Functional dynamics of hippocampal glutamate during associative learning assessed with in vivo 1H functional magnetic resonance spectroscopy

The importance of covert memory consolidation in schizophrenia: Dysfunctional network profiles of the hippocampus and the dorsolateral prefrontal cortex

Altered brain network profiles in schizophrenia (SCZ) during memory consolidation are typically observed during task-active periods such as encoding or retrieval. However active processes are also sub served by covert periods of memory consolidation. These periods are active in that they allow memories to be recapitulated even in the absence of overt sensorimotor processing. It is plausible that regions central to memory formation like the dlPFC and the hippocampus, exert network signatures during covert periods. Are these signatures altered in patients? The question is clinically relevant because real world learning and memory is facilitated by covert processing, and may be impaired in schizophrenia. Here, we compared network signatures of the dlPFC and the hippocampus during covert periods of a learning and memory task. Because behavioral proficiency increased non-linearly, functional connectivity of the dlPFC and hippocampus [psychophysiological interaction (PPI)] was estimated for each of the Early (linear increases in performance) and Late (asymptotic performance) covert periods. During Early periods, we observed hypo-modulation by the hippocampus but hyper-modulation by dlPFC. Conversely, during Late periods, we observed hypo-modulation by both the dlPFC and the hippocampus. We stitch these results into a conceptual model of network deficits during covert periods of memory consolidation.

Excitatory and inhibitory neurochemical markers of anxiety in young females

Between the ages of 10-25 years the maturing brain is sensitive to a multitude of changes, including neurochemical variations in metabolites. Of the different metabolites, gamma-aminobutyric acid (GABA) has long been linked neurobiologically to anxiety symptomology, which begins to manifest in adolescence. To prevent persistent anxiety difficulties into adulthood, we need to understand the maturational trajectories of neurochemicals and how these relate to anxiety levels during this sensitive period. We used magnetic resonance spectroscopy in a sample of younger (aged 10-11) and older (aged 18-25) females to estimate GABA and glutamate levels in brain regions linked to emotion regulation processing, as well as a conceptually distinct control region. Within the Bayesian framework, we found that GABA increased and glutamate decreased with age, negative associations between anxiety and glutamate and GABA ratios in the dorsolateral prefrontal cortex, and a positive relationship of GABA with anxiety levels. The results support the neural over-inhibition hypothesis of anxiety based on GABAergic activity.

HIV chronicity as a predictor of hippocampal memory deficits in daily cannabis users living with HIV

Background

Antiretroviral medications have increased the lifespan of persons living with HIV (PLWH) thereby unmasking memory decline that may be attributed to chronological age, HIV symptomatology, HIV disease chronicity, and/or substance use (especially cannabis use which is common among PLWH). To date, few studies have attempted to disentangle these effects. In a sample of daily cannabis-using PLWH, we investigated whether hippocampal memory function, assessed via an object-location associative learning task, was associated with age, HIV chronicity and symptom severity, or substance use.

Methods

48 PLWH (12.9 ± 9.6 years since HIV diagnosis), who were 44 years old on average (range: 24-64 years; 58 % male) and reported daily cannabis use (recent use confirmed by urinalysis) completed the study. We assessed each participant's demographics, substance use, medical history, current HIV symptoms, and hippocampal memory function via a well-validated object-location associative learning task.

Results

Multiple regression analyses found that living more years since HIV+ diagnosis predicted significantly worse associative learning total score (r=-0.40) and learning rate (r=-0.34) whereas chronological age, cannabis-use characteristics, and recent HIV symptom severity were not significantly related to hippocampal memory function.

Conclusions

In daily cannabis-using PLWH, HIV chronicity was related to worse hippocampal memory function independent from cannabis use, age, and HIV symptomatology. Object-location associative learning performance could serve as an 'early-warning' metric of cognitive decline among PLWH. Future research should examine longitudinal changes in associative learning proficiency and evaluate interventions to prevent hippocampal memory decline among PLWH. ClinicalTrials.gov: NCT01536899.

Basal glutamate in the hippocampus and the dorsolateral prefrontal cortex in schizophrenia: Relationships to cognitive proficiency investigated with structural equation modelling

OBJECTIVES

Schizophrenia is characterised by deficits across multiple cognitive domains and altered glutamate related neuroplasticity. The purpose was to investigate whether glutamate deficits are related to cognition in schizophrenia, and whether glutamate-cognition relationships are different between schizophrenia and controls.

