Sensitivity of the cross-correlation between simulated surface EMGs for two muscles to detect motor unit synchronization

The role of clinical neurophysiology in the definition and assessment of fatigue and fatigability

Though a common symptom, fatigue is difficult to define and investigate, occurs in a wide variety of neurological and systemic disorders, with differing pathological causes. It is also often accompanied by a psychological component. As a symptom of long-term COVID-19 it has gained more attention. In this review, we begin by differentiating fatigue, a perception, from fatigability, quantifiable through biomarkers. Central and peripheral nervous system and muscle disorders associated with these are summarised. We provide a comprehensive and objective framework to help identify potential causes of fatigue and fatigability in a given disease condition. It also considers the effectiveness of neurophysiological tests as objective biomarkers for its assessment. Among these, twitch interpolation, motor cortex stimulation, electroencephalography and magnetencephalography, and readiness potentials will be described for the assessment of central fatigability, and surface and needle electromyography (EMG), single fibre EMG and nerve conduction studies for the assessment of peripheral fatigability. The purpose of this review is to guide clinicians in how to approach fatigue, and fatigability, and to suggest that neurophysiological tests may allow an understanding of their origin and interactions. In this way, their differing types and origins, and hence their possible differing treatments, may also be defined more clearly.

Uterine slow wave: directionality and changes with imminent delivery

OBJECTIVE

The slow wave (SW) of the electrohysterogram (EHG) may contain relevant information on the electrophysiological condition of the uterus throughout pregnancy and labor. Our aim was to assess differences in the SW as regards the imminence of labor and the directionality of uterine myoelectrical activity.

APPROACH

The SW of the EHG was extracted from the signals of the Icelandic 16-electrode EHG database in the bandwidth [5, 30] mHz and its power, spectral content, complexity and synchronization between the horizontal (X) and vertical (Y) directions were characterized by the root mean square (RMS), dominant frequency (domF), sample entropy (SampEn) and maximum cross-correlation (CCmax) of the signals, respectively. Significant differences between parameters at time-to-delivery (TTD) ≤7 vs. >7 days and between the horizontal vs. vertical directions were assessed.

MAIN RESULTS

The SW power significantly increased in both directions as labor approached (TTD≤7d vs. >7d (mean±SD): x= 0.12±0.10 vs. 0.08±0.06mV; y= 0.12±0.09 vs. 0.08±0.05mV), as well as the dominant frequency in the horizontal direction (= 9.1±1.3 vs. 8.5±1.2mHz) and the synchronization between both directions (= 0.44±0.16 vs. 0.36±0.14). Furthermore, its complexity decreased in the vertical direction (= 6.13·10-2±8.7·10-3 vs. 6.50·10-2±8.3·10-3), suggesting a higher cell-to-cell electrical coupling. Whereas there were no differences between the SW features in both directions in the general population, statistically significant differences were obtained between them in individuals in many cases.

SIGNIFICANCE

Our results suggest that the SW of the EHG is related to bioelectrical events in the uterus and could provide objective information to clinicians in challenging obstetric scenarios.

Effects of detection system parameters on cross-correlations between MUAPs generated from parallel and inclined muscle fibres

The aim of this study was to investigate the effects of inter-electrode distance (IED), electrode radius (ER) and electrodes configurations on cross-correlation coefficient (CC) between motor unit action potentials (MUAPs) generated in a motor unit (MU) of parallel fibres and in a MU of inclined fibres with respect to the detection system. The fibres inclination angle (FIA) varied from 0° to 180° by a step of 5°. Six spatial filters (the longitudinal single differential (LSD), longitudinal double differential (LDD), bi-transversal double differential (BiTDD), normal double differential (NDD), an inverse binomial filter of order two (IB2) and maximum kurtosis filter (MKF)), three values of IED and three values of ER were considered.

A cylindrical multilayer volume conductor constituted by bone, muscle, fat and skin layers was used to simulate the MUAPs.

The cross-correlation coefficient analysis showed that with the increase of the FIA, the pairs of MUAPs detected by the IB2 system were more correlated than those detected by the five other systems. For each FIA, the findings also showed that the MUAPs pairs detected by BiTDD, NDD, IB2 and MKF systems were more correlated with smaller IEDs than with larger ones, while inverse results were found with the LSD and LDD systems. In addition, the pairs of MUAPs detected by the LDD, BiTDD, IB2 and MKF systems were more correlated with large ERs than with smaller ones. However, inverse results were found with the LSD and NDD systems.

