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The mapping of the sensorimotor cortex gives information about the cortical motor and sensory functions. Typical mapping methods are navigated transcranial magnetic stimulation (TMS) and magnetoencephalography (MEG). The differences between these mapping methods are, however, not fully known. TMS center of gravities (CoGs), MEG somatosensory evoked fields (SEFs), corticomuscular coherence (CMC), and corticokinematic coherence (CKC) were mapped in ten healthy adults. TMS mapping was performed for first dorsal interosseous (FDI) and extensor carpi radialis (ECR) muscles. SEFs were induced by tactile stimulation of the index finger. CMC and CKC were determined as the coherence between MEG signals and the electromyography or accelerometer signals, respectively, during voluntary muscle activity. CMC was mapped during the activation of FDI and ECR muscles separately, whereas CKC was measured during the waving of the index finger at a rate of 3–4 Hz. The maximum CMC was found at beta frequency range, whereas maximumCKC was found at the movement frequency. The mean Euclidean distances between different localizations were within 20 mm. The smallest distance was found between TMS FDI and TMS ECR CoGs and longest between CMC FDI and CMC ECR sites. TMS-inferred localizations (CoGs) were less variable across participants than MEG-inferred localizations (CMC, CKC). On average, SEF locations were 8 mm lateral to the TMS CoGs (p < 0.01). No differences between hemispheres were found. Based on the results, TMS appears to be more viable than MEG in locating motor cortical areas.

In this paper, we propose a new method for jointly compressing EEG and EMG biosignals based on the so-called cortico-muscular coherence, a function that takes into account the simultaneous frequency changes of the brain and the muscles activity, and can be used, e.g., to classify different kinds of movement. It is shown that this method increases the achievable compression rate compared to transmitting EEG and EMG samples separately, while trading-off with the accuracy of the classification. This can be exploited in several kinds of life and health applications e.g., motor rehabilitation and drivers attention monitoring; it could be especially useful for low-power wireless technologies, such as Bluetooth Low Energy or IEEE 802.15.6, whose transmission resources are limited.

Tongue movements contribute to oral functions including swallowing, vocalizing, and breathing. Fine tongue movements are regulated through efferent and afferent connections between the cortex and tongue. It has been demonstrated that cortico-muscular coherence (CMC) is reflected at two frequency bands during isometric tongue protrusions: the beta (β) band at 15-35Hz and the low-frequency band at 2-10Hz. The CMC at the β band (β-CMC) reflects motor commands from the primary motor cortex (M1) to the tongue muscles through hypoglossal motoneuron pools. However, the generator mechanism of the CMC at the low-frequency band (low-CMC) remains unknown. Here, we evaluated the mechanism of low-CMC during isometric tongue protrusion using magnetoencephalography (MEG). Somatosensory evoked fields (SEFs) were also recorded following electrical tongue stimulation. Significant low-CMC and β-CMC were observed over both hemispheres for each side of the tongue. Time-domain analysis showed that the MEG signal followed the electromyography signal for low-CMC, which was contrary to the finding that the MEG signal preceded the electromyography signal for β-CMC. The mean conduction time from the tongue to the cortex was not significantly different between the low-CMC (mean, 80.9ms) and SEFs (mean, 71.1ms). The cortical sources of low-CMC were located significantly posterior (mean, 10.1mm) to the sources of β-CMC in M1, but were in the same area as tongue SEFs in the primary somatosensory cortex (S1). These results reveal that the low-CMC may be driven by proprioceptive afferents from the tongue muscles to S1, and that the oscillatory interaction was derived from each side of the tongue to both hemispheres. Oscillatory proprioceptive feedback from the tongue muscles may aid in the coordination of sophisticated tongue movements in humans.

