A novel algorithm to remove electrical cross-talk between surface EMG recordings and its application to the measurement of short-term synchronisation in humans

Nonlinear spatio-temporal filter to reduce crosstalk in bipolar electromyogram

Objective.The wide detection volume of surface electromyogram (EMG) makes it prone to crosstalk, i.e. the signal from other muscles than the target one. Removing this perturbation from bipolar recordings is an important open problem for many applications.Approach.An innovative nonlinear spatio-temporal filter is developed to estimate the EMG generated by the target muscle by processing noisy signals from two bipolar channels, placed over the target and the crosstalk muscle, respectively. The filter is trained on some calibration data and then can be applied on new signals. Tests are provided in simulations (considering different thicknesses of the subcutaneous tissue, inter-electrode distances, locations of the EMG channels, force levels) and experiments (from pronator teres and flexor carpi radialis of 8 healthy subjects).Main results.The proposed filter allows to reduce the effect of crosstalk in all investigated conditions, with a statistically significant reduction of its root mean squared of about 20%, both in simulated and experimental data. Its performances are also superior to those of a blind source separation method applied to the same data.Significance.The proposed filter is simple to be applied and feasible in applications in which single bipolar channels are placed over the muscles of interest. It can be useful in many fields, such as in gait analysis, tests of myoelectric fatigue, rehabilitation with EMG biofeedback, clinical studies, prosthesis control.

Crosstalk in Facial EMG and Its Reduction Using ICA

There is ample evidence that electromyography (EMG) signals from the corrugator supercilii and zygomatic major muscles can provide valuable information for the assessment of subjective emotional experiences. Although previous research suggested that facial EMG data could be affected by crosstalk from adjacent facial muscles, it remains unproven whether such crosstalk occurs and, if so, how it can be reduced. To investigate this, we instructed participants (n = 29) to perform the facial actions of frowning, smiling, chewing, and speaking, in isolation and combination. During these actions, we measured facial EMG signals from the corrugator supercilii, zygomatic major, masseter, and suprahyoid muscles. We performed an independent component analysis (ICA) of the EMG data and removed crosstalk components. Speaking and chewing induced EMG activity in the masseter and suprahyoid muscles, as well as the zygomatic major muscle. The ICA-reconstructed EMG signals reduced the effects of speaking and chewing on zygomatic major activity, compared with the original signals. These data suggest that: (1) mouth actions could induce crosstalk in zygomatic major EMG signals, and (2) ICA can reduce the effects of such crosstalk.

Coherence between electromyographic signals of anterior tibialis, soleus, and gastrocnemius during standing balance tasks

Introduction

Knowledge about the mechanics and physiological features of balance for healthy individuals enhances understanding of impairments of balance related to neuropathology secondary to aging, diseases of the central nervous system (CNS), and traumatic brain injury, such as concussion.

Methods

We examined the neural correlations during muscle activation related to quiet standing from the intermuscular coherence in different neural frequency bands. Electromyography (EMG) signals were recorded from six healthy participants (fs = 1,200 Hz for 30 s) from three different muscles bilaterally: anterior tibialis, medial gastrocnemius, and soleus. Data were collected for four different postural stability conditions. In decreasing order of stability these were feet together eyes open, feet together eyes closed, tandem eyes open, and tandem eyes closed. Wavelet decomposition was used to extract the neural frequency bands: gamma, beta, alpha, theta, and delta. Magnitude-squared-coherence (MSC) was computed between different muscle pairs for each of the stability conditions.

Results and discussion

There was greater coherence between muscle pairs in the same leg. Coherence was greater in lower frequency bands. For all frequency bands, the standard deviation of coherence between different muscle pairs was always higher in the less stable positions. Time-frequency coherence spectrograms also showed higher intermuscular coherence for muscle pairs in the same leg and in less stable positions. Our data suggest that coherence between EMG signals may be used as an independent indicator of the neural correlates for stability.

A Review of EMG-, FMG-, and EIT-Based Biosensors and Relevant Human–Machine Interactivities and Biomedical Applications

Wearables developed for human body signal detection receive increasing attention in the current decade. Compared to implantable sensors, wearables are more focused on body motion detection, which can support human–machine interaction (HMI) and biomedical applications. In wearables, electromyography (EMG)-, force myography (FMG)-, and electrical impedance tomography (EIT)-based body information monitoring technologies are broadly presented. In the literature, all of them have been adopted for many similar application scenarios, which easily confuses researchers when they start to explore the area. Hence, in this article, we review the three technologies in detail, from basics including working principles, device architectures, interpretation algorithms, application examples, merits and drawbacks, to state-of-the-art works, challenges remaining to be solved and the outlook of the field. We believe the content in this paper could help readers create a whole image of designing and applying the three technologies in relevant scenarios.

Prediction of knee trajectory based on surface electromyogram with independent component analysis combined with support vector regression

In recent years, surface electromyogram signals have been increasingly used to operate wearable devices. These devices can aid to help workers or soldiers to lower the load in the task to boost efficiency. However, achieving effective signal prediction has always been a challenge. It is critical to use an appropriate signal preprocessing method and prediction algorithm when developing a controller that can accurately predict and control human movements in real time. For this purpose, this article investigates the effect of various surface electromyogram preprocessing methods and algorithms on prediction results. Walking data (surface electromyogram angle) were collected from 10 adults (5 males and 5 females). To investigate the effect of preprocessing methods on the experimental results, the raw surface electromyogram signals were grouped and subjected to different preprocessing (bandpass/principal component analysis/independent component analysis, respectively). The processed data were then imported into the random forest and support vector regression algorithm for training and prediction. Multiple scenarios were combined to compare the results. The independent component analysis-processed data had the best performance in terms of convergence time and prediction accuracy in the support vector regression algorithm. The prediction accuracy of knee motion with this scheme was 94.54% ± 2.98. Notably, the forecast time was halved in comparison to the other combinations. The independent component analysis algorithm’s “blind source separation” feature effectively separates the original surface electromyogram signal and reduces signal noise, hence increasing prediction efficiency. The main contribution of this work is that the method (independent component analysis + support vector regression) has the potency of best prediction of surface electromyogram signal for knee movement. This work is the first step toward myoelectric control of assisted exoskeleton robots through discrete decoding.