METHODS

Magnetic resonance spectroscopy (MRS) at 3 Tesla was acquired from the dorsolateral prefrontal cortex (dlPFC) and hippocampus in 44 schizophrenia participants and 39 controls during passive viewing visual task. Cognitive performance (working memory, episodic memory, and processing speed) was assessed on a separate session. Group differences in neurochemistry and mediation/moderation effects using structural equation modelling (SEM) were investigated.

RESULTS

Schizophrenia participants showed lower hippocampal glutamate (p = .0044) and myo-Inositol (p = .023) levels, and non-significant dlPFC levels. Schizophrenia participants also demonstrated poorer cognitive performance (p < .0032). SEM-analyses demonstrated no mediation or moderation effects, however, an opposing dlPFC glutamate-processing speed association between groups was observed.

CONCLUSIONS

Hippocampal glutamate deficits in schizophrenia participants are consistent with evidence of reduced neuropil density. Moreover, SEM analyses indicated that hippocampal glutamate deficits in schizophrenia participants as measured during a passive state were not driven by poorer cognitive ability. We suggest that functional MRS may provide a better framework for investigating glutamate-cognition relationships in schizophrenia.

Approach-avoidance behavior and motor-specific modulation towards smoking-related cues in smokers

AIMS

By performing three transcranial magnetic stimulation (TMS) experiments, we measured the motor-specific modulatory mechanisms in the primary motor cortex (M1) at both the intercortical and intracortical levels when smokers actively approach or avoid smoking-related cues.

DESIGN, SETTING AND PARTICIPANTS

For all experiments, the design was group (smokers versus non-smokers) × action (approach versus avoidance) × image type (neutral versus smoking-related). The study was conducted at the Shanghai University of Sport, CHN, TMS Laboratory. For experiment 1, 30 non-smokers and 30 smokers; for experiment 2, 16 non-smokers and 16 smokers; for experiment 3, 16 non-smokers and 16 smokers.

MEASUREMENTS

For all experiments, the reaction times were measured using the smoking stimulus-response compatibility task. While performing the task, single-pulse TMS was applied to the M1 in experiment 1 to measure the excitability of the corticospinal pathways, and paired-pulse TMS was applied to the M1 in experiments 2 and 3 to measure the activity of intracortical facilitation (ICF) and short-interval intracortical inhibition (SICI) circuits, respectively.

FINDINGS

Smokers had faster responses when approaching smoking-related cues (F1,58  = 36.660, P < 0.001, η p 2  = 0.387), accompanied by higher excitability of the corticospinal pathways (F1,58  = 10.980, P = 0.002, η p 2  = 0.159) and ICF circuits (F1,30  = 22.187, P < 0.001, η p 2  = 0.425), while stronger SICI effects were observed when they avoided these cues (F1,30  = 10.672, P = 0.003, η p 2  = 0.262).

CONCLUSIONS

Smokers appear to have shorter reaction times, higher motor-evoked potentials and stronger intracortical facilitation effects when performing approach responses to smoking-related cues and longer reaction times, a lower primary motor cortex descending pathway excitability and a stronger short-interval intracortical inhibition effect when avoiding them.

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.

Learning without contingencies: A loss of synergy between memory and reward circuits in schizophrenia

Motivational deficits in schizophrenia may interact with foundational cognitive processes including learning and memory to induce impaired cognitive proficiency. If such a loss of synergy exists, it is likely to be underpinned by a loss of synchrony between the brains learning and reward sub-networks. Moreover, this loss should be observed even during tasks devoid of explicit reward contingencies given that such tasks are better models of real world performance than those with artificial contingencies. Here we applied undirected functional connectivity (uFC) analyses to fMRI data acquired while participants engaged in an associative learning task without contingencies or feedback. uFC was estimated and inter-group differences (between schizophrenia patients and controls, n = 54 total, n = 28 patients) were assessed within and between reward (VTA and NAcc) and learning/memory (Basal Ganglia, DPFC, Hippocampus, Parahippocampus, Occipital Lobe) sub-networks. The task paradigm itself alternated between Encoding, Consolidation, and Retrieval conditions, and uFC differences were quantified for each of the conditions. Significantly reduced uFC dominated the connectivity profiles of patients across all conditions. More pertinent to our motivations, these reductions were observed within and across classes of sub-networks (reward-related and learning/memory related). We suggest that disrupted functional connectivity between reward and learning sub-networks may drive many of the performance deficits that characterize schizophrenia. Thus, cognitive deficits in schizophrenia may in fact be underpinned by a loss of synergy between reward-sensitivity and cognitive processes.