Available online 9 September 2019 Electroencephalographic and magnetoencephalographic data have characterized two types of brain–body interactions observed during various types of motor actions, “corticokinematic” and “corticomuscular” coupling. Here, we review the literature on these interactions in healthy individuals, discuss several open debates, and outline current limitations and directions for future research. Corticokinematic coupling (commonly referred to as corticokinematic coherence) probes the relationship between activity of sensorimotor network nodes and various movement-related signals (e.g., speed, velocity, acceleration). It is mainly driven by movement rhythmicity during active, passive, and observed dynamic motor actions. It typically predominates at the primary sensorimotor cortex contralateral to the moving limb, occurs at movement frequency and its harmonics, and predominantly reflects the cortical processing of proprioceptive feedback driven by movement rhythmicity in a broad range of dynamic motor actions. Corticomuscular coupling (commonly referred to as corticomuscular coherence) probes the interaction between sensorimotor cortical rhythms and electromyographic (EMG) activity that mainly occurs during steady isometric muscle contraction. We will here focus on the ~20-Hz coupling that is observed during weak isometric contraction and is linked to the modulation of the descending motor command by the ~20-Hz sensorimotor rhythm. This review argues that corticokinematic and corticomuscular couplings have different neural bases. Corticokinematic coupling is mainly driven by afferent signals, while corticomuscular coupling is mainly (but not solely) driven by efferent signals. This distinction should be considered when investigating interactions between brain and body movements. Mathieu Bourguignon was supported by the program Attract of Innoviris (grant 2015-BB2B-10), by the Marie Skłodowska-Curie Action of the European Commission (grant 743562) and by the Spanish Ministry of Economy and Competitiveness (grant PSI2016-77175-P). Sarang S. Dalal was supported by the European Research Council (Starting Grant 640448). Karim Jerbi is supported by funding from the Canada Research Chairs program and a Discovery Grant (RGPIN-2015-04854) from the Natural Sciences and Engineering Research Council of Canada, a New Investigators Award from the Fonds de Recherche du Qu ebec - Nature et Technologies (2018-NC-206005) and an IVADO-Apog ee fundamental research project grant. Xavier De Ti ege is Post-doctorate Clinical Master Specialist at the FRS-FNRS. The MEG project at the CUB H^opital Erasme is financially supported by the Fonds Erasme (Research convention “Les Voies du Savoir”, Fonds Erasme, Brussels, Belgium). We would like to warmly thank Professor Riitta Hari for her helpful comments on the manuscript.

This work presents an innovative application of the well-known concept of cortico-muscular coherence for the classification of various motor tasks, i.e., grasps of different kinds of objects. Our approach can classify objects with different weights (motor-related features) and different surface frictions (haptics-related features) with high accuracy (over 0.8). The outcomes presented here provide information about the synchronization existing between the brain and the muscles during specific activities; thus, this may represent a new effective way to perform activity recognition.

Background To explore the cortical network sustaining action myoclonus and to found markers of the resulting functional impairment, we evaluated the distribution of the cortico-muscular coherence (CMC) and the frequency of coherent cortical oscillations with magnetoencephalography (MEG). All patients had EPM1 (Unverricht-Lundborg) disease known to present with prominent and disabling movement-activated myoclonus. Methods Using autoregressive models, we evaluated CMC on MEG sensors grouped in regions of interests (ROIs) above the main cortical areas. The movement was a repeated sustained isometric extension of the right hand and right foot. We compared the data obtained in 10 EPM1 patients with those obtained in 10 age-matched controls. Results As expected, CMC in beta band was significantly higher in EPM1 patients compared to controls in the ROIs exploring the sensorimotor cortex, but, it was also significantly higher in adjacent ROIs ipsilateral and contralateral to the activated limb. Moreover, the beta-CMC peak occurred at frequencies significantly slower and more stable frequencies in EPM1 patients with respect to controls. The frequency of the beta-CMC peak inversely correlated with the severity of myoclonus. Conclusions the high and spatially extended beta-CMC peaking in a restricted range of low-beta frequencies in EPM1 patients, suggest that action myoclonus may result not only from an enhanced local synchronization but also from a specific oscillatory activity involving an expanded neuronal pool. The significant relationship between beta-CMC peak frequency and the severity of the motor impairment can represent a useful neurophysiological marker for the patients’ evaluation and follow-up.

