GABAergic neurotransmission within the cortex plays a key role in learning and is altered in several brain diseases. Quantification of bulk GABA in the human brain is typically obtained by magnetic resonance spectroscopy (MRS). However, the interpretation of MRS-GABA is still debated. A recent mathematical simulation contends that MRS detects extrasynaptic GABA, mediating tonic inhibition. Nevertheless, no empirical data have yet confirmed this hypothesis. Here we collected ultra-high-field 7 Tesla MRS and transcranial magnetic stimulation coupled with high-density electroencephalography (TMS-hdEEG) from the motor cortex of 20 healthy participants (age 23.95 ± 6.4 years), while they were at rest. We first applied a neural mass model (NMM) to TMS-evoked potentials to disentangle the contribution of different GABAergic pools. We then assessed to which of these different pools MRS-GABA was related to by means of parametric empirical Bayesian (PEB) analysis. We found that MRS-GABA was mostly positively related to the NMM-derived measures of tonic inhibition and overall functionality of the GABAergic synapse. This relationship was reliable enough to predict MRS-GABA from NMM-GABA. These findings clarify the mesoscopic underpinnings of GABA levels measured by MRS. Our work will help fulfil the promises of MRS-GABA, enhancing our understanding of human behaviour, brain physiology and pathophysiology. KEY POINTS: GABA neurotransmission is essential for synaptic plasticity and learning (especially motor learning) and is altered in several brain disorders, such as epilepsy and stroke. Quantification of GABA in the human brain is typically obtained by magnetic resonance spectroscopy (MRS). However, the interpretation of MRS-GABA is still debated. By using a biophysical neural mass model, here we show that MRS-GABA relates to physiological measures of tonic inhibition in the human cortex.

Motor cortical high-gamma oscillations (60-90 Hz) occur at movement onset and are spatially focused over the contralateral primary motor cortex. Although high-gamma oscillations are widely recognized for their significance in human motor control, their precise function on a cortical level remains elusive. Importantly, their relevance in human stroke pathophysiology is unknown. Because motor deficits are fundamental determinants of symptom burden after stroke, understanding the neurophysiological processes of motor coding could be an important step in improving stroke rehabilitation. We recorded magnetoencephalography data during a thumb movement rate task in 14 chronic stroke survivors, 15 age-matched control participants and 29 healthy young participants. Motor cortical high-gamma oscillations showed a strong relation with movement rate as trials with higher movement rate were associated with greater high-gamma power. Although stroke survivors showed reduced cortical high-gamma power, this reduction primarily reflected the scaling of high-gamma power with movement rate, yet after matching movement rate in stroke survivors and age-matched controls, the reduction of high-gamma power exceeded the effect of their decreased movement rate alone. Even though motor skill acquisition was evident in all three groups, it was not linked to high-gamma power. Our study quantifies high-gamma oscillations after stroke, revealing a reduction in movement-related high-gamma power. Moreover, we provide strong evidence for a pivotal role of motor cortical high-gamma oscillations in encoding movement rate. KEY POINTS: Neural oscillations in the high-gamma frequency range (60-90 Hz) emerge in the human motor cortex during movement. The precise function of these oscillations in motor control remains unclear, and they have never been characterized in stroke survivors. In a magnetoencephalography study, we demonstrate that high-gamma oscillations in motor cortical areas scale with movement rate, and we further explore their temporal and spatial characteristics. Stroke survivors exhibit lower high-gamma power during movement than age-matched control participants, even after matching for movement rate. The results contribute to the understanding of the role of high-gamma oscillations in motor control and have important implications for neuromodulation in stroke rehabilitation.