Multimodal neuroimaging data from a 5-week heart rate variability biofeedback randomized clinical trial

We present data from the Heart Rate Variability and Emotion Regulation (HRV-ER) randomized clinical trial testing effects of HRV biofeedback. Younger (N = 121) and older (N = 72) participants completed baseline magnetic resonance imaging (MRI) including T1-weighted, resting and emotion regulation task functional MRI (fMRI), pulsed continuous arterial spin labeling (PCASL), and proton magnetic resonance spectroscopy (1H MRS). During fMRI scans, physiological measures (blood pressure, pulse, respiration, and end-tidal CO2) were continuously acquired. Participants were randomized to either increase heart rate oscillations or decrease heart rate oscillations during daily sessions. After 5 weeks of HRV biofeedback, they repeated the baseline measurements in addition to new measures (ultimatum game fMRI, training mimicking during blood oxygen level dependent (BOLD) and PCASL fMRI). Participants also wore a wristband sensor to estimate sleep time. Psychological assessment comprised three cognitive tests and ten questionnaires related to emotional well-being. A subset (N = 104) provided plasma samples pre- and post-intervention that were assayed for amyloid and tau. Data is publicly available via the OpenNeuro data sharing platform.

The future is 2D: spectral-temporal fitting of dynamic MRS data provides exponential gains in precision over conventional approaches

PURPOSE

Many MRS paradigms produce 2D spectral-temporal datasets, including diffusion-weighted, functional, and hyperpolarized and enriched (carbon-13, deuterium) experiments. Conventionally, temporal parameters-such as T₂ , T₁ , or diffusion constants-are assessed by first fitting each spectrum independently and subsequently fitting a temporal model (1D fitting). We investigated whether simultaneously fitting the entire dataset using a single spectral-temporal model (2D fitting) would improve the precision of the relevant temporal parameter.

METHODS

We derived a Cramer Rao lower bound for the temporal parameters for both 1D and 2D approaches for 2 experiments: a multi-echo experiment designed to estimate metabolite T₂ s, and a functional MRS experiment designed to estimate fractional change ( δ $$ \delta $$ ) in metabolite concentrations. We investigated the dependence of the relative standard deviation (SD) of T₂ in multi-echo and δ $$ \delta $$ in functional MRS.

RESULTS

When peaks were spectrally distant, 2D fitting improved precision by approximately 20% relative to 1D fitting, regardless of the experiment and other parameter values. These gains increased exponentially as peaks drew closer. Dependence on temporal model parameters was weak to negligible.

CONCLUSION

Our results strongly support a 2D approach to MRS fitting where applicable, and particularly in nuclei such as hydrogen and deuterium, which exhibit substantial spectral overlap.

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.

The topology, stability, and instability of learning-induced brain network repertoires in schizophrenia

There is a paucity of graph theoretic methods applied to task-based data in schizophrenia (SCZ). Tasks are useful for modulating brain network dynamics, and topology. Understanding how changes in task conditions impact inter-group differences in topology can elucidate unstable network characteristics in SCZ. Here, in a group of patients and healthy controls (n = 59 total, 32 SCZ), we used an associative learning task with four distinct conditions (Memory Formation, Post-Encoding Consolidation, Memory Retrieval, and Post-Retrieval Consolidation) to induce network dynamics. From the acquired fMRI time series data, betweenness centrality (BC), a metric of a node's integrative value was used to summarize network topology in each condition. Patients showed (a) differences in BC across multiple nodes and conditions; (b) decreased BC in more integrative nodes, but increased BC in less integrative nodes; (c) discordant node ranks in each of the conditions; and (d) complex patterns of stability and instability of node ranks across conditions. These analyses reveal that task conditions induce highly variegated patterns of network dys-organization in SCZ. We suggest that the dys-connection syndrome that is schizophrenia, is a contextually evoked process, and that the tools of network neuroscience should be oriented toward elucidating the limits of this dys-connection.

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.