"In thiswork a time-frequency approach to estimate the Cortico-Muscular Coherence for the detection of the movement intent is presented, assessed on simulated data, and evaluated experimentally during different motor tasks performed by healthy subjects and patients suffering from different types of tremor. Cortico-Muscular Coherence is an index of the coupling of EEG signal in the cortical area with sEMG activity in the frequency domain, and its contributions in the beta band (15–30 Hz) have been associated to the movement intent. Cortico-Muscular Coherence estimation is here achieved by considering a closed-loop representation of the signals under analysis obtained through Multivariate Auto Regressive modeling. Significance levels for Cortico-Muscular Coherence are assessed by means of a surrogate data analysis approach. The detection technique is able to reveal significant Cortico-Muscular Coherence changes in 79% of the experimental trials, with a mean anticipation of 1.35 s with respect to movement onset. Time-frequency estimation of CMC can provide an insight for the development of a multimodal BCI able to integrate information from the brain activity in the functioning of assistive devices." In this work a time-frequency approach to estimate the Cortico-Muscular Coherence for the detection of the movement intent is presented, assessed on simulated data, and evaluated experimentally during different motor tasks performed by healthy subjects and patients suffering from different types of tremor. Cortico-Muscular Coherence is an index of the coupling of EEG signal in the cortical area with sEMG activity in the frequency domain, and its contributions in the beta band (15-30 Hz) have been associated to the movement intent. Cortico-Muscular Coherence estimation is here achieved by considering a closed-loop representation of the signals under analysis obtained through Multivariate Auto Regressive modeling. Significance levels for Cortico-Muscular Coherence are assessed by means of a surrogate data analysis approach. The detection technique is able to reveal significant Cortico-Muscular Coherence changes in 79% of the experimental trials, with a mean anticipation of 1.35 s with respect to movement onset. Time-frequency estimation of Cortico-Muscular Coherence can provide an insight for the development of a multimodal BCI able to integrate information from the brain activity in the functioning of assistive devices. © 2012 - IOS Press and the authors. All rights reserved.

To obtain a direct sensorimotor integration assessment in primary hand cortical areas (M1) of patients suffering from focal task-specific hand dystonia, magnetoencephalographic (MEG) and opponens pollicis electromyographic (EMG) activities were acquired during a motor task expressly chosen not to induce dystonic movements in our patients, to disentangle abnormalities indicating a possible substrate on which dystonia develops. A simple isometric contraction was performed either alone or in combination with median nerve stimulation, i.e. when a non-physiological sensory inflow was overlapping with the physiological feedback. As control condition, median nerve stimulation was also performed at rest. The task was performed bilaterally both in eight patients and in 16 healthy volunteers. In comparison with results in controls we found that in dystonic patients: i) MEG-EMG coherence was higher; ii) it reduced much less during galvanic stimulation in the hemisphere contralateral to the dystonic arm, simultaneously with iii) stronger inhibition of the sensory areas responsiveness due to movement; iv) the cortical component including contributions from sensory inhibitory and motor structures was reduced and v) much more inhibited during movement. It is documented that a simultaneous cortico-muscular coherence increase occurs in presence of a reduced M1 responsiveness to the inflow from the sensory regions. This could indicate an unbalance of the fronto-parietal functional impact on M1, with a weakening of the parietal components. Concurrently, signs of a less differentiated sensory hand representation--possibly due to impaired inhibitory mechanisms efficiency--and signs of a reduced repertoire of voluntary motor control strategies were found.

Movement control requires continuous and reciprocal exchange of information between activities of motor areas involved in the task program execution and those elaborating proprioceptive sensory information. Our aim was to investigate the sensorimotor interactions in the region dedicated to hand control in healthy humans, focusing onto primary sensory and motor cortices, by selecting the time window at very early latencies. Through magnetoencephalographic recordings, we obtained a simultaneous assessment of sensory cortex activity modulation due to movement and of motor cortex activity modulation due to sensory stimulation, by eliciting a galvanic stimulation to the nerve (the median nerve) innervating a muscle (the opponens pollicis), at rest or during voluntary contraction. The primary sensory and motor cortices activities were investigated respectively through excitability in response to sensory stimulation and the cortico-muscular coherence. The task was performed bilaterally. A clear reduction of the cortico-muscular coherence was found in the short time window following stimuli (between around 150-450 ms). In the same time period, the motor control of isometric contraction was preserved. This could suggest that cortical component of voluntary movement control was transiently mediated by neuronal firing rate tuning more than by cortico-muscular synchronization. In addition to the known primary sensory cortex inhibition due to movement, a more evident reduction was found for the component known to include a contribution from primary motor areas. Gating effects were lower in the dominant left hemisphere, suggesting that sensorimotor areas dominant for hand control benefit of narrowing down gating effects.

