EEG motor imagery decoding: a framework for comparative analysis with channel attention mechanisms.

Objective.The objective of this study is to investigate the application of various channel attention mechanisms within the domain of brain-computer interface (BCI) for motor imagery decoding. Channel attention mechanisms can be seen as a powerful evolution of spatial filters traditionally used for motor imagery decoding. This study systematically compares such mechanisms by integrating them into a lightweight architecture framework to evaluate their impact.Approach.We carefully construct a straightforward and lightweight baseline architecture designed to seamlessly integrate different channel attention mechanisms. This approach is contrary to previous works which only investigate one attention mechanism and usually build a very complex, sometimes nested architecture. Our framework allows us to evaluate and compare the impact of different attention mechanisms under the same circumstances. The easy integration of different channel attention mechanisms as well as the low computational complexity enables us to conduct a wide range of experiments on four datasets to thoroughly assess the effectiveness of the baseline model and the attention mechanisms.Results.Our experiments demonstrate the strength and generalizability of our architecture framework as well as how channel attention mechanisms can improve the performance while maintaining the small memory footprint and low computational complexity of our baseline architecture.Significance.Our architecture emphasizes simplicity, offering easy integration of channel attention mechanisms, while maintaining a high degree of generalizability across datasets, making it a versatile and efficient solution for electroencephalogram motor imagery decoding within BCIs.

A System for Reproducible 3D Ultrasound Measurements of Skeletal Muscles.

In 3D freehand ultrasound imaging, operator dependent variations in applied forces and movements can lead to errors in the reconstructed images. In this paper, we introduce an automated 3D ultrasound system, which enables acquisitions with controlled movement trajectories by using motors, which electrically move the probe. Due to integrated encoders there is no need of position sensors. An included force control mechanism ensures a constant contact force to the skin. We conducted 8 trials with the automated 3D ultrasound system on 2 different phantoms with 3 force settings and 10 trials on a human tibialis anterior muscle with 2 force settings. For comparison, we also conducted 8 freehand 3D ultrasound scans from 2 operators (4 force settings) on one phantom and 10 with one operator on the tibialis anterior muscle. Both freehand and automated trials showed small errors in volume and length computations of the reconstructions, however the freehand trials showed larger standard deviations. We also computed the thickness of the phantom and the tibialis anterior muscle. We found significant differences in force settings for the operators and higher coefficients of variation for the freehand trials. Overall, the automated 3D ultrasound system shows a high accuracy in reconstruction. Due to the smaller coefficients of variation, the automated 3D ultrasound system enables more reproducible ultrasound examinations than the freehand scanning. Therefore, the automated 3D ultrasound system is a reliable tool for 3D investigations of skeletal muscle.

Effects of robotic guidance on the coordination of locomotion.

BACKGROUND: Functional integration of motor activity patterns enables the production of coordinated movements, such as walking. The activation of muscles by weightened summation of activation signals has been demonstrated to represent the spatiotemporal components that determine motor behavior during walking. Exoskeleton robotic devices are now often used in the rehabilitation practice to assist physical therapy of individuals with neurological disorders. These devices are used to promote motor recovery by providing guidance force to the patients. The guidance should in principle lead to a muscle coordination similar to physiological human walking. However, the influence of robotic devices on locomotor patterns needs still to be characterized. The aim of this study was to analyze the effect of force guidance and gait speed on the modular organization of walking in a group of eight healthy subjects. METHOD: A group of healthy subjects walked on a treadmill with and without robotic aiding at speeds of 1.5, 2.0 and 2.5 Km/h. The guidance force was varied between 20%, 40%, 70% and 100% level of assistance. EMG recordings were obtained from seven leg muscles of the dominant leg and kinematic and kinetic features of the knee and hip joints were extracted. RESULTS: Four motor modules were sufficient to represent the variety of behavioral goals demanded during robotic guidance, with similar relationships between muscle patterns and biomechanical parameters across subjects, confirming that the low-dimensional and impulsive control of human walking is maintained using robotic force guidance. The conditions of guidance force and speed that maintained correct and incorrect (not natural) modular control were identified. CONCLUSION: In neurologically intact subjects robotic-guided walking at various force guidance and speed levels does not alter the basic locomotor control and timing. This allows the design of robotic-aided rehabilitation strategies aimed at the modulation of motor modules, which are altered in stroke.

Optimal Identification of Muscle Synergies From Typical Sit-to-Stand Clinical Tests.