Three's Company: Neuroimmune activation, sex, and memory at the tripartite synapse

The neuroimmune system is required for normal cognitive functions such as learning and memory in addition to its critical role in detecting and responding to invading pathogens and injury. Understanding the functional convergence of neurons, astrocytes, and microglia at the synapse, particularly in the hippocampus, is key to understanding the nuances of such diverse roles. In the healthy brain, communication between all three cells is important for regulating neuronal activation and synaptic plasticity mechanisms, and during neuroinflammation, the activity and functions of all three cells can produce and be modulated by inflammatory cytokines. An important remaining component to this system is the conclusive evidence of sex differences in hippocampal plasticity mechanisms, hormone modulation of synaptic plasticity, functional properties of hippocampal neurons, and in neuroimmune activation. Sex as a biological variable here is necessary to consider given sex differences in the prevalence of memory-related disorders such as Alzheimer's disease and Post-Traumatic Stress disorder, both of which present with neuroimmune dysregulation. To make meaningful progress towards a deeper understanding of sex biases in memory-related disease prevalence, I propose that the next chapter of psychoneuroimmune research must focus on the signal integration and transduction at the synapse between experience-dependent plasticity mechanisms, neuroimmune activation, and the influence of biological sex.

A role for GABA in the modulation of striatal and hippocampal systems under stress

Previous research has demonstrated that stress modulates the competitive interaction between the hippocampus and striatum, two structures known to be critically involved in motor sequence learning. These earlier investigations, however, have largely focused on blood oxygen-level dependent (BOLD) responses. No study to date has examined the link between stress, motor learning and levels of striatal and hippocampal gamma-aminobutyric acid (GABA). This knowledge gap is surprising given the known role of GABA in neuroplasticity subserving learning and memory. The current study thus examined: a) the effects of motor learning and stress on striatal and hippocampal GABA levels; and b) how learning- and stress-induced changes in GABA relate to the neural correlates of learning. To do so, fifty-three healthy young adults were exposed to a stressful or non-stressful control intervention before motor sequence learning. Striatal and hippocampal GABA levels were assessed at baseline and post-intervention/learning using magnetic resonance spectroscopy. Regression analyses indicated that stress modulated the link between striatal GABA levels and functional plasticity in both the hippocampus and striatum during learning as measured with fMRI. This study provides evidence for a role of GABA in the stress-induced modulation of striatal and hippocampal systems.

From mathematics to medicine: A practical primer on topological data analysis (TDA) and the development of related analytic tools for the functional discovery of latent structure in fMRI data

fMRI is the preeminent method for collecting signals from the human brain in vivo, for using these signals in the service of functional discovery, and relating these discoveries to anatomical structure. Numerous computational and mathematical techniques have been deployed to extract information from the fMRI signal. Yet, the application of Topological Data Analyses (TDA) remain limited to certain sub-areas such as connectomics (that is, with summarized versions of fMRI data). While connectomics is a natural and important area of application of TDA, applications of TDA in the service of extracting structure from the (non-summarized) fMRI data itself are heretofore nonexistent. “Structure” within fMRI data is determined by dynamic fluctuations in spatially distributed signals over time, and TDA is well positioned to help researchers better characterize mass dynamics of the signal by rigorously capturing shape within it. To accurately motivate this idea, we a) survey an established method in TDA (“persistent homology”) to reveal and describe how complex structures can be extracted from data sets generally, and b) describe how persistent homology can be applied specifically to fMRI data. We provide explanations for some of the mathematical underpinnings of TDA (with expository figures), building ideas in the following sequence: a) fMRI researchers can and should use TDA to extract structure from their data; b) this extraction serves an important role in the endeavor of functional discovery, and c) TDA approaches can complement other established approaches toward fMRI analyses (for which we provide examples). We also provide detailed applications of TDA to fMRI data collected using established paradigms, and offer our software pipeline for readers interested in emulating our methods. This working overview is both an inter-disciplinary synthesis of ideas (to draw researchers in TDA and fMRI toward each other) and a detailed description of methods that can motivate collaborative research.

Asymmetric left-right hippocampal glutamatergic modulation of cognitive control in ApoE-isoform subjects is unrelated to neuroinflammation

The glutamatergic cycle is essential in modulating memory processing by the hippocampal circuitry. Our combined proton magnetic resonance spectroscopy (¹H‐MRS) and task‐based functional magnetic resonance imaging (fMRI) study (using face‐name paired‐associates encoding and retrieval task) of a cognitively normal cohort of 67 healthy adults (18 ApoE4 carriers and 49 non‐ApoE4 carriers) found altered patterns of relationships between glutamatergic‐modulated synaptic signalling and neuronal activity or functional hyperaemia in the ApoE4 isoforms. Our study highlighted the asymmetric left–right hippocampal glutamatergic system in modulating neuronal activities in ApoE4 carriers versus non‐carriers. Such brain differentiation might be developmental cognitive advantages or compensatory due to impaired synaptic integrity and plasticity in ApoE4 carriers. As there was no difference in myoinositol levels measured by MRS between the ApoE4 and non‐ApoE4 subgroups, the mechanism is unlikely to be a response to neuroinflammation.

