Increased Glutamate concentrations during prolonged motor activation as measured using functional Magnetic Resonance Spectroscopy at 3T

Combining frequency navigator and optical prospective motion correction for functional MRS during motor activation at 3 T: A feasibility study

BACKGROUND

Functional magnetic resonance spectroscopy (fMRS) is a powerful tool for investigating neurometabolic dynamics in response to physiological stimuli in vivo. However, fMRS is challenging due to the low SNR of the spectrum and small neurochemical changes. Many existing studies were conducted at ultrahigh field strength (7 T). To translate fMRS studies to the more common 3 T clinical field strength, averaging more transients can improve SNR. However, this results in a long scan time compounds physiological motion which incurs degradations in spectrum quality and consistency.

PURPOSE

Investigate the feasibility of PRESS fMRS studies at 3 T assisted by the combination of prospective motion correction (PMC) system and frequency navigator.

METHODS

A combination of markerless PMC system and frequency navigator was applied to an fMRS study during motor activation with a clinical PRESS protocol at 3 T. Twenty-one volunteers were involved in the study. The functional task paradigm consisted of three blocks REST-TASK-REST. During the TASK period, the volunteer was asked to squeeze a hand-hold balloon according to a red rectangle flashing at 2 Hz shown centered in a black background. The same motor task was repeated twice, once with PMC ON and once with PMC OFF. The data were processed and quantified by in-house VDI software. The following two analyses were performed: a motion pattern analysis and a metabolite dynamics analysis. The motion analysis was used to compare the motion states when PMC was ON and OFF. The metabolite dynamic change was a key assessment for the fMRS study. It was estimated viaΔ = μ t a s k - μ r e s t μ r e s t ≡ Δ μ μ r e s t ${{\Delta}} = \frac{{{\mu }_{task} - {\mu }_{rest}}}{{{\mu }_{rest}}}\ \equiv \frac{{\Delta \mu }}{{{\mu }_{rest}}}$ . p-values < 0.05 were considered significant.

RESULTS

A statistically significant increase in Glx of 5.73% when the PMC was switched on was observed. No statistically significant increase in any of the metabolites with PMC OFF was observed. The major singlets (tCho, tCr, and tNAA) for both PMC ON and OFF keep constant.

CONCLUSIONS

With a markerless PMC system and frequency navigator, PRESS fMRS at 3 T is capable of detecting small changes of a few percent in Glx concentration during functional activation.

The Reciprocal Relationship Between Short- and Long-Term Motor Learning and Neurometabolites

Skill acquisition requires practice to stimulate neuroplasticity. Changes in inhibitory and excitatory neurotransmitters, such as gamma-aminobutyric acid (GABA) and glutamate, are believed to play a crucial role in promoting neuroplasticity. Magnetic resonance spectroscopy (MRS) at 3 T, using the MEGA-PRESS sequence, and behavioral data were collected from 62 volunteers. Participants completed a 4-week protocol, practicing either complex (n = 32) or simple (n = 30) bimanual tracking tasks (BTT). Neurotransmitter levels and skill levels at baseline, after 2 and 4 weeks of motor training were compared for the left and right primary sensorimotor cortex (SM1) and the left dorsal premotor cortex (PMd). Furthermore, task-related modulations of neurotransmitter levels in the left PMd were assessed. The study yielded that baseline neurotransmitter levels in motor-related brain regions predicted training success. Furthermore, lower GABA+ (p = 0.0347) and higher Glx (glutamate + glutamine compound) levels (p = 0.0234) in left PMd correlated with better long-term learning of simple and complex tasks, respectively, whereas higher GABA+ in right SM1 correlated with complex task learning (p = 0.0064). Resting neurometabolite levels changed during the intervention: Left SM1 Glx decreased with complex training toward Week 4 (p = 0.0135), whereas right SM1 Glx was increased at Week 2 (p = 0.0043), regardless of training type. Group-level analysis showed no task-related neurometabolite modulation in the left PMd. However, individual baseline GABA+ and Glx modulation influenced short-term motor learning (interaction: p = 0.0213). These findings underscore the importance of an interplay between inhibitory and excitatory neurotransmitters during motor learning and suggest potential for future personalized approaches to optimize motor learning.