Surface EMG cross talk quantified at the motor unit population level for muscles of the hand, thigh, and calf

Cross talk is an important source of error in interpreting surface electromyography (EMG) signals. Here, we aimed at characterizing cross talk for three groups of synergistic muscles by the identification of individual motor unit action potentials. Moreover, we explored whether spatial filtering (single and double differential) of the EMG signals influences the level of cross talk. Three experiments were conducted. Participants (total 25) performed isometric contractions at 10% of the maximal voluntary contraction (MVC) with digit muscles and knee extensors and at 30% MVC with plantar flexors. High-density surface EMG signals were recorded and decomposed into motor unit spike trains. For each muscle, we quantified the cross talk induced to neighboring muscles and the level of contamination by the nearby muscle activity. We also estimated the influence of cross talk on the EMG power spectrum and intermuscular correlation. Most motor units (80%) generated significant cross-talk signals to neighboring muscle EMG in monopolar recording mode, but this proportion decreased with spatial filtering (50% and 42% for single and double differential, respectively). Cross talk induced overestimations of intermuscular correlation and has a small effect on the EMG power spectrum, which indicates that cross talk is not reduced with high-pass temporal filtering. Conversely, spatial filtering reduced the cross-talk magnitude and the overestimations of intermuscular correlation, confirming to be an effective and simple technique to reduce cross talk. This paper presents a new method for the identification and quantification of cross talk at the motor unit level and clarifies the influence of cross talk on EMG interpretation for muscles with different anatomy.NEW & NOTEWORTHY We proposed a new method for the identification and quantification of cross talk at the motor unit level. We show that surface EMG cross talk can lead to physiological misinterpretations of EMG signals such as overestimations in the muscle activity and intermuscular correlation. Cross talk had little influence on the EMG power spectrum, which indicates that conventional temporal filtering cannot minimize cross talk. Spatial filter (single and double differential) effectively reduces but not abolish cross talk.

Distinct sensorimotor feedback loops for dynamic and static control of primate precision grip

Volitional limb motor control involves dynamic and static muscle actions. It remains elusive how such distinct actions are controlled through separated or shared neural circuits. Here we explored the potential separation for dynamic and static controls in primate hand actions, by investigating the neuronal coherence between local field potentials (LFPs) of the spinal cord and the forelimb electromyographic activity (EMGs), and LFPs of the motor cortex and the EMGs during the performance of a precision grip in macaque monkeys. We observed the emergence of beta-range coherence with EMGs at spinal cord and motor cortex in the separated phases; spinal coherence during the grip phase and cortical coherence during the hold phase. Further, both of the coherences were influenced by bidirectional interactions with reasonable latencies as beta oscillatory cycles. These results indicate that dedicated feedback circuits comprising spinal and cortical structures underlie dynamic and static controls of dexterous hand actions.

Does the cerebellum shape the spatiotemporal organization of muscle patterns? Insights from subjects with cerebellar ataxias

The role of the cerebellum in motor control has been investigated extensively, but its contribution to the muscle pattern organization underlying goal-directed movements is still not fully understood. Muscle synergies may be used to characterize multimuscle pattern organization irrespective of time (spatial synergies), in time irrespective of the muscles (temporal synergies), and both across muscles and in time (spatiotemporal synergies). The decomposition of muscle patterns as combinations of different types of muscle synergies offers the possibility to identify specific changes due to neurological lesions. In this study, we recorded electromyographic activity from 13 shoulder and arm muscles in subjects with cerebellar ataxias (CA) and in age-matched healthy subjects (HS) while they performed reaching movements in multiple directions. We assessed whether cerebellar damage affects the organization of muscle patterns by extracting different types of muscle synergies from the muscle patterns of each HS and using these synergies to reconstruct the muscle patterns of all other participants. We found that CA muscle patterns could be accurately captured only by spatial muscle synergies of HS. In contrast, there were significant differences in the reconstruction R² values for both spatiotemporal and temporal synergies, with an interaction between the two synergy types indicating a larger difference for spatiotemporal synergies. Moreover, the reconstruction quality using spatiotemporal synergies correlated with the severity of impairment. These results indicate that cerebellar damage affects the temporal and spatiotemporal organization, but not the spatial organization, of the muscle patterns, suggesting that the cerebellum plays a key role in shaping their spatiotemporal organization.NEW & NOTEWORTHY In recent studies, the decomposition of muscle activity patterns has revealed a modular organization of the motor commands. We show, for the first time, that muscle patterns of subjects with cerebellar damage share with healthy controls spatial, but not temporal and spatiotemporal, modules. Moreover, changes in spatiotemporal organization characterize the severity of the subject's impairment. These results suggest that the cerebellum has a specific role in shaping the spatiotemporal organization of the muscle patterns.

Decoding of muscle activity from the sensorimotor cortex in freely behaving monkeys

Remarkable advances have recently been made in the development of Brain-Machine Interface (BMI) technologies for restoring or enhancing motor function. However, the application of these technologies may be limited to patients in static conditions, as these developments have been largely based on studies of animals (e.g., non-human primates) in constrained movement conditions. The ultimate goal of BMI technology is to enable individuals to move their bodies naturally or control external devices without physical constraints. Here, we demonstrate accurate decoding of muscle activity from electrocorticogram (ECoG) signals in unrestrained, freely behaving monkeys. We recorded ECoG signals from the sensorimotor cortex as well as electromyogram signals from multiple muscles in the upper arm while monkeys performed two types of movements with no physical restraints, as follows: forced forelimb movement (lever-pull task) and natural whole-body movement (free movement within the cage). As in previous reports using restrained monkeys, we confirmed that muscle activity during forced forelimb movement was accurately predicted from simultaneously recorded ECoG data. More importantly, we demonstrated that accurate prediction of muscle activity from ECoG data was possible in monkeys performing natural whole-body movement. We found that high-gamma activity in the primary motor cortex primarily contributed to the prediction of muscle activity during natural whole-body movement as well as forced forelimb movement. In contrast, the contribution of high-gamma activity in the premotor and primary somatosensory cortices was significantly larger during natural whole-body movement. Thus, activity in a larger area of the sensorimotor cortex was needed to predict muscle activity during natural whole-body movement. Furthermore, decoding models obtained from forced forelimb movement could not be generalized to natural whole-body movement, which suggests that decoders should be built individually and according to different behavior types. These results contribute to the future application of BMI systems in unrestrained individuals.

A review on crosstalk in myographic signals

PURPOSE

Crosstalk in myographic signals is a major hindrance to the understanding of local information related to individual muscle function. This review aims to analyse the problem of crosstalk in electromyography and mechanomyography.

METHODS

An initial search of the SCOPUS database using an appropriate set of keywords yielded 290 studies, and 59 potential studies were selected after all the records were screened using the eligibility criteria. This review on crosstalk revealed that signal contamination due to crosstalk remains a major challenge in the application of surface myography techniques. Various methods have been employed in previous studies to identify, quantify and reduce crosstalk in surface myographic signals.

RESULTS

Although correlation-based methods for crosstalk quantification are easy to use, there is a possibility that co-contraction could be interpreted as crosstalk. High-definition EMG has emerged as a new technique that has been successfully applied to reduce crosstalk.

