Motor Unit Discharge Patterns Research Articles

Voluntary co-contraction of ankle muscles alters motor unit discharge characteristics and reduces estimates of persistent inward currents.

Motoneuronal persistent inward currents (PICs) are facilitated by neuromodulatory inputs but are highly sensitive to local inhibitory circuits. Estimates of PICs are reduced by group Ia reciprocal inhibition, and increased with the diffuse actions of neuromodulators released during remote muscle contraction. However, it remains unknown how motoneurons function in the presence of simultaneous excitatory and inhibitory commands. To probe this topic, we investigated motor unit discharge patterns and estimated PICs during voluntary co-contraction of ankle muscles, which simultaneously demands the contraction of agonist-antagonist pairs. Twenty participants performed triangular ramps of both co-contraction (simultaneous dorsiflexion and plantar flexion) and isometric dorsiflexion to a peak of 30% of their maximum muscle activity from a maximal voluntary contraction. Motor unit spike trains were decomposed from high-density surface EMG activity recorded from tibialis anterior using blind source separation algorithms. Voluntary co-contraction altered motor unit discharge rate characteristics. Discharge rate at recruitment and peak discharge rate were modestly reduced (∼6% change; P<0.001; d=0.22) and increased (∼2% change; P=0.001, d=-0.19), respectively, in the entire dataset but no changes were observed when motor units were tracked across conditions. The largest effects during co-contraction were that estimates of PICs (ΔF) were reduced by ∼20% (4.47 vs. 5.57 pulses per second during isometric dorsiflexion; P<0.001, d=0.641). These findings suggest that, during voluntary co-contraction, the inhibitory input from the antagonist muscle overcomes the additional excitatory and neuromodulatory drive that may occur due to the co-contraction of the antagonist muscle, which constrains PIC behaviour. KEY POINTS: Voluntary co-contraction is a unique motor behaviour that concurrently provides excitatory and inhibitory synaptic input to motoneurons. Co-contraction of agonist-antagonist pairs alters agonist motor unit discharge characteristics, consistent with reductions in persistent inward current magnitude.

Functional force stimulation alters motor neuron discharge patterns.

Beneficial effects have been observed for mechanical vibration stimulation (MVS), which are mainly attributed to tonic vibration reflex (TVR). TVR is reported to elicit synchronized motor unit activation during locally applied vibration. Similar effects are also observed in a novel vibration system referred to as functional force stimulation (FFS). However, the manifestation of TVR in FFS is doubted due to the use of global electromyography (EMG) features in previous analysis. Our study aims to investigate the effects of FFS on motor unit discharge patterns of the human biceps brachii by analyzing the motor unit spike trains decoded from the high-density surface EMG. Eighteen healthy subjects volunteered in FFS training with different amplitudes and frequencies. One hundred and twenty-eight channel surface EMG was recorded from the biceps brachii and then decoded after motion-artifact removal. The discharge timings were extracted and the coherence between different motor unit spike trains was calculated to quantify synchronized activation. Significant synchronization within the vibration cycle and/or its integer multiples is observed for all FFS trials, which increases with increased FFS amplitude. Our results reveal the basic physiological mechanism involved in FFS, providing a theoretical foundation for analyzing and introducing FFS into clinical rehabilitation programs.

High-density magnetomyography is superior to high-density surface electromyography for motor unit decomposition: a simulation study