Investigating Neurometabolite Changes in Response to Median Nerve Stimulation

BACKGROUND

Rhythmic median nerve stimulation (MNS) at 10 Hz has been shown to cause a substantial reduction in tic frequency in individuals with Tourette syndrome. The mechanism of action is currently unknown but is hypothesized to involve entrainment of oscillations within the sensorimotor cortex.

OBJECTIVE

We used functional magnetic resonance spectroscopy (fMRS) to explore the dynamic effects of MNS on neurometabolite concentrations.

METHODS

Here, we investigated the effects of rhythmic and arrhythmic 10 Hz MNS on glutamate (Glu) and GABA concentrations in the contralateral sensorimotor cortex in 15 healthy controls, using a blocked fMRS design. We used a Mescher-Garwood-semi-localized by adiabatic selective refocusing (MEGA-sLASER) sequence at 7 T.

RESULTS

Our results show no difference in the difference-from-baseline measures between the two stimulation conditions. Looking at the effect of MNS over both conditions there is a trend for an initial increase in Glu/tCr (total creatine) followed by a decrease over time, whereas GABA/tCr decreased during each stimulation block.

CONCLUSIONS

These results suggest that despite entrainment of oscillations during rhythmic MNS, there are no significant differences in the tonic neuromodulatory effects of rhythmic and arrhythmic stimulation. The reduction in Glu over the course of stimulation may reflect a decrease in the glutamatergic firing due to adaptation. This may make it less likely that an involuntary movement is generated during continuous stimulation.

Functional Magnetic Resonance Spectroscopy of Prolonged Motor Activation using Conventional and Spectral GLM Analyses

Background

Functional MRS (fMRS) is a technique used to measure metabolic changes in response to increased neuronal activity, providing unique insights into neurotransmitter dynamics and neuroenergetics. In this study we investigate the response of lactate and glutamate levels in the motor cortex during a sustained motor task using conventional spectral fitting and explore the use of a novel analysis approach based on the application of linear modelling directly to the spectro-temporal fMRS data.

Methods

fMRS data were acquired at a field strength of 3 Tesla from 23 healthy participants using a short echo-time (28ms) semi-LASER sequence. The functional task involved rhythmic hand clenching over a duration of 8 minutes and standard MRS preprocessing steps, including frequency and phase alignment, were employed. Both conventional spectral fitting and direct linear modelling were applied, and results from participant-averaged spectra and metabolite-averaged individual analyses were compared.

Results

We observed a 20% increase in lactate in response to the motor task, consistent with findings at higher magnetic field strengths. However, statistical testing showed some variability between the two averaging schemes and fitting algorithms. While lactate changes were supported by the direct spectral modelling approach, smaller increases in glutamate (2%) were inconsistent. Exploratory spectral modelling identified a 4% decrease in aspartate, aligning with conventional fitting and observations from prolonged visual stimulation.

Conclusion

We demonstrate that lactate dynamics in response to a prolonged motor task are observed using short-echo time semi-LASER at 3 Tesla, and that direct linear modelling of fMRS data is a useful complement to conventional analysis. Future work includes mitigating spectral confounds, such as scalp lipid contamination and lineshape drift, and further validation of our novel direct linear modelling approach through experimental and simulated datasets.

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.

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.

