Effects of surface EMG rectification on power and coherence analyses: An EEG and MEG study

Cortical entrainment of human hypoglossal motor unit activities

Output from the primary motor cortex contains oscillations that can have frequency-specific effects on the firing of motoneurons (MNs). Whereas much is known about the effects of oscillatory cortical drive on the output of spinal MN pools, considerably less is known about the effects on cranial motor nuclei, which govern speech/oromotor control. Here, we investigated cortical input to one such motor pool, the hypoglossal motor nucleus (HMN), which controls muscles of the tongue. We recorded intramuscular genioglossus electromyogram (EMG) and scalp EEG from healthy adult subjects performing a tongue protrusion task. Cortical entrainment of HMN population activity was assessed by measuring coherence between EEG and multiunit EMG activity. In addition, cortical entrainment of individual MN firing activity was assessed by measuring phase locking between single motor unit (SMU) action potentials and EEG oscillations. We found that cortical entrainment of multiunit activity was detectable within the 15- to 40-Hz frequency range but was inconsistent across recordings. By comparison, cortical entrainment of SMU spike timing was reliable within the same frequency range. Furthermore, this effect was found to be intermittent over time. Our study represents an important step in understanding corticomuscular synchronization in the context of human oromotor control and is the first study to document SMU entrainment by cortical oscillations in vivo.

Selective movement preparation is subserved by selective increases in corticomuscular gamma-band coherence

Local groups of neurons engaged in a cognitive task often exhibit rhythmically synchronized activity in the gamma band, a phenomenon that likely enhances their impact on downstream areas. The efficacy of neuronal interactions may be enhanced further by interareal synchronization of these local rhythms, establishing mutually well timed fluctuations in neuronal excitability. This notion suggests that long-range synchronization is enhanced selectively for connections that are behaviorally relevant. We tested this prediction in the human motor system, assessing activity from bilateral motor cortices with magnetoencephalography and corresponding spinal activity through electromyography of bilateral hand muscles. A bimanual isometric wrist extension task engaged the two motor cortices simultaneously into interactions and coherence with their respective corresponding contralateral hand muscles. One of the hands was cued before each trial as the response hand and had to be extended further to report an unpredictable visual go cue. We found that, during the isometric hold phase, corticomuscular coherence was enhanced, spatially selective for the corticospinal connection that was effectuating the subsequent motor response. This effect was spectrally selective in the low gamma-frequency band (40-47 Hz) and was observed in the absence of changes in motor output or changes in local cortical gamma-band synchronization. These findings indicate that, in the anatomical connections between the cortex and the spinal cord, gamma-band synchronization is a mechanism that may facilitate behaviorally relevant interactions between these distant neuronal groups.

Corticomuscular coherence reflects interindividual differences in the state of the corticomuscular network during low-level static and dynamic forces

In the investigation of corticomuscular coherence (CMC), it remained unclear why some subjects do not present significant CMC. We predicted that such subjects will develop CMC as a result of learning as indexed by improved performance during a visuomotor task. We investigated CMC, cortical motor spectral power (SP), and performance in 14 subjects during isometric compensation of a static force or dynamic force (DF) with their right index finger. We compared data from the beginning of the experiment (Time-Period 1) and after learning (Time-Period 2). Eight subjects (Group CMC++) presented CMC during Period 1 which increased during Period 2. Six subjects (Group CMC-+) presented CMC only during Period 2. Group CMC-+ was "more desynchronized" (lower SP, and stronger task-related desynchronization) than Group CMC++. The performance was better in Group CMC++ than in Group CMC-+. Learning was associated with higher SP, higher CMC, and better performance in both groups. However, in the more complicated DF condition, Group CMC++ learned better than Group CMC-+. The present study demonstrates the presence of CMC in all subjects tested and evidence that this is due to the fact that individuals may fall into 2 different groups in terms of oscillatory motor control: Group CMC-+ presents CMC only after learning.