CONCLUSIONS

The phenomenon of crosstalk needs to be investigated carefully because it depends on many factors related to muscle task and physiology. This review article not only provides a good summary of the literature on crosstalk in myographic signals but also discusses new directions related to techniques for crosstalk identification, quantification and reduction. The review also provides insights into muscle-related issues that impact crosstalk in myographic signals.

Specificity of surface EMG recordings for gastrocnemius during upright standing

The relatively large pick-up volume of surface electrodes has for long motivated the concern that muscles other than that of interest may contribute to surface electromyograms (EMGs). Recent findings suggest however the pick-up volume of surface electrodes may be smaller than previously appreciated, possibly leading to the detection of surface EMGs insensitive to muscle activity. Here we combined surface and intramuscular recordings to investigate how comparably action potentials from gastrocnemius and soleus are represented in surface EMGs detected with different inter-electrode distances. We computed the firing instants of motor units identified from intramuscular EMGs detected from gastrocnemius and soleus while five participants stood upright. We used these instants to trigger and average surface EMGs detected from multiple skin regions along gastrocnemius. Results from 66 motor units (whereof 31 from gastrocnemius) revealed the surface-recorded amplitude of soleus action potentials was 6% of that of gastrocnemius and did not decrease for inter-electrode distances smaller than 4 cm. Gastrocnemius action potentials were more likely detected for greater inter-electrode distances and their amplitude increased steeply up to 5 cm inter-electrode distance. These results suggest that reducing inter-electrode distance excessively may result in the detection of surface EMGs insensitive to gastrocnemius activity without substantial attenuation of soleus crosstalk.

Neural basis for hand muscle synergies in the primate spinal cord

Grasping is a highly complex movement that requires the coordination of multiple hand joints and muscles. Muscle synergies have been proposed to be the functional building blocks that coordinate such complex motor behaviors, but little is known about how they are implemented in the central nervous system. Here we demonstrate that premotor interneurons (PreM-INs) in the primate cervical spinal cord underlie the spatiotemporal patterns of hand muscle synergies during a voluntary grasping task. Using spike-triggered averaging of hand muscle activity, we found that the muscle fields of PreM-INs were not uniformly distributed across hand muscles but rather distributed as clusters corresponding to muscle synergies. Moreover, although individual PreM-INs have divergent activation patterns, the population activity of PreM-INs reflects the temporal activation of muscle synergies. These findings demonstrate that spinal PreM-INs underlie the muscle coordination required for voluntary hand movements in primates. Given the evolution of neural control of primate hand functions, we suggest that spinal premotor circuits provide the fundamental coordination of multiple joints and muscles upon which more fractionated control is achieved by superimposed, phylogenetically newer, pathways.

Magnitude and behavior of cross-talk effects in multichannel electrophysiology experiments

Modern neurophysiological experiments frequently involve multiple channels separated by very small distances. A unique methodological concern for multiple-electrode experiments is that of capacitive coupling (cross-talk) between channels. Yet the nature of the cross-talk recording circuit is not well known in the field, and the extent to which it practically affects neurophysiology experiments has never been fully investigated. Here we describe a simple electrical circuit model of simultaneous recording and stimulation with two or more channels and experimentally verify the model using ex vivo brain slice and in vivo whole-brain preparations. In agreement with the model, we find that cross-talk amplitudes increase nearly linearly with the impedance of a recording electrode and are larger for higher frequencies. We demonstrate cross-talk contamination of action potential waveforms from intracellular to extracellular channels, which is observable in part because of the different orders of magnitude between the channels. This contamination is electrode impedance-dependent and matches predictions from the model. We use recently published parameters to simulate cross-talk in high-density multichannel extracellular recordings. Cross-talk effectively spatially smooths current source density (CSD) estimates in these recordings and induces artefactual phase shifts where underlying voltage gradients occur; however, these effects are modest. We show that the effects of cross-talk are unlikely to affect most conclusions inferred from neurophysiology experiments when both originating and receiving electrode record signals of similar magnitudes. We discuss other types of experiments and analyses that may be susceptible to cross-talk, techniques for detecting and experimentally reducing cross-talk, and implications for high-density probe design.NEW & NOTEWORTHY We develop and experimentally verify an electrical circuit model describing cross-talk that necessarily occurs between two channels. Recorded cross-talk increased with electrode impedance and signal frequency. We recorded cross-talk contamination of spike waveforms from intracellular to extracellular channels. We simulated high-density multichannel extracellular recordings and demonstrate spatial smoothing and phase shifts that cross-talk enacts on CSD measurements. However, when channels record similar-magnitude signals, effects are modest and unlikely to affect most conclusions.

Musculoskeletal model-based control interface mimics physiologic hand dynamics during path tracing task

OBJECTIVE

We investigated the feasibility of a novel, customizable, simplified EMG-driven musculoskeletal model for estimating coordinated hand and wrist motions during a real-time path tracing task.

APPROACH

A two-degree-of-freedom computational musculoskeletal model was implemented for real-time EMG-driven control of a stick figure hand displayed on a computer screen. After 5-10 minutes of undirected practice, subjects were given three attempts to trace 10 straight paths, one at a time, with the fingertip of the virtual hand. Able-bodied subjects completed the task on two separate test days.

MAIN RESULTS

Across subjects and test days, there was a significant linear relationship between log-transformed measures of accuracy and speed (Pearson's r  =  0.25, p  <  0.0001). The amputee subject could coordinate movement between the wrist and MCP joints, but favored metacarpophalangeal joint motion more highly than able-bodied subjects in 8 of 10 trials. For able-bodied subjects, tracing accuracy was lower at the extremes of the model's range of motion, though there was no apparent relationship between tracing accuracy and fingertip location for the amputee. Our result suggests that, unlike able-bodied subjects, the amputee's motor control patterns were not accustomed to the multi-joint dynamics of the wrist and hand, possibly as a result of post-amputation cortical plasticity, disuse, or sensory deficits.

SIGNIFICANCE

To our knowledge, our study is one of very few that have demonstrated the real-time simultaneous control of multi-joint movements, especially wrist and finger movements, using an EMG-driven musculoskeletal model, which differs from the many data-driven algorithms that dominate the literature on EMG-driven prosthesis control. Real-time control was achieved with very little training and simple, quick (~15 s) calibration. Thus, our model is potentially a practical and effective control platform for multifunctional myoelectric prostheses that could restore more life-like hand function for individuals with upper limb amputation.