OBJECTIVE:A non-invasive measure of cerebral motor system dysfunction would be valuable as a biomarker in amyotrophic lateral sclerosis (ALS). Task-based magnetoencephalography (tMEG) measures the magnetic fields generated by cortical neuronal oscillatory activity during task performance. Gamma activations are periods of high-power and high-frequency cortical oscillations integral to motor control. METHODS:tMEG was undertaken during 60 bilateral isometric hand grip exercises in ALS (n = 42) and compared with healthy controls (HC, n = 33). Gamma activation spread (GAS) was estimated by calculating the number of activated regions during each 100 ms time-bin and compared statistically between groups. Gamma activation patterns were visualised by plotting each participant's brain activity separately as a 2-dimensional video. RESULTS:There was no difference in grip strength between groups. GAS was greatly increased in the ALS group compared to HC (p < 0.001) and correlated positively with rate of ALSFRS-R progression (t = 1.35, p = 0.023) and a fine motor sub-score (t = -1.18, p = 0.047). CONCLUSIONS:ALS was associated with a marked increase in regional spread of gamma frequency activation, greater in those with higher disease progression rates. SIGNIFICANCE:The regional spread of gamma activity may reflect disease activity in ALS, with potential application as an experimental medicine readout.

Transcranial ultrasound stimulation (TUS) is an emerging technology for non-invasive brain stimulation. The International Transcranial Ultrasonic Stimulation Safety and Standards consortium (ITRUSST) has established consensus on considerations for nonsignificant biophysical risk of TUS, drawing upon the literature and established regulations for biomedical devices. Here, we assume the application of TUS to individuals without contraindications, compromised thermoregulation, vascular vulnerabilities, or administered ultrasound contrast agents. In this context, we present a concise yet comprehensive set of levels for nonsignificant risks of TUS application. For mechanical effects, it is non-significant risk if the mechanical index (MI) or the mechanical index for transcranial application (MItc) does not exceed 1.9. For thermal effects, it is non-significant risk if any of the following three levels are met: the peak temperature rise does not exceed 2°C or the peak absolute temperature does not exceed 39°C, assuming a baseline temperature of 37°C, the thermal dose does not exceed 2 CEM43 in brain tissue, 16 CEM43 in bone tissue, and 21 CEM43 in skin tissue, or specific values of the thermal index (TI) for a given exposure time. This report reflects a consensus expert opinion and can inform, but not replace, regulatory guidelines or official international standards. Similarly, this consensus can inform, but not replace, ethical evaluation, which weighs the total burden, risks, and benefits of the proposed action. The stated levels are not safety limits per se, and further data is needed to establish the threshold for significant risk. We review literature relevant to our considerations and discuss limitations and future developments of our approach.

Movement-related dynamics in the beta and gamma bands have been studied in relation to motor execution and learning during unimanual movements, but their roles in complex bimanual tasks remain largely unexplored. This study aimed to investigate how beta and gamma activity differs between unimanual and bimanual movements and how these neural signatures evolve during the learning process. Our motor task incorporated varying levels of bimanual interaction: unimanual, bimanual-equal, and bimanual-unequal. Magnetoencephalography data were recorded in healthy participants (N = 43,27 females) during task performance, and beta and gamma activity was quantified. As expected, increasing task complexity from unimanual to bimanual-equal and then to bimanual-unequal movements resulted in slower and less accurate performance. Across all conditions, significant beta event-related desynchronization (ERD) and gamma event-related synchronization (ERS) were observed during movement, as well as beta ERS after movement. Bimanual movements exhibited greater beta ERD, beta ERS, and gamma ERS compared with unimanual movements. With practice, participants demonstrated faster and more accurate movements, accompanied by enhanced beta ERS responses. Furthermore, learning-related reductions in errors correlated with increases in beta ERS. These findings suggest the distinct behavioral and neural demands of unimanual versus bimanual movements and highlight the important role of beta activity in motor performance and learning.