Objective. Studying motor units is essential for understanding motor control, the detection of neuromuscular disorders and the control of human–machine interfaces. Individual motor unit firings are currently identified in vivo by decomposing electromyographic (EMG) signals. Due to our body’s properties and anatomy, individual motor units can only be separated to a limited extent with surface EMG. Unlike electrical signals, magnetic fields do not interact with human tissues. This physical property and the emerging technology of quantum sensors make magnetomyography (MMG) a highly promising methodology. However, the full potential of MMG to study neuromuscular physiology has not yet been explored. Approach. In this work, we perform in silico trials that combine a biophysical model of EMG and MMG with state-of-the-art algorithms for the decomposition of motor units. This allows the prediction of an upper-bound for the motor unit decomposition accuracy. Main results. It is shown that non-invasive high-density MMG data is superior over comparable high-density surface EMG data for the robust identification of the discharge patterns of individual motor units. Decomposing MMG instead of EMG increased the number of identifiable motor units by 76%. Notably, MMG exhibits a less pronounced bias to detect superficial motor units. Significance. The presented simulations provide insights into methods to study the neuromuscular system non-invasively and in vivo that would not be easily feasible by other means. Hence, this study provides guidance for the development of novel biomedical technologies.

A peel-off convolution kernel compensation method for surface electromyography decomposition

Objective:Estimating discharge patterns of motor units by electromyography (EMG) decomposition has shown promising perspectives in neurophysiologic investigations and human–machine interfaces. However, the number of decoded motor units is still limited, especially under high excitation and noisy conditions, which is a major barrier to the broad application of EMG decomposition. In this work, we applied a peel-off decomposition strategy to the convolution kernel compensation (CKC) algorithm to extract more motor units non-invasively. Methods:EMG signals were firstly decomposed into motor unit spike trains (MUSTs) using the CKC. After each decomposition, the motor unit action potentials (MUAPs) were reconstructed and subtracted from the EMG signals. Then the same CKC decomposition was applied to the residual signals. This peel-off procedure was repeated until no valid motor units were identified. The proposed decomposition strategy was validated on synthetic EMG signals by convolving simulated MUSTs and experimentally extracted MUAPs under multiple excitations and noise conditions. Then the decomposition performance was evaluated on experimental data. Main results:Compared with the classic CKC method, the number of the identified motor units from synthetic signals was significantly increased by 7 to 43 in each decomposition. Moreover, the average agreement between identified MUST and ground truth was 0.80 ± 0.20, indicating a high decomposition accuracy. From experimental EMG signals, the peel-off method could identify more motor units (>20) with high confidence than the classic method (<5) across three excitation levels. Conclusion and Significance:These results demonstrate the efficiency of the proposed method in identifying more motor units from EMG signals, extending the potential applications of surface EMG decomposition for neural decoding.

A geometric approach to quantifying the neuromodulatory effects of persistent inward currents on individual motor unit discharge patterns

Objective. All motor commands flow through motoneurons, which entrain control of their innervated muscle fibers, forming a motor unit (MU). Owing to the high fidelity of action potentials within MUs, their discharge profiles detail the organization of ionotropic excitatory/inhibitory as well as metabotropic neuromodulatory commands to motoneurons. Neuromodulatory inputs (e.g. norepinephrine, serotonin) enhance motoneuron excitability and facilitate persistent inward currents (PICs). PICs introduce quantifiable properties in MU discharge profiles by augmenting depolarizing currents upon activation (i.e. PIC amplification) and facilitating discharge at lower levels of excitatory input than required for recruitment (i.e. PIC prolongation). Approach. Here, we introduce a novel geometric approach to estimate neuromodulatory and inhibitory contributions to MU discharge by exploiting discharge non-linearities introduced by PIC amplification during time-varying linear tasks. In specific, we quantify the deviation from linear discharge (‘brace height’) and the rate of change in discharge (i.e. acceleration slope, attenuation slope, angle). We further characterize these metrics on a simulated motoneuron pool with known excitatory, inhibitory, and neuromodulatory inputs and on human MUs (number of MUs; Tibialis Anterior: 1448, Medial Gastrocnemius: 2100, Soleus: 1062, First Dorsal Interosseus: 2296). Main results. In the simulated motor pool, we found brace height and attenuation slope to consistently indicate changes in neuromodulation and the pattern of inhibition (excitation–inhibition coupling), respectively, whereas the paired MU analysis (ΔF) was dependent on both neuromodulation and inhibition pattern. Furthermore, we provide estimates of these metrics in human MUs and show comparable variability in ΔF and brace height measures for MUs matched across multiple trials. Significance. Spanning both datasets, we found brace height quantification to provide an intuitive method for achieving graded estimates of neuromodulatory and inhibitory drive to individual MUs. This complements common techniques and provides an avenue for decoupling changes in the level of neuromodulatory and pattern of inhibitory motor commands.