High-Frequency Intermuscular Coherence between Arm Muscles during Robot-Mediated Motor Adaptation

Adaptation of arm reaching in a novel force field involves co-contraction of upper limb muscles, but it is not known how the co-ordination of multiple muscle activation is orchestrated. We have used intermuscular coherence (IMC) to test whether a coherent intermuscular coupling between muscle pairs is responsible for novel patterns of activation during adaptation of reaching in a force field. Subjects (N = 16) performed reaching trials during a null force field, then during a velocity-dependent force field and then again during a null force field. Reaching trajectory error increased during early adaptation to the force-field and subsequently decreased during later adaptation. Co-contraction in the majority of all possible muscle pairs also increased during early adaptation and decreased during later adaptation. In contrast, IMC increased during later adaptation and only in a subset of muscle pairs. IMC consistently occurred in frequencies between ~40–100 Hz and during the period of arm movement, suggesting that a coherent intermuscular coupling between those muscles contributing to adaptation enable a reduction in wasteful co-contraction and energetic cost during reaching.

Plastic Changes in Human Motor Cortical Output Induced by Random but not Closed-Loop Peripheral Stimulation: the Curse of Causality

Previous work showed that repetitive peripheral nerve stimulation can induce plastic changes in motor cortical output. Triggering electrical stimulation of central structures from natural activity can also generate plasticity. In this study, we tested whether triggering peripheral nerve stimulation from muscle activity would likewise induce changes in motor output. We developed a wearable electronic device capable of recording electromyogram (EMG) and delivering electrical stimulation under closed-loop control. This allowed paired stimuli to be delivered over longer periods than standard laboratory-based protocols. We tested this device in healthy human volunteers. Motor cortical output in relaxed thenar muscles was first assessed via the recruitment curve of responses to contralateral transcranial magnetic stimulation. The wearable device was then configured to record thenar EMG and stimulate the median nerve at the wrist (intensity around motor threshold, rate ~0.66 Hz). Subjects carried out normal daily activities for 4-7 h, before returning to the laboratory for repeated recruitment curve assessment. Four stimulation protocols were tested (9-14 subjects each): No Stim, no stimuli delivered; Activity, stimuli triggered by EMG activity above threshold; Saved, stimuli timed according to a previous Activity session in the same subject; Rest, stimuli given when EMG was silent. As expected, No Stim did not modify the recruitment curve. Activity and Rest conditions produced no significant effects across subjects, although there were changes in some individuals. Saved produced a significant and substantial increase, with average responses 2.14 times larger at 30% stimulator intensity above threshold. We argue that unavoidable delays in the closed loop feedback, due mainly to central and peripheral conduction times, mean that stimuli in the Activity paradigm arrived too late after cortical activation to generate consistent plastic changes. By contrast, stimuli delivered essentially at random during the Saved paradigm may have caused a generalized increase in cortical excitability akin to stochastic resonance, leading to plastic changes in corticospinal output. Our study demonstrates that non-invasive closed loop stimulation may be critically limited by conduction delays and the unavoidable constraint of causality.

A survey of sensor devices: use in sports biomechanics

This paper examines the use of sensor devices in sports biomechanics, focusing on current frequency of use of Electromyography (EMG) device preferences. Researchers in the International Society of Biomechanics in Sports were invited to participate in an online survey. Responses on multiple sensor devices highlighting frequency of use, device features and improvements researchers sought in acquisition and analysis methods were obtained via an online questionnaire. Results of the investigation showed that the force platform is the most frequently used device, with inertial measurement units and EMG devices growing in popularity. Wireless functionality and ease of use for both the participant and the practitioner proved to be important features. The main findings of the survey demonstrated need for a simple, low power, multi-channel device which incorporates the various sensors into one single device. Biomechanists showed they were looking for more availability of wireless sensor devices with acquisition and analysis features. The study found there is a need to develop software analysis tools to accompany the multi-channel device, providing all the basic functions while maintaining compatibility with existing systems.

Awake behaving electrophysiological correlates of forelimb hyperreflexia, weakness and disrupted muscular synchronization following cervical spinal cord injury in the rat

Spinal cord injury usually occurs at the level of the cervical spine and results in profound impairment of forelimb function. In this study, we recorded awake behaving intramuscular electromyography (EMG) from the biceps and triceps muscles of the impaired forelimb during volitional and reflexive forelimb movements before and after unilateral cervical spinal cord injury (cSCI) in rats. C5/C6 hemicontusion reduced volitional forelimb strength by more than 50% despite weekly rehabilitation for one month post-injury. Triceps EMG during volitional strength assessment was reduced by more than 60% following injury, indicating reduced descending drive. Biceps EMG during reflexive withdrawal from a thermal stimulus was increased by 500% following injury, indicating flexor withdrawal hyperreflexia. The reduction in volitional forelimb strength was significantly correlated with volitional and reflexive biceps EMG activity. Our results support the hypothesis that biceps hyperreflexia and descending volitional drive both significantly contribute to forelimb strength deficits after cSCI and provide new insight into dynamic muscular dysfunction after cSCI. The use of multiple automated quantitative measures of forelimb dysfunction in the rodent cSCI model will likely aid the search for effective regenerative, pharmacological, and neuroprosthetic treatments for spinal cord injury.

Different Stimulation Frequencies Alter Synchronous Fluctuations in Motor Evoked Potential Amplitude of Intrinsic Hand Muscles-a TMS Study

The amplitude of motor-evoked potentials (MEPs) elicited with transcranial magnetic stimulation (TMS) varies from trial-to-trial. Synchronous oscillations in cortical neuronal excitability contribute to this variability, however it is not known how different frequencies of stimulation influence MEP variability, and whether these oscillations are rhythmic or aperiodic. We stimulated the motor cortex with TMS at different regular (i.e., rhythmic) rates, and compared this with pseudo-random (aperiodic) timing. In 18 subjects, TMS was applied at three regular frequencies (0.05 Hz, 0.2 Hz, 1 Hz) and one aperiodic frequency (mean 0.2 Hz). MEPs (n = 50) were recorded from three intrinsic hand muscles of the left hand with different functional and anatomical relations. MEP amplitude correlation was highest for the functionally related muscle pair, less for the anatomically related muscle pair and least for the functionally- and anatomically-unrelated muscle pair. MEP correlations were greatest with 1 Hz, and least for stimulation at 0.05 Hz. Corticospinal neuron synchrony is higher with shorter TMS intervals. Further, corticospinal neuron synchrony is similar irrespective of whether the stimulation is periodic or aperiodic. These findings suggest TMS frequency is a crucial consideration for studies using TMS to probe correlated activity between muscle pairs.

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.

