation level-dependent (BOLD) signal form the basis for calibrated fMRI, where the focus is on oxidative energy demanded by neural activity. An important part of calibrated fMRI is the power-law relationship between the BOLD signal and the deoxyhemoglobin concentration, which in turn is related to the ratio between oxidative demand (CMRO2) and blood flow (CBF). The power-law dependence between BOLD signal and deoxyhemoglobin concentration is signified by a scaling exponent β. Until recently most studies assumed a β value of 1.5, which is based on numerical simulations of the extravascular BOLD component. Since the basal value of CMRO2 and CBF can vary from subject-to-subject and/or region-to-region, a method to independently measure β in vivo should improve the accuracy of calibrated fMRI results. We describe a new method for β mapping through characterizing R2' - the most sensitive relaxation component of BOLD signal (i.e., the reversible magnetic susceptibility component that is predominantly of extravascular origin at high magnetic field) - as a function of intravascular magnetic susceptibility induced by an FDA-approved superparamagnetic contrast agent. In α-chloralose anesthetized rat brain, at 9.4 T, we measured β values of ~0.8 uniformly across large neocortical swathes, with lower magnitude and more heterogeneity in subcortical areas. Comparison of β maps in rats anesthetized with medetomidine and α-chloralose revealed that β is independent of neural activity levels at these resting states. We anticipate that this method for β mapping can help facilitate calibrated fMRI for clinical studies.

Brain region and activity-dependent properties of M for calibrated fMRI

Calibrated fMRI extracts changes in oxidative energy demanded by neural activity based on hemodynamic and metabolic dependencies of the blood oxygenation level-dependent (BOLD) response. This procedure requires the parameter M, which is determined from the dynamic range of the BOLD signal between deoxyhemoglobin (paramagnetic) and oxyhemoglobin (diamagnetic). Since it is unclear if the range of M-values in human calibrated fMRI is due to regional/state differences, we conducted a 9.4T study to measure M-values across brain regions in deep (α-chloralose) and light (medetomidine) anesthetized rats, as verified by electrophysiology. Because BOLD signal is captured differentially by gradient-echo (R2*) and spin-echo (R2) relaxation rates, we measured M-values by the product of the fMRI echo time and R2' (i.e., the reversible magnetic susceptibility component), which is given by the absolute difference between R2* and R2. While R2' mapping was shown to be dependent on the k-space sampling method used, at nominal spatial resolutions achieved at high magnetic field of 9.4T the M-values were quite homogenous across cortical gray matter. However cortical M-values varied in relation to neural activity between brain states. The findings from this study could improve precision of future calibrated fMRI studies by focusing on the global uniformity of M-values in gray matter across different resting activity levels.