Predicting learning and achievement using GABA and glutamate concentrations in human development

Previous research has highlighted the role of glutamate and gamma-aminobutyric acid (GABA) in learning and plasticity. What is currently unknown is how this knowledge translates to real-life complex cognitive abilities that emerge slowly and how the link between these neurotransmitters and human learning and plasticity is shaped by development. While some have suggested a generic role of glutamate and GABA in learning and plasticity, others have hypothesized that their involvement shapes sensitive periods during development. Here we used a cross-sectional longitudinal design with 255 individuals (spanning primary school to university) to show that glutamate and GABA in the intraparietal sulcus explain unique variance both in current and future mathematical achievement (approximately 1.5 years). Furthermore, our findings reveal a dynamic and dissociable role of GABA and glutamate in predicting learning, which is reversed during development, and therefore provide novel implications for models of learning and plasticity during childhood and adulthood.

Ocular measures during associative learning predict recall accuracy

The ability to form associations between stimuli and commit those associations to memory is a cornerstone of human cognition. Dopamine and noradrenaline are critical neuromodulators implicated in a range of cognitive functions, including learning and memory. Eye blink rate (EBR) and pupil diameter have been shown to index dopaminergic and noradrenergic activity. Here, we examined how these ocular measures relate to accuracy in a paired-associate learning task where participants (N = 73) learned consistent object-location associations over eight trials consisting of pre-trial fixation, encoding, delay, and retrieval epochs. In order to examine how within-subject changes and between-subject changes in ocular metrics related to accuracy, we mean centered individual metric values on each trial based on within-person and across-subject means for each epoch. Within-participant variation in EBR was positively related to accuracy in both encoding and delay epochs: faster EBR within the individual predicted better retrieval. Differences in EBR across participants was negatively related to accuracy in the encoding epoch and in early trials of the pre-trial fixation: faster EBR, relative to other subjects, predicted poorer retrieval. Visual scanning behavior in pre-trial fixation and delay epochs was also positively related to accuracy in early trials: more scanning predicted better retrieval. We found no relationship between pupil diameter and accuracy. These results provide novel evidence supporting the utility of ocular metrics in illuminating cognitive and neurobiological mechanisms of paired-associate learning.

Determinants of Schizophrenia Endophenotypes Based on Neuroimaging and Biochemical Parameters

Despite extensive research, there is no convincing evidence of a reliable diagnostic biomarker for schizophrenia beyond clinical observation. Disorders of glutamatergic neurotransmission associated with N-methyl-D-aspartate (NMDA) receptor insufficiency, neuroinflammation, and redox dysregulation are the principal common mechanism linking changes in the periphery with the brain, ultimately contributing to the emergence of negative symptoms of schizophrenia that underlie differential diagnosis. The aim of the study was to evaluate the influence of these systems via peripheral and cerebral biochemical indices in relation to the patient's clinical condition. Using neuroimaging diagnostics, we were able to define endophenotypes of schizophrenia based on objective laboratory data that form the basis of a personalized approach to diagnosis and treatment. The two distinguished endophenotypes differed in terms of the quality of life, specific schizophrenia symptoms, and glutamatergic neurotransmission metabolites in the anterior cingulate gyrus. Our results, as well as further studies of the excitatory or inhibitory balance of microcircuits, relating the redox systems on the periphery with the distant regions of the brain might allow for predicting potential biomarkers of neuropsychiatric diseases, including schizophrenia. To the best of our knowledge, our study is the first to identify an objective molecular biomarker of schizophrenia outcome.

Effects of SSRI treatment on GABA and glutamate levels in an associative relearning paradigm

Impaired cognitive flexibility represents a widespread symptom in psychiatric disorders, including major depressive disorder (MDD), a disease, characterized by an imbalance of neuro-transmitter concentrations. While memory formation is mostly associated with glutamate, also gamma-Aminobutyric acid (GABA) and serotonin show attributions in a complex interplay between neurotransmitter systems. Treatment with selective serotonin reuptake inhibitors (SSRIs) does not solely affect the serotonergic system but shows downstream effects on GABA- and glutamatergic neurotransmission, potentially helping to restore cognitive function via neuroplastic effects. Hence, this study aims to elaborate the effects of associative relearning and SSRI treatment on GABAergic and glutamatergic function within and between five brain regions using magnetic resonance spectroscopy imaging (MRSI).