Crosstalk in Mechanomyographic Signals From Elbow Flexor Muscles During Submaximal to Maximal Isometric Flexion, Pronation, and Supination Torque Tasks

This study analyzed the crosstalk in mechanomyographic (MMG) signals from elbow flexors during isometric muscle actions from 20% to 100% maximum voluntary isometric contraction (MVIC). Twenty-five young, healthy, male participants performed the isometric elbow flexion, forearm pronation, and supination tasks at an elbow joint angle of 90 deg. The MMG signals from the biceps brachii (BB), brachialis (BRA), and brachioradialis (BRD) muscles were recorded using accelerometers. The cross-correlation coefficient was used to quantify the crosstalk in MMG signals, recorded in a direction transverse to muscle fiber axis, among the muscle pairs (P1: BB and BRA, P2: BRA and BRD, and P3: BB and BRD). In addition, the MMG RMS and MPF were quantified. The mean normalized RMS and mean MPF exhibited increasing (r > 0.900) and decreasing (r < -0.900) trends, respectively, with increases in the effort levels in all three tasks. The magnitude of crosstalk ranged from 0.915% to 21.565% in all three muscle pairs. The crosstalk was found to exhibit high positive correlations with submaximal to maximal flexion [P1 (r = 0.970), P2 (r = 0.951), and P3 (r = 0.824)], pronation [P1 (r = 0.811), P2 (r = 0.763), and P3 (r = 0.901)] and supination [P1 (r = 0.898), P2 (r = 0.838), and P3 (r = 0.852)] torque levels (eight out of nine p-values were < 0.05). Regardless of the high positive correlation between crosstalk and level of effort, the crosstalk remained at a low range (0.915-21.565%) with increases in the torque levels.

Association of anthropometric parameters with amplitude and crosstalk of mechanomyographic signals during forearm flexion, pronation and supination torque tasks

This study aimed to quantify the association of four anthropometric parameters of the human arm, namely, the arm circumference (CA), arm length (LA), skinfold thickness (ST) and inter-sensor distance (ISD), with amplitude (RMS) and crosstalk (CT) of mechanomyography (MMG) signals. Twenty-five young, healthy, male participants were recruited to perform forearm flexion, pronation and supination torque tasks. Three accelerometers were employed to record the MMG signals from the biceps brachii (BB), brachialis (BRA) and brachioradialis (BRD) at 80% maximal voluntary contraction (MVC). Signal RMS was used to quantify the amplitude of the MMG signals from a muscle, and cross-correlation coefficients were used to quantify the magnitude of the CT among muscle pairs (BB & BRA, BRA & BRD, and BB & BRD). For all investigated muscles and pairs, RMS and CT showed negligible to low negative correlations with CA, LA and ISD (r = −0.0001–−0.4611), and negligible to moderate positive correlations with ST (r = 0.004–0.511). However, almost all of these correlations were statistically insignificant (p > 0.05). These findings suggest that RMS and CT values for the elbow flexor muscles recorded and quantified using accelerometers appear invariant to anthropometric parameters.

The extraction of neural strategies from the surface EMG: an update

A surface EMG signal represents the linear transformation of motor neuron discharge times by the compound action potentials of the innervated muscle fibers and is often used as a source of information about neural activation of muscle. However, retrieving the embedded neural code from a surface EMG signal is extremely challenging. Most studies use indirect approaches in which selected features of the signal are interpreted as indicating certain characteristics of the neural code. These indirect associations are constrained by limitations that have been detailed previously (Farina D, Merletti R, Enoka RM. J Appl Physiol 96: 1486-1495, 2004) and are generally difficult to overcome. In an update on these issues, the current review extends the discussion to EMG-based coherence methods for assessing neural connectivity. We focus first on EMG amplitude cancellation, which intrinsically limits the association between EMG amplitude and the intensity of the neural activation and then discuss the limitations of coherence methods (EEG-EMG, EMG-EMG) as a way to assess the strength of the transmission of synaptic inputs into trains of motor unit action potentials. The debated influence of rectification on EMG spectral analysis and coherence measures is also discussed. Alternatively, there have been a number of attempts to identify the neural information directly by decomposing surface EMG signals into the discharge times of motor unit action potentials. The application of this approach is extremely powerful, but validation remains a central issue.