Transcranial ultrasonic stimulation (TUS) has the potential to usher in a new era for human neuroscience by allowing spatially precise and high-resolution non-invasive targeting of both deep and superficial brain regions. Currently, fundamental research on the mechanisms of interaction between ultrasound and neural tissues is progressing in parallel with application-focused research. However, a major hurdle in the wider use of TUS is the selection of optimal parameters to enable safe and effective neuromodulation in humans. In this paper, we will discuss the major factors that determine the efficacy of TUS. We will discuss the thermal and mechanical biophysical effects of ultrasound, which underlie its biological effects, in the context of their relationships with tunable parameters. Based on this knowledge of biophysical effects, and drawing on concepts from radiotherapy, we propose a framework for conceptualising TUS dose.

Stroke is the most prevalent neurological disorder, the primary cause of long-term disability, and the second leading cause of mortality. Post-stroke motor symptoms critically impact and limit stroke survivors' quality of life. Rehabilitation aims to restore motor function by promoting neuroplasticity and neuronal reorganisation. A promising therapeutic approach involves combining non-invasive brain stimulation (NIBS) with activity-based training to enhance neuroplasticity. NIBS are thought to promote the innate neuronal reorganisation of the functionally relevant networks after a stroke. Amongst NIBS techniques, a pioneering method, often referred to as cortico-cortical paired associative stimulation (ccPAS), allows to enhance neuroplasticity in cortical networks. Unlike traditional approaches, ccPAS enables the manipulation of interregional connectivity within specific cortical pathways. In particular, ccPAS can promote synaptic plasticity and connectivity in a functionally relevant cortico-cortical route tailoring the interventions to individual lesion-specific network alterations. In this viewpoint, we propose and critically evaluate the use of ccPAS as a therapeutic tool using upper-limb motor rehabilitation as a primary example, highlighting its potential for post-stroke recovery. We summarise the limited and contrasting evidence supporting the use of ccPAS after a stroke and make suggestions to overcome the current limitations emphasising the need for further future research.

Transcranial electrical stimulation (tES) encompasses non-invasive neuromodulation techniques, such as transcranial direct and alternating current stimulation, which modulate the central nervous system to probe causal links between the brain and behavior and treat disorders. Unfortunately, fixed stimulation paradigms induce variable effects due to intra- and interindividual factors. Consequently, personalized approaches to tES are increasingly used. In this review, we highlight this emerging domain of human brain stimulation, examining strategies for the personalization of stimulation parameters and their underlying rationales. Multiparameter personalization and the identification of markers indicating tES efficacy represent promising directions. Personalization is not a panacea for all the challenges of tES, but marks an essential step toward reducing the variability of this technique.

We introduce an advanced transcranial ultrasound stimulation (TUS) system for precise deep brain neuromodulation, featuring a 256-element helmet-shaped transducer array (555 kHz), stereotactic positioning, individualised planning, and real-time fMRI monitoring. Experiments demonstrated selective modulation of the lateral geniculate nucleus (LGN) and connected visual cortex regions. Participants showed significantly increased visual cortex activity during concurrent TUS and visual stimulation, with high cross-individual reproducibility. A theta-burst TUS protocol produced robust neuromodulatory effects, decreasing visual cortex activity for at least 40 min post-stimulation. Control experiments confirmed these effects were specific to the targeted LGN. Our findings reveal this system's potential to non-invasively modulate deep brain circuits with unprecedented precision and specificity, offering new avenues for studying brain function and developing targeted therapies for neurological and psychiatric disorders, with transformative potential for both research and clinical applications.

Inhibition mediated by γ-aminobutyric acid (GABA) is implicated in motor plasticity and learning, with [GABA] in the motor cortex decreasing during motor learning. However, the causal relationship between [GABA] and learning has yet to be determined. Here, we conducted a within-subject, double-blind, placebo-controlled, crossover study to investigate the effect of increased GABAergic inhibition via GABAB-receptor agonist baclofen on motor learning and Magnetic Resonance Spectroscopic Imaging (MRSI) metrics. Increasing GABA-mediated inhibition with baclofen did not change response times, but significantly impaired motor sequence learning. In parallel, we demonstrated a blunting of the expected decrease in [GABA] during motor learning. These results highlight a causal role for GABAergic inhibition in motor learning and may have clinical implications: baclofen is commonly used to treat post brain-injury spasticity, but may impair motor learning during rehabilitation.