Motor Unit Discharge Patterns in Response to Focal Tendon Vibration of the Lower Limb in Cats and Humans.

High-frequency vibration of the tendon provides potent activation of Ia afferents time-locked to the stimulation frequency and provides excitatory ionotropic activation of homonymous motor pools. In cats, the evoked motor unit discharge is constrained to discharge at integer multiples of the vibration frequency, resulting in a probability of discharge that is highly punctuated. Here we quantify the robustness of this punctuated response in the cat and evaluate whether it is present in the human. Soleus electromyography (EMG) was collected from eight cats using 64 channel electrodes during three modes of motoneuron activation. First, tendon vibration parameters were modified. Second, secondary reflex inputs are applied concurrently with tendon vibration. Third, the state of the spinal cord was altered through pharmacological or surgical manipulations. Analogous surface high-density EMG was collected from the lower leg of six humans during both vibration evoked and matched volitional contractions. Array EMG signals from both the cat and human were decomposed into corresponding motor unit action potential spike trains, and the punctuation in discharge was quantified. In the cat, regardless of vibration parameters, secondary synaptic drive, and state of spinal circuitry, focal tendon vibration evoked punctuated motor unit discharge. However, in the human lower limb, the vibration-evoked contractions do not produce punctuated motor unit discharge.

Inter-Person Differences in Isometric Coactivations of Triceps Surae and Tibialis Anterior Decrease in Young, but Not in Older Adults After 14 Days of Bed Rest

We examined activation patterns of the gastrocnemius medialis (GM), gastrocnemius lateralis (GL), soleus (SO), and tibialis anterior (TA) muscles in eight older (58.4 ± 3.3 years) and seven young (23.1 ± 2.9 years) participants, before and after 14 days of horizontal bed rest. Visual feedback on the exerted muscle torque was provided to the participants. The discharge patterns of individual motor units (MUs) were studied in three repetitions of isometric plantar flexion at 30 and 60% of Maximum Voluntary Contraction (MVC), before, and 1 day after the 14-day bed rest, respectively. In the GL and GM muscles, the older participants demonstrated higher MU discharge rates than the young, regardless of the contraction level, both before and after the bed rest. In the TA and SO muscles, the differences between the older and young participants were less consistent. Detailed analysis revealed person-specific changes in the MU discharge rates after the bed rest. To quantify the coactivation patterns we calculated the correlation coefficients between the cumulative spike trains of identified MUs from each muscle, and measured the root mean square difference of the correlation coefficients between the trials of the same session (intra-session variability) and between different sessions (inter-session variability) in each participant (intra-person comparison) and across participants (inter-person comparison). In the intra-person comparison, the inter-session variability was higher than the intra-session variability, either before or after the bed rest. At 60% MVC torque, the young demonstrated higher inter-person variability of coactivation than the older participants, but this variability decreased significantly after the bed rest. In older participants, inter-person variability was consistently lower at 60% than at 30% MVC torque. In young participants, inter-person variability became lower at 60% than at 30% MVC torque only after the bed rest. Precaution is required when analyzing the MU discharge and coactivation patterns, as individual persons demonstrate individual adaptations to aging or bed rest.

Deficit in knee extension strength following anterior cruciate ligament reconstruction is explained by a reduced neural drive to the vasti muscles.