Cross-talk in mechanomyographic signals from the forearm muscles during sub-maximal to maximal isometric grip force

PURPOSE

This study aimed: i) to examine the relationship between the magnitude of cross-talk in mechanomyographic (MMG) signals generated by the extensor digitorum (ED), extensor carpi ulnaris (ECU), and flexor carpi ulnaris (FCU) muscles with the sub-maximal to maximal isometric grip force, and with the anthropometric parameters of the forearm, and ii) to quantify the distribution of the cross-talk in the MMG signal to determine if it appears due to the signal component of intramuscular pressure waves produced by the muscle fibers geometrical changes or due to the limb tremor.

METHODS

Twenty, right-handed healthy men (mean ± SD: age  = 26.7±3.83 y; height  = 174.47±6.3 cm; mass  = 72.79±14.36 kg) performed isometric muscle actions in 20% increment from 20% to 100% of the maximum voluntary isometric contraction (MVIC). During each muscle action, MMG signals generated by each muscle were detected using three separate accelerometers. The peak cross-correlations were used to quantify the cross-talk between two muscles.

RESULTS

The magnitude of cross-talk in the MMG signals among the muscle groups ranged from, R2(x, y) = 2.45-62.28%. Linear regression analysis showed that the magnitude of cross-talk increased linearly (r2 = 0.857-0.90) with the levels of grip force for all the muscle groups. The amount of cross-talk showed weak positive and negative correlations (r2 = 0.016-0.216) with the circumference and length of the forearm respectively, between the muscles at 100% MVIC. The cross-talk values significantly differed among the MMG signals due to: limb tremor (MMGTF), slow firing motor unit fibers (MMGSF) and fast firing motor unit fibers (MMGFF) between the muscles at 100% MVIC (p<0.05, η2 = 0.47-0.80).

SIGNIFICANCE

The results of this study may be used to improve our understanding of the mechanics of the forearm muscles during different levels of the grip force.

Establishment of a recording method for surface electromyography in the iliopsoas muscle

We examined the availability and reliability of surface electromyography (EMG) signals from the iliopsoas muscle (IL). Using serial magnetic resonance images from fifty healthy young males, we evaluated whether the superficial region of IL was adequate for attaching surface EMG electrodes. Subsequently, we assessed EMG cross-talk from the sartorius muscle (SA)-the nearest to IL-using a selective cooling method in fourteen subjects. The skin above SA was cooled, and the median frequencies of EMG signals from IL and SA were determined. The maximum voluntary contraction during isometric hip flexion was measured before and after selective cooling, and surface EMG signals from SA and IL were measured. The superficial area of IL was adequately large (13.2±2.7cm(2)) for recording surface EMG in all fifty subjects. The maximum perimeter for the medial-lateral skin facing IL was noted at a level 3-5cm distal to the anterior superior iliac spine. Following cooling, the median frequency for SA decreased significantly (from 70.1 to 51.9Hz, p<0.001); however, that for IL did not alter significantly. These results demonstrated that EMG cross-talk from SA was negligible for surface EMG signals from IL during hip flexion.

Identification of common synaptic inputs to motor neurons from the rectified electromyogram

Oscillatory common inputs of cortical or peripheral origin can be identified from the motor neuron output with coherence analysis. Linear transmission is possible despite the motor neuron non-linearity because the same input is sent commonly to several neurons. Because of the linear transmission, common input components to motor neurons can be investigated from the surface EMG, for example by EEG-EMG or EMG-EMG coherence. In these studies, there is an open debate on the utility and appropriateness of EMG rectification. The present study addresses this issue using an analytical, simulation and experimental approach. The main novel theoretical contribution that we report is that the spectra of both the rectified and the raw EMG contain input spectral components to motor neurons. However, they differ by the contribution of amplitude cancellation which influences the rectified EMG spectrum when extracting common oscillatory inputs. Therefore, the degree of amplitude cancellation has an impact on the effectiveness of EMG rectification in extracting input spectral peaks. The theoretical predictions were exactly confirmed by realistic simulations of a pool of motor neurons innervating a muscle in a cylindrical volume conductor of EMG generation and by experiments conducted on the first dorsal interosseous and the abductor pollicis brevis muscles of seven healthy subjects during pinching. It was concluded that when the contraction level is relatively low, EMG rectification may be preferable for identifying common inputs to motor neurons, especially when the energy of the action potentials in the low frequency range is low. Nonetheless, different levels of cancellation across conditions influence the relative estimates of the degree of linear transmission of oscillatory inputs to motor neurons when using the rectified EMG.