Goal: The goal of this manuscript is to investigate the optimal methods for extracting muscle synergies from a sit-to-stand test; in particular, the performance in identifying the modular structures from signals of different length is characterized. Methods: Surface electromyography signals have been recorded from instrumented sit-to-stand trials. Muscle synergies have then been extracted from signals of different duration (i.e. 5 times sit to stand and 30 seconds sit to stand) from different portions of a complete sit-to-stand-to-sit cycle. Performance have then been characterized using cross-validation procedures. Moreover, an optimal method based on a modified Akaike Information Criterion measure is applied on the signal for selecting the correct number of synergies from each trial. Results: Results show that it is possible to identify correctly muscle synergies from relatively short signals in a sit-to-stand experiment. Moreover, the information about motor control structures is identified with a higher consistency when only the sit-to-stand phase of the complete cycle is considered. Conclusions: Defining a set of optimal methods for the extraction of muscle synergies from a clnical test such as the sit-to-stand is of key relevance to ensure the applicability of any synergy-related analysis in the clinical practice, without requiring knowledge of the technical signal processing methods and the underlying features of the signal.

Predicting EEG Responses to Attended Speech via Deep Neural Networks for Speech.

Attending to the speech stream of interest in multi-talker environments can be a challenging task, particularly for listeners with hearing impairment. Research suggests that neural responses assessed with electroencephalography (EEG) are modulated by listener's auditory attention, revealing selective neural tracking (NT) of the attended speech. NT methods mostly rely on hand-engineered acoustic and linguistic speech features to predict the neural response. Only recently, deep neural network (DNN) models without specific linguistic information have been used to extract speech features for NT, demonstrating that speech features in hierarchical DNN layers can predict neural responses throughout the auditory pathway. In this study, we go one step further to investigate the suitability of similar DNN models for speech to predict neural responses to competing speech observed in EEG. We recorded EEG data using a 64-channel acquisition system from 17 listeners with normal hearing instructed to attend to one of two competing talkers. Our data revealed that EEG responses are significantly better predicted by DNN-extracted speech features than by hand-engineered acoustic features. Furthermore, analysis of hierarchical DNN layers showed that early layers yielded the highest predictions. Moreover, we found a significant increase in auditory attention classification accuracies with the use of DNN-extracted speech features over the use of hand-engineered acoustic features. These findings open a new avenue for development of new NT measures to evaluate and further advance hearing technology.

Low-frequency oscillations of the neural drive to the muscle are increased with experimental muscle pain.

We investigated the influence of nociceptive stimulation on the accuracy of task execution and motor unit spike trains during low-force isometric contractions. Muscle pain was induced by infusion of hypertonic saline into the abductor digiti minimi muscle of 11 healthy men. Intramuscular EMG signals were recorded from the same muscle during four isometric contractions of 60-s duration at 10% of the maximal force [maximal voluntary contraction (MVC)] performed before injection (baseline), after injection of isotonic (control) or hypertonic saline (pain), and 15 min after pain was no longer reported. Each contraction was preceded by three 3-s ramp contractions from 0% to 10% MVC. The low-frequency oscillations of motor unit spike trains were analyzed by the first principal component of the low-pass filtered spike trains [first common component (FCC)], which represents the effective neural drive to the muscle. Pain decreased the accuracy of task performance [coefficient of variation (CoV) for force: baseline, 2.8 ± 1.8%, pain, 3.9 ± 1.8%; P < 0.05] and reduced motor unit discharge rates [11.6 ± 2.3 pulses per second (pps) vs. 10.7 ± 1.7 pps; P < 0.05]. Motor unit recruitment thresholds (2.2 ± 1.2% MVC vs. 2.4 ± 1.6% MVC), interspike interval variability (18.4 ± 4.9% vs. 19.1 ± 5.4%), strength of motor unit short-term synchronization [common input strength (CIS) 1.02 ± 0.44 vs. 0.83 ± 0.22], and strength of common drive (0.47 ± 0.08 vs. 0.47 ± 0.06) did not change across conditions. The FCC signal was correlated with force (R = 0.45 ± 0.06), and the CoV for FCC increased in the painful condition (5.69 ± 1.29% vs. 7.83 ± 2.61%; P < 0.05). These results indicate that nociceptive stimulation increased the low-frequency variability in synaptic input to motoneurons.

Modular organization of balance control following perturbations during walking.