Spinal premotor interneurons mediate dynamic and static motor commands for precision grip in monkeys

The extent of spinal interneuron (IN) contribution to dexterous hand movements is unclear. Here, we studied the response patterns and force relationships of spinal premotor INs (PreM-INs) in three awake, behaving monkeys performing a precision grip task. We recorded activity from the cervical spinal cord (C5-T1) simultaneously with electromyographic (EMG) activity from hand and arm muscles during the task. Spike-triggered averaging of EMGs showed that 25 PreM-INs had postspike effects on EMG activity. Most PreM-INs (23/25) displayed movement-related firing rate modulations: 11 had phasic followed by tonic facilitation (p+t+); 4 were pure phasic; 4 were pure tonic; and 4 were deactivated, while their target muscles consistently had p+t+ activity (65/66 muscles). PreM-IN phasic activity started earlier than target muscle activity (49 ± 81.4 ms, mean ± SD), and the peak amplitude was correlated with the peak amplitude of the rate of change of grip force (4/17, p < 0.05), suggesting that they contributed to force initiation. In contrast, PreM-IN tonic activity started at almost the same time as the target muscle activity and the mean firing rate was correlated with the mean grip force during the hold period (4/15, p < 0.05), suggesting that they contributed to force maintenance. These results indicated that the neural pathway mediated by the spinal PreM-INs makes a significant contribution to the control of precision grip in primates.

Synaptic and functional linkages between spinal premotor interneurons and hand-muscle activity during precision grip

Grasping is a highly complex movement that requires the coordination of a number of hand joints and muscles. Previous studies showed that spinal premotor interneurons (PreM-INs) in the primate cervical spinal cord have divergent synaptic effects on hand motoneurons and that they might contribute to hand-muscle synergies. However, the extent to which these PreM-IN synaptic connections functionally contribute to modulating hand-muscle activity is not clear. In this paper, we explored the contribution of spinal PreM-INs to hand-muscle activation by quantifying the synaptic linkage (SL) and functional linkage (FL) of the PreM-INs with hand-muscle activities. The activity of 23 PreM-INs was recorded from the cervical spinal cord (C6–T1), with EMG signals measured simultaneously from hand and arm muscles in two macaque monkeys performing a precision grip task. Spike-triggered averages (STAs) of rectified EMGs were compiled for 456 neuron–muscle pairs; 63 pairs showed significant post-spike effects (PSEs; i.e., SL). Conversely, 231 of 456 pairs showed significant cross-correlations between the IN firing rate and rectified EMG (i.e., FL). Importantly, a greater proportion of the neuron–muscle pairs with SL showed FL (43/63 pairs, 68%) compared with the pairs without SL (203/393, 52%), and the presence of SL was significantly associated with that of FL. However, a significant number of pairs had SL without FL (SL∩!FL, n = 20) or FL without SL (!SL∩FL, n = 203), and the proportions of these incongruities exceeded the number expected by chance. These results suggested that spinal PreM-INs function to significantly modulate hand-muscle activity during precision grip, but the contribution of other neural structures is also needed to recruit an adequate combination of hand-muscle motoneurons.

Variant and invariant features characterizing natural and reverse whole-body pointing movements

Previous investigations showed that kinematics and muscle activity associated with natural whole-body movements along the gravity direction present modular organizations encoding specific aspects relative to both the motor plans and the motor programmes underlying movement execution. It is, however, still unknown whether such modular structures characterize also the reverse movements, when the displacement of a large number of joints is required to take the whole body back to a standing initial posture. To study what motor patterns are conserved across the reversal of movement direction, principal component analysis and non-negative matrix factorization were therefore applied, respectively, to the time series describing the temporal evolution of the elevation angles associated with all the body links and to the electromyographic signals of both natural and reverse whole-body movements. Results revealed that elevation angles were highly co-varying in time and that despite some differences in the global parameters characterizing the different movements (indicating differences in high-level variable associated with the selected motor plans), the level of joint co-variation did not change across movement direction. In contrast, muscle organization of the forward whole-body pointing tasks was found to be different with respect to that characterizing the reverse movements. Such results agree with previous findings, according to which the central nervous system exploits, dependently on the direction of motion, different motor plans for the execution of whole-body movements. However, in addition, this study shows how such motor plans are translated into different muscle strategies that equivalently assure a high level of co-variation in the joint space.

Superposition and modulation of muscle synergies for reaching in response to a change in target location

We have recently shown that the muscle patterns for reaching are well described by the combination of a few time-varying muscle synergies supporting the notion of a modular architecture for arm control. Here we investigated whether the muscle patterns for reaching movements involving online corrections are also generated by the combination of the same set of time-varying muscle synergies used for point-to-point movements. We recorded endpoint kinematics and EMGs from up to 16 arm muscles of 5 subjects reaching from a central location to 8 peripheral targets in the frontal plane, from each peripheral target to 1 of the 2 adjacent targets, and from the central location initially to 1 peripheral target and, after a delay of either 50, 150, or 250 ms from the go signal, to 1 of the 2 adjacent targets. Time-varying muscle synergies were extracted from the averaged, phasic, normalized EMGs of point-to-point movements and fit to the patterns of target change movements using an iterative optimization algorithm. In all subjects, three time-varying muscle synergies explained a large fraction of the data variation of point-to-point movements. The superposition and modulation of the same three synergies reconstructed the muscle patterns for target change movements better than the superposition and modulation of the corresponding point-to-point muscle patterns, appropriately aligned. While at the kinematic level the corrective trajectory for reaching during a change in target location can be obtained by the delayed superposition of the trajectory from the initial to the final target, at the muscle level the underlying phasic muscle patterns are captured by the amplitude and timing modulation of the same time-varying muscle synergies recruited for point-to-point movements. These results suggest that a common modular architecture is used for the control of unperturbed arm movement and for its visually guided online corrections.

Spinal interneurons facilitate coactivation of hand muscles during a precision grip task in monkeys

Grasping is a highly complex movement requiring coordination of a number of hand joints and muscles. In contrast to cortical descending systems, the contribution of the subcortical system for coordinating this higher degree of freedom is largely unknown. Here we explore how spinal interneurons (INs) contribute to the coordination of hand muscles by recording their activity from the cervical spinal cord (C5-T1) simultaneously with electromyographic (EMG) activity from hand and arm muscles in three monkeys performing a precision grip task. Spike-triggered averages of the rectified EMGs were compiled for 255 neurons (4821 neuron-muscle pairs). Twenty-six neurons produced 68 significant postspike effects in hand and arm muscles and were identified as premotor interneurons (PreM-INs), which presumably have relatively direct synaptic effects on spinal motoneurons. The majority of the PreM-INs (22/26 neurons) produced postspike effects in finger muscles (intrinsic and extrinsic hand muscles) compared with wrist (9/26 neurons) and elbow muscles (1/26 neurons). The effects in finger muscles were mostly facilitative [postspike facilitations (PSFs), 19/22 neurons], and few had suppressive effects (postspike suppressions, 3/22 neurons). Moreover, PreM-INs produced more divergent PSFs in intrinsic hand muscles (2.5 ± 1.9 muscles/neuron) than in wrist muscles (1.2 ± 0.4 muscles/neurons). We conclude that spinal PreM-INs produce divergent facilitations preferentially in intrinsic hand muscles. These results suggest that spinal interneurons contribute to the control of hand grasping in primates by combining and coordinating multiple finger muscles.

