Glutamatergic correlates of gamma-band oscillatory activity during cognition: a concurrent ER-MRS and EEG study

Considerations for event-related gamma-aminobutyric acid functional magnetic resonance spectroscopy

The use of sequential proton magnetic resonance spectroscopy (MRS) to follow glutamate and gamma-aminobutyric acid (GABA) changes during functional task-based paradigms, functional MRS (fMRS), has increased. This technique has been used to investigate GABA dynamics during both sensory and behavioural tasks, usually with long 'block design' paradigms. Recently, there has been an increase in interest in the use of short stimuli and 'event-related' tasks. While changes in glutamate can be readily followed by collecting multiple individual transients (or shots), measurement of GABA, especially at 3 T, is usually performed using editing techniques like Mescher-Garwood point-resolved spectroscopy (MEGA-PRESS), which by its nature is a dual shot approach. This poses problems when considering an event-related experiment, where it is unclear when GABA may change, or how this may affect the individual subspectra of the MEGA-PRESS acquisition. To address this issue, MEGA-PRESS data were simulated to reflect the effect of a transient change in GABA concentration due to a short event-related stimulus. The change in GABA was simulated for both the ON and OFF subspectra, and the effect of three different conditions (increase only during ON acquisition, increase during OFF acquisition and increase across both) on the corresponding edited GABA spectrum was modelled. Results show that a transient increase in GABA that only occurs during the ON subspectral acquisition, while not changing the results much from when GABA is changed across both conditions, will give a much larger change in the edited GABA spectrum than a transient increase that occurs only during the OFF subspectral acquisition. These results suggest that researchers should think carefully about the design of any event-related fMRS studies using MEGA-PRESS, as well as the analysis of other functional paradigms where transient changes in GABA may be expected. Experimental design considerations are therefore discussed, and suggestions are made.

GABA and glutamate response to social processing: a functional MRS feasibility study

Several studies have suggested that atypical social processing in neurodevelopmental conditions (e.g. autism) is associated with differences in excitation and inhibition, through changes in the levels of glutamate and gamma-aminobutyric acid (GABA). While associations between baseline metabolite levels and behaviours can be insightful, assessing the neurometabolic response of GABA and glutamate during social processing may explain altered neurochemical function in more depth. Thus far, there have been no attempts to determine whether changes in metabolite levels are detectable using functional MRS (fMRS) during social processing in a control population. We performed Mescher-Garwood point resolved spectroscopy edited fMRS to measure the dynamic response of GABA and glutamate in the superior temporal sulcus (STS) and visual cortex (V1) while viewing social stimuli, using a design that allows for analysis in both block and event-related approaches. Sliding window analyses were used to investigate GABA and glutamate dynamics at higher temporal resolution. The changes of GABA and glutamate levels with social stimulus were largely non-significant. A small decrease in GABA levels was observed during social stimulus presentation in V1, but no change was observed in STS. Conversely, non-social stimulus elicited changes in both GABA and glutamate levels in both regions. Our findings suggest that the current experimental design primarily captures effects of visual stimulation, not social processing. Here, we discuss the feasibility of using fMRS analysis approaches to assess changes in metabolite response.

Laying the foundations for a theory of consciousness: the significance of critical brain dynamics for the formation of conscious states

Empirical evidence indicates that conscious states, distinguished by the presence of phenomenal qualities, are closely linked to synchronized neural activity patterns whose dynamical characteristics can be attributed to self-organized criticality and phase transitions. These findings imply that insight into the mechanism by which the brain controls phase transitions will provide a deeper understanding of the fundamental mechanism by which the brain manages to transcend the threshold of consciousness. This article aims to show that the initiation of phase transitions and the formation of synchronized activity patterns is due to the coupling of the brain to the zero-point field (ZPF), which plays a central role in quantum electrodynamics (QED). The ZPF stands for the presence of ubiquitous vacuum fluctuations of the electromagnetic field, represented by a spectrum of normal modes. With reference to QED-based model calculations, the details of the coupling mechanism are revealed, suggesting that critical brain dynamics is governed by the resonant interaction of the ZPF with the most abundant neurotransmitter glutamate. The pyramidal neurons in the cortical microcolumns turn out to be ideally suited to control this interaction. A direct consequence of resonant glutamate-ZPF coupling is the amplification of specific ZPF modes, which leads us to conclude that the ZPF is the key to the understanding of consciousness and that the distinctive feature of neurophysiological processes associated with conscious experience consists in modulating the ZPF. Postulating that the ZPF is an inherently sentient field and assuming that the spectrum of phenomenal qualities is represented by the normal modes of the ZPF, the significance of resonant glutamate-ZPF interaction for the formation of conscious states becomes apparent in that the amplification of specific ZPF modes is inextricably linked with the excitation of specific phenomenal qualities. This theory of consciousness, according to which phenomenal states arise through resonant amplification of zero-point modes, is given the acronym TRAZE. An experimental setup is specified that can be used to test a corollary of the theory, namely, the prediction that normally occurring conscious perceptions are absent under experimental conditions in which resonant glutamate-ZPF coupling is disrupted.

GABA, glutamatergic dynamics and BOLD contrast assessed concurrently using functional MRS during a cognitive task

A recurring issue in functional neuroimaging is how to link task-driven haemodynamic blood oxygen level dependent functional MRI (BOLD-fMRI) responses to underlying neurochemistry at the synaptic level. Glutamate and γ-aminobutyric acid (GABA), the major excitatory and inhibitory neurotransmitters respectively, are typically measured with MRS sequences separately from fMRI, in the absence of a task. The present study aims to resolve this disconnect, developing acquisition and processing techniques to simultaneously assess GABA, glutamate and glutamine (Glx) and BOLD in relation to a cognitive task, at 3 T. Healthy subjects (N = 81) performed a cognitive task (Eriksen flanker), which was presented visually in a task-OFF, task-ON block design, with individual event onset timing jittered with respect to the MRS readout. fMRS data were acquired from the medial anterior cingulate cortex during task performance, using an adapted MEGA-PRESS implementation incorporating unsuppressed water-reference signals at a regular interval. These allowed for continuous assessment of BOLD activation, through T2 *-related changes in water linewidth. BOLD-fMRI data were additionally acquired. A novel linear model was used to extract modelled metabolite spectra associated with discrete functional stimuli, building on well established processing and quantification tools. Behavioural outcomes from the flanker task, and activation patterns from the BOLD-fMRI sequence, were as expected from the literature. BOLD response assessed through fMRS showed a significant correlation with fMRI, specific to the fMRS-targeted region of interest; fMRS-assessed BOLD additionally correlated with lengthening of response time in the incongruent flanker condition. While no significant task-related changes were observed for GABA+, a significant increase in measured Glx levels (~8.8%) was found between task-OFF and task-ON periods. These findings verify the efficacy of our protocol and analysis pipelines for the simultaneous assessment of metabolite dynamics and BOLD. As well as establishing a robust basis for further work using these techniques, we also identify a number of clear directions for further refinement in future studies.

Dynamics of γ-aminobutyric acid concentration in the human brain in response to short visual stimulation

OBJECTIVE

To find a possible quantitative relation between activation-induced fast (< 10 s) changes in the γ-aminobutyric acid (GABA) level and the amplitude of a blood oxygen level-dependent contrast (BOLD) response (according to magnetic resonance spectroscopy [MRS] and functional magnetic resonance imaging [fMRI]).

MATERIALS AND METHODS

fMRI data and MEGA-PRESS magnetic resonance spectra [echo time (TE)/repetition time (TR) = 68 ms/1500 ms] of an activated area in the visual cortex of 33 subjects were acquired using a 3 T MR scanner. Stimulation was performed by presenting an image of a flickering checkerboard for 3 s, repeated with an interval of 13.5 s. The time course of GABA and creatine (Cr) concentrations and the width and height of resonance lines were obtained with a nominal time resolution of 1.5 s. Changes in the linewidth and height of n-acetylaspartate (NAA) and Cr signals were used to determine the BOLD effect.

RESULTS

In response to the activation, the BOLD-corrected GABA + /Cr ratio increased by 5.0% (q = 0.027) and 3.8% (q = 0.048) at 1.6 and 3.1 s, respectively, after the start of the stimulus. Time courses of Cr and NAA signal width and height reached a maximum change at the 6th second (~ 1.2-1.5%, q < 0.05).

