tDCS induced GABA change is associated with the simulated electric field in M1, an effect mediated by grey matter volume in the MRS voxel.

BACKGROUND AND OBJECTIVE: Transcranial direct current stimulation (tDCS) has wide ranging applications in neuro-behavioural and physiological research, and in neurological rehabilitation. However, it is currently limited by substantial inter-subject variability in responses, which may be explained, at least in part, by anatomical differences that lead to variability in the electric field (E-field) induced in the cortex. Here, we tested whether the variability in the E-field in the stimulated cortex during anodal tDCS, estimated using computational simulations, explains the variability in tDCS induced changes in GABA, a neurophysiological marker of stimulation effect. METHODS: Data from five previously conducted MRS studies were combined. The anode was placed over the left primary motor cortex (M1, 3 studies, N = 24) or right temporal cortex (2 studies, N = 32), with the cathode over the contralateral supraorbital ridge. Single voxel spectroscopy was performed in a 2x2x2cm voxel under the anode in all cases. MRS data were acquired before and either during or after 1 mA tDCS using either a sLASER sequence (7T) or a MEGA-PRESS sequence (3T). sLASER MRS data were analysed using LCModel, and MEGA-PRESS using FID-A and Gannet. E-fields were simulated in a finite element model of the head, based on individual structural MR images, using SimNIBS. Separate linear mixed effects models were run for each E-field variable (mean and 95th percentile; magnitude, and components normal and tangential to grey matter surface, within the MRS voxel). The model included effects of time (pre or post tDCS), E-field, grey matter volume in the MRS voxel, and a 3-way interaction between time, E-field and grey matter volume. Additionally, we ran a permutation analysis using PALM to determine whether E-field anywhere in the brain, not just in the MRS voxel, correlated with GABA change. RESULTS: In M1, higher mean E-field magnitude was associated with greater anodal tDCS-induced decreases in GABA (t(24) = 3.24, p = 0.003). Further, the association between mean E-field magnitude and GABA change was moderated by the grey matter volume in the MRS voxel (t(24) = -3.55, p = 0.002). These relationships were consistent across all E-field variables except the mean of the normal component. No significant relationship was found between tDCS-induced GABA decrease and E-field in the temporal voxel. No significant clusters were found in the whole brain analysis. CONCLUSIONS: Our data suggest that the electric field induced by tDCS within the brain is variable, and is significantly related to anodal tDCS-induced decrease in GABA, a key neurophysiological marker of stimulation. These findings strongly support individualised dosing of tDCS, at least in M1. Further studies examining E-fields in relation to other outcome measures, including behaviour, will help determine the optimal E-fields required for any desired effects.

Comparison of Multivendor Single-Voxel MR Spectroscopy Data Acquired in Healthy Brain at 26 Sites.

Background The hardware and software differences between MR vendors and individual sites influence the quantification of MR spectroscopy data. An analysis of a large data set may help to better understand sources of the total variance in quantified metabolite levels. Purpose To compare multisite quantitative brain MR spectroscopy data acquired in healthy participants at 26 sites by using the vendor-supplied single-voxel point-resolved spectroscopy (PRESS) sequence. Materials and Methods An MR spectroscopy protocol to acquire short-echo-time PRESS data from the midparietal region of the brain was disseminated to 26 research sites operating 3.0-T MR scanners from three different vendors. In this prospective study, healthy participants were scanned between July 2016 and December 2017. Data were analyzed by using software with simulated basis sets customized for each vendor implementation. The proportion of total variance attributed to vendor-, site-, and participant-related effects was estimated by using a linear mixed-effects model. P values were derived through parametric bootstrapping of the linear mixed-effects models (denoted Pboot). Results In total, 296 participants (mean age, 26 years ± 4.6; 155 women and 141 men) were scanned. Good-quality data were recorded from all sites, as evidenced by a consistent linewidth of N-acetylaspartate (range, 4.4-5.0 Hz), signal-to-noise ratio (range, 174-289), and low Cramér-Rao lower bounds (≤5%) for all of the major metabolites. Among the major metabolites, no vendor effects were found for levels of myo-inositol (Pboot > .90), N-acetylaspartate and N-acetylaspartylglutamate (Pboot = .13), or glutamate and glutamine (Pboot = .11). Among the smaller resonances, no vendor effects were found for ascorbate (Pboot = .08), aspartate (Pboot > .90), glutathione (Pboot > .90), or lactate (Pboot = .28). Conclusion Multisite multivendor single-voxel MR spectroscopy studies performed at 3.0 T can yield results that are coherent across vendors, provided that vendor differences in pulse sequence implementation are accounted for in data analysis. However, the site-related effects on variability were more profound and suggest the need for further standardization of spectroscopic protocols. © RSNA, 2020 Online supplemental material is available for this article.

Modulating Regional Motor Cortical Excitability with Noninvasive Brain Stimulation Results in Neurochemical Changes in Bilateral Motor Cortices.

Learning a novel motor skill is dependent both on regional changes within the primary motor cortex (M1) contralateral to the active hand and also on modulation between and within anatomically distant but functionally connected brain regions. Interregional changes are particularly important in functional recovery after stroke, when critical plastic changes underpinning behavioral improvements are observed in both ipsilesional and contralesional M1s. It is increasingly understood that reduction in GABA in the contralateral M1 is necessary to allow learning of a motor task. However, the physiological mechanisms underpinning plasticity within other brain regions, most importantly the ipsilateral M1, are not well understood. Here, we used concurrent two-voxel magnetic resonance spectroscopy to simultaneously quantify changes in neurochemicals within left and right M1s in healthy humans of both sexes in response to transcranial direct current stimulation (tDCS) applied to left M1. We demonstrated a decrease in GABA in both the stimulated (left) and nonstimulated (right) M1 after anodal tDCS, whereas a decrease in GABA was only observed in nonstimulated M1 after cathodal stimulation. This GABA decrease in the nonstimulated M1 during cathodal tDCS was negatively correlated with microstructure of M1:M1 callosal fibers, as quantified by diffusion MRI, suggesting that structural features of these fibers may mediate GABA decrease in the unstimulated region. We found no significant changes in glutamate. Together, these findings shed light on the interactions between the two major network nodes underpinning motor plasticity, offering a potential framework from which to optimize future interventions to improve motor function after stroke.SIGNIFICANCE STATEMENT Learning of new motor skills depends on modulation both within and between brain regions. Here, we use a novel two-voxel magnetic resonance spectroscopy approach to quantify GABA and glutamate changes concurrently within the left and right primary motor cortex (M1) during three commonly used transcranial direct current stimulation montages: anodal, cathodal, and bilateral. We also examined how the neurochemical changes in the unstimulated hemisphere were related to white matter microstructure between the two M1s. Our results provide insights into the neurochemical changes underlying motor plasticity and may therefore assist in the development of further adjunct therapies.