Corticomuscular coherence between motor cortex, somatosensory areas and forearm muscles in the monkey

Corticomuscular coherence has previously been reported between primary motor cortex (M1) and contralateral muscles. We examined whether such coherence could also be seen from somatosensory areas. Local field potentials (LFPs) were recorded from primary somatosensory cortex (S1; areas 3a and 2) and posterior parietal cortex (PPC; area 5) simultaneously with M1 LFP and forearm EMG activity in two monkeys during an index finger flexion task. Significant beta-band ( approximately 20 Hz) corticomuscular coherence was found in all areas investigated. Directed coherence (Granger causality) analysis was used to investigate the direction of effects. Surprisingly, the strongest beta-band directed coherence was in the direction from S1/PPC to muscle; it was much weaker in the ascending direction. Examination of the phase of directed coherence provided estimates of the time delay from cortex to muscle. Delays were longer from M1 ( approximately 62 ms for the first dorsal interosseous muscle) than from S1/PPC ( approximately 36 ms). We then looked at coherence and directed coherence between M1 and S1 for clues to this discrepancy. Directed coherence showed large beta-band effects from S1/PPC to M1, with smaller directed coherence in the reverse direction. The directed coherence phase suggested a delay of approximately 40 ms from M1 to S1. Corticomuscular coherence from S1/PPC could involve multiple pathways; the most important is probably common input from M1 to S1/PPC and muscles. If correct, this implies that somatosensory cortex receives oscillatory efference copy information from M1 about the motor command. This could allow sensory inflow to be interpreted in the light of its motor context.

An examination of cross-talk among surface mechanomyographic signals from the superficial quadriceps femoris muscles during isometric muscle actions

The purpose of this study was to examine cross-talk among the mechanomyographic (MMG) signals from the superficial quadriceps femoris muscles during submaximal to maximal isometric muscle actions of the leg extensors. Eleven healthy men (age=20.1+/-1.1yr, mean+/-SD) volunteered to randomly perform isometric muscle actions in 10% increments from 10% to 90% of the maximum voluntary contraction (MVC). During each muscle action, MMG signals were detected from the vastus lateralis, rectus femoris, and vastus medialis with three separate accelerometers. Cross-correlation was used to quantify cross-talk among the vastus lateralis, rectus femoris, and vastus medialis during each muscle action. The results showed cross-correlation coefficients that ranged from R(x,y)=.124-.714, but generally speaking, the coefficients were between .1 and .3. In addition, there were no consistent differences among the cross-talk levels for the three muscles, and the cross-correlation coefficients generally did not increase with isometric torque. Thus, MMG can be used to examine muscle function from each of the superficial quadriceps femoris muscles during isometric muscle actions.

A method to estimate EMG crosstalk between two muscles based on the silent period following an H-reflex

The crosstalk phenomenon consists in recording the volume-conducted electromyographic activity of muscles other than that under study. This interference may impair the correct interpretation of the results in a variety of experiments. A new protocol is presented here for crosstalk assessment between two muscles based on changes in their electrical activity following a reflex discharge in one of the muscles in response to nerve stimulation. A reflex compound muscle action potential (H-reflex) was used to induce a silent period in the muscle that causes the crosstalk, called here the remote muscle. The rationale is that if the activity recorded in the target muscle is influenced by a distant source (the remote muscle) a silent period observed in the electromyogram (EMG) of the remote muscle would coincide with a decrease in the EMG activity of the target muscle. The new crosstalk index is evaluated based on the root mean square (RMS) values of the EMGs obtained in two distinct periods (background EMG and silent period) of both the remote and the target muscles. In the present work the application focused on the estimation of the degree of crosstalk from the soleus muscle to the tibialis anterior muscle during quiet stance. However, the technique may be extended to other pairs of muscles provided a silent period may be evoked in one of them.

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.

Computed myography (CMG): three dimensional reconstruction of motor functions from surface EMG data

We describe a methodology to qualitatively and quantitatively determine the activation level of individual muscles by voltage measurements from an array of voltage sensors on the skin surface. A physical finite element model for electrostatics simulation is constructed from morphometric data and numerical inversion techniques are used to determine muscle activation patterns. Preliminary results from experiments with simulated and human data are presented for activation reconstructions of three muscles in the upper arm (biceps brachii, bracialis, and triceps). This approach potentially offers a new clinical tool to sensitively assess muscle function in patients suffering from neurological disorders (e.g., spinal cord injury) and could more accurately guide advances in the evaluation of specific rehabilitation training regimens.

Multichannel SEMG in clinical gait analysis: a review and state-of-the-art

BACKGROUND

Application of surface electromyography (SEMG) to the clinical evaluation of neuromuscular disorders can provide relevant "diagnostic" contributions in terms of nosological classification, localization of focal impairments, detection of pathophysiological mechanisms, and functional assessment.

METHODS

The present review article elaborates on: (i) the technical aspects of the myoelectric signals acquisition within a protocol of clinical gait analysis (multichannel recording, surface vs. deep probes, electrode placing, encumbrance effects), (ii) the sequence of procedures for the subsequent data processing (filtering, averaging, normalization, repeatability control), and (iii) a set of feasible strategies for the final extraction of clinically useful information.

FINDINGS

Relevant examples of SEMG application to functional diagnosis are provided.

INTERPRETATION

Emphasis is given to the key role of SEMG along with kinematic and kinetic analysis, for non-invasive assessment of relevant pathophysiological mechanisms potentially hindering the gait function, such as changes in passive muscle-tendon properties (peripheral non-neural component), paresis, spasticity, and loss of selectivity of motor output in functionally antagonist muscles.

Correlations between groups of premotor neurons carry information about prehension

How distinct parameters are bound together in brain activity is unknown. Combination coding by interneuronal interactions is one possibility, but, to coordinate parameters, interactions between neuronal pairs must carry information about them. To address this issue, we recorded neural activity from multiple sites in the premotor cortices of monkeys that memorized reach direction and grasp type followed by actual prehension. We found that correlations between individual spiking neurons are generally weak and carry little information about prehension. In contrast, correlations and synchronous interactions between small groups of neurons, quantified by multiunit activity (MUA), are an order of magnitude stronger. A substantial fraction of the information carried by pairwise interactions between MUAs is about combinations of reach and grasp. This contrasts with the information carried by individual neurons and individual MUAs, which is mainly about reach and/or grasp but much less about their combinations. The main contribution of pairwise interactions to the coding of reach-grasp combinations is when animals memorize prehension parameters, consistent with an internal composite representation. The informative interactions between neuronal groups may facilitate the coordination of reach and grasp into coherent prehension.