CONCLUSION

The quick response of the observed GABA concentration to the short stimulus is most likely due to a release of GABA from vesicles followed by its packaging back into vesicles.

Boltzmann's Theorem Revisited: Inaccurate Time-to-Action Clocks in Affective Disorders

Timely goal-oriented behavior is essential for survival and is shaped by experience. In this paper, a multileveled approach was employed, ranging from the polymorphic level through thermodynamic molecular, cellular, intracellular, extracellular, non-neuronal organelles and electrophysiological waves, attesting for signal variability. By adopting Boltzmann's theorem as a thermodynamic conceptualization of brain work, we found deviations from excitation-inhibition balance and wave decoupling, leading to wider signal variability in affective disorders compared to healthy individuals. Recent evidence shows that the overriding on-off design of clock genes paces the accuracy of the multilevel parallel sequencing clocks and that the accuracy of the time-to-action is more crucial for healthy behavioral reactions than their rapidity or delays. In affective disorders, the multilevel clocks run free and lack accuracy of responsivity to environmentally triggered time-to-action as the clock genes are not able to rescue mitochondria organelles from oxidative stress to produce environmentally-triggered energy that is required for the accurate time-to-action and maintenance of the thermodynamic equilibrium. This maintenance, in turn, is dependent on clock gene transcription of electron transporters, leading to higher signal variability and less signal accuracy in affective disorders. From a Boltzmannian thermodynamic and energy-production perspective, the option of reversibility to a healthier time-toaction, reducing entropy is implied. We employed logic gates to show deviations from healthy levelwise communication and the reversed conditions through compensations implying the role of nonneural cells and the extracellular matrix in return to excitation-inhibition balance and accuracy in the time-to-action signaling.

Protocol to conduct functional magnetic resonance spectroscopy in different age groups of human participants

We present a protocol to conduct functional magnetic resonance spectroscopy (fMRS) in human participants before, during, and after training on a visual task. We describe steps for participant setup, volume-of-interest placement, fMRS measurement, and post-scan tests. We discuss the design, analysis, and interpretation of fMRS experiments. This protocol can be adapted to investigate the dynamics of chief excitatory and inhibitory neurotransmitters (glutamate and γ-aminobutyric acid, GABA, respectively) while participants perform or learn perceptual, motor, or cognitive tasks. For complete details on the use and execution of this protocol, please refer to Frank et al. (2022).1.

Electrophysiological connectivity of logical deduction: Early cortical MEG study

Complex human reasoning involves minimal abilities to extract conclusions implied in the available information. These abilities are considered "deductive" because they exemplify certain abstract relations among propositions or probabilities called deductive arguments. However, the electrophysiological dynamics which supports such complex cognitive processes has not been addressed yet. In this work we consider typically deductive logico-probabilistically valid inferences and aim to verify or refute their electrophysiological functional connectivity differences from invalid inferences with the same content (same relational variables, same stimuli, same relevant and salient features). We recorded the brain electrophysiological activity of 20 participants (age = 20.35 ± 3.23) by means of an MEG system during two consecutive reasoning tasks: a search task (invalid condition) without any specific deductive rules to follow, and a logically valid deductive task (valid condition) with explicit deductive rules as instructions. We calculated the functional connectivity (FC) for each condition and conducted a seed-based analysis in a set of cortical regions of interest. Finally, we used a cluster-based permutation test to compare the differences between logically valid and invalid conditions in terms of FC. As a first novel result we found higher FC for valid condition in beta band between regions of interest and left prefrontal, temporal, parietal, and cingulate structures. FC analysis allows a second novel result which is the definition of a propositional network with operculo-cingular, parietal and medial nodes, specifically including disputed medial deductive "core" areas. The experiment discloses measurable cortical processes which do not depend on content but on truth-functional propositional operators. These experimental novelties may contribute to understand the cortical bases of deductive processes.

Event-related functional magnetic resonance spectroscopy

Proton-Magnetic Resonance Spectroscopy (MRS) is a non-invasive brain imaging technique used to measure the concentration of different neurochemicals. "Single-voxel" MRS data is typically acquired across several minutes, before individual transients are averaged through time to give a measurement of neurochemical concentrations. However, this approach is not sensitive to more rapid temporal dynamics of neurochemicals, including those that reflect functional changes in neural computation relevant to perception, cognition, motor control and ultimately behaviour. In this review we discuss recent advances in functional MRS (fMRS) that now allow us to obtain event-related measures of neurochemicals. Event-related fMRS involves presenting different experimental conditions as a series of trials that are intermixed. Critically, this approach allows spectra to be acquired at a time resolution in the order of seconds. Here we provide a comprehensive user guide for event-related task designs, choice of MRS sequence, analysis pipelines, and appropriate interpretation of event-related fMRS data. We raise various technical considerations by examining protocols used to quantify dynamic changes in GABA, the primary inhibitory neurotransmitter in the brain. Overall, we propose that although more data is needed, event-related fMRS can be used to measure dynamic changes in neurochemicals at a temporal resolution relevant to computations that support human cognition and behaviour.

Neurochemistry-enriched dynamic causal models of magnetoencephalography, using magnetic resonance spectroscopy

We present a hierarchical empirical Bayesian framework for testing hypotheses about neurotransmitters' concertation as empirical prior for synaptic physiology using ultra-high field magnetic resonance spectroscopy (7T-MRS) and magnetoencephalography data (MEG). A first level dynamic causal modelling of cortical microcircuits is used to infer the connectivity parameters of a generative model of individuals' neurophysiological observations. At the second level, individuals' 7T-MRS estimates of regional neurotransmitter concentration supply empirical priors on synaptic connectivity. We compare the group-wise evidence for alternative empirical priors, defined by monotonic functions of spectroscopic estimates, on subsets of synaptic connections. For efficiency and reproducibility, we used Bayesian model reduction (BMR), parametric empirical Bayes and variational Bayesian inversion. In particular, we used Bayesian model reduction to compare alternative model evidence of how spectroscopic neurotransmitter measures inform estimates of synaptic connectivity. This identifies the subset of synaptic connections that are influenced by individual differences in neurotransmitter levels, as measured by 7T-MRS. We demonstrate the method using resting-state MEG (i.e., task-free recording) and 7T-MRS data from healthy adults. Our results confirm the hypotheses that GABA concentration influences local recurrent inhibitory intrinsic connectivity in deep and superficial cortical layers, while glutamate influences the excitatory connections between superficial and deep layers and connections from superficial to inhibitory interneurons. Using within-subject split-sampling of the MEG dataset (i.e., validation by means of a held-out dataset), we show that model comparison for hypothesis testing can be highly reliable. The method is suitable for applications with magnetoencephalography or electroencephalography, and is well-suited to reveal the mechanisms of neurological and psychiatric disorders, including responses to psychopharmacological interventions.

Non-linear variations in glutamate dynamics during a cognitive task engagement in schizophrenia

To investigate the role of glutamate in psychosis, we employ functional magnetic resonance spectroscopy at an ultra-high magnetic field (7T) and employ fuzzy-approximate entropy (F-ApEn) and Hurst Exponent (HE) to capture time-varying nature of glutamate signaling during a cognitive task. We recruited thirty first-episode psychosis patients (FEP) with age- and gender-matched healthy controls (HC) and administered the Color-Word Stroop paradigm, providing 128 raw MRS time-points per subject over a period of 16 min. We then performed metabolite quantification of glutamate in the dorsal anterior cingulate cortex, a region reliably activated during the Stroop task. Symptoms/cognitive functioning was measured using Positive and Negative Syndrome Scale-8 score, Social and Occupational Functioning (SOFAS) score, digit symbol) coding score, and Stroop accuracy. These scores were related to the Entropy/HE data from the overall glutamate time-series. Patients with FEP had significantly higher HE compared to HC, with individuals displaying significantly higher HE having lower functional performance (SOFAS) in both HC and FEP groups. Among healthy individuals, higher HE also indicated significantly lower cognitive function through Stroop accuracy and DSST scores. F-ApEn had an inverse Pearson correlation with HE, and tracked diagnosis, cognition and function as expected, but with lower effect sizes not reaching statistical significance. We demonstrate notable diagnostic differences in the temporal course of glutamate signaling during a cognitive task in psychosis.

