Mixed-polarity random-dot stereograms alter GABA and Glx concentration in the early visual cortex

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.

Neurochemical Predictors of Generalized Learning Induced by Brain Stimulation and Training

Methods of cognitive enhancement for humans are most impactful when they generalize across tasks. However, the extent to which such "transfer" is possible via interventions is widely debated. In addition, the contribution of excitatory and inhibitory processes to such transfer is unknown. Here, in a large-scale neuroimaging individual differences study with humans (both sexes), we paired multitasking training and noninvasive brain stimulation (transcranial direct current stimulation, tDCS) over multiple days and assessed performance across a range of paradigms. In addition, we varied tDCS dosage (1.0 and 2.0 mA), electrode montage (left or right prefrontal regions), and training task (multitasking vs a control task) and assessed GABA and glutamate concentrations via ultrahigh field 7T magnetic resonance spectroscopy. Generalized benefits were observed in spatial attention, indexed by visual search performance, when multitasking training was combined with 1.0 mA stimulation targeting either the left or right prefrontal cortex (PFC). This transfer effect persisted for ∼30 d post intervention. Critically, the transferred benefits associated with right prefrontal tDCS were predicted by pretraining concentrations of glutamate in the PFC. Thus, the effects of this combined stimulation and training protocol appear to be linked predominantly to excitatory brain processes.

Anxious individuals shift emotion control from lateral frontal pole to dorsolateral prefrontal cortex

Anxious individuals consistently fail in controlling emotional behavior, leading to excessive avoidance, a trait that prevents learning through exposure. Although the origin of this failure is unclear, one candidate system involves control of emotional actions, coordinated through lateral frontopolar cortex (FPl) via amygdala and sensorimotor connections. Using structural, functional, and neurochemical evidence, we show how FPl-based emotional action control fails in highly-anxious individuals. Their FPl is overexcitable, as indexed by GABA/glutamate ratio at rest, and receives stronger amygdalofugal projections than non-anxious male participants. Yet, high-anxious individuals fail to recruit FPl during emotional action control, relying instead on dorsolateral and medial prefrontal areas. This functional anatomical shift is proportional to FPl excitability and amygdalofugal projections strength. The findings characterize circuit-level vulnerabilities in anxious individuals, showing that even mild emotional challenges can saturate FPl neural range, leading to a neural bottleneck in the control of emotional action tendencies.

On the relationship between GABA+ and glutamate across the brain

Equilibrium between excitation and inhibition (E/I balance) is key to healthy brain function. Conversely, disruption of normal E/I balance has been implicated in a range of central neurological pathologies. Magnetic resonance spectroscopy (MRS) provides a non-invasive means of quantifying in vivo concentrations of excitatory and inhibitory neurotransmitters, which could be used as diagnostic biomarkers. Using the ratio of excitatory and inhibitory neurotransmitters as an index of E/I balance is common practice in MRS work, but recent studies have shown inconsistent evidence for the validity of this proxy. This is underscored by the fact that different measures are often used in calculating E/I balance such as glutamate and Glx (glutamate and glutamine). Here we used a large MRS dataset obtained at ultra-high field (7 T) measured from 193 healthy young adults and focused on two brain regions - prefrontal and occipital cortex - to resolve this inconsistency. We find evidence that there is an inter-individual common ratio between GABA+ (γ-aminobutyric acid and macromolecules) and Glx in the occipital, but not prefrontal cortex. We further replicate the prefrontal result in a legacy dataset (n = 78) measured at high-field (3 T) strength. By contrast, with ultra-high field MRS data, we find extreme evidence that there is a common ratio between GABA+ and glutamate in both prefrontal and occipital cortices, which cannot be explained by participant demographics, signal quality, fractional tissue volume, or other metabolite concentrations. These results are consistent with previous electrophysiological and theoretical work supporting E/I balance. Our findings indicate that MRS-detected GABA+ and glutamate (but not Glx), are a reliable measure of E/I balance .