A simulation-based analysis of motor unit number index (MUNIX) technique using motoneuron pool and surface electromyogram models

Motor unit number index (MUNIX) measurement has recently achieved increasing attention as a tool to evaluate the progression of motoneuron diseases. In our current study, the sensitivity of the MUNIX technique to changes in motoneuron and muscle properties was explored by a simulation approach utilizing variations on published motoneuron pool and surface electromyogram (EMG) models. Our simulation results indicate that, when keeping motoneuron pool and muscle parameters unchanged and varying the input motor unit numbers to the model, then MUNIX estimates can appropriately characterize changes in motor unit numbers. Such MUNIX estimates are not sensitive to different motor unit recruitment and rate coding strategies used in the model. Furthermore, alterations in motor unit control properties do not have a significant effect on the MUNIX estimates. Neither adjustment of the motor unit recruitment range nor reduction of the motor unit firing rates jeopardizes the MUNIX estimates. The MUNIX estimates closely correlate with the maximum M-wave amplitude. However, if we reduce the amplitude of each motor unit action potential rather than simply reduce motor unit number, then MUNIX estimates substantially underestimate the motor unit numbers in the muscle. These findings suggest that the current MUNIX definition is most suitable for motoneuron diseases that demonstrate secondary evidence of muscle fiber reinnervation. In this regard, when MUNIX is applied, it is of much importance to examine a parallel measurement of motor unit size index (MUSIX), defined as the ratio of the maximum M-wave amplitude to the MUNIX. However, there are potential limitations in the application of the MUNIX methods in atrophied muscle, where it is unclear whether the atrophy is accompanied by loss of motor units or loss of muscle fiber size.

Sensitivity of EMG-EMG coherence to detect the common oscillatory drive to hand muscles in young and older adults

Multichannel surface electromyograms (EMGs) were used to examine the sensitivity of EMG-EMG coherence to infer changes in common oscillatory drive to hand muscles in young and older adults. Previous research has shown that measures of coherence calculated from different neurophysiological signals are influenced by the age of the subject, the visual feedback provided to the subject, and the task being performed. The change in the magnitude of EMG-EMG coherence across experimental conditions is often interpreted as a change in the oscillatory drive to motoneuron pools of a pair of muscles. However, signal processing (e.g., full-wave rectification) and electrode location are also reported to influence EMG-EMG coherence, which could decrease the sensitivity of EMG-EMG coherence to infer a change in common oscillatory drive to motoneurons. In this study, multichannel EMGs were used to compare EMG-EMG coherence in young (n = 11) and older (n = 10) adults during index finger abduction and pinch grip tasks performed at 2 and 3.5 N with a low and a high visual feedback gain. We found that, across all conditions, EMG-EMG coherence was influenced by electrode location (P < 0.001) but not by subject age, visual feedback gain, task, or signal processing. These results suggest that EMG-EMG coherence is most sensitive to electrode location. The results are discussed in terms of the potential issues related to inferring a common oscillatory drive to hand muscles with surface EMGs.

Hand dominance during constant force isometric contractions: evidence of different cortical drive commands

The purpose of this study was to investigate force variability and sensoriomotor strategies of dominant and nondominant hands of right and left-handed subjects during a submaximal isometric force production task. Twelve right-handed adults (9 men and 3 women; 23 ± 3 year) and twelve left-handed adults (4 men and 8 women; 24 ± 3 year) performed an isometric constant force contraction sustained at 30 and 50% of maximal force for 10 s. Surface EMG signals were obtained from forearm flexors and extensors. Force signals were analyzed in the time (CV of force) and frequency (0-10 Hz) domain. The neural activation of the involved muscles was investigated from the EMG structure using the cross-wavelet spectra of the interference EMG signals of six different frequency bands of the EMG signals were quantified (5-13, 13-30, 30-60, 60-100, 100-150 and 150-200 Hz). The major findings were: (1) dominant and nondominant hands of right- and left-handed subjects exhibited similar CV of force; (2) the power spectrum of force is influenced by handedness, with greater 1-3 Hz oscillations for left-handed subjects when compared to right-handed subjects; (3) right-handed subjects have greater 30-60 Hz neuromuscular activation when compared to left-handed subjects. Our results indicate that right-handed individuals may rely preferentially in visual feedback to carry out a task with visual and proprioceptive feedback because of the left hemisphere specialization on the visuomotor control.