Balance recovery during walking requires complex sensory-motor integration. Mechanisms to avoid falls are active concomitantly with human locomotion motor patterns. It has been suggested that gait can be described by a set of motor modules (synergies), but little is known on the modularity of gait during recovery of balance due to unexpected slips. Our hypothesis was that muscular activation during reactive recovery of balance during gait has a modular organization. The aim of the study was to verify this hypothesis when perturbations were delivered in different directions. Eight healthy men walked on a 7-m walkway, which had a moveable force platform embedded in the middle. Subjects experienced unperturbed walking as well as perturbations delivered in the sagittal (forward and backward) and frontal (leftward and rightward) planes. Bilateral full-body kinematics and surface electromyography (EMG) from lower limbs, trunk, and neck were recorded during walking. Synergies and activation signals were extracted from surface EMG signals. Four modules were sufficient to explain the unperturbed gait and the gait perturbed in any of the perturbation directions. Moreover, three of four modules extracted from the unperturbed gait were the same for gait perturbed forward, leftward, and rightward (similarity in synergies = 0.94 ± 0.03). On the other hand, the activation signals were different between unperturbed and perturbed gait (average correlation coefficient = 0.55 ± 0.16). These strategies to recover balance were robust across subjects. In conclusion, changes in lower limb and trunk kinematics provoked by perturbations were reflected in minimal adjustments in the muscular modular organization of walking, with three of four modules preserved from normal walking. Conversely, the activation signals were all substantially influenced by the perturbations, being the result of integration of afferent information and supraspinal control.

Changes in human muscle oxygen saturation and mean fiber conduction velocity during intense dynamic exercise--effect of muscular training status.

INTRODUCTION: In this study we investigated whether an association exists between muscle fiber conduction velocity (MFCV) and local muscle oxygen saturation (StO(2)) in the superficial part of the latissimus dorsi muscle of runners and swimmers during exhaustive dynamic exercise. METHODS: Participants performed arm cranking with increasing intensity until exhaustion. RESULTS: Runners' MFCV was unchanged with increasing arm-cranking exercise intensity, but was higher (P < 0.05) than swimmers' MFCV at the same workload. Swimmers' MFCV increased (P < 0.05) with increasing exercise intensity and reached values at exhaustion similar to those of the runners. StO(2) was similar in swimmers and runners at rest and decreased with increasing exercise intensity. StO(2) was higher (P < 0.05) at the same workload in swimmers compared with runners. StO(2) and MFCV were significantly but very weakly correlated in both swimmers and runners. CONCLUSION: No association exists between surface MFCV and StO(2) in either trained or untrained human skeletal muscle during exhaustive intense dynamic exercise.

Motor modules in robot-aided walking.

BACKGROUND: It is hypothesized that locomotion is achieved by means of rhythm generating networks (central pattern generators) and muscle activation generating networks. This modular organization can be partly identified from the analysis of the muscular activity by means of factorization algorithms. The activity of rhythm generating networks is described by activation signals whilst the muscle intervention generating network is represented by motor modules (muscle synergies). In this study, we extend the analysis of modular organization of walking to the case of robot-aided locomotion, at varying speed and body weight support level. METHODS: Non Negative Matrix Factorization was applied on surface electromyographic signals of 8 lower limb muscles of healthy subjects walking in gait robotic trainer at different walking velocities (1 to 3 km/h) and levels of body weight support (0 to 30%). RESULTS: The muscular activity of volunteers could be described by low dimensionality (4 modules), as for overground walking. Moreover, the activation signals during robot-aided walking were bursts of activation timed at specific phases of the gait cycle, underlying an impulsive controller, as also observed in overground walking. This modular organization was consistent across the investigated speeds, body weight support level, and subjects. CONCLUSIONS: These results indicate that walking in a Lokomat robotic trainer is achieved by similar motor modules and activation signals as overground walking and thus supports the use of robotic training for re-establishing natural walking patterns.

Predictive simulation of sit-to-stand based on reflexive-controllers.