In this study, healthy subjects were randomized into four groups which underwent three weeks of an associative relearning paradigm, with or without emotional connotation, under SSRI (10mg escitalopram) or placebo administration. MRSI measurements, using a spiral-encoded, 3D-GABA-edited MEGA-LASER sequence at 3T, were performed on the first and last day of relearning. Mean GABA+/tCr (GABA+ = GABA + macromolecules; tCr = total creatine) and Glx/tCr (Glx = glutamate + glutamine) ratios were quantified in a ROI-based approach for the hippocampus, insula, putamen, pallidum and thalamus, using LCModel. A total of 66 subjects ((37 female, mean age ± SD = 25.4±4.7) for Glx/tCr and 58 subjects (32 female, mean age ± SD = 25.1±4.7) for GABA+/tCr were included in the final analysis.

A significant measurement by region and treatment (SSRI vs placebo) interaction on Glx/tCr ratios was found (p_cor=0.017), with post hoc tests confirming differential effects on hippocampus and thalamus (p_cor=0.046). Moreover, treatment by time comparison, for each ROI independently, showed a reduction of hippocampal Glx/tCr ratios after SSRI treatment (p_uncor=0.033). No significant treatment effects on GABA+/tCr ratios or effects of relearning condition on any neurotransmitter ratio could be found.

Here, we showed a significant SSRI- and relearning-driven interaction effect of hippocampal and thalamic Glx/tCr levels, suggesting differential behavior based on different serotonin transporter and receptor densities. Moreover, an indication for Glx/tCr adaptions in the hippocampus after three weeks of SSRI treatment could be revealed. Our findings are in line with animal studies reporting glutamate adaptions in the hippocampus following chronic SSRI intake. Due to the complex interplay of serotonin and hippocampal function, involving multiple serotonin receptor subtypes on glutamatergic cells and GABAergic interneurons, the interpretation of underlying neurobiological actions remains challenging.

Complementary contributions of non-REM and REM sleep to visual learning

Sleep is beneficial for learning. However, it remains unclear whether learning is facilitated by non-REM (NREM) sleep or by REM sleep, whether it results from plasticity increases or stabilization, and whether facilitation results from learning-specific processing. Here, we trained volunteers on a visual task, and measured the excitatory and inhibitory (E/I) balance in early visual areas during subsequent sleep as an index of plasticity. E/I balance increased during NREM sleep irrespective of whether pre-sleep learning occurred, but it was associated with post-sleep performance gains relative to pre-sleep performance. By contrast, E/I balance decreased during REM sleep but only after pre-sleep training, and the decrease was associated with stabilization of pre-sleep learning. These findings indicate that NREM sleep promotes plasticity, leading to performance gains independent of learning, while REM sleep decreases plasticity to stabilize learning in a learning-specific manner.

Disordered directional brain network interactions during learning dynamics in schizophrenia revealed by multivariate autoregressive models

Directional network interactions underpin normative brain function in key domains including associative learning. Schizophrenia (SCZ) is characterized by altered learning dynamics, yet dysfunctional directional functional connectivity (dFC) evoked during learning is rarely assessed. Here, nonlinear learning dynamics were induced using a paradigm alternating between conditions (Encoding and Retrieval). Evoked fMRI time series data were modeled using multivariate autoregressive (MVAR) models, to discover dysfunctional direction interactions between brain network constituents during learning stages (Early vs. Late), and conditions. A functionally derived subnetwork of coactivated (healthy controls [HC] ∩ SCZ] nodes was identified. MVAR models quantified directional interactions between pairs of nodes, and coefficients were evaluated for intergroup differences (HC ≠ SCZ). In exploratory analyses, we quantified statistical effects of neuroleptic dosage on performance and MVAR measures. During Early Encoding, SCZ showed reduced dFC within a frontal–hippocampal–fusiform network, though during Late Encoding reduced dFC was associated with pathways toward the dorsolateral prefrontal cortex (dlPFC). During Early Retrieval, SCZ showed increased dFC in pathways to and from the dorsal anterior cingulate cortex, though during Late Retrieval, patients showed increased dFC in pathways toward the dlPFC, but decreased dFC in pathways from the dlPFC. These discoveries constitute novel extensions of our understanding of task‐evoked dysconnection in schizophrenia and motivate understanding of the directional aspect of the dysconnection in schizophrenia. Disordered directionality should be investigated using computational psychiatric approaches that complement the MVAR method used in our work.