No balance between glutamate+glutamine and GABA+ in visual or motor cortices of the human brain: A magnetic resonance spectroscopy study

Theoretical work, supported by electrophysiological evidence, asserts that a balance between excitation and inhibition (E/I) is critical for healthy brain function. In magnetic resonance spectroscopy (MRS) studies, the ratio of excitatory (glutamate) and inhibitory (γ-aminobutyric acid, GABA) neurotransmitters is often used as a proxy for this E/I balance. Recent MRS work found a positive correlation between GABA+ and Glx (glutamate+glutamine) in medial parietal cortex, providing validation for this proxy and supporting the link between the E/I balance observed in electrophysiology and that detected with MRS. Here we assess the same relationship, between GABA+ and Glx, in visual and motor cortices of male and female human participants. We find moderate to strong evidence that there is no positive correlation between these neurotransmitters in either location. We show this holds true when controlling for a range of other factors (i.e., demographics, signal quality, tissue composition, other neurochemicals) and regardless of the state of neural activity (i.e., resting/active). These results show that there is no brain-wide balance between excitatory and inhibitory neurotransmitters and indicates a dissociation between the E/I balance observed in electrophysiological work and the ratio of MRS-detected neurotransmitters.

Comparison of methods for spectral alignment and signal modelling of GABA-edited MR spectroscopy data

Many methods exist for aligning and quantifying magnetic resonance spectroscopy (MRS) data to measure in vivo γ-aminobutyric acid (GABA). Research comparing the performance of these methods is scarce partly due to the lack of ground-truth measurements. The concentration of GABA is approximately two times higher in grey matter than in white matter. Here we use the proportion of grey matter within the MRS voxel as a proxy for ground-truth GABA concentration to compare the performance of four spectral alignment methods (i.e., retrospective frequency and phase drift correction) and six GABA signal modelling methods. We analyse a diverse dataset of 432 MEGA-PRESS scans targeting multiple brain regions and find that alignment to the creatine (Cr) signal produces GABA+ estimates that account for approximately twice as much of the variance in grey matter as the next best performing alignment method. Further, Cr alignment was the most robust, producing the fewest outliers. By contrast, all signal modelling methods, except for the single-Lorentzian model, performed similarly well. Our results suggest that variability in performance is primarily caused by differences in the zero-order phase estimated by each alignment method, rather than frequency, resulting from first-order phase offsets within subspectra. These results provide support for Cr alignment as the optimal method of processing MEGA-PRESS to quantify GABA. However, more broadly, they demonstrate a method of benchmarking quantification of in vivo metabolite concentration from other MRS sequences.

Investigating the neurochemistry of the human visual system using magnetic resonance spectroscopy

Biochemical processes underpin the structure and function of the visual cortex, yet our understanding of the fundamental neurochemistry of the visual brain is incomplete. Proton magnetic resonance spectroscopy (¹H-MRS) is a non-invasive brain imaging tool that allows chemical quantification of living tissue by detecting minute differences in the resonant frequency of molecules. Application of MRS in the human brain in vivo has advanced our understanding of how the visual brain consumes energy to support neural function, how its neural substrates change as a result of disease or dysfunction, and how neural populations signal during perception and plasticity. The aim of this review is to provide an entry point to researchers interested in investigating the neurochemistry of the visual system using in vivo measurements. We provide a basic overview of MRS principles, and then discuss recent findings in four topics of vision science: (i) visual perception, plasticity in the (ii) healthy and (iii) dysfunctional visual system, and (iv) during visual stimulation. Taken together, evidence suggests that the neurochemistry of the visual system provides important novel insights into how we perceive the world.

Low- and High-resolution Dynamic Analyses for Magnetic Resonance Spectroscopy Data

Magnetic resonance spectroscopy (MRS) can be used to measure in vivo concentrations of neurometabolites. This information can be used to identify neurotransmitter involvement in healthy (e.g., perceptual and cognitive processes) and unhealthy brain function (e.g., neurological and psychiatric illnesses). The standard approach for analyzing MRS data is to combine spectral transients acquired over a ~10 min scan to yield a single estimate that reflects the average metabolite concentration during that period. The temporal resolution of metabolite measurements is sacrificed in this manner to achieve a sufficient signal-to-noise ratio to produce a reliable estimate. Here we introduce two analyses that can be used to increase the temporal resolution of neurometabolite estimates produced from MRS measurements. The first analysis uses a sliding window approach to create a smoothed trace of neurometabolite concentration for each MRS scan. The second analysis combines transients across participants, rather than time, producing a single "group trace" with the highest possible temporal resolution achievable with the data. These analyses advance MRS beyond the current "static" application by allowing researchers to measure dynamic changes in neurometabolite concentration and expanding the types of questions that the technique can be used to address.