Sit-to-stand can be defined as a set of movements that allow humans to rise from a sitting position to a bipedal standing pose. These movements, often categorized as four distinct kinematic phases, must be coordinated for assuring personal autonomy and can be compromised by ageing or physical impairments. To solve this, rehabilitation techniques and assistive devices demand proper description of the principles that lead to the correct completion of this motor task. While the muscular dynamics of the sit-to-stand task have been analysed, the underlying neural activity remains unknown and largely inaccessible for conventional measurement systems. Predictive simulations can propose motor controllers whose plausibility is evaluated through the comparison between simulated and experimental kinematics. In the present work, we modelled an array of reflexes that originate muscle activations as a function of proprioceptive and vestibular feedback. This feedback encodes torso position, displacement velocity and acceleration of a modelled human body with 7 segments, 9 degrees of freedom, and 50 actuators. We implemented two controllers: a four-phases controller where the reflex gains and composition vary depending on the kinematic phase, and a simpler two-phases controller, where three of the kinematic phases share the same reflex gains. Gains were optimized using Covariance Matrix Adaptation. The results of the simulations reveal, for both controllers, human-like sit-to-stand movement, with joint angles and muscular activity comparable to experimental data. The results obtained with the simplified two-phases controller indicate that a simple set of reflexes could be sufficient to drive this motor task.

Investigating the spatial resolution of EMG and MMG based on a systemic multi-scale model.

While electromyography (EMG) and magnetomyography (MMG) are both methods to measure the electrical activity of skeletal muscles, no systematic comparison between both signals exists. Within this work, we propose a novel in silico model for EMG and MMG and test the hypothesis that MMG surpasses EMG in terms of spatial selectivity, i.e. the ability to distinguish spatially shifted sources. The results show that MMG provides a slightly better spatial selectivity than EMG when recorded directly on the muscle surface. However, there is a remarkable difference in spatial selectivity for non-invasive surface measurements. The spatial selectivity of the MMG components aligned with the muscle fibres and normal to the body surface outperforms the spatial selectivity of surface EMG. Particularly, for the MMG's normal-to-the-surface component the influence of subcutaneous fat is minimal. Further, for the first time, we analyse the contribution of different structural components, i.e. muscle fibres from different motor units and the extracellular space, to the measurable biomagnetic field. Notably, the simulations show that for the normal-to-the-surface MMG component, the contribution from volume currents in the extracellular space and in surrounding inactive tissues, is negligible. Further, our model predicts a surprisingly high contribution of the passive muscle fibres to the observable magnetic field.

Dynamic 3D Ultrasound Imaging of the Tibialis Anterior Muscle.

Skeletal muscle volume has been mainly investigated under static conditions, i.e. isometric contractions. The aim of our study is to use ultrasound imaging to determine muscle deformation during movement. We used a custom-designed scanning rig to obtain 3D ultrasound images of a subject moving the foot from plantarflexion to dorsiflexion at constant velocity. Using motion capture, we computed the respective angle of the ankle for each frame and collected them in bins based on the measured angle (rounded on the next normal number). For each degree, we used Stradwin for the 3D reconstruction of the respective volume. We found increasing cross-sectional areas for increasing dorsiflexion angles. The proposed method is a promising approach for determining muscle volume during movement. Future studies aim at collecting more data to compute muscle volume and length during contraction and compare the results to isometric measurements.

Optimizing NV magnetometry for Magnetoneurography and Magnetomyography applications.

Magnetometers based on color centers in diamond are setting new frontiers for sensing capabilities due to their combined extraordinary performances in sensitivity, bandwidth, dynamic range, and spatial resolution, with stable operability in a wide range of conditions ranging from room to low temperatures. This has allowed for its wide range of applications, from biology and chemical studies to industrial applications. Among the many, sensing of bio-magnetic fields from muscular and neurophysiology has been one of the most attractive applications for NV magnetometry due to its compact and proximal sensing capability. Although SQUID magnetometers and optically pumped magnetometers (OPM) have made huge progress in Magnetomyography (MMG) and Magnetoneurography (MNG), exploring the same with NV magnetometry is scant at best. Given the room temperature operability and gradiometric applications of the NV magnetometer, it could be highly sensitive in the pT / Hz -range even without magnetic shielding, bringing it close to industrial applications. The presented work here elaborates on the performance metrics of these magnetometers to the state-of-the-art techniques by analyzing the sensitivity, dynamic range, and bandwidth, and discusses the potential benefits of using NV magnetometers for MMG and MNG applications.

Impulses of activation but not motor modules are preserved in the locomotion of subacute stroke patients.