Hippocampal GABA levels correlate with retrieval performance in an associative learning paradigm

Neural plasticity is a complex process dependent on neurochemical underpinnings. Next to the glutamatergic system which contributes to memory formation via long-term potentiation (LTP) and long-term depression (LTD), the main inhibitory neurotransmitter, GABA is crucially involved in neuroplastic processes. Hence, we investigated changes in glutamate and GABA levels in the brain in healthy participants performing an associative learning paradigm. Twenty healthy participants (10 female, 25 ± 5 years) underwent paired multi-voxel magnetic resonance spectroscopy imaging before and after completing 21 days of a facial associative learning paradigm in a longitudinal study design. Changes of GABA and glutamate were compared to retrieval success in the hippocampus, insula and thalamus. No changes in GABA and glutamate concentration were found after 21 days of associative learning. However, baseline hippocampal GABA levels were significantly correlated with initial retrieval success (pcor = 0.013, r = 0.690). In contrast to the thalamus and insula (pcor>0.1), higher baseline GABA levels in the hippocampus were associated with better retrieval performance in an associative learning paradigm. Therefore, our findings support the importance of hippocampal GABA levels in memory formation in the human brain in vivo.

Glutamate transporters: Gene expression regulation and signaling properties

Glutamate is the major excitatory neurotransmitter in the vertebrate central nervous system. During synaptic activity, glutamate is released and binds to specific membrane receptors and transporters activating, in the one hand, a wide variety of signal transduction cascades, while in the other hand, its removal from the synaptic cleft. Extracellular glutamate concentrations are maintained within physiological levels mainly by glia glutamate transporters. Inefficient clearance of this amino acid is neurotoxic due to a prolonged hyperactivation of its postsynaptic receptors, exacerbating a wide array of intracellular events linked to an ionic imbalance, that results in neuronal cell death. This process is known as excitotoxicity and is the underlying mechanisms of an important number of neurodegenerative diseases. Therefore, it is important to understand the regulation of glutamate transporters function. The transporter activity can be regulated at different levels: gene expression, transporter protein targeting and trafficking, and post-translational modifications of the transporter protein. The identification of these mechanisms has paved the way to our current understanding the role of glutamate transporters in brain physiology and will certainly provide the needed biochemical information for the development of therapeutic strategies towards the establishment of novel therapeutic approaches for the treatment and/or prevention of pathologies associated with excitotoxicity insults. This article is part of the issue entitled 'Special Issue on Neurotransmitter Transporters'.

Pharmacological stress impairs working memory performance and attenuates dorsolateral prefrontal cortex glutamate modulation

Working memory processes are associated with the dorsolateral prefrontal cortex (dlPFC). Prior research using proton functional magnetic resonance spectroscopy (¹H fMRS) observed significant dlPFC glutamate modulation during letter 2-back performance, indicative of working memory-driven increase in excitatory neural activity. Acute stress has been shown to impair working memory performance. Herein, we quantified dlPFC glutamate modulation during working memory under placebo (oral lactose) and acute stress conditions (oral yohimbine 54 mg + hydrocortisone 10 mg). Using a double-blind, randomized crossover design, participants (N = 19) completed a letter 2-back task during left dlPFC ¹H fMRS acquisition (Brodmann areas 45/46; 4.5 cm³). An automated fitting procedure integrated with LCModel was used to quantify glutamate levels. Working memory-induced glutamate modulation was calculated as percentage change in glutamate levels from passive visual fixation to 2-back levels. Results indicated acute stress significantly attenuated working memory-induced glutamate modulation and impaired 2-back response accuracy, relative to placebo levels. Follow-up analyses indicated 2-back performance significantly modulated glutamate levels relative to passive visual fixation during placebo but not acute stress. Biomarkers, including blood pressure and saliva cortisol, confirmed that yohimbine + hydrocortisone dosing elicited a significant physiological stress response. These findings support a priori hypotheses and demonstrate that acute stress impairs dlPFC function and excitatory activity. This study highlights a neurobiological mechanism through which acute stress may contribute to psychiatric dysfunction and derail treatment progress. Future research is needed to isolate noradrenaline vs. cortisol effects and evaluate anti-stress medications and/or behavioral interventions.

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.