The persistence of quadriceps weakness represents a major concern following anterior cruciate ligament reconstruction (ACLR). The underlying adaptations occurring in the activity of spinal motoneurons are still unexplored. This study examined the discharge patterns of large populations of motor units (MUs) in the vastus lateralis (VL) and vastus medialis muscles following ACLR. Nine ACLR individuals and 10 controls performed unilateral trapezoidal contractions of the knee extensor muscles at 35%, 50% and 70% of the maximal voluntary isometric force (MVIF). High-density surface electromyography (HDsEMG) was used to record the myoelectrical activity of the vasti muscles in both limbs. HDsEMG signals were decomposed with a convolutive blind source separation method and MU properties were extracted and compared between sides and groups. The ACLR group showed a lower MVIF on the reconstructed side compared to the contralateral side (28.1%; P<0.001). This force deficit was accompanied by reduced MU discharge rates (∼21%; P<0.05), lower absolute MU recruitment and derecruitment thresholds (∼22% and ∼22.5%, respectively; P<0.05) and lower input-output gain of motoneurons (27.3%; P=0.009). Deficits in MU discharge rates of the VL and in absolute recruitment and derecruitment thresholds of both vasti MUs were associated with deficits in MVIF (P<0.05). A strong between-side correlation was found for MU discharge rates of the VL of ACLR individuals (P<0.01). There were no significant between-group differences (P>0.05). These results indicate that mid- to long-term strength deficits following ACLR may be attributable to a reduced neural drive to vasti muscles, with potential changes in excitatory and inhibitory synaptic inputs. KEY POINTS: Impaired expression and control of knee extension forces is common after anterior cruciate ligament reconstruction and is related to high risk of a second injury. To provide novel insights into the neural basis of this impairment, the discharge patterns of motor units in the vastus lateralis and vastus medialis were investigated during voluntary force contractions. There was lower knee extensor strength on the reconstructed side with respect to the contralateral side, which was explained by deficits in motor unit discharge rate and an altered motoneuronal input-output gain. Insufficient excitatory inputs to motoneurons and increased inhibitory afferent signals potentially contributed to these alterations. These results further our understanding of the neural underpinnings of quadriceps weakness following anterior cruciate ligament reconstruction and can help to develop effective rehabilitation protocols to regain muscle strength and reduce the risk of a second injury.

Acute physiological responses to combined blood flow restriction and low-level laser.

Blood flow restriction (BFR) is an innovation in fitness to train muscles with low loads at low oxygen levels. Low-level laser therapy (LLLT) is a bio-energetic approach to alleviate muscle fatigue during resistance training. This study investigated the immediate effect of LLLT pre-conditioning on BFR that accelerates muscle fatigue due to ischemia. Fifteen young adults participated in this study of a crossover randomized design. They completed a low-load contraction with various pre-conditioning (blood flow restriction with low-level laser therapy (LLLT + BFR), blood flow restriction with sham low-level laser therapy (BFR), and control). Force fluctuation dynamics, muscle oxygen saturation of hemoglobin and myoglobin (SmO2), and discharge patterns of motor units (MU) were compared. Normalized SmO2 during low-load contractions significantly varied with the pre-contraction protocols (Control (83.6 ± 3.0%) > LLLT + BFR (70.3 ± 2.8%) > BFR (55.4 ± 2.4%). Also, force fluctuations and MU discharge varied with the pre-contraction protocols. Multi-scale entropy and mean frequency of force fluctuations were greater in the LLLT + BFR condition (31.95 ± 0.67) than in the BFR condition (29.47 ± 0.73). The mean inter-spike interval of MUs was greater in the LLLT + BFR condition (53.32 ± 2.70ms) than in the BFR condition (45.04 ± 1.08ms). In particular, MUs with higher recruitment thresholds exhibited greater LLLT-related discharge complexity (LLLT + BFR (0.201 ± 0.012) > BFR (0.154 ± 0.006)). LLLT pre-conditioning can minimize the BFR-related decline in muscle oxygen saturation, leading to force gradation and MU discharge in a cost-effective and complex manner.