Excitation-Inhibition Imbalance in Migraine: From Neurotransmitters to Brain Oscillations

Migraine is among the most common and debilitating neurological disorders typically affecting people of working age. It is characterised by a unilateral, pulsating headache often associated with severe pain. Despite the intensive research, there is still little understanding of the pathophysiology of migraine. At the electrophysiological level, altered oscillatory parameters have been reported within the alpha and gamma bands. At the molecular level, altered glutamate and GABA concentrations have been reported. However, there has been little cross-talk between these lines of research. Thus, the relationship between oscillatory activity and neurotransmitter concentrations remains to be empirically traced. Importantly, how these indices link back to altered sensory processing has to be clearly established as yet. Accordingly, pharmacologic treatments have been mostly symptom-based, and yet sometimes proving ineffective in resolving pain or related issues. This review provides an integrative theoretical framework of excitation-inhibition imbalance for the understanding of current evidence and to address outstanding questions concerning the pathophysiology of migraine. We propose the use of computational modelling for the rigorous formulation of testable hypotheses on mechanisms of homeostatic imbalance and for the development of mechanism-based pharmacological treatments and neurostimulation interventions.

Control systems theory revisited: new insights on the brain clocks of time-to-action

To outline the complex biological rhythms underlying the time-to-action of goal-oriented behavior in the adult brain, we employed a Boolean Algebra model based on Control Systems Theory. This suggested that "timers" of the brain reflect a metabolic excitation-inhibition balance and that healthy clocks underlying goal-oriented behavior (optimal range of signal variability) are maintained by XOR logic gates in parallel sequences between cerebral levels. Using truth tables, we found that XOR logic gates reflect healthy, regulated time-to-action events between levels. We argue that the brain clocks of time-to-action are active within multileveled, parallel-sequence complexes shaped by experience. We show the metabolic components of time-to-action in levels ranging from the atom level through molecular, cellular, network and inter-regional levels, operating as parallel sequences. We employ a thermodynamic perspective, suggest that clock genes calculate free energy versus entropy and derived time-to-action level-wise as a master controller, and show that they are receivers, as well as transmitters of information. We argue that regulated multileveled time-to-action processes correspond to Boltzmann's thermodynamic theorem of micro- and macro-states, and that the available metabolic free-energy-entropy matrix determines the brain's reversible states for its age-appropriate chrono-properties at given moments. Thus, healthy timescales are not a precise number of nano- or milliseconds of activity nor a simple phenotypic distinction between slow vs. quick time-to-action, but rather encompass a range of variability, which depends on the molecules' size and dynamics with the composition of receptors, protein and RNA isoforms.

Electrical analysis of logical complexity: an exploratory eeg study of logically valid/invalid deducive inference

INTRODUCTION

Logically valid deductive arguments are clear examples of abstract recursive computational procedures on propositions or on probabilities. However, it is not known if the cortical time-consuming inferential processes in which logical arguments are eventually realized in the brain are in fact physically different from other kinds of inferential processes.

METHODS

In order to determine whether an electrical EEG discernible pattern of logical deduction exists or not, a new experimental paradigm is proposed contrasting logically valid and invalid inferences with exactly the same content (same premises and same relational variables) and distinct logical complexity (propositional truth-functional operators). Electroencephalographic signals from 19 subjects (24.2 ± 3.3 years) were acquired in a two-condition paradigm (100 trials for each condition). After the initial general analysis, a trial-by-trial approach in beta-2 band allowed to uncover not only evoked but also phase asynchronous activity between trials.

RESULTS

showed that (i) deductive inferences with the same content evoked the same response pattern in logically valid and invalid conditions, (ii) mean response time in logically valid inferences is 61.54% higher, (iii) logically valid inferences are subjected to an early (400 ms) and a late reprocessing (600 ms) verified by two distinct beta-2 activations (p-value < 0,01, Wilcoxon signed rank test).

CONCLUSION

We found evidence of a subtle but measurable electrical trait of logical validity. Results put forward the hypothesis that some logically valid deductions are recursive or computational cortical events.

Individual/Peak Gamma Frequency: What Do We Know?

In recent years, the concept of individualized measures of electroencephalographic (EEG) activity has emerged. Gamma-band activity plays an important role in many sensory and cognitive processes. Thus, peak frequency in the gamma range has received considerable attention. However, peak or individual gamma frequency (IGF) is rarely used as a primary measure of interest; consequently, little is known about its nature and functional significance. With this review, we attempt to comprehensively overview available information on the functional properties of peak gamma frequency, addressing its relationship with certain processes and/or modulation by various factors. Here, we show that IGFs seem to be related to various endogenous and exogenous factors. Broad functional aspects that are related to IGF might point to the differences in underlying mechanisms. Therefore, research utilizing different types of stimulation for IGF estimation and covering several functional aspects in the same population is required. Moreover, IGFs span a wide range of frequencies (30-100 Hz). This could be partly due to the variability of methods used to extract the measures of IGF. In order to overcome this issue, further studies aiming at the optimization of IGF extraction would be greatly beneficial.

Functional MRS studies of GABA and glutamate/Glx - A systematic review and meta-analysis

Functional magnetic resonance spectroscopy (fMRS) can be used to investigate neurometabolic responses to external stimuli in-vivo, but findings are inconsistent. We performed a systematic review and meta-analysis on fMRS studies of the primary neurotransmitters Glutamate (Glu), Glx (Glutamate + Glutamine), and GABA. Data were extracted, grouped by metabolite, stimulus domain, and brain region, and analysed by determining standardized effect sizes. The quality of individual studies was rated. When results were analysed by metabolite type small to moderate effect sizes of 0.29-0.47 (p < 0.05) were observed for changes in Glu and Glx regardless of stimulus domain and brain region, but no significant effects were observed for GABA. Further analysis suggests that Glu, Glx and GABA responses differ by stimulus domain or task and vary depending on the time course of stimulation and data acquisition. Here, we establish effect sizes and directionality of GABA, Glu and Glx response in fMRS. This work highlights the importance of standardised reporting and minimal best practice for fMRS research.

Hypoxia alters posterior cingulate cortex metabolism during a memory task: A 1H fMRS study

Environmental hypoxia (fraction of inspired oxygen (F_IO₂) ∼ 0.120) is known to trigger a global increase in cerebral blood flow (CBF). However, regionally, a heterogeneous response is reported, particularly within the posterior cingulate cortex (PCC) where decreased CBF is found after two hours of hypoxic exposure. Furthermore, hypoxia reverses task-evoked BOLD signals within the PCC, and other regions of the default mode network, suggesting a reversal of neurovascular coupling. An alternative explanation is that the neural architecture supporting cognitive tasks is reorganised. Therefore, to confirm if this previous result is neural or vascular in origin, a measure of neural activity that is not haemodynamic-dependant is required. To achieve this, we utilised functional magnetic resonance spectroscopy to probe the glutamate response to memory recall in the PCC during normoxia (F_IO₂ = 0.209) and after two hours of poikilocapnic hypoxia (F_IO₂ = 0.120). We also acquired ASL-based measures of CBF to confirm previous findings of reduced CBF within the PCC in hypoxia. Consistent with previous findings, hypoxia induced a reduction in CBF within the PCC and other regions of the default mode network. Under normoxic conditions, memory recall was associated with an 8% increase in PCC glutamate compared to rest (P = 0.019); a change which was not observed during hypoxia. However, exploratory analysis of other neurometabolites showed that PCC glucose was reduced during hypoxia compared to normoxia both at rest (P = 0.039) and during the task (P = 0.046). We conclude that hypoxia alters the activity-induced increase in glutamate, which may reflect a reduction in oxidative metabolism within the PCC. The reduction in glucose in hypoxia reflects continued metabolism, presumably by non-oxidative means, without replacement of glucose due to reduced CBF.