Stimuli Characteristics and Psychophysical Requirements for Visual Training in Amblyopia: A Narrative Review

Active vision therapy using perceptual learning and/or dichoptic or binocular environments has shown its potential effectiveness in amblyopia, but some doubts remain about the type of stimuli and the mode and sequence of presentation that should be used. A search was performed in PubMed, obtaining 143 articles with information related to the stimuli used in amblyopia rehabilitation, as well as to the neural mechanisms implied in such therapeutic process. Visual deficits in amblyopia and their neural mechanisms associated are revised, including visual acuity loss, contrast sensitivity reduction and stereopsis impairment. Likewise, the most appropriate stimuli according to the literature that should be used for an efficient rehabilitation of the amblyopic eye are described in detail, including optotypes, Gabor’s patches, random-dot stimuli and Vernier’s stimuli. Finally, the properties of these stimuli that can be modified during the visual training are discussed, as well as the psychophysical method of their presentation and the type of environment used (perceptual learning, dichoptic stimulation or virtual reality). Vision therapy using all these revised concepts can be an effective option for treating amblyopia or accelerating the treatment period when combining with patching. It is essential to adapt the stimuli to the patient’s individual features in both monocular and binocular training.

Temporal Dynamics of GABA and Glx in the Visual Cortex

Magnetic resonance spectroscopy (MRS) can be used in vivo to quantify neurometabolite concentration and provide evidence for the involvement of different neurotransmitter systems (e.g., inhibitory and excitatory) in sensory and cognitive processes. The relatively low signal-to-noise ratio of MRS measurements has shaped the types of questions that it has been used to address. In particular, temporal resolution is often sacrificed in MRS studies to achieve a signal sufficient to produce a reliable estimate of neurometabolite concentration. Here we apply novel analyses with large datasets from human participants (both sexes) to reveal the dynamics of GABA⁺ and Glx in visual cortex while participants are at rest (with eyes closed) and compare this with changes in posterior cingulate cortex from a previously collected dataset (under different conditions). We find that the dynamic concentration of GABA⁺ and Glx in visual cortex drifts in opposite directions; that is, GABA⁺ decreases while Glx increases over time. Further, we find that in visual, but not posterior cingulate cortex, the concentration of GABA⁺ predicts that of Glx 120 s later, such that a change in GABA⁺ is correlated with a subsequent opposite change in Glx. Together, these results expose novel temporal trends and interdependencies of primary neurotransmitters in visual cortex. More broadly, we demonstrate the feasibility of using MRS to investigate in vivo dynamic changes of neurometabolites.

EEG based dynamic RDS recognition with frequency domain selection and bispectrum feature optimization

BACKGROUND

Stereopsis plays a vital role in many aspects of human daily life. Random-dot stereogram (RDS) is often used to detect stereoacuity and perform research on visual cognition. Electroencephalogram (EEG) is one of the commonly adopted visual cognition techniques due to its noninvasive collection.

NEW METHOD

In this study, a methodology named WPT-BED based on wavelet packet transform (WPT) and bispectral eigenvalues of differential signals (BED) is proposed, which can classify the three-pattern EEG signals evoked by dynamic RDS (DRDS). Specifically, the signals are decomposed into different frequency bands by WPT. The appropriate sub-bands are selected for reconstruction. Finally, the optimized bispectrum features are extracted for classification to achieve higher accuracy.

RESULTS

The classification performance of the proposed method in different periods of signal processing are investigated. The method WPT-BED has the highest classification accuracy 84.38%, and the average classification accuracy is 73.98%. The active channels with higher accuracy are focused on the visual pathway in the human cerebral cortex.

COMPARISON WITH EXISTING METHODS

Comparison with other methods for EEG signals classification is performed to identify the effectiveness of the proposed methodology.

CONCLUSIONS

The proposed methodology can effectively distinguish the EEG signals evoked by DRDS. It demonstrates the feasibility of DRDS recognition based on EEG.