Improved detection limits of J-coupled neurometabolites in the human brain at 7 T with a J-refocused sLASER sequence

In a standard spin echo, the time evolution due to homonuclear couplings is not reversed, leading to echo time (TE)-dependent modulation of the signal amplitude and signal loss in the case of overlapping multiplet resonances. This has an adverse effect on quantification of several important metabolites such as glutamate and glutamine. Here, we propose a J-refocused variant of the sLASER sequence (J-sLASER) to improve quantification of J-coupled metabolites at ultrahigh field (UHF). The use of the sLASER sequence is particularly advantageous at UHF as it minimizes chemical shift displacement error and results in relatively homogenous refocusing. We simulated the MRS signal from brain metabolites over a broad range of TE values with sLASER and J-sLASER, and showed that the signal of J-coupled metabolites was increased with J-sLASER with TE values up to ~80 ms. We further simulated "brain-like" spectra with both sequences at the shortest TE available on our scanner. We showed that, despite the slightly longer TE, the J-sLASER sequence results in significantly lower Cramer-Rao lower bounds (CRLBs) for J-coupled metabolites compared with those obtained with sLASER. Following phantom validation, we acquired spectra from two brain regions in 10 healthy volunteers (age 38 ± 15 years) using both sequences. We showed that using J-sLASER results in a decrease of CRLBs for J-coupled metabolites. In particular, we measured a robust ~38% decrease in the mean CRLB (glutamine) in parietal white matter and posterior cingulate cortex (PCC). We further showed, in 10 additional healthy volunteers (age 34 ± 15 years), that metabolite quantification following two separate acquisitions with J-sLASER in the PCC was repeatable. The improvement in quantification of glutamine may in turn improve the independent quantification of glutamate, the main excitatory neurotransmitter in the brain, and will simultaneously help to track possible modulations of glutamine, which is a key player in the glutamatergic cycle in astrocytes.

The effect of parietal glutamate/GABA balance on test anxiety levels in early childhood in a cross-sectional and longitudinal study

The increased prevalence of test anxiety in our competitive society makes it a health issue of public concern. However, its neurobiological basis, especially during the years of formal education, is currently scant. Previous research has highlighted the association between neural excitation/inhibition balance and psychopathology and disease. We examined whether the glutamate/GABA profile tracks test anxiety levels in development, using a cross-sectional and longitudinal design in a cohort spanning from early childhood to early adulthood (N = 289), reassessed approximately 21 months later (N = 194). We used magnetic resonance spectroscopy to noninvasively quantify glutamate and gamma-Aminobutyric acid (GABA) levels in the intraparietal sulcus (IPS) and the middle frontal gyrus. We show that the glutamate/GABA balance within the IPS relates to current individual variation in test anxiety levels and predict future test anxiety approximately 21 months later. Critically, this relationship was observed during early childhood but not during the later developmental stages. Our results extend the use of the excitation/inhibition balance framework to characterize the psychopathology mechanisms of test anxiety, an underexplored yet widespread and debilitating condition that can impact early child development. Our findings provide a better understanding of the neurotransmitter basis underlying the emergence of anxiety disorders during development.

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.

High temporal resolution functional magnetic resonance spectroscopy in the mouse upon visual stimulation

Functional magnetic resonance spectroscopy (fMRS) quantifies metabolic variations upon presentation of a stimulus and can therefore provide complementary information compared to activity inferred from functional magnetic resonance imaging (fMRI). Improving the temporal resolution of fMRS can be beneficial to clinical applications where detailed information on metabolism can assist the characterization of brain function in healthy and sick populations as well as for neuroscience applications where information on the nature of the underlying activity could be potentially gained. Furthermore, fMRS with higher temporal resolution could benefit basic studies on animal models of disease and for investigating brain function in general. However, to date, fMRS has been limited to sustained periods of activation which risk adaptation and other undesirable effects. Here, we performed fMRS experiments in the mouse with high temporal resolution (12 s), and show the feasibility of such an approach for reliably quantifying metabolic variations upon activation. We detected metabolic variations in the superior colliculus of mice subjected to visual stimulation delivered in a block paradigm at 9.4 T. A robust modulation of glutamate is observed on the average time course, on the difference spectra and on the concentration distributions during active and recovery periods. A general linear model is used for the statistical analysis, and for exploring the nature of the modulation. Changes in NAAG, PCr and Cr levels were also detected. A control experiment with no stimulation reveals potential metabolic signal "drifts" that are not correlated with the functional activity, which should be taken into account when analyzing fMRS data in general. Our findings are promising for future applications of fMRS.