It has been hypothesized that the coordinated activation of muscles is controlled by the central nervous system by means of a small alphabet of control signals (also referred to as activation signals) and motor modules (synergies). We analyzed the locomotion of 10 patients recently affected by stroke (maximum of 20 wk) and compared it with that of healthy controls. The aim was to assess whether the walking of subacute stroke patients is based on the same motor modules and/or activation signals as healthy subjects. The activity of muscles of the lower and upper limb and the trunk was measured and used for extracting motor modules. Four modules were sufficient to explain the majority of variance in muscle activation in both controls and patients. Modules from the affected side of stroke patients were different from those of healthy controls and from the unaffected side of stroke patients. However, the activation signals were similar between groups and between the affected and unaffected side of stroke patients, and were characterized by impulses at specific time instants within the gait cycle, underlying an impulsive controller of gait. In conclusion, motor modules observed in healthy subjects during locomotion are different from those used by subacute stroke patients, despite similar impulsive activation signals. We suggest that this pattern is consistent with a neuronal network in which the timing of activity generated by central pattern generators is directed to the motoneurons via a premotor network that distributes the activity in a task-dependent manner determined by sensory and descending control information.

Variations in Muscle Activity and Exerted Torque During Temporary Blood Flow Restriction in Healthy Individuals.

Recent studies suggest that transitory blood flow restriction (BFR) may improve the outcomes of training from anatomical (hypertrophy) and neural control perspectives. Whilst the chronic consequences of BFR on local metabolism and tissue adaptation have been extensively investigated, its acute effects on motor control are not yet fully understood. In this study, we compared the neuromechanical effects of continuous BFR against non-restricted circulation (atmospheric pressure-AP), during isometric elbow flexions. BFR was achieved applying external pressure either between systolic and diastolic (lower pressure-LP) or 1.3 times the systolic pressure (higher pressure-HP). Three levels of torque (15, 30, and 50% of the maximal voluntary contraction-MVC) were combined with the three levels of pressure for a total of 9 (randomized) test cases. Each condition was repeated 3 times. The protocol was administered to 12 healthy young adults. Neuromechanical measurements (torque and high-density electromyography-HDEMG) and reported discomfort were used to investigate the response of the central nervous system to BFR. The investigated variables were: root mean square (RMS), and area under the curve in the frequency domain-for the torque, and average RMS, median frequency and average muscle fibres conduction velocity-for the EMG. The discomfort caused by BFR was exacerbated by the level of torque and accumulated over time. The torque RMS value did not change across conditions and repetitions. Its spectral content, however, revealed a decrease in power at the tremor band (alpha-band, 5-15 Hz) which was enhanced by the level of pressure and the repetition number. The EMG amplitude showed no differences whilst the median frequency and the conduction velocity decreased over time and across trials, but only for the highest levels of torque and pressure. Taken together, our results show strong yet transitory effects of BFR that are compatible with a motor neuron pool inhibition caused by increased activity of type III and IV afferences, and a decreased activity of spindle afferents. We speculate that a compensation of the central drive may be necessary to maintain the mechanical output unchanged, despite disturbances in the afferent volley to the motor neuron pool.

Neuromechanical evidence of improved neuromuscular control around knee joint in volleyball players.

The aim of the present work was to verify that skilled volleyball players present specific adaptations in both neuromuscular control and movement biomechanics, showing an improved neuromuscular control around the knee joint than in non-jumper athletes. Seven male volleyball players and seven male non-jumper athletes were recruited for this study. The following tests were performed in a random order: single countermovement jump (CMJ), single squat jump. At the end of the series, subjects performed a repetitive CMJ test. Electromyographic signals were recorded from vastus lateralis and biceps femoris muscles on both sides. Ground reaction forces and moments were measured with a force plate. Volleyball athletes performed better in all tests and were more resistant to fatigue than non-jumper athletes. Furthermore, volleyball athletes showed a reduced co-activation of knee flexor/extensor muscles. The present results seem to stand for a neural adaptation of the motor control scheme to training.

Effects of altered muscle temperature on neuromuscular properties in young and older women.

Muscle temperature has a profound effect on the neuromuscular system of young individuals, however, little is known about the effects of altered temperature on the muscles of older individuals. The purpose of this study was to investigate the effect of altered local temperature on maximal torque and electromyography signal characteristics in 15 young (21.5 +/- 2.2 years; mean +/- SD) and 12 older (73.6 +/- 3.2 years) women. Subjects completed maximal voluntary isometric knee extension and flexion, together with isokinetic knee extensions (30, 60, 90, 120 and 240 degrees/s) at three muscle temperatures: control (approximately 34 degrees C), cold (approximately 30 degrees C) and warm (approximately 38 degrees C). The torque was lower in the older compared to young subjects at all temperatures (range of difference for 240 degrees /s, 25-40%; P < 0.001). Warming had no effect on torque in either group, whereas cooling decreased the torque during the isokinetic contractions in the young group only (range of decrease 6-10%; P < 0.05). In both groups, muscle fibre conduction velocity was slower with cooling compared to the warm condition (-15% in the young and -17% in the older subjects; P < 0.05).Temperature, however, had no effect on the agonist-antagonist coactivation level or the rate of force development in either group. The results suggest that, in particular, cooling the muscles has a greater effect on motor performance in young than older adults, which may indicate reduced adaptation of the neuromuscular system of older adults to altered temperature.