Differences in steady-state glutamate levels and variability between 'non-task-active' conditions: Evidence from 1H fMRS of the prefrontal cortex

Proton functional magnetic resonance spectroscopy (1H fMRS) is a noninvasive neuroimaging technique capable of detecting dynamic changes in glutamate related to task-related demands at a temporal resolution under 1 min. Several recent 1H fMRS studies demonstrated elevated steady-state levels of glutamate of 2% or greater during different 'task-active' conditions, relative to a 'non-task-active' control condition. However, the 'control' condition from these studies does vary with respect to the degree of constraining behavior, which may lead to different glutamate levels or variability between 'control' conditions. The purpose of this 1H fMRS study was to compare the steady-state levels and variability of glutamate in the left dorsolateral prefrontal cortex (dlPFC) of 16 healthy adults across four different putative 'non-task-active' conditions: relaxed with eyes closed, passive visual fixation crosshair, visual flashing checkerboard, and finger tapping. Results showed significantly lower glutamate levels during the passive visual fixation crosshair than the visual flashing checkerboard and the finger tapping conditions. Moreover, glutamate was significantly less variable during the passive visual fixation crosshair and the visual flashing checkerboard than the relaxed eyes closed condition. Of the four conditions, the passive visual fixation crosshair condition demonstrated the lowest and least variable glutamate levels potentially reflecting the least dlPFC engagement, but greatest behavioral constraint. These results emphasize the importance of selecting a proper 'control' condition to reflect accurately a 'non-task-active' steady-state level of glutamate with minimal variability during 1H MRS investigations.

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.

Functional Magnetic Resonance Spectroscopy: The "New" MRS for Cognitive Neuroscience and Psychiatry Research

Proton magnetic resonance spectroscopy (¹H MRS) is a well-established technique for quantifying the brain regional biochemistry in vivo. In most studies, however, the ¹H MRS is acquired during rest with little to no constraint on behavior. Measured metabolite levels, therefore, reflect steady-state concentrations whose associations with behavior and cognition are unclear. With the recent advances in MR technology-higher-field MR systems, robust acquisition techniques and sophisticated quantification methods-¹H MRS is now experiencing a resurgence. It is sensitive to task-related and pathology-relevant regional dynamic changes in neurotransmitters, including the most ubiquitous among them, glutamate. Moreover, high temporal resolution approaches allow tracking glutamate modulations at a time scale of under a minute during perceptual, motor, and cognitive tasks. The observed task-related changes in brain glutamate are consistent with new metabolic steady states reflecting the neural output driven by shifts in the local excitatory and inhibitory balance on local circuits. Unlike blood oxygen level differences-base functional MRI, this form of in vivo MRS, also known as functional MRS (¹H fMRS), yields a more direct measure of behaviorally relevant neural activity and is considerably less sensitive to vascular changes. ¹H fMRS enables noninvasive investigations of task-related glutamate changes that are relevant to normal and impaired cognitive performance, and psychiatric disorders. By targeting brain glutamate, this approach taps into putative neural correlates of synaptic plasticity. This review provides a concise survey of recent technological advancements that lay the foundation for the successful use of ¹H fMRS in cognitive neuroscience and neuropsychiatry, including a review of seminal ¹H fMRS studies, and the discussion of biological significance of task-related changes in glutamate modulation. We conclude with a discussion of the promises, limitations, and outstanding challenges of this new tool in the armamentarium of cognitive neuroscience and psychiatry research.

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.

Cortical-hippocampal functional connectivity during covert consolidation sub-serves associative learning: Evidence for an active "rest" state

We studied modulation of undirected functional connectivity (uFC) in cortical-hippocampal sub-networks during associative learning. Nineteen healthy individuals were studied (fMRI acquired on a Siemens Verio 3T), and uFC was studied between nodes in a network of regions identified by standard activation models based on bivariate correlational analyses of time series data. The paradigm alternated between Memory Encoding, Rest and Retrieval. "Rest" intervals promoted covert consolidation. Over the task, performance was broadly separable into linear (Early) and asymptomatic (Late) regimes, with late performance reflecting successful memory consolidation. Significant modulation of uFC was observed during periods of covert consolidation. The sub-networks which were modulated constituted connections between frontal regions such as the dorsal prefrontal cortex (dPFC) and dorsal anterior cingulate cortex (dACC), the medial temporal lobe (hippocampus, HPC), the superior parietal cortex (SPC) and the fusiform gyrus (FG). uFC patterns were dynamic in that sub-networks modulated during Early learning (dACC ↔ SPC, dACC ↔ FG, dPFC ↔ HPC) were not identical to those modulated during Late learning (dACC ↔ HPC, dPFC ↔ FG, FG ↔ SPC). Covert consolidation exerts systematic effects, and these results add to emerging evidence for the constructive role of the brain's "resting state" in potentiating action.