Optimal imaging of cortico-muscular coherence through a novel regression technique based on multi-channel EEG and un-rectified EMG

Cortico-muscular coherence (CMC) reflects interactions between muscular and cortical activities as detected with EMG and EEG recordings, respectively. Most previous studies utilized EMG rectification for CMC calculation. Yet, recent modeling studies predicted that EMG rectification might have disadvantages for CMC evaluation. In addition, previously the effect of rectification on CMC was estimated with single-channel EEG which might be suboptimal for detection of CMC. In order to optimally detect CMC with un-rectified EMG and resolve the issue of EMG rectification for CMC estimation, we introduce a novel method, Regression CMC (R-CMC), which maximizes the coherence between EEG and EMG. The core idea is to use multiple regression where narrowly filtered EEG signals serve as predictors and EMG is the dependent variable. We investigated CMC during isometric contraction of the abductor pollicis brevis muscle. In order to facilitate the comparison with previous studies, we estimated the effect of rectification with frequently used Laplacian filtering and C3/C4 vs. linked earlobes. For all three types of analysis, we detected CMC in the beta frequency range above the contralateral sensorimotor areas. The R-CMC approach was validated with simulations and real data and was found capable of recovering CMC even in case of high levels of background noise. When using single channel data, there were no changes in the strength of CMC estimated with rectified or un-rectified EMG--in agreement with the previous findings. Critically, for both Laplacian and R-CMC analyses EMG rectification resulted in significantly smaller CMC values compared to un-rectified EMG. Thus, the present results provide empirical evidence for the predictions from the earlier modeling studies that rectification of EMG can reduce CMC.

Weakening of synergist muscle coupling during reaching movement in stroke patients

BACKGROUND

After hemiparetic stroke, coordination of the shoulder flexor and elbow extensor muscles during a reaching movement is impaired and contributes to poor performance.

OBJECTIVE

The aim was to determine whether functional coupling between electromyographic signals of synergist muscles during reaching was weakened in stroke patients who had poor motor coordination.

METHODS

Surface electromyography (EMG) from the anterior deltoid, triceps brachii, biceps brachii, pectoralis major, supraspinatus, and latissimus dorsi of the affected upper limb in 11 stroke patients (mean Fugl-Meyer upper extremity score 27 ± 8) and in the dominant arm of 8 healthy controls were measured.

RESULTS

Coherence between the EMG of the anterior deltoid and triceps brachii, 2 synergists for reaching, was lower in patients compared with controls, in the 0- to 11-Hz range. Detailed segmented frequency-range analysis indicated significant differences in the coherence between groups in 0- to 3.9-Hz and 4- to 7.9-Hz ranges.

CONCLUSIONS

This weakened functional coupling may contribute to poor reaching performance and could be a consequence of a loss of common drive at the frequency bands as a result of interruption of information flow in the corticospinal pathway.

Corticospinal interaction during isometric compensation for modulated forces with different frequencies

Background

During isometric compensation of modulated low-level forces corticomuscular coherence (CMC) has been shown to occur in high-beta or gamma-range. The influence of the frequency of force modulation on CMC has up to now remained unexplored. We addressed this question by investigating CMC, motor performance, and cortical spectral power during a visuomotor task in which subjects had to compensate a modulated force of 8% of the maximum voluntary contraction exerted on their right index finger. The effect of three frequencies of force modulation (0.6, 1.0 and 1.6 Hz) was tested. EEG, EMG from first dorsal interosseus, hand flexor and extensor muscles, and finger position were recorded in eight right-handed women.

Results

Five subjects showed CMC in gamma- (28-45 Hz) and three in beta-range (15-30 Hz). Beta- and gamma-range CMC and cortical motor spectral power were not modulated by the various frequencies. However, a sharp bilateral CMC peak at 1.6 Hz was observed, but only in the five gamma-range CMC subjects. The performance error increased linearly with the frequency.

Conclusions

Our findings suggest that the frequency of force modulation has no effect on the beta- and gamma-range CMC during isometric compensation for modulated forces at 8% MVC. The beta- and gamma-range CMC may be related to interindividual differences and possibly to strategy differences.

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.