Ultrasound assessment of the anatomical validity of T3 and L4 as sEMG recording sites

The accuracy of surface EMG measurement is dependent upon minimizing potential crosstalk from other muscles. Although they are deeply situated, in places the erector spinae are covered with electrically silent aponeuroses rather than active muscle tissue. Theoretically these aponeuroses can serve as windows for sEMG recordings. A recent anatomical study concluded that T3 and L4 are ideal sites for recording the ES because the superficial muscle aponeuroses are wide at these sites. The aim of this prospective study was to investigate these sites in vivo using real time ultrasound. Ultrasound images from 20 subjects (10<30 years and 10>70 years; equal numbers of males and females in each group) were acquired during rest and in prone extension with the arms in three different positions. The most superficial aponeurosis widths were measured. The mean T3 aponeurosis width reduced significantly in extension from 4.4±4.7mm at rest to 1.8±2.6mm in extension (p<0.0001). Males had significantly smaller T3 aponeurosis widths than females (p=0.049). The mean L4 aponeurosis width also significantly decreased in extension from 35.5±7.0mm at rest to 29.9±7.2mm in extension (p<0.0001) due to 'doming' of the aponeurosis. Our results demonstrate that T3 is not a reliable site over which to record the ES because the aponeurosis width is too narrow. L4 is a good site if the electrodes are placed no more than 20mm from the midline.

Coherence between surface electromyograms is influenced by electrode placement in hand muscles

We used multi-channel surface electromyograms (EMGs) to examine if electrode location influences coherence measures derived from pairs of EMGs recorded from two hand muscles during a pinch task. A linear probe of 16 electrodes was used to estimate the location of the innervation zone in first dorsal interosseous (FDI) and abductor pollicis brevis (APB). Four electrodes were then placed on the skin overlying each muscle and three bipolar electrode configurations were constructed with their center points directly over the innervation zone, and 15mm distal and proximal to the innervation zone. Ten subjects performed two force-matching tasks for 120s at 2N and 3.5N by pressing a force sensor held between the thumb and index finger. Coherence spectra were calculated from pairs of EMGs recorded from the two muscles. Maximal coherence from 1 to 15Hz and 16 to 32Hz was calculated at both force levels from the EMGs with electrodes centered over the innervation zones of FDI and APB. These values were compared to the maximal coherence from all other EMG comparisons across muscles recorded with electrodes that avoided the innervation zones. ANOVA revealed significant main effects only for electrode location, with a 58.1% increase (p=0.001) in maximal coherence for EMGs detected from pairs of electrodes that avoided the innervation zone (from 0.11±0.02 to 0.18±0.03; mean±95% confidence interval). These results indicate that electrode location relative to the innervation zone influences EMG-EMG coherence and should be carefully considered when placing EMG electrodes on hand muscles.

Assessment of across-muscle coherence using multi-unit vs. single-unit recordings

Coherence between electromyographic (EMG) signals has been used to identify correlated neural inputs to motor units (MUs) innervating different muscles. Simulations using a motor-unit model (Fuglevand et al. 1992) were performed to determine the ability of coherence between two multi-unit EMGs (mEMG) to detect correlated MU activity and the range of correlation strengths in which mEMG coherence can be usefully employed. Coherence between motor-unit and mEMG activities in two muscles was determined as we varied the strength of a 30-Hz periodic common input, the number of correlated MU pairs and variability of MU discharge relative to the common input. Pooled and mEMG coherence amplitudes positively and negatively accelerated, respectively, toward the strongest and most widespread correlating inputs. Furthermore, the relation between pooled and mEMG coherence was also nonlinear and was essentially the same whether correlation strength varied by changing common input strength or its distribution. However, the most important finding is that while the mEMG coherence saturates at the strongest common input strengths, this occurs at common input strengths greater than found in most physiological studies. Thus, we conclude that mEMG coherence would be a useful measure in many experimental conditions and our simulation results suggest further guidelines for using and interpreting coherence between mEMG signals.

Extraction of individual muscle mechanical action from endpoint force

Most motor tasks require the simultaneous coordination of multiple muscles. That coordination is poorly understood in part because there is no noninvasive means of isolating a single muscle's contribution to the resultant endpoint force. The contribution of a single motor unit to isometric tasks can, however, be characterized using the spike-triggered averaging (STA) technique, applied to a single motor unit's spike train. We propose that a technique analogous to STA, which we call electromyogram (EMG)-weighted averaging (EWA), can be applied to surface EMGs to extract muscle mechanical action from the natural endpoint force fluctuations generated during steady isometric contraction. We demonstrate this technique on simultaneous recordings of fingertip force and surface EMG from the first dorsal interosseous (FDI) and extensor indicis (EI) of humans. The EWA direction was approximately the same across a wide range of fingertip force directions, and the average EWA direction was consistent with mechanical action direction of these muscles estimated from cadaveric and imaging data: the EWA directions were 193 +/- 2 degrees for the FDI and 71 +/- 5 degrees for the EI (95% confidence). EWA transient behavior also appears to capture temporal characteristics of muscle force fluctuations with peak force time and general waveform shape similar to that of the associated spike-triggered averages from single motor units. The EWA may provide a means of empirically characterizing the complex transformation between muscle force and endpoint force without the need for invasive electrode recordings or complex anatomical measurements of musculoskeletal geometry.

