Biology subjects

Hinson, E. L.

Publications and source records attributed to Hinson, E. L..

4 recordsLinked to original sources

bioRxiv2022

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 ObjectiveTranscranial 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 tDCS, estimated using computational simulations, explains the variability in tDCS induced changes in GABA, a neurophysiological marker of stimulation effect. MethodsData 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 1mA 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 MPRAGE 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. ResultsIn M1, higher mean E-field magnitude was associated with greater 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. ConclusionsOur data suggest that the electric field induced by tDCS within the brain is variable, and is significantly related to 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. HighlightsO_LIWe study the link between individually simulated electric field dose and tDCS-induced change in GABA in the cortex. C_LIO_LIThe electric field strength in the brain correlates with a decrease in GABA in the motor cortex. C_LIO_LIThe correlation between the electric field and GABA change is modulated by the amount of grey matter in the MRS voxel. C_LIO_LIWe find no association between the electric field and GABA in the temporal cortex. C_LI

neuroscience↗

bioRxiv2021

Human motor cortical gamma activity relates to GABAergic signalling and to behaviour

Gamma activity ({gamma}, >30 Hz) is universally demonstrated across brain regions and species. However, the physiological basis and functional role of {gamma} sub-bands (slow-{gamma}, mid-{gamma}, fast-{gamma}) have been predominantly studied in rodent hippocampus; {gamma} activity in the human neocortex is much less well understood. Here we combined neuroimaging and non-invasive brain stimulation to examine the properties of {gamma} activity sub-bands in the primary motor cortex (M1), and their relationship to both local GABAergic activity and to motor learning. In 33 healthy individuals, we quantified movement-related {gamma} activity in M1 using magnetoencephalography, assessed GABAergic signaling using transcranial magnetic stimulation (TMS), and estimated motor learning via a serial reaction time task. We characterised two distinct {gamma} sub-bands (slow-{gamma}, mid-{gamma}) which show movement-related increase in activity during unilateral index finger movements and are characterised by distinct temporal-spectral-spatial profiles. Bayesian correlation analysis revealed strong evidence for a positive relationship between slow-{gamma} ([~]30-60Hz) peak frequency and endogenous GABA signalling during movement preparation (as assessed using the TMS-metric short interval intracortical inhibition). There was also moderate evidence for a relationship between power of the movement-related mid-{gamma} activity (60-90Hz) and motor learning. These relationships were neurochemically- and frequency-specific. These data provide new insights into the neurophysiological basis and functional roles of {gamma} activity in human M1 and allow the development of a new theoretical framework for {gamma} activity in the human neocortex. Significance StatementGamma ({gamma}) activity is ubiquitous in the brain, yet our understanding of the mechanisms and function of {gamma} activity in the human neocortex, and particularly in the human motor cortex, is limited. Using a multimodal approach, we characterised two patterns of movement-related {gamma} activity in the human motor cortex (slow-{gamma} and mid-{gamma}), with different spatial, temporal and spectral properties. Slow-{gamma} peak frequency was correlated to local GABA-A activity, whereas mid-gamma power predicted performance in a subsequent motor learning task. Based on these findings and previous research, we propose a theoretical framework to explain how human motor cortical {gamma} activities may arise and their potential role in plasticity and motor learning, providing new hypotheses to be tested in future studies. Key PointsO_LIWe combined neuroimaging (i.e. MEG) and non-invasive brain stimulation (i.e. TMS) to examine the properties of {gamma} activity sub-bands in the primary motor cortex. C_LIO_LITwo distinct {gamma} sub-bands (slow-{gamma}, mid-{gamma}) show a movement-related increase in activity during finger movements and are characterised by distinct temporal-spectral-spatial profiles. C_LIO_LIWe found strong evidence for a positive relationship between slow-{gamma} ([~]30-60Hz) peak frequency and endogenous GABA signalling during movement preparation (as assessed using the TMS-metric short interval intracortical inhibition). C_LI

neuroscience↗

bioRxiv2018

Motor learning shapes temporal activity in human sensorimotor cortex

Although neuroimaging techniques have provided vital insights into the anatomical regions involved in motor learning, the underlying changes in temporal dynamics are not well understood. Using magnetoencephalography and Hidden Markov Modelling to model the dynamics of neural oscillations on data-adaptive time-scales, we detected specific changes in movement-related sensorimotor {beta}-activity during practice of a self-paced sequential visuo-motor task. The behaviourally-relevant neural signature generalised to another motor task, emphasising the centrality of {beta}-activity in motor plasticity.

neuroscience↗

bioRxiv2018

The dynamics of cortical GABA in human motor learning

The ability to learn novel motor skills is both a central part of our daily lives and can provide a model for rehabilitation after a stroke. However, there are still fundamental gaps in our understanding of the physiological mechanisms that underpin human motor plasticity. The acquisition of new motor skills is dependent on changes in local circuitry within the primary motor cortex (M1). This reorganisation has been hypothesised to be facilitated by a decrease in local inhibition via modulation of the neurotransmitter GABA, but this link has not been conclusively demonstrated in humans. Here, we used 7T MR Spectroscopy to investigate the dynamics of GABA concentrations in human M1 during the learning of an explicit, serial reaction time task. We observed a significant reduction in GABA concentration during motor learning that was not seen in an equivalent motor task lacking a learnable sequence, nor during a passive resting task of the same duration. No change in glutamate was observed in any group. Furthermore, baseline M1 GABA was strongly predictive of the degree of subsequent learning, such that greater inhibition was associated with poorer subsequent learning. This result suggests that higher levels of cortical inhibition may present a barrier that must be surmounted in order achieve an increase in M1 excitability, and hence encoding of a new motor skill. These results provide strong support for the mechanistic role of GABAergic inhibition in motor plasticity, raising questions regarding the link between population variability in motor learning and GABA metabolism in the brain.\n\nFunding informationJ.K.:Wellcome Trust Sir Henry Wellcome Postdoctoral Fellowship (204696/Z/16/Z). C.J.S.: Wellcome Trust/Royal Society Henry Dale Fellowships (102584/Z/13/Z).

neuroscience↗