Modelling the electrical activity of skeletal muscle tissue using a multi-domain approach.

Electromyography (EMG) can be used to study the behaviour of the motor neurons and thus provides insights into the physiology of the central nervous system. However, due to the high complexity of neuromuscular control, EMG signals are challenging to interpret. While the exact knowledge of the excitation patterns of a specific muscle within an in vivo experimental setting remains elusive, simulations allow to systematically investigate EMG signals in a controlled environment. Within this context, simulations can provide virtual EMG data, which, for example, can be used to validate and optimise signal analysis methods that aim to estimate the relationship between EMG signals and the output of motor neuron pools. However, since existing methods, which are employed to compute EMG signals, exhibit deficiencies with respect to the physical model itself as well as with respect to numerical aspects, we propose a novel homogenised continuum model that closely resolves the electro-physiological behaviour of skeletal muscle tissue. The proposed model is based on an extension of the well-established bidomain model and includes a biophysically detailed description of the electrical activity within the tissue, which is due to the depolarisation of the muscle fibre membranes. In contrast to all other published EMG models, which assume that the electrical potential field for each muscle fibre can be calculated independently, the proposed model assumes that the electrical potential in the muscle fibres is coupled to the electrical potential in the extracellular space. We show that the newly proposed model is able to simulate realistic EMG signals and demonstrate the potential to employ the predicted virtual EMG signal in order to evaluate the goodness of automated decomposition algorithms.

A Systematic Review and Meta-Analysis on the Longitudinal Effects of Unilateral Knee Extension Exercise on Muscle Strength.

The aim of the study was to investigate the time-dependent increase in the knee extensors' isometric strength as a response to voluntary, unilateral, isometric knee extension exercise (UIKEE). To do so, a systematic review was carried out to obtain data for a Bayesian longitudinal model-based meta-analysis (BLMBMA). For the systematic review, PubMed, Web of Science, SCOPUS, Chochrane Library were used as databases. The systematic review included only studies that reported on healthy, young individuals performing UIKEE. Studies utilizing a bilateral training protocol were excluded as the focus of this review lied on unilateral training. Out of the 3,870 studies, which were reviewed, 20 studies fulfilled the selected inclusion criteria. These 20 studies were included in the BLMBMA to investigate the time-dependent effects of UIKEE. If compared to the baseline strength of the trained limb, these data reveal that UKIEE can increase the isometric strength by up to 46%. A meta-analysis based on the last time-point of each available study was employed to support further investigations into UIKEE-induced strength increase. A sensitivity analysis showed that intensity of training (%MVC), fraction of male subjects and the average age of the subject had no significant influence on the strength gain. Convergence of BLMBMA revealed that the peak strength increase is reached after ~4 weeks of UIKEE training.

Myofascial trigger points alter the modular control during the execution of a reaching task: a pilot study.

Myofascial trigger points (TP) constitute a conundrum in research and clinical practice as their etiopathogenesis is debated. Several studies investigating one or few muscles have shown that both active and latent TP causes an increased muscle activity, however the influence of TP on modular motor control during a reaching task is still unclear. Electromyographic signals, recorded from the muscles of the shoulder girdle and upper arm during a reaching task, were decomposed with Non-Negative Matrix Factorization algorithm. The extracted matrices of motor modules and activation signals were used to label the muscles condition as dominant or non-dominant. The presence of latent and active TP was detected in each muscle with manual examination. Despite a similar muscle activity was observed, we found that muscles with active TP had increased weighting coefficients when labeled in the dominant condition. No influences were found when muscles were in the non-dominant condition. These findings suggest that TP altered the motor control without co-contraction patterns. As a preliminary evidence, the present results suggest that the increased weighting coefficients in presence of TPs are associated with an alteration of the modular motor control without affecting the dimensionality of motor modules for each individual and reciprocal inhibition.