The functional source separation procedure (FSS) was applied to identify the activities of the primary sensorimotor areas (SM1) devoted to hand control. FSS adds a functional constraint to the cost function of the basic independent component analysis, and obtains source activity all along different processing states. Magnetoencephalographic signals from the left SM1 were recorded in 14 healthy subjects during a simple sensorimotor paradigm—galvanic right median nerve stimuli intermingled with submaximal isometric thumb opposition. Two functional sources related to the sensory flow in the primary cortex were extracted requiring maximal responsiveness to the nerve stimulation at around 20 and 30 ms (S1a, S1b). Maximal cortico‐muscular coherence was required for the extraction of the motor source (M1). Sources were multiplied by the Euclidean norm of their corresponding weight vectors, allowing amplitude comparisons among sources in a fixed position. In all subjects, S1a, S1b, M1 were successfully obtained, positioned consistently with the SM1 organization, and behaved as physiologically expected during the movement and processing of the sensory stimuli. The M1 source reacted to the nerve stimulation with higher intensity at latencies around 30 ms than around 20 ms. The FSS method was demonstrated to be able to obtain the dynamics of different primary cortical network activities, two devoted mainly to sensory inflow, and the other to the motor control of the contralateral hand. It was possible to observe each source both during pure sensory processing and during motor tasks. In all conditions, a direct comparison of source intensities can be achieved. Hum Brain Mapp, 2008. © 2007 Wiley‐Liss, Inc.

Background: Dystonia is often currently treated with botulinum toxin injections to spastic muscles, or deep brain stimulation to the basal ganglia. In addition to these pharmacological or neurosurgical measures, a new noninvasive treatment concept, functional modulation using a brain-computer interface, was tested for feasibility. We recorded electroencephalograms (EEGs) over the bilateral sensorimotor cortex from a patient suffering from chronic writer’s cramp. The patient was asked to suppress an exaggerated beta frequency component in the EEG during hand extension., Results: The patient completed biweekly one-hour training for 5 months without any adverse effects. Significant decrease of the beta frequency component during handwriting was confirmed, and was associated with clear functional improvement., Conclusion: The current pilot study suggests that a brain-computer Interface can give explicit feedback of ongoing cortical excitability to patients with dystonia and allow them to suppress exaggerated neural activity, resulting in functional recovery., This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

The aim of this study is to investigate bursts- related EEG signals in a focal hand dystonia patient. Despite of considering time domain and frequency domain techniques as mutually exclusive analysis, in this contribution we have taken advantage from both of them: particularly, in the frequency domain, coherence was used to identify the most likely frequency bands of interaction between brain and muscles, then, in the time domain, cross-correlation was exploited to verify the physiological reliability of such a relationship in terms of signal transmission delay from the centre to the periphery. Our preliminary results suggest - in line with recent literature - that activity in the high beta band (around 30 Hz) could represent an electroencephalographic correlate for the pathological electromyographic bursts affecting the focal hand dystonia condition. Even though a future study on a larger sample is needed to statistically support these preliminary findings, this contribution allows to think of new kinds of rehabilitation from focal hand dystonia that could target the actual electroencephalographic correlate of the pathology, i.e. phenotypically expressed by bursts, with the consequence of a relevant functional improvement., Comment: 5 pages, 6 figures. Submitted and accepted at Global Wireless Summit (GWS) 2016 at Aarhus University, Denmark. http://www.riverpublishers.com/search_ebook.php?val=gws&type=research&Search=Search, Proceedings of the Global Wireless Summit 2016. Editor: Peter Lindgren, Aarhus University, Denmark. e-ISBN: 9788793609297