Variants in the zinc transporter-3 encoding gene (SLC30A3) in schizophrenia and bipolar disorder: Effects on brain glutamate-A pilot study

Zinc transporter 3 (ZnT3) has been implicated in the aetiopathology of schizophrenia. In this pilot study, we tested the hypothesis that the presence of a minor allele of two variants in the gene encoding ZnT3 (SLC30A3) affects brain glutamate and cognitive activity in patients with schizophrenia and bipolar affective disorder. Fifteen patients with schizophrenia (SCZ), 15 with bipolar affective disorder type 2 (BD), and 14 healthy volunteers (HV) were genotyped for two SLC30A3 single nucleotide polymorphisms (rs11126936 and rs11126929). They also underwent structural and functional MRI (n-back) imaging as well as static (PRESS) and functional magnetic resonance spectroscopy (n-back) on a 3 Tesla MRI system. SCZ with at least one copy of the minor allele showed reductions in dorsal anterior cingulate cortex glutamate during the n-back task, whereas SCZ without the minor allele showed an increase in glutamate. BD with the minor allele had reduced glutamate in the anterior cingulate cortex (p < 0.05). There was no effect of SLC30A3 genotype on BOLD activation during n-back or on cortical brain volume. This study supports the further investigation of SLC30A3 and its role in glutamatergic neurotransmission and in the neuropathology of mental illness.

Predicting treatment response using EEG in major depressive disorder: A machine-learning meta-analysis

Selecting a course of treatment in psychiatry remains a trial-and-error process, and this long-standing clinical challenge has prompted an increased focus on predictive models of treatment response using machine learning techniques. Electroencephalography (EEG) represents a cost-effective and scalable potential measure to predict treatment response to major depressive disorder. We performed separate meta-analyses to determine the ability of models to distinguish between responders and non-responders using EEG across treatments, as well as a performed subgroup analysis of response to transcranial magnetic stimulation (rTMS), and antidepressants (Registration Number: CRD42021257477) in Major Depressive Disorder by searching PubMed, Scopus, and Web of Science for articles published between January 1960 and February 2022. We included 15 studies that predicted treatment responses among patients with major depressive disorder using machine-learning techniques. Within a random-effects model with a restricted maximum likelihood estimator comprising 758 patients, the pooled accuracy across studies was 83.93% (95% CI: 78.90-89.29), with an Area-Under-the-Curve (AUC) of 0.850 (95% CI: 0.747-0.890), and partial AUC of 0.779. The average sensitivity and specificity across models were 77.96% (95% CI: 60.05-88.70), and 84.60% (95% CI: 67.89-92.39), respectively. In a subgroup analysis, greater performance was observed in predicting response to rTMS (Pooled accuracy: 85.70% (95% CI: 77.45-94.83), Area-Under-the-Curve (AUC): 0.928, partial AUC: 0.844), relative to antidepressants (Pooled accuracy: 81.41% (95% CI: 77.45-94.83, AUC: 0.895, pAUC: 0.821). Furthermore, across all meta-analyses, the specificity (true negatives) of EEG models was greater than the sensitivity (true positives), suggesting that EEG models thus far better identify non-responders than responders to treatment in MDD. Studies varied widely in important features across models, although relevant features included absolute and relative power in frontal and temporal electrodes, measures of connectivity, and asymmetry across hemispheres. Predictive models of treatment response using EEG hold promise in major depressive disorder, although there is a need for prospective model validation in independent datasets, and a greater emphasis on replicating physiological markers. Crucially, standardization in cut-off values and clinical scales for defining clinical response and non-response will aid in the reproducibility of findings and the clinical utility of predictive models. Furthermore, several models thus far have used data from open-label trials with small sample sizes and evaluated performance in the absence of training and testing sets, which increases the risk of statistical overfitting. Large consortium studies are required to establish predictive signatures of treatment response using EEG, and better elucidate the replicability of specific markers. Additionally, it is speculated that greater performance was observed in rTMS models, since EEG is assessing neural networks more likely to be directly targeted by rTMS, comprising electrical activity primarily near the surface of the cortex. Prospectively, there is a need for models that examine the comparative effectiveness of multiple treatments across the same patients. However, this will require a thoughtful consideration towards cumulative treatment effects, and whether washout periods between treatments should be utilised. Regardless, longitudinal cross-over trials comparing multiple treatments across the same group of patients will be an important prerequisite step to both facilitate precision psychiatry and identify generalizable physiological predictors of response between and across treatment options.

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.

Neurochemical and functional interactions for improved perceptual decisions through training

Learning and experience are known to improve our ability to make perceptual decisions. Yet, our understanding of the brain mechanisms that support improved perceptual decisions through training remains limited. Here, we test the neurochemical and functional interactions that support learning for perceptual decisions in the context of an orientation identification task. Using magnetic resonance spectroscopy (MRS), we measure neurotransmitters (i.e., glutamate, GABA) that are known to be involved in visual processing and learning in sensory [early visual cortex (EV)] and decision-related [dorsolateral prefrontal cortex (DLPFC)] brain regions. Using resting-state functional magnetic resonance imaging (rs-fMRI), we test for functional interactions between these regions that relate to decision processes. We demonstrate that training improves perceptual judgments (i.e., orientation identification), as indicated by faster rates of evidence accumulation after training. These learning-dependent changes in decision processes relate to lower EV glutamate levels and EV-DLPFC connectivity, suggesting that glutamatergic excitation and functional interactions between visual and dorsolateral prefrontal cortex facilitate perceptual decisions. Further, anodal transcranial direct current stimulation (tDCS) in EV impairs learning, suggesting a direct link between visual cortex excitation and perceptual decisions. Our findings advance our understanding of the role of learning in perceptual decision making, suggesting that glutamatergic excitation for efficient sensory processing and functional interactions between sensory and decision-related regions support improved perceptual decisions.NEW & NOTEWORTHY Combining multimodal brain imaging [magnetic resonance spectroscopy (MRS), functional connectivity] with interventions [transcranial direct current stimulation (tDCS)], we demonstrate that glutamatergic excitation and functional interactions between sensory (visual) and decision-related (dorsolateral prefrontal cortex) areas support our ability to optimize perceptual decisions through training.

Memory recall involves a transient break in excitatory-inhibitory balance

The brain has a remarkable capacity to acquire and store memories that can later be selectively recalled. These processes are supported by the hippocampus which is thought to index memory recall by reinstating information stored across distributed neocortical circuits. However, the mechanism that supports this interaction remains unclear. Here, in humans, we show that recall of a visual cue from a paired associate is accompanied by a transient increase in the ratio between glutamate and GABA in visual cortex. Moreover, these excitatory-inhibitory fluctuations are predicted by activity in the hippocampus. These data suggest the hippocampus gates memory recall by indexing information stored across neocortical circuits using a disinhibitory mechanism.

Visual Attention Modulates Glutamate-Glutamine Levels in Vestibular Cortex: Evidence from Magnetic Resonance Spectroscopy

Attending to a stimulus enhances the neuronal responses to it, while responses to nonattended stimuli are not enhanced and may even be suppressed. Although the neural mechanisms of response enhancement for attended stimuli have been intensely studied, the neural mechanisms underlying attentional suppression remain largely unknown. It is uncertain whether attention acts to suppress the processing in sensory cortical areas that would otherwise process the nonattended stimulus or the subcortical input to these cortical areas. Moreover, the neurochemical mechanisms inducing a reduction or suppression of neuronal responses to nonattended stimuli are as yet unknown. Here, we investigated how attention directed toward visual processing cross-modally acts to suppress vestibular responses in the human brain. By using functional magnetic resonance spectroscopy in a group of female and male subjects, we find that attention to visual motion downregulates in a load-dependent manner the concentration of excitatory neurotransmitter (glutamate and its precursor glutamine, referred to together as Glx) within the parietoinsular vestibular cortex (PIVC), a core cortical area of the vestibular system, while leaving the concentration of inhibitory neurotransmitter (GABA) in PIVC unchanged. This makes PIVC less responsive to excitatory thalamic vestibular input, as corroborated by functional magnetic resonance imaging. Together, our results suggest that attention acts to suppress the processing of nonattended sensory cues cortically by neurochemically rendering the core cortical area of the nonattended sensory modality less responsive to excitatory thalamic input.SIGNIFICANCE STATEMENT Here, we address a fundamental problem that has eluded attention research for decades, namely, how the brain ignores irrelevant stimuli. To date, three classes of solutions to this problem have been proposed: (1) enhancement of GABAergic interneuron activity in cortex, (2) downregulation of glutamatergic cell activity in cortex; and (3) downregulation of neural activity in thalamic projection areas, which would then provide the cortex with less input. Here, we use magnetic resonance spectroscopy in humans and find support for the second hypothesis, implying that attention to one sensory modality involves the suppression of irrelevant stimuli of another sensory modality by downregulating glutamate in the cortex.