Sleep is often disrupted after stroke. However, little is known about how stroke lesion extent or location influences sleep, particularly at the chronic stage of recovery. In this pragmatic study, we aimed to explore whether lesion characteristics could explain sleep variability in chronic stroke survivors. We analysed previously collected structural brain images (Magnetic Resonance Imaging) from 38 stroke participants (11 female, mean (SD) age 64 (12), mean (SD) time since stroke 95 (66) months) and sleep data (questionnaires (N=38, actigraphy (N=37), and electrophysiology (N=18)) which were collected in their home environment. Neither lesion volume nor lesion overlap with regions of interest (brainstem, basal ganglia, amygdala, hippocampus, thalamus) significantly predicted interindividual variability in subjective or objective sleep measures. However, a data-driven approach revealed clusters of voxels disconnected by the stroke lesions were linked to lower spindle density and amplitude (threshold free cluster enhancement p < 0.050). Overall, these results provide preliminary insights that lesion induced brain disconnection, rather than the extent and overlap of the lesion with grey matter regions, may be more informative when explaining sleep variability. However, larger prospective studies are needed to fully understand the effect of stroke lesions on sleep. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work is supported by the Wellcome Trust and the NIHR Oxford Health Biomedical Research Centre (NIHR203316). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. MKF is Funded by Guarantors of Brain and HJB is funded by the Wellcome Trust (222446/Z/21/Z). CJS holds a Senior Research Fellowship, funded by the Wellcome Trust (224430/Z/21/Z). The Wellcome Centre for Integrative Neuroimaging is supported by core funding from the Wellcome Trust (203139/Z/16/Z and 203139/A/16/Z). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The study was approved by the Central University Research Ethics Committee, University of Oxford (reference R85306) I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data derivatives and analysis scripts will be made available here: https://osf.io/vbu7c/. Raw data are available upon reasonable request from the corresponding author.

Understanding the presymptomatic biology in those at high risk of developing amyotrophic lateral sclerosis (ALS) is essential for the development of preventative therapeutic interventions. Approximately 10% of ALS is associated with a C9orf72 expansion or pathogenic variants in SOD1. Magnetoencephalography (MEG), combined with machine learning algorithms, can model brain network dynamics in such at-risk populations to develop pathogenic biomarkers. Individuals with symptomatic ALS (symALS, n = 61), asymptomatic C9orf72 carriers (aC9, n = 16), or pathological SOD1 carriers (aSOD, n = 12), and healthy controls (n = 84) underwent resting-state MEG recordings. Extracted metrics included regional oscillatory power, connectivity, and spectral shape. 'DyNeMo' was trained to identify six functional dynamic brain networks. Metrics were compared between groups. A classifier was trained to distinguish asymptomatic gene carriers from controls. Compared to controls, beta frequency power was decreased in both symALS and aC9 groups. The aC9 group showed a marked slowing of frontal oscillatory activity, while the aSOD group showed a marked acceleration. Dynamic network coactivation was dramatically disrupted in aC9, more than in both symALS and aSOD. The classifier accurately distinguished genetically at-risk groups from controls (receiver-operator-characteristic area-under-curve 0.89). The cerebral network dynamics of aC9 are markedly different from both aSOD and symALS, supporting the concept of profoundly different upstream pathways in SOD1 ALS, sparing wider cortical pathology when compared to C9orf72 ALS. aC9 changes may reflect chronic adaptive changes relating to neurodevelopmental factors or underpin aspects of system vulnerability that define penetrance variability. MEG metrics might provide important biomarkers of prevention therapy efficacy and phenoconversion in at-risk populations.