Adaptive Real-Time Identification of Motor Unit Discharges From Non-Stationary High-Density Surface Electromyographic Signals.

Estimation of the discharge pattern of motor units by electromyography (EMG) decomposition has been applied for neurophysiologic investigations, clinical diagnosis, and human-machine interfacing. However, most of the methods for EMG decomposition are currently applied offline. Here, we propose an approach for high-density surface EMG decomposition in real-time. A real-time decomposition scheme including two sessions, offline training and online decomposition, is proposed based on the convolutional kernel compensation algorithm. The estimation parameters, separation vectors and the thresholds for spike extraction, are first computed during offline training, and then they are directly applied to estimate motor unit spike trains (MUSTs) during the online decomposition. The estimation parameters are updated with the identification of new discharges to adapt to non-stationary conditions. The decomposition accuracy was validated on simulated EMG signals by convolving synthetic MUSTs with motor unit action potentials (MUAPs). Moreover, the accuracy of the online decomposition was assessed from experimental signals recorded from forearm muscles using a signal-based performance metrics (pulse-to-noise ratio, PNR). The proposed algorithm yielded a high decomposition accuracy and robustness to non-stationary conditions. The accuracy of MUSTs identified from simulated EMG signals was 80% for most conditions. From experimental EMG signals, on average, 12 ± 2 MUSTs were identified from each electrode grid with PNR of 25.0 ± 1.8dB, corresponding to an estimated decomposition accuracy 75%. These results indicate the feasibility of real-time identification of motor unit activities non-invasively during variable force contractions, extending the potential applications of high-density EMG as a neural interface.

Changes in motor unit discharge patterns following strength training.

Changes in motor unit discharge patterns following strength training.

Characterizing Residual Muscle Properties in Lower Limb Amputees Using High Density EMG Decomposition: A Pilot Study.

As research is progressing towards EMG control of lower limb prostheses, it is vital to understand the neurophysiology of the residual muscles in the amputated limb, which has been largely ignored. Therefore, the goal of this study was to characterize the activation patterns (muscle recruitment and motor unit discharge patterns) of the residual muscles of lower limb amputees. One transtibial amputee subject was recruited for this pilot study. The participant wore three high-density EMG electrode pads (8x8 grid with 64 channels) on each limb (a total of six pads) - one on the tibialis anterior (TA), medial gastrocnemius (MG), and lateral gastrocnemius (LG), respectively. The participant was asked to follow a ramping procedure plateauing at 50% of maximum voluntary contraction (MVC) for both the TA and Gastrocnemius muscles. The EMG signals were then decomposed offline; the firing rate and spatial activation patterns of the muscle were analyzed. Results showed slower and more variable firing rate in motor units of residual muscles than those of intact side. In addition, the spatial pattern of muscle activation differed between residual and intact muscles. These results indicate that surface EMG signals recorded from residual muscles present modified signal features from intact shank muscles, which should be considered when implementing myoelectric control schemes.

Tremor severity in Parkinson's disease and cortical changes of areas controlling movement sequencing: A preliminary study.

There remains much to learn about the changes in cortical anatomy that are associated with tremor severity in Parkinson's disease (PD). For this reason, we used a combination of structural neuroimaging to measure cortical thickness and neurophysiological studies to analyze whether PD tremor was associated with cortex integrity. Magnetic resonance imaging and neurophysiological assessment were performed in 13 nondemented PD patients (9 women, 69.2%) with a clearly tremor-dominant phenotype. Cortical reconstruction and volumetric segmentation were performed with the Freesurfer image analysis software. Assessment of tremor was performed by means of high-density surface electromyography (hdEMG) and inertial measurement units (IMUs). Individual motor unit discharge patterns were identified from surface hdEMG and tremor metrics quantifying motor unit synchronization from IMUs. Increased motor unit synchronization (i.e., more severe tremor) was associated with cortical changes (i.e., atrophy) in wide-spread cortical areas, including caudal middle frontal regions bilaterally (dorsal premotor cortices), left inferior parietal lobe (posterior parietal cortex), left lateral orbitofrontal cortex, cingulate cortex bilaterally, left posterior and transverse temporal cortex, and left occipital lobe, as well as reduced left middle temporal volume. Given that the majority of these areas are involved in controlling movement sequencing, our results support Albert's classic hypothesis that PD tremor may be the result of an involuntary activation of a program of motor behavior used in the genesis of rapid voluntary alternating movements.