Can myometrial electrical activity identify patients in preterm labor?

OBJECTIVE

The objective of the study was to determine whether myometrial electrical activity can differentiate false from true preterm labor.

STUDY DESIGN

Electrical uterine myography (EUM) was measured prospectively on 87 women, gestational age less than 35 weeks. The period between contractions, power of contraction peaks and movement of center of electrical activity (RMS), was used to develop an index score (1-5) for prediction of preterm delivery (PTD) within 14 days of the test. The score was compared with fetal fibronectin (fFN) and cervical length (CL).

RESULTS

Patients delivering within 14 days from testing showed a higher index and mean RMS (P = .000). No patients with EUM index scores of 1-2 delivered in this time frame. Combining EUM with CL or fFN increased predictability. Logistic regression revealed that history of PTD and EUM index had 4- to 5-fold increased risk for PTD. Gestational age at testing, body mass index, fFN, and CL were nonsignificant contributors to PTD risk.

CONCLUSION

Measuring myometrial electrical activity may enhance identification of patients in true premature labor.

Modulation of Phasic and Tonic Muscle Synergies With Reaching Direction and Speed

How the CNS masters the many degrees of freedom of the musculoskeletal system to control goal-directed movements is a long-standing question. We have recently provided support to the hypothesis that the CNS relies on a modular control architecture by showing that the phasic muscle patterns for fast reaching movements in different directions are generated by combinations of a few time-varying muscle synergies: coordinated recruitment of groups of muscles with specific activation profiles. However, natural reaching movements occur at different speeds and require the control of both movement and posture. Thus we have investigated whether muscle synergies also underlie reaching at different speeds as well as the maintenance of stable arm postures. Hand kinematics and shoulder and elbow muscle surface EMGs were recorded in five subjects during reaches to eight targets in the frontal plane at different speeds. We found that the amplitude modulation of three time-invariant synergies captured the variations in the postural muscle patterns at the end of the movement. During movement, three phasic and three tonic time-varying synergies could reconstruct the time-normalized muscle pattern in all conditions. Phasic synergies were modulated in both amplitude and timing by direction and speed. Tonic synergies were modulated only in amplitude by direction. The directional tuning of both types of synergies was well described by a single or a double cosine function. These results suggest that muscle synergies are basic control modules that allow generating the appropriate muscle patterns through simple modulation and combination rules.

Modulation of muscle synergy recruitment in primate grasping

In grasping, the CNS controls a particularly large number of degrees of freedom. We tested the idea that this control is facilitated by the presence of muscle synergies. According to the strong version of this concept, these synergies are invariant, hard-wired patterns of activation across muscles. Synergies may serve as modules that linearly sum, each with specific amplitude and timing coefficients, to generate a large array of muscle patterns. We tested two predictions of the synergy model. A small number of synergies should (1) account for a large fraction of variation in muscle activity, and (2) be modulated in their recruitment by task variables, even in novel behavioral contexts. We also examined whether the synergies would (3) have broadly similar structures across animals. We recorded from 15 to 19 electrodes implanted in forelimb muscles of two rhesus macaques as they grasped and transported 25 objects of variable shape and size. We show that three synergies accounted for 81% of the electromyographic data variation in each monkey. Each synergy was modulated in its recruitment strength and/or timing by object shape and/or size. Even when synergies were extracted from a small subset of object shape and size conditions and then used to reconstruct the entire dataset, we observed highly similar synergies and patterns of modulation. The synergies were well conserved between monkeys, with two of the synergies exceeding chance structural similarity, and the third being recruited, in both animals, in proportion to the size of the object handled.

Bilateral representation in the deep cerebellar nuclei

The cerebellum is normally assumed to represent ipsilateral movements. We tested this by making microelectrode penetrations into the deep cerebellar nuclei (mainly nucleus interpositus) of monkeys trained to perform a reach and grasp task with either hand. Following weak single electrical stimuli, many sites produced clear bilateral facilitation of multiple forelimb muscles. The short onset latencies, which were similar for each side, suggested that at least some of the muscle responses were mediated by descending tracts originating in the brainstem, rather than via the cerebral cortex. Additionally, cerebellar neurones modulated their discharge with both ipsilateral and contralateral movements. This was so, even when we carefully excluded contralateral trials with evidence of electromyogram modulation on the ipsilateral side. We conclude that the deep cerebellar nuclei have a bilateral movement representation, and relatively direct, powerful access to limb muscles on both sides of the body. This places the cerebellum in an ideal position to coordinate bilateral movements.

Muscle responses to transcranial stimulation in man depend on background oscillatory activity

Muscle responses to transcranial stimulation show high sweep-to-sweep variability, which may reflect an underlying noise process in the motor system. We examined whether response amplitude correlated with the level of prestimulus background EMG, and network oscillations. Transcranial magnetic or electrical stimulation was delivered to primary motor cortex whilst human subjects performed a precision grip task known to promote beta-band ( approximately 20 Hz) cortical oscillations. Responses were recorded from two intrinsic hand muscles. Response magnitude correlated significantly with the level of background EMG (mean r(2) = 0.20). Using a novel wavelet method, we quantified the amplitude and phase of oscillations in prestimulus sensorimotor EEG. Surprisingly, response magnitude showed no significant correlation with EEG oscillations at any frequency. However, oscillations in the prestimulus EMG were significantly correlated with response size; the correlation coefficient had peaks around 20 Hz. When oscillations in one muscle were used to predict response amplitude in a different muscle, correlations were substantially smaller. Finally, for each recording, we calculated the best possible prediction of response size obtainable from up to 20 measures of prestimulus EEG and EMG oscillations. Such optimal predictions had low correlation coefficients (mean r(2) = 0.2; 76% were below 0.3). We conclude that prestimulus oscillations, mainly in the beta-band, do explain some of the variability in responses to transcranial stimulation. Oscillations may likewise increase the noise of natural motor processing, explaining why this form of network activity is usually suppressed prior to dynamic movements. However, the majority of the variation is determined by other factors, which are not accessible by noninvasive recordings.