Objective Extraction of Evoked Event-Related Oscillation from Time-Frequency Representation of Event-Related Potentials

Evoked event-related oscillations (EROs) have been widely used to explore the mechanisms of brain activities for both normal people and neuropsychiatric disease patients. In most previous studies, the calculation of the regions of evoked EROs of interest is commonly based on a predefined time window and a frequency range given by the experimenter, which tends to be subjective. Additionally, evoked EROs sometimes cannot be fully extracted using the conventional time-frequency analysis (TFA) because they may be overlapped with each other or with artifacts in time, frequency, and space domains. To further investigate the related neuronal processes, a novel approach was proposed including three steps: (1) extract the temporal and spatial components of interest simultaneously by temporal principal component analysis (PCA) and Promax rotation and project them to the electrode fields for correcting their variance and polarity indeterminacies, (2) calculate the time-frequency representations (TFRs) of the back-projected components, and (3) compute the regions of evoked EROs of interest on TFRs objectively using the edge detection algorithm. We performed this novel approach, conventional TFA, and TFA-PCA to analyse both the synthetic datasets with different levels of SNR and an actual ERP dataset in a two-factor paradigm of waiting time (short/long) and feedback (loss/gain) separately. Synthetic datasets results indicated that N2-theta and P3-delta oscillations can be stably detected from different SNR-simulated datasets using the proposed approach, but, by comparison, only one oscillation was obtained via the last two approaches. Furthermore, regarding the actual dataset, the statistical results for the proposed approach revealed that P3-delta was sensitive to the waiting time but not for that of the other approaches. This study manifested that the proposed approach could objectively extract evoked EROs of interest, which allows a better understanding of the modulations of the oscillatory responses.

Excitatory-inhibitory balance within EEG microstates and resting-state fMRI networks: assessed via simultaneous trimodal PET-MR-EEG imaging

The symbiosis of neuronal activities and glucose energy metabolism is reflected in the generation of functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) signals. However, their association with the balance between neuronal excitation and inhibition (E/I-B), which is closely related to the activities of glutamate and γ-aminobutyric acid (GABA) and the receptor availability (RA) of GABAA and mGluR5, remains unexplored. This research investigates these associations during the resting state (RS) condition using simultaneously recorded PET/MR/EEG (trimodal) data. The trimodal data were acquired from three studies using different radio-tracers such as, [11C]ABP688 (ABP) (N = 9), [11C]Flumazenil (FMZ) (N = 10) and 2-[18F]fluoro-2-deoxy-D-glucose (FDG) (N = 10) targeted to study the mGluR5, GABAA receptors and glucose metabolism respectively. Glucose metabolism and neuroreceptor binding availability (non-displaceable binding potential (BPND)) of GABAA and mGluR5 were found to be significantly higher and closely linked within core resting-state networks (RSNs). The neuronal generators of EEG microstates and the fMRI measures were most tightly associated with the BPND of GABAA relative to mGluR5 BPND and the glucose metabolism, emphasising a predominance of inhibitory processes within in the core RSNs at rest. Changes in the neuroreceptors leading to an altered coupling with glucose metabolism may render the RSNs vulnerable to psychiatric conditions. The paradigm employed here will likely help identify the precise neurobiological mechanisms behind these alterations in fMRI functional connectivity and EEG oscillations, potentially benefitting individualised healthcare treatment measures.

Number of subjects required in common study designs for functional GABA magnetic resonance spectroscopy in the human brain at 3 Tesla

Magnetic resonance spectroscopy (MRS) is a research tool for measuring the concentration of metabolites such as γ-aminobutyric acid (GABA) and glutamate in the brain. MEGA-PRESS has been the preferred pulse sequence for GABA measurements due to low physiological GABA concentrations, hence low signal. To compensate, researchers incorporate long acquisition durations (7-10 min) making functional measurements of this metabolite challenging. Here, the acquisition duration and sample sizes required to detect specific concentration changes in GABA using MEGA-PRESS at 3 T are presented for both between-groups and within-session study designs. 75 spectra were acquired during rest using MEGA-PRESS from 41 healthy volunteers in 6 different brain regions at 3 T with voxel sizes between 13 and 22 cm3 . Between-group and within-session variance was calculated for different acquisition durations and power calculations were performed to determine the number of subjects required to detect a given percentage change in GABA/NAA signal ratio. Within-subject variability was assessed by sampling different segments of a single acquisition. Power calculations suggest that detecting a 15% change in GABA using a 2 min acquisition and a 27 cm3 voxel size, depending on the region, requires between 8 and 93 subjects using a within-session design. A between-group design typically requires more participants to detect the same difference. In brain regions with suboptimal shimming, the subject numbers can be up to 4-fold more. Collecting data for longer than 4 min in brain regions examined in this study is deemed unnecessary, as variance in the signal did not reduce further for longer durations.

Atypical gamma functional connectivity pattern during light sleep in children with attention deficit hyperactivity disorder

INTRODUCTION

We examined functional connectivity analyses in electroencephalograms (EEGs) of patients with attention deficit hyperactivitydisorder (ADHD) and in those of typically developing children (TDC) to uncover neurobiological abnormalities.

METHODOLOGY

We enrolled 31 children with ADHD (mean age 11.1 years; 23 boys) and 17 sex-, age-, and intelligence-matched TDC to undergo 19-channel EEGs during light sleep. We estimated functional connectivity using the phase lag index (PLI) and coherence measurements that capture the synchronization of EEG signals and graphed metrics with GRETNA. We also performed continuous performance tests (CPTs) on the children and obtained answered questionnaires on ADHD and autism spectrum disorder.

RESULTS

The central-to-posterior gamma PLI was lower in children with ADHD than that in TDC. The other PLI frequency bands and all coherence frequency bands were not statistically different between both groups. Individuals with high hyperactivity scores on questionnaires and low reaction times (SDs) on CPT had low motor and occipital pairs of gamma PLIs. Graph metrics showed no differences between the groups.

CONCLUSIONS

The difference in averaged gamma PLI (especially with motor and occipital pairs) between groups was more suitable for diagnosis than the averaged coherence. Lower averaged gamma PLIs reflected more severe ADHD symptoms. A prospective study with more controlled conditions is warranted to determine if gamma-band PLI can be used as an auxiliary tool for ADHD diagnosis.

Functional magnetic resonance spectroscopy in patients with schizophrenia and bipolar affective disorder: Glutamate dynamics in the anterior cingulate cortex during a working memory task

The glutamate system is implicated in the pathophysiology of schizophrenia and mood disorders. Using functional magnetic resonance spectroscopy (¹H-fMRS), it is possible to monitor glutamate dynamically in activated brain areas and may give a closer estimate of glutamatergic neurotransmission than standard magnetic resonance spectroscopy. 14 patients with schizophrenia, 15 patients with bipolar disorder II (BPII) and 14 healthy volunteers underwent a 15 min N-back task in a 48s block design during ¹H-fMRS acquisition. Data from the first, second and third 16s group of 8 spectra for each block were analysed to measure levels of glutamate and Glx (glutamate + glutamine), scaled to total creatine (TCr), across averaged 0-back and 2-back conditions. A 6 × 3 repeated-measures analysis of variance (rmANOVA) demonstrated a significant main effect of time for Glx/TCr (P = 0.022). There was a significant increase in Glu/TCr (P = 0.004) and Glx/TCr (P < 0.001) between the final spectra of the 0-back and first spectra of the 2-back condition in the healthy control group only. 2 × 2 rmANOVA revealed a significant time by group interaction for Glx/TCr (P = 0.019) across the 0-back condition, with levels reducing in healthy controls and increasing in the schizophrenia group. While healthy volunteers showed significant increases in glutamatergic measures between task conditions, the lack of such a response in patients with schizophrenia and BPII may reflect deficits in glutamatergic neurotransmission. Abnormal increases during periods of relatively low executive load, without the same dynamic modulation as healthy volunteers with increasing task difficulty, further suggests underlying abnormalities of glutamatergic neurotransmission in schizophrenia.