Modeling nonlinear errors in surface electromyography due to baseline noise: a new methodology

The surface electromyographic (EMG) signal is often contaminated by some degree of baseline noise. It is customary for scientists to subtract baseline noise from the measured EMG signal prior to further analyses based on the assumption that baseline noise adds linearly to the observed EMG signal. The stochastic nature of both the baseline and EMG signal, however, may invalidate this assumption. Alternately, "true" EMG signals may be either minimally or nonlinearly affected by baseline noise. This information is particularly relevant at low contraction intensities when signal-to-noise ratios (SNR) may be lowest. Thus, the purpose of this simulation study was to investigate the influence of varying levels of baseline noise (approximately 2-40% maximum EMG amplitude) on mean EMG burst amplitude and to assess the best means to account for signal noise. The simulations indicated baseline noise had minimal effects on mean EMG activity for maximum contractions, but increased nonlinearly with increasing noise levels and decreasing signal amplitudes. Thus, the simple baseline noise subtraction resulted in substantial error when estimating mean activity during low intensity EMG bursts. Conversely, correcting EMG signal as a nonlinear function of both baseline and measured signal amplitude provided highly accurate estimates of EMG amplitude. This novel nonlinear error modeling approach has potential implications for EMG signal processing, particularly when assessing co-activation of antagonist muscles or small amplitude contractions where the SNR can be low.

The alpha-motoneuron pool as transmitter of rhythmicities in cortical motor drive

OBJECTIVE

Investigate the effectiveness and frequency dependence of central drive transmission via the alpha-motoneuron pool to the muscle.

METHODS

We describe a model for the simulation of alpha-motoneuron firing and the EMG signal as response to central drive input. The transfer in the frequency domain is investigated. Coherence between stochastical central input and EMG is also evaluated.

RESULTS

The transmission of central rhythmicities to the EMG signal relates to the spectral content of the latter. Coherence between central input to the alpha-motoneuron pool and the EMG signal is significant whereby the coupling strength hardly depends on the frequency in a range from 1 to 100 Hz. Common central input to pairs of alpha-motoneurons strongly increases the coherence levels. The often-used rectification of the EMG signal introduces a clear frequency dependence.

CONCLUSIONS

Oscillatory phenomena are strongly transmitted via the alpha-motoneuron pool. The motoneuron firing frequencies do play a role in the transmission gain, but do not influence the coherence levels. Rectification of the EMG signal enhances the transmission gain, but lowers coherence and introduces a strong frequency dependency. We think that it should be avoided.

SIGNIFICANCE

Our findings show that rhythmicities are translated into alpha-motoneuron activity without strong non-linearities.

Increased voluntary drive is associated with changes in common oscillations from 13 to 60 Hz of interference but not rectified electromyography

The purpose of this study was to compare the capability of interference and rectified electromyography (EMG) to detect changes in the beta (13-30-HZ) and Piper (30-60-HZ) bands when voluntary force is increased. Twenty adults exerted a constant force abduction of the index finger at 15% and 50% of maximum. The common oscillations at various frequency bands (0-500 HZ) were estimated from the first dorsal interosseous muscle using cross wavelets of interference and rectified EMG. For the interference EMG signals, normalized power significantly (P < 0.01) increased with force in the beta (9.0 +/- 0.9 vs. 15.5 +/- 2.1%) and Piper (13.6 +/- 0.9 vs. 21 +/- 1.7%) bands. For rectified EMG signals, however, the beta and Piper bands remained unchanged (P > 0.4). Although rectified EMG is used in many clinical studies to identify changes in the oscillatory drive to the muscle, our findings suggest that only interference EMG can accurately capture the increase in oscillatory drive from 13 to 60 HZ with voluntary force.

Time frequency based coherence analysis between EEG and EMG activities in fatigue duration

In voluntary movements, functional role of synchronized neuronal activity in the human motor system is important to detect and diagnose of the some diseases. In some previous studies, EEG signals and responses belong to an exercise are examined and an increased EEG activity reported in alpha frequency band. The reason of this is not clear whether a change is a direct result of the exhaustion or whether it is an adaptation. Time frequency based coherence analysis may be excellent tools to asses the fatigue stages. The experiment was planned with three fatigue stage and the cortical-muscular synchronizations were observed and examined. Simultaneously cortical electroencephalography (EEG) activities and electromyography (EMG) activities that are activated by phasic voluntary movements are recorded for 10 healthy young person and relation of the coherence between the signals are observed in time frequency domain. There is a decreasing significant coherence activity in third fatigue stage against to first and second fatigue stages. Time frequency based coherence analysis is a good method to explore motor cortex control of muscle activity in the fatigued persons. Time frequency based coherence analysis gives useful result for recordings of simultaneously cortical activity EEG and EMG during a phasic voluntary movement to determination of fatigue levels.