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

The purpose of the study was to evaluate the use of cross-correlation analysis between simulated surface electromyograms (EMGs) of two muscles to quantify motor unit synchronization. The volume conductor simulated a cylindrical limb with two muscles and bone, fat, and skin tissues. Models of two motor neuron pools were used to simulate 120 s of surface EMG that were detected over both muscles. Short-term synchrony was established using a phenomenological model that aligned the discharge times of selected motor units within and across muscles to simulate physiological levels of motor unit synchrony. The correlation between pairs of surface EMGs was estimated as the maximum of the normalized cross-correlation function. After imposing four levels of motor unit synchrony across muscles, five parameters were varied concurrently in the two muscles to examine their influence on the correlation between the surface EMGs: 1) excitation level (5, 10, 15, and 50% of maximum); 2) muscle size (350 and 500 motor units); 3) fat thickness (1 and 4 mm); 4) skin conductivity (0.1 and 1 S/m); and 5) mean motor unit conduction velocity (2.5 and 4 m/s). Despite a constant and high level of motor unit synchronization among pairs of motor units across the two muscles, the cross-correlation index ranged from 0.08 to 0.56, with variation in the five parameters. For example, cross-correlation of EMGs from pairs of hand muscles, each having thin layers of subcutaneous fat and mean motor unit conduction velocities of 4 m/s, may be relatively insensitive to the level of synchronization across muscles. In contrast, cross-correlation of EMGs from pairs of leg muscles, with larger fat thickness, may exhibit a different sensitivity. These results indicate that cross correlation of the surface EMGs from two muscles provides a limited measure of the level of synchronization between motor units in the two muscles.

Manipulation of peripheral neural feedback loops alters human corticomuscular coherence

Sensorimotor EEG shows approximately 20 Hz coherence with contralateral EMG. This could involve efferent and/or afferent components of the sensorimotor loop. We investigated the pathways responsible for coherence genesis by manipulating nervous conduction delays using cooling. Coherence between left sensorimotor EEG and right EMG from three hand and two forearm muscles was assessed in healthy subjects during the hold phase of a precision grip task. The right arm was then cooled to 10 degrees C for approximately 90 min, increasing peripheral motor conduction time (PMCT) by approximately 35% (assessed by F-wave latency). EEG and EMG recordings were repeated, and coherence recalculated. Control recordings revealed a heterogeneous subject population. In 6/15 subjects (Group A), the corticomuscular coherence phase increased linearly with frequency, as expected if oscillations were propagated along efferent pathways from cortex to muscle. The mean corticomuscular conduction delay for intrinsic hand muscles calculated from the phase-frequency regression slope was 10.4 ms; this is smaller than the delay expected for conduction over fast corticospinal pathways. In 8/15 subjects (Group B), the phase showed no dependence with frequency. One subject showed both Group A and Group B patterns over different frequency ranges. Following cooling, averaged corticomuscular coherence was decreased in Group A subjects, but unchanged for Group B, even though both groups showed comparable slowing of nervous conduction. The delay calculated from the slope of the phase-frequency regression was increased following cooling. However, the size of this increase was around twice the rise in PMCT measured using the F-wave (regression slope 2.33, 95% confidence limits 1.30-3.36). Both afferent and efferent peripheral nerves will be slowed by similar amounts following cooling. The change in delay calculated from the coherence phase therefore better matches the rise in total sensorimotor feedback loop time caused by cooling, rather than just the change in the efferent limb. A model of corticomuscular coherence which assumes that only efferent pathways contribute cannot be reconciled to these results. The data rather suggest that afferent feedback pathways may also play a role in the genesis of corticomuscular coherence.

Blind separation of linear instantaneous mixtures of nonstationary surface myoelectric signals

Electromyographic (EMG) recordings detected over the skin may be mixtures of signals generated by different active muscles due to the phenomena related to volume conduction. Separation of the sources is necessary when single muscle activity has to be detected. Signals generated by different muscles may be considered uncorrelated but in general overlap in time and frequency. Under certain assumptions, mixtures of surface EMG signals can be considered as linear instantaneous but no a priori information about the mixing matrix is available when different muscles are active. In this study, we applied blind source separation (BSS) methods to separate the signals generated by two active muscles during a force-varying task. As the signals are non stationary, an algorithm based on spatial time-frequency distributions was applied on simulated and experimental EMG signals. The experimental signals were collected from the flexor carpi radialis and the pronator teres muscles which could be activated selectively for wrist flexion and rotation, respectively. From the simulations, correlation coefficients between the reference and reconstructed sources were higher than 0.85 for signals largely overlapping both in time and frequency and for signal-to-noise ratios as low as 5 dB. The Choi-Williams and Bessel kernels, in this case, performed better than the Wigner-Ville one. Moreover, the selection of time-frequency points for the procedure of joint diagonalization used in the BSS algorithm significantly influenced the results. For the experimental signals, the interference of the other source in each reconstructed source was significantly attenuated by the application of the BSS method. The ratio between root-mean-square values of the signals from the two sources detected over one of the muscles increased from (mean +/- standard deviation) 2.33 +/- 1.04 to 4.51 +/- 1.37 and from 1.55 +/- 0.46 to 2.72 +/- 0.65 for wrist flexion and rotation, respectively. This increment was statistically significant. It was concluded that the BSS approach applied is promising for the separation of surface EMG signals, with applications ranging from muscle assessment to detection of muscle activation intervals, and to the control of myoelectric prostheses.

The extraction of neural strategies from the surface EMG

This brief review examines some of the methods used to infer central control strategies from surface electromyogram (EMG) recordings. Among the many uses of the surface EMG in studying the neural control of movement, the review critically evaluates only some of the applications. The focus is on the relations between global features of the surface EMG and the underlying physiological processes. Because direct measurements of motor unit activation are not available and many factors can influence the signal, these relations are frequently misinterpreted. These errors are compounded by the counterintuitive effects that some system parameters can have on the EMG signal. The phenomenon of crosstalk is used as an example of these problems. The review describes the limitations of techniques used to infer the level of muscle activation, the type of motor unit recruited, the upper limit of motor unit recruitment, the average discharge rate, and the degree of synchronization between motor units. Although the global surface EMG is a useful measure of muscle activation and assessment, there are limits to the information that can be extracted from this signal.

Postural rhythmic muscle bursting activity in Angelman syndrome

Postural impairment is one of the most consistent features of Angelman syndrome. Using multiple-channel electromyography, we studied a lower limb and an upper limb isometric postural task in 14 patients with Angelman syndrome and 18 unimpaired control subjects. Both tasks were associated with synchronous bursts of activity at frequencies of 6-8 s(-1) in all recorded muscles in all patients with Angelman syndrome and none of the control subjects. This pattern was not altered by extra-loading. Electroencephalogram recorded during the upper limb task showed no change in relation to the task. Burst-locked back-averaging of the electroencephalogram showed no spiking before or during the bursts. Various physiological and pathological rhythmic muscle activities have been proposed to be a manifestation of oscillations in the central nervous system and it has been suggested that such oscillations may have a role in the processing of motor commands. The mechanism of the rhythmic muscle bursting activity associated with maintaining posture in patients with Angelman syndrome is not clear, although it could be consistent with cerebellar Purkinje cell dysfunction, either as a pathological feature or as an adaptive process to overcome deficits in motor coordination.