Effect of cancellation on triggered averaging used to determine synchronization between motor unit discharge in separate muscles

Synchronization between single motor unit (SMU) discharges in separate muscles has been estimated from peaks in averaged electromyographic (EMG) recordings from one muscle triggered from SMU discharge in another. This study evaluated the effect of EMG signal cancellation on this measure of synchronization. SMU activity was recorded with 8 fine-wire electrodes in vastus medialis obliquus (VMO) and vastus lateralis (VL) during gentle isometric knee extension in 7 subjects. Data from 5 VL recordings were summed then rectified, or rectified then summed, to produce multi-unit recordings with and without cancellation, respectively. Averages of summed VL data were triggered from VMO SMUs. Synchronization, defined as a peak >3 SD above the triggered average mean, occurred in 73.68% and 78.95% of recordings with and without cancellation, respectively. To further investigate the effect of cancellation on synchronization, 250 "virtual" EMG recordings were created from VL data. VL SMUs were sorted and modified with respect to discharge rate, amplitude and polarity to create a collection of possible SMU discharge patterns. Virtual recordings were added one-by-one to VL recordings that showed synchronization. Virtual channels were rectified then added or added then rectified, to create data with and without cancellation. Identification of synchronization decreased similarly in both conditions with addition of virtual data. Our data show estimation of synchronization from triggered averages is more likely to detect synchronization in recordings with fewer SMUs, but cancellation has little effect. Synchronization must be interpreted with caution if number of SMUs changes between conditions.

Endpoint force fluctuations reveal flexible rather than synergistic patterns of muscle cooperation

We developed a new approach to investigate how the nervous system activates multiple redundant muscles by studying the endpoint force fluctuations during isometric force generation at a multi-degree-of-freedom joint. We hypothesized that, due to signal-dependent muscle force noise, endpoint force fluctuations would depend on the target direction of index finger force and that this dependence could be used to distinguish flexible from synergistic activation of the musculature. We made high-gain measurements of isometric forces generated to different target magnitudes and directions, in the plane of index finger metacarpophalangeal joint abduction-adduction/flexion-extension. Force fluctuations from each target were used to calculate a covariance ellipse, the shape of which varied as a function of target direction. Directions with narrow ellipses were approximately aligned with the estimated mechanical actions of key muscles. For example, targets directed along the mechanical action of the first dorsal interosseous (FDI) yielded narrow ellipses, with 88% of the variance directed along those target directions. It follows the FDI is likely a prime mover in this target direction and that, at most, 12% of the force variance could be explained by synergistic coupling with other muscles. In contrast, other target directions exhibited broader covariance ellipses with as little as 30% of force variance directed along those target directions. This is the result of cooperation among multiple muscles, based on independent electromyographic recordings. However, the pattern of cooperation across target directions indicates that muscles are recruited flexibly in accordance with their mechanical action, rather than in fixed groupings.

Fatigue-related changes in motor-unit synchronization of quadriceps muscles within and across legs

Two experiments were conducted to examine effects of muscle fatigue on motor-unit synchronization of quadriceps muscles (rectus femoris, vastus medialis, vastus lateralis) within and between legs. We expected muscle fatigue to result in an increased common drive to different motor units of synergists within a leg and, hence, to increased synchronization, i.e., an increased coherence between corresponding surface EMGs. We further expected fatigue-related motor overflow to cause motor-unit synchronization of homologous muscles of both legs, although to a lesser extent than for synergists within a leg. In the first experiment, different levels of fatigue were induced by varying posture (knee angle), whereas in the second experiment fatigue was induced in a fixed posture by instructing participants to produce different force levels. EMG coherence was found in two distinct frequency bands (6-11 and 13-18 Hz) and was higher within a leg than between legs. The fatigue-related increase of 6-11 Hz inter-limb synchronization resembled the increased motor overflow during unimanual contractions and thus hinted at an increase in bilateral coupling. Synchronization at 13-18 Hz was clearly different and appeared to be related to posture.