EXTENDED ATTENUATION OF CORTICOSTRIATAL POWER AND COHERENCE AFTER ACUTE EXPOSURE TO VAPOURIZED Δ9 TETRAHYDROCANNABINOL IN RATS

Introduction

Over 14% of Canadians use cannabis, with nearly 60% of these individuals reporting daily or weekly use. Inhalation of cannabis vapour has recently gained popularity, but the effects of this exposure on neural activity remain unknown. In this study, we assessed the impact of acute exposure to vapourized Δ9-tetrahydrocannabinol (THC) on neural circuit dynamics in rats.

Objectives

We aimed to characterize the changes in neural activity in the dorsal striatum (dStr), orbitofrontal cortex (OFC), and prefrontal cortex (PFC), after acute exposure to THC vapour.

Methods

Rats were implanted with electrode arrays targeting the dStr, OFC, and PFC. Rats were administered THC (or vehicle) using a Volcano® vapourizer and local field potential recordings were performed in a plexiglass chamber in a cross-over design with a week-long washout period.

Results

Decreased spectral power was observed within the dStr, OFC, and PFC in the gamma range (>32-100 Hz) following vapourized THC administration. Most changes in gamma were still present 7 days after THC administration. Decreased gamma coherence was also observed between the OFC-PFC and dStr-PFC region-pairs.

Conclusion

A single exposure to vapourized THC suppresses cortical and dorsal striatal gamma power and coherence, effects that appear to last at least a week. Given the role of gamma hypofunction in schizophrenia, these findings may provide mechanistic insights into the known psychotomimetic effects of THC.

Comparison of Neurochemical and BOLD Signal Contrast Response Functions in the Human Visual Cortex

We investigated the relationship between neurochemical and hemodynamic responses as a function of image contrast in the human primary visual cortex (V1). Simultaneously acquired BOLD-fMRI and single voxel proton MR spectroscopy signals were measured in V1 of 24 healthy human participants of either sex at 7 tesla field strength, in response to presentations (64 s blocks) of different levels of image contrast (3%, 12.5%, 50%, 100%). Our results suggest that complementary measures of neurotransmission and energy metabolism are in partial agreement: BOLD and glutamate signals were linear with image contrast; however, a significant increase in glutamate concentration was evident only at the highest intensity level. In contrast, GABA signals were steady across all intensity levels. These results suggest that neurochemical concentrations are maintained at lower ranges of contrast levels, which match the statistics of natural vision, and that high stimulus intensity may be critical to increase sensitivity to visually modulated glutamate signals in the early visual cortex using MR spectroscopy.SIGNIFICANCE STATEMENT Glutamate and GABA are the major excitatory and inhibitory neurotransmitters of the brain. To better understand the relationship between MRS-visible neurochemicals, the BOLD signal change, and stimulus intensity, we measured combined neurochemical and BOLD signals (combined fMRI-MRS) to different image contrasts in human V1 at 7 tesla. While a linear change to contrast was present for both signals, the increase in glutamate was significant only at the highest stimulus intensity. These results suggest that hemodynamic and neurochemical signals reflect common metabolic markers of neural activity, whereas the mismatch at lower contrast levels may indicate a sensitivity threshold for detecting neurochemical changes during visual processing. Our results highlight the challenge and importance of reconciling cellular and metabolic measures of neural activity in the human brain.

Multimodal imaging reveals a complex pattern of dysfunction in corticolimbic pathways in major depressive disorder

Major depressive disorder (MDD) is highly prevalent and associated with considerable morbidity, yet its pathophysiology remains only partially understood. While numerous studies have investigated the neurobiological correlates of MDD, most have used only a single neuroimaging modality. In particular, diffusion tensor imaging (DTI) studies have failed to yield uniform results. In this context, examining key tracts and using information from multiple neuroimaging modalities may better characterize potential abnormalities in the MDD brain. This study analyzed data from 30 participants with MDD and 26 healthy participants who underwent DTI, magnetic resonance spectroscopy (MRS), resting-state functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG). Tracts connecting the subgenual anterior cingulate cortex (sgACC) and the left and right amygdala, as well as connections to the left and right hippocampus and thalamus, were examined as target areas. Reduced fractional anisotropy (FA) was observed in the studied tracts. Significant differences in the correlation between medial prefrontal glutamate concentrations and FA were also observed between MDD and healthy participants along tracts connecting the sgACC and right amygdala; healthy participants exhibited a strong correlation but MDD participants showed no such relationship. In the same tract, a correlation was observed between FA and subsequent antidepressant response to ketamine infusion in MDD participants. Exploratory models also suggested group differences in the relationship between DTI, fMRI, and MEG measures. This study is the first to combine MRS, DTI, fMRI, and MEG data to obtain multimodal indices of MDD and antidepressant response and may lay the foundation for similar future analyses.

Alterations in resting-state gamma activity in patients with schizophrenia: a high-density EEG study

Alterations of EEG gamma activity in schizophrenia have been reported during sensory and cognitive tasks, but it remains unclear whether changes are present in resting state. Our aim was to examine whether changes occur in resting state, and to delineate those brain regions where gamma activity is altered. Furthermore, we wanted to identify the associations between changes in gamma activity and psychopathological characteristics. We studied gamma activity (30-48 Hz) in 60 patients with schizophrenia and 76 healthy controls. EEGs were acquired in resting state with closed eyes using a high-density, 256-channel EEG-system. The two groups were compared in absolute power measures in the gamma frequency range. Compared to controls, in patients with schizophrenia the absolute power was significantly elevated (false discovery rate corrected p < 0.05). The alterations clustered into fronto-central and posterior brain regions, and were positively associated with the severity of psychopathology, measured by the PANSS. Changes in gamma activity can lead to disturbed coordination of large-scale brain networks. Thus, the increased gamma activity in certain brain regions that we found may result in disturbances in temporal coordination of task-free/resting-state networks in schizophrenia. Positive association of increased gamma power with psychopathology suggests that altered gamma activity provides a contribution to symptom presentation.

Toward a Glutamate Hypothesis of Frontotemporal Dementia

Frontotemporal dementia (FTD) is a heterogenous neurodegenerative disorder, characterized by diverse clinical presentations, neuropathological characteristics and underlying genetic causes. Emerging evidence has shown that FTD is characterized by a series of changes in several neurotransmitter systems, including serotonin, dopamine, GABA and, above all, glutamate. Indeed, several studies have now provided preclinical and clinical evidence that glutamate is key in the pathogenesis of FTD. Animal models of FTD have shown a selective hypofunction in N-methyl D-aspartate (NMDA) and α-amino-3-hydroxyl-5-methyl-4-isoxazolepropionic acid (AMPA) receptors, while in patients, glutamatergic pyramidal neurons are depleted in several areas, including the frontal and temporal cortices. Recently, a selective involvement of the AMPA GluA3 subunit has been observed in patients with autoimmune anti-GluA3 antibodies, which accounted for nearly 25% of FTD patients, leading to a decrease of the GluA3 subunit synaptic localization of the AMPA receptor and loss of dendritic spines. Other in vivo evidence of the involvement of the glutamatergic system in FTD derives from non-invasive brain stimulation studies using transcranial magnetic stimulation, in which specific stimulation protocols have indirectly identified a selective and prominent impairment in glutamatergic circuits in patients with both sporadic and genetic FTD. In view of limited disease modifying therapies to slow or revert disease progression in FTD, an important approach could consist in targeting the neurotransmitter deficits, similarly to what has been achieved in Parkinson’s disease with dopaminergic therapy or Alzheimer’s disease with cholinergic therapy. In this review, we summarize the current evidence concerning the involvement of the glutamatergic system in FTD, suggesting the development of new therapeutic strategies.