Linear and nonlinear information flow based on time-delayed mutual information method and its application to corticomuscular interaction

OBJECTIVE

To propose a model-free method to show linear and nonlinear information flow based on time-delayed mutual information (TDMI) by employing uni- and bi-variate surrogate tests and to investigate whether there are contributions of the nonlinear information flow in corticomuscular (CM) interaction.

METHODS

Using simulated data, we tested whether our method would successfully detect the direction of information flow and identify a relationship between two simulated time series. As an experimental data application, we applied this method to investigate CM interaction during a right wrist extension task.

RESULTS

Results of simulation tests show that we can correctly detect the direction of information flow and the relationship between two time series without a prior knowledge of the dynamics of their generating systems. As experimental results, we found both linear and nonlinear information flow from contralateral sensorimotor cortex to muscle.

CONCLUSIONS

Our method is a viable model-free measure of temporally varying causal interactions that is capable of distinguishing linear and nonlinear information flow. With respect to experimental application, there are both linear and nonlinear information flows in CM interaction from contralateral sensorimotor cortex to muscle, which may reflect the motor command from brain to muscle.

SIGNIFICANCE

This is the first study to show separate linear and nonlinear information flow in CM interaction.

Rectification of the EMG signal impairs the identification of oscillatory input to the muscle

Rectification of EMG signals is a common processing step used when performing electroencephalographic-electromyographic (EEG-EMG) coherence and EMG-EMG coherence. It is well known, however, that EMG rectification alters the power spectrum of the recorded EMG signal (interference EMG). The purpose of this study was to determine whether rectification of the EMG signal influences the capability of capturing the oscillatory input to a single EMG signal and the common oscillations between two EMG signals. Several EMG signals were reconstructed from experimentally recorded EMG signals from the surface of the first dorsal interosseus muscle and were manipulated to have an oscillatory input or common input (for pairs of reconstructed EMG signals) at various frequency bands (in Hz: 0-12, 12-30, 30-50, 50-100, 100-150, 150-200, 200-250, 250-300, and 300-400), one at a time. The absolute integral and normalized integral of power, peak power, and peak coherence (for pairs of EMG signals) were quantified from each frequency band. The power spectrum of the interference EMG accurately detected the changes to the oscillatory input to the reconstructed EMG signal, whereas the power spectrum of the rectified EMG did not. Similarly, the EMG-EMG coherence between two interference EMG signals accurately detected the common input to the pairs of reconstructed EMG signals, whereas the EMG-EMG coherence between two rectified EMG signals did not. The frequency band from 12 to 30 Hz in the power spectrum of the rectified EMG and the EMG-EMG coherence between two rectified signals was influenced by the input from 100 to 150 Hz but not from the input from 12 to 30 Hz. The study concludes that the power spectrum of the EMG and EMG-EMG coherence should be performed on interference EMG signals and not on rectified EMG signals because rectification impairs the identification of the oscillatory input to a single EMG signal and the common oscillatory input between two EMG signals.

Beta-Range EEG-EMG Coherence With Isometric Compensation for Increasing Modulated Low-Level Forces

Corticomuscular synchronization has been shown to occur in beta (15–30 Hz) and gamma range (30–45 Hz) during isometric compensation of static and dynamic (periodically modulated) low-level forces, respectively. However, it is still unknown to what extent these synchronization processes in beta and gamma range are modified with increasing modulated force. We addressed this question by investigating the corticomuscular coherence (CMC) between the electroencephalogram (EEG) and electromyogram (EMG) from the first dorsal interosseus muscle (FDI) as well as the cortical and muscular spectral power during a visuomotor task where different levels of a dynamic (modulated) force were used. Seven healthy right-handed female subjects compensated dynamic forces at 8, 16, and 24% of the maximal voluntary contraction (MVC) isometrically with their right index finger. Under the three conditions investigated, we found a broad-band CMC comprising both beta and gamma range and peaking at ∼22 Hz within the beta band. This broad-band coherence increased linearly with higher force level. A separate analysis of the gamma range CMC did not show significant modulation of the CMC by the force levels. EEG and EMG spectral power did not show any significant difference among the three force conditions. Our results favor the view that the function of beta range CMC is not specific for low-level static forces only. The sensorimotor system may resort to stronger and also broader beta-range CMC to generate stable corticospinal interaction during increased force level, as well as when compensating for dynamic modulated forces. This finding re-enforces the importance of the beta-range EEG-EMG coherence in sensorimotor integration.