Motor unit territories in human genioglossus estimated with multichannel intramuscular electrodes.

The discharge patterns of genioglossus motor units during breathing have been well-characterized in previous studies, but their localization and territories are not known. In this study, we used two newly developed intramuscular multichannel electrodes to estimate the territories of genioglossus motor units in the anterior and posterior regions of the muscle. Seven healthy men participated. Each electrode contained fifteen bipolar channels, separated by 1 mm, and was inserted percutaneously below the chin, perpendicular to the skin, to a depth of 36 mm. Single motor unit activity was recorded with subjects awake, supine, and breathing quietly through a nasal mask for 180 s. Motor unit territories were estimated from the spike-triggered averages of the electromyographic signal from each channel. A total of 30 motor units were identified: 22 expiratory tonic, 1 expiratory phasic, 2 tonic, 3 inspiratory tonic, and 2 inspiratory phasic. Motor units appeared to be clustered based on unit type, with peak activities for expiratory units predominantly located in the anterior and superficial fibers of genioglossus and inspiratory units in the posterior region. Of these motor unit types, expiratory tonic units had the largest estimated territory, a mean 11.3 mm (SD 1.9). Estimated territories of inspiratory motor units ranged from 3 to 6 mm. In accordance with the distribution of motor unit types, the estimated territory of genioglossus motor units varied along the sagittal plane, decreasing from anterior to posterior. Our findings suggest that genioglossus motor units have large territories relative to the cross-sectional size of the muscle. NEW & NOTEWORTHY In this study, we used a new multichannel intramuscular electrode to address a fundamental property of human genioglossus motor units. We describe the territory of genioglossus motor units in the anterior and posterior regions of the muscle and show a decrease in territory size from anterior to posterior and that expiratory-related motor units have larger estimated territories than inspiratory-related motor units.

New Perspectives for Computer-Aided Discrimination of Parkinson’s Disease and Essential Tremor

Pathological tremor is a common but highly complex movement disorder, affecting ~5% of population older than 65 years. Different methodologies have been proposed for its quantification. Nevertheless, the discrimination between Parkinson’s disease tremor and essential tremor remains a daunting clinical challenge, greatly impacting patient treatment and basic research. Here, we propose and compare several movement-based and electromyography-based tremor quantification metrics. For the latter, we identified individual motor unit discharge patterns from high-density surface electromyograms and characterized the neural drive to a single muscle and how it relates to other affected muscles in 27 Parkinson’s disease and 27 essential tremor patients. We also computed several metrics from the literature. The most discriminative metrics were the symmetry of the neural drive to muscles, motor unit synchronization, and the mean log power of the tremor harmonics in movement recordings. Noteworthily, the first two most discriminative metrics were proposed in this study. We then used decision tree modelling to find the most discriminative combinations of individual metrics, which increased the accuracy of tremor type discrimination to 94%. In summary, the proposed neural drive-based metrics were the most accurate at discriminating and characterizing the two most common pathological tremor types.