Opposite Dynamics of GABA and Glutamate Levels in the Occipital Cortex during Visual Processing

Magnetic resonance spectroscopy (MRS) measures the two most common inhibitory and excitatory neurotransmitters, GABA and glutamate, in the human brain. However, the role of MRS-derived GABA and glutamate signals in relation to system-level neural signaling and behavior is not fully understood. In this study, we investigated levels of GABA and glutamate in the visual cortex of healthy human participants (both genders) in three functional states with increasing visual input. Compared with a baseline state of eyes closed, GABA levels decreased after opening the eyes in darkness and Glx levels remained stable during eyes open but increased with visual stimulation. In relevant states, GABA and Glx correlated with amplitude of fMRI signal fluctuations. Furthermore, visual discriminatory performance correlated with the level of GABA, but not Glx. Our study suggests that differences in brain states can be detected through the contrasting dynamics of GABA and Glx, which has implications in interpreting MRS measurements.SIGNIFICANCE STATEMENT GABA and glutamate are the two most abundant neurotransmitters in human brain. Their interaction, known as inhibitory-excitatory balance, plays a crucial role in establishing spontaneous and stimulus-driven brain activity. Yet, the relationship between magnetic resonance spectroscopy (MRS)-derived levels of both metabolites and fMRI is still a matter of dispute. In this work, we study GABA and glutamate in three states of visual processing and in relation to fMRI and visual discriminatory performance in healthy people. We found that states of visual processing can be detected through the contrasting dynamics of GABA and glutamate and their correlation with fMRI signals. We also demonstrated that GABA, but not glutamate, in the visual system predicts visual performance. Our results provide insights into MRS-derived GABA and glutamate measurements.

Abnormal early dynamic individual patterns of functional networks in low gamma band for depression recognition

BACKGROUND

The functional networks are associated with emotional processing in depression. The mapping of dynamic spatio-temporal brain networks is used to explore individual performance during early negative emotional processing. However, the dysfunctions of functional networks in low gamma band and their discriminative potentialities during early period of emotional face processing remain to be explored.

METHODS

Functional brain networks were constructed from the MEG recordings of 54 depressed patients and 54 controls in low gamma band (30-48 Hz). Dynamic connectivity regression (DCR) algorithm analyzed the individual change points of time series in response to emotional stimuli and constructed individualized spatio-temporal patterns. The nodal characteristics of patterns were calculated and fed into support vector machine (SVM). Performance of the classification algorithm in low gamma band was validated by dynamic topological characteristics of individual patterns in comparison to alpha and beta band.

RESULTS

The best discrimination accuracy of individual spatio-temporal patterns was 91.01% in low gamma band. Individual temporal patterns had better results compared to group-averaged temporal patterns in all bands. The most important discriminative networks included affective network (AN) and fronto-parietal network (FPN) in low gamma band.

LIMITATIONS

The sample size is relatively small. High gamma band was not considered.

CONCLUSIONS

The abnormal dynamic functional networks in low gamma band during early emotion processing enabled depression recognition. The individual information processing is crucial in the discovery of abnormal spatio-temporal patterns in depression during early negative emotional processing. Individual spatio-temporal patterns may reflect the real dynamic function of subjects while group-averaged data may neglect some individual information.

Towards a theory of functional magnetic resonance spectroscopy (fMRS): A meta-analysis and discussion of using MRS to measure changes in neurotransmitters in real time

Proton magnetic resonance spectroscopy is a powerful tool to investigate neurochemistry and physiology in vivo. Recently researchers have started to use MRS to measure neurotransmitter changes related to neural activity, so called functional MRS (fMRS). Particular interest has been placed on measuring glutamate changes associated with neural function, but differences are reported in the size of changes seen. This review discusses fMRS, and includes meta-analyses of the relative size of glutamate changes seen in fMRS, and the impact experimental design and stimulus paradigm may have. On average glutamate was found to increase by 6.97% (±1.739%) in response to neural activation. However, factors of experimental design may have a large impact on the size of these changes. For example an increase of 4.749% (±1.45%) is seen in block studies compared to an increase of 13.429% (±3.59) in studies using event related paradigms. The stimulus being investigated also seems to play a role with prolonged visual stimuli showing a small mean increase in glutamate of 2.318% (±1.227%) while at the other extreme, pain stimuli show a mean stimulation effect of 14.458% (±3.736%). These differences are discussed with regards to possible physiologic interpretations, as well experimental design implications.

Inhibitory and excitatory mechanisms in the human cingulate-cortex support reinforcement learning: A functional Proton Magnetic Resonance Spectroscopy study

The dorsal anterior cingulate cortex (dACC) is crucial for motivation, reward- and error-guided decision-making, yet its excitatory and inhibitory mechanisms remain poorly explored in humans. In particular, the balance between excitation and inhibition (E/I), demonstrated to play a role in animal studies, is difficult to measure in behaving humans. Here, we used functional magnetic-resonance-spectroscopy (¹H-fMRS) to measure the brain's major inhibitory (GABA) and excitatory (Glutamate) neurotransmitters during reinforcement learning with three different conditions: high cognitive load (uncertainty); probabilistic discrimination learning; and a control null-condition. Participants learned to prefer the gain option in the discrimination phase and had no preference in the other conditions. We found increased GABA levels during the uncertainty condition, potentially reflecting recruitment of inhibitory systems during high cognitive load when trying to learn. Further, higher GABA levels during the null (baseline) condition correlated with improved discrimination learning. Finally, glutamate and GABA levels were correlated during high cognitive load. These results suggest that availability of dACC inhibitory resources enables successful learning. Our approach helps elucidate the potential contribution of the balance between excitation and inhibition to learning and motivation in behaving humans.

Beyond static measures: A review of functional magnetic resonance spectroscopy and its potential to investigate dynamic glutamatergic abnormalities in schizophrenia

Abnormalities of the glutamate system are increasingly implicated in schizophrenia but their exact nature remains unknown. Proton magnetic resonance spectroscopy (¹H-MRS), while fundamental in revealing glutamatergic alterations in schizophrenia, has, until recently, been significantly limited and thought to only provide static measures. Functional magnetic resonance spectroscopy (fMRS), which uses sequential scans for dynamic measurement of a range of brain metabolites in activated brain areas, has lately been applied to a variety of task or stimulus conditions, producing interesting insights into neurometabolite responses to neural activation. Here, we summarise the existing ¹H-MRS studies of brain glutamate in schizophrenia. We then present a comprehensive review of research studies that have utilised fMRS, and lastly consider how fMRS methods might further the understanding of glutamatergic abnormalities in schizophrenia.

Working Memory Modulates Glutamate Levels in the Dorsolateral Prefrontal Cortex during 1H fMRS

Glutamate is involved in excitatory neurotransmission and metabolic processes related to brain function. Previous studies using proton functional magnetic resonance spectroscopy (¹H fMRS) have demonstrated elevated cortical glutamate levels by 2-4% during visual and motor stimulation, relative to periods of no stimulation. Here, we extended this approach to working memory cognitive task performance, which has been consistently associated with dorsolateral prefrontal cortex (dlPFC) activation. Sixteen healthy adult volunteers completed a continuous visual fixation "rest" task followed by a letter 2-back working memory task during ¹H fMRS acquisition of the left dlPFC, which encompassed Brodmann areas 45 and 46 over a 4.5-cm³ volume. Using a 100% automated fitting procedure integrated with LCModel, raw spectra were eddy current-, phase-, and shift-corrected prior to quantification resulting in a 32s temporal resolution or 8 averages per spectra. Task compliance was high (95 ± 11% correct) and the mean Cramer-Rao Lower Bound of glutamate was 6.9 ± 0.9%. Relative to continuous passive visual fixation, left dlPFC glutamate levels were significantly higher by 2.7% (0.32 mmol/kg wet weight) during letter 2-back performance. Elevated dlPFC glutamate levels reflect increased metabolic activity and excitatory neurotransmission driven by working memory-related cognitive demands. These results provide the first in vivo demonstration of elevated dlPFC glutamate levels during working memory.

Task-based changes in proton MR spectroscopy signal during configural working memory in human medial temporal lobe

PURPOSE

To detect local cholinergic changes in human medial temporal lobe during configural working memory performance.

MATERIALS AND METHODS

Proton magnetic resonance spectroscopy (¹ H-MRS) measurements were acquired at 3T from a 2 × 2 × 3 cm voxel in right medial temporal lobe from 36 subjects during performance of a configural visual working memory task (cWMT). In order to compensate for expected task-based blood oxygenation level-dependent (BOLD) T₂ * effects, resonance signal changes of unbound choline-containing metabolites (Cho) were referenced to an internal standard of creatine + phosphocreatine metabolites (Cre) and compared between four task blocks: rest, memorization, active memory maintenance, and recognition. An unannounced memory retention test was conducted in 21 subjects. Quality assurance analyses examined task-based Cho and Cre individually as well as referenced to resonance signal from N-acetylaspartate (NAA).

RESULTS

Increases from a resting baseline in the Cho/Cre ratio were observed during 60-second blocks of active memory maintenance across the group (P = 0.0042). Behavioral accuracy during task performance correlated with memory retention (r = 0.48, P = 0.027). Quality assurance measures showed task-based changes in Cre resonance signal both individually (P = 0.00099) and when utilized as a noncholinergic internal reference (NAA/Cre, P = 0.00079).

CONCLUSION

Increases in human medial temporal lobe ¹ H-MRS Cho/Cre ratio occur during the maintenance of configural working memory information. However, interpretation of these results as driven by cholinergic activity cannot be assumed, as NAA, a noncholinergic metabolite, shows similar results when utilizing Cre as a reference. Caution is advised when considering Cre as an internal standard for task-based ¹ H-MRS measurements.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:682-691.

Proton and multinuclear magnetic resonance spectroscopy in the human brain at ultra-high field strength: A review

Magnetic Resonance Spectroscopy (MRS) allows for a non-invasive and non-ionizing determination of in vivo tissue concentrations and metabolic turn-over rates of more than 20 metabolites and compounds in the central nervous system of humans. The aim of this review is to give a comprehensive overview about the advantages, challenges and advances of ultra-high field MRS with regard to methodological development, discoveries and applications from its beginnings around 15 years ago up to the current state. The review is limited to human brain and spinal cord application at field strength of 7T and 9.4T and includes all relevant nuclei (¹H, ³¹P, ¹³C).

GABA metabolism and its role in gamma-band oscillatory activity during auditory processing: An MRS and EEG study

Gamma-aminobutyric acid (GABA) and glutamate are believed to have inhibitory and exhibitory neuromodulatory effects that regulate the brain's response to sensory perception. Furthermore, frequency-specific synchronization of neuronal excitability within the gamma band (30-80 Hz) is attributable to a homeostatic balance between excitation and inhibition. However, our understanding of the physiological mechanism underlying gamma rhythms is based on animal models. Investigations of the relationship between GABA concentrations, glutamate concentrations, and gamma band activity in humans were mostly restricted to the visual cortex and are conflicting. Here, we performed a multimodal imaging study combining magnetic resonance spectroscopy (MRS) with electroencephalography (EEG) in the auditory cortex. In 14 healthy subjects, we investigated the impact of individual differences in GABA and glutamate concentration on gamma band response (GBR) following auditory stimulus presentation. We explored the effects of bulk GABA on the GBR across frequency (30-200 Hz) and time (-200 to 600 ms) and found no significant relationship. Furthermore, no correlations were found between gamma peak frequency or power measures and metabolite concentrations (GABA, glutamate, and GABA/glutamate ratio). These findings suggest that, according to MRS measurements, and given the auditory stimuli used in this study, GABA and glutamate concentrations are unlikely to play a significant role in the inhibitory and excitatory drive in the generation of gamma band activity in the auditory cortex. Hum Brain Mapp 38:3975-3987, 2017. © 2017 Wiley Periodicals, Inc.

Analysis of Gamma-Band Activity from Human EEG Using Empirical Mode Decomposition

The purpose of this paper is to determine whether gamma-band activity detection is improved when a filter, based on empirical mode decomposition (EMD), is added to the pre-processing block of single-channel electroencephalography (EEG) signals. EMD decomposes the original signal into a finite number of intrinsic mode functions (IMFs). EEGs from 25 control subjects were registered in basal and motor activity (hand movements) using only one EEG channel. Over the basic signal, IMF signals are computed. Gamma-band activity is computed using power spectrum density in the 30–60 Hz range. Event-related synchronization (ERS) was defined as the ratio of motor and basal activity. To evaluate the performance of the new EMD based method, ERS was computed from the basic and IMF signals. The ERS obtained using IMFs improves, from 31.00% to 73.86%, on the original ERS for the right hand, and from 22.17% to 47.69% for the left hand. As EEG processing is improved, the clinical applications of gamma-band activity will expand.

In vivo functional neurochemistry of human cortical cholinergic function during visuospatial attention

Cortical acetylcholine is involved in key cognitive processes such as visuospatial attention. Dysfunction in the cholinergic system has been described in a number of neuropsychiatric disorders. Levels of brain acetylcholine can be pharmacologically manipulated, but it is not possible to directly measure it in vivo in humans. However, key parts of its biochemical cascade in neural tissue, such as choline, can be measured using magnetic resonance spectroscopy (MRS). There is evidence that levels of choline may be an indirect but proportional measure of acetylcholine availability in brain tissue. In this study, we measured relative choline levels in the parietal cortex using functional (event-related) MRS (fMRS) during performance of a visuospatial attention task, with a modelling approach verified using simulated data. We describe a task-driven interaction effect on choline concentration, specifically driven by contralateral attention shifts. Our results suggest that choline MRS has the potential to serve as a proxy of brain acetylcholine function in humans.

Microstructural and functional correlates of glutamate concentration in the posterior cingulate cortex

Glutamate is the major excitatory neurotransmitter in the human brain and has a central role in both intrinsic and stimulus-induced activity. We conducted a study in a cohort of healthy, male volunteers in which glutamate levels were measured in the posterior cingulate cortex (PCC) using 1H magnetic resonance spectroscopy at 3T. The advantages of simultaneous electroencephalography and magnetic resonance imaging (EEG-MRI) were exploited and the subjects were measured in the same session and under the same physiological conditions. Diffusion tensor imaging (DTI), functional MRI (fMRI) and EEG were measured in order to investigate the functional and microstructural correlates of glutamate. The concentration of glutamate (institute units) was calculated and those values were tested for correlation with the metrics of resting state fMRI, DTI, and EEG electrical sources. Our results showed that the concentration of glutamate in the PCC had a significant negative correlation with the tissue mean diffusivity in the same area. The analysis of resting state networks did not show any relationship between the concentration of glutamate and the intrinsic activity of the resting state networks. The concentration of glutamate showed a positive correlation with the electrical generators of α-1 frequency and a negative correlation with the generators of α-2 and β-1 electrical generators. © 2017 Wiley Periodicals, Inc.

Reduced γ-Aminobutyric Acid and Glutamate+Glutamine Levels in Drug-Naïve Patients with First-Episode Schizophrenia but Not in Those at Ultrahigh Risk

Altered γ-aminobutyric acid (GABA), glutamate (Glu) levels, and an imbalance between GABAergic and glutamatergic neurotransmissions have been involved in the pathophysiology of schizophrenia. However, it remains unclear how these abnormalities impact the onset and course of psychosis. In the present study, 21 drug-naïve subjects at ultrahigh risk for psychosis (UHR), 16 drug-naïve patients with first-episode schizophrenia (FES), and 23 healthy controls (HC) were enrolled. In vivo GABA and glutamate+glutamine (Glx) levels in the medial prefrontal cortex were measured using proton magnetic resonance spectroscopy. Medial prefrontal GABA and Glx levels in FES patients were significantly lower than those in HC and UHR, respectively. GABA and Glx levels in UHR were comparable with those in HC. In each group, there was a positive correlation between GABA and Glx levels. Reduced medial prefrontal GABA and Glx levels thus may play an important role in the early stages of schizophrenia.

Measuring neural excitation and inhibition in autism: Different approaches, different findings and different interpretations

The balance of neural excitation and inhibition (E/I balance) is often hypothesised to be altered in autism spectrum disorder (ASD). One widely held view is that excitation levels are elevated relative to inhibition in ASD. Understanding whether, and how, E/I balance may be altered in ASD is important given the recent interest in trialling pharmacological interventions for ASD which target inhibitory neurotransmitter function. Here we provide a critical review of evidence for E/I balance in ASD. We conclude that data from a number of domains provides support for alteration in excitation and inhibitory neurotransmission in ASD, but when considered collectively, the available literature provide little evidence to support claims for either a net increase in excitation or a net increase in inhibition. Strengths and limitations of available techniques are considered, and directions for future research discussed.