Altered motor unit discharge patterns in paretic muscles of stroke survivors assessed using surface electromyography

Objective. Hemispheric stroke survivors often show impairments in voluntary muscle activation. One potential source of these impairments could come from altered control of muscle, via disrupted motor unit (MU) firing patterns. In this study, we sought to determine whether MU firing patterns are modified on the affected side of stroke survivors, as compared with the analogous contralateral muscle. Approach. Using a novel surface electromyogram (EMG) sensor array, coupled with advanced template recognition software (dEMG) we recorded surface EMG signals over the first dorsal interosseous (FDI) muscle on both paretic and contralateral sides. Recordings were made as stroke survivors produced isometric index finger abductions over a large force range (20%–60% of maximum). Utilizing the dEMG algorithm, MU firing rates, recruitment thresholds, and action potential amplitudes were estimated for concurrently active MUs in each trial. Main results. Our results reveal significant changes in the firing rate patterns in paretic FDI muscle, in that the discharge rates, characterized in relation to recruitment force threshold and to MU size, were less clearly correlated with recruitment force than in contralateral FDI muscles. Firing rates in the affected muscle also did not modulate systematically with the level of voluntary muscle contraction, as would be expected in intact muscles. These disturbances in firing properties also correlated closely with the impairment of muscle force generation. Significance. Our results provide strong evidence of disruptions in MU firing behavior in paretic muscles after a hemispheric stroke, suggesting that modified control of the spinal motoneuron pool could be a contributing factor to muscular weakness in stroke survivors.

Are Human Digit Muscles Devoid of Recurrent Inhibition?

Are Human Digit Muscles Devoid of Recurrent Inhibition?

Altered motor unit discharge patterns in paretic muscles of stroke survivors assessed using surface electromyography

Altered motor unit discharge patterns in paretic muscles of stroke survivors assessed using surface electromyography

Accurate identification of motor unit discharge patterns from high-density surface EMG and validation with a novel signal-based performance metric

Objective. A signal-based metric for assessment of accuracy of motor unit (MU) identification from high-density surface electromyograms (EMG) is introduced. This metric, so-called pulse-to-noise-ratio (PNR), is computationally efficient, does not require any additional experimental costs and can be applied to every MU that is identified by the previously developed convolution kernel compensation technique. Approach. The analytical derivation of the newly introduced metric is provided, along with its extensive experimental validation on both synthetic and experimental surface EMG signals with signal-to-noise ratios ranging from 0 to 20 dB and muscle contraction forces from 5% to 70% of the maximum voluntary contraction. Main results. In all the experimental and simulated signals, the newly introduced metric correlated significantly with both sensitivity and false alarm rate in identification of MU discharges. Practically all the MUs with PNR > 30 dB exhibited sensitivity >90% and false alarm rates <2%. Therefore, a threshold of 30 dB in PNR can be used as a simple method for selecting only reliably decomposed units. Significance. The newly introduced metric is considered a robust and reliable indicator of accuracy of MU identification. The study also shows that high-density surface EMG can be reliably decomposed at contraction forces as high as 70% of the maximum.

Modulation of human motoneuron activity by a mental arithmetic task

This study aimed to determine whether the performance of a mental task affects motoneuron activity. To this end, the tonic discharge pattern of wrist extensor motor units was analyzed in healthy subjects while they were required to maintain a steady wrist extension force and to concurrently perform a mental arithmetic (MA) task. A shortening of the mean inter-spike interval (ISI) and a decrease in ISI variability occurred when MA task was superimposed to the motor task. Aloud and silent MA affected equally the rate and variability of motoneuron discharge. Increases in surface EMG activity and force level were consistent with the modulation of the motor unit discharge rate. Trial-by-trial analysis of the characteristics of motor unit firing revealed that performing MA increases activation of wrist extensor SMU. It is suggested that increase in muscle spindle afferent activity, resulting from fusimotor drive activation by MA, may have contributed to the increase in synaptic inputs to motoneurons during the mental task performance, likely together with enhancement in the descending drive. The finding that a mental task affects motoneuron activity could have consequences in assessment of motor disabilities and in rehabilitation in motor pathologies.