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

Subthalamic nucleus input-output dynamics are correlated with Parkinson's burden and treatment efficacy

The subthalamic nucleus (STN) is pivotal in basal ganglia function in health and disease. Micro-electrode recordings of >25,000 recording sites from 146 Parkinson's patients undergoing deep brain stimulation (DBS) allowed differentiation between subthalamic input, represented by local field potential (LFP), and output, reflected in spike discharge rate (SPK). As with many natural systems, STN neuronal activity exhibits power-law dynamics characterized by the exponent α. We, therefore, dissected STN data into aperiodic and periodic components using the Fitting Oscillations & One Over F (FOOOF) tool. STN LFP showed significantly higher aperiodic exponents than SPK. Additionally, SPK beta oscillations demonstrated a downward frequency shift compared to LFP. Finally, the STN aperiodic and spiking parameters explained a significant fraction of the variance of the burden and treatment efficacy of Parkinson's disease. The unique STN input-output dynamics may clarify its role in Parkinson's physiology and can be utilized in closed-loop DBS therapy.

Influencing factors of corticomuscular coherence in stroke patients

Stroke, also known as cerebrovascular accident, is an acute cerebrovascular disease with a high incidence, disability rate, and mortality. It can disrupt the interaction between the cerebral cortex and external muscles. Corticomuscular coherence (CMC) is a common and useful method for studying how the cerebral cortex controls muscle activity. CMC can expose functional connections between the cortex and muscle, reflecting the information flow in the motor system. Afferent feedback related to CMC can reveal these functional connections. This paper aims to investigate the factors influencing CMC in stroke patients and provide a comprehensive summary and analysis of the current research in this area. This paper begins by discussing the impact of stroke and the significance of CMC in stroke patients. It then proceeds to elaborate on the mechanism of CMC and its defining formula. Next, the impacts of various factors on CMC in stroke patients were discussed individually. Lastly, this paper addresses current challenges and future prospects for CMC.

The Impact of Feature Extraction on Classification Accuracy Examined by Employing a Signal Transformer to Classify Hand Gestures Using Surface Electromyography Signals

Interest in developing techniques for acquiring and decoding biological signals is on the rise in the research community. This interest spans various applications, with a particular focus on prosthetic control and rehabilitation, where achieving precise hand gesture recognition using surface electromyography signals is crucial due to the complexity and variability of surface electromyography data. Advanced signal processing and data analysis techniques are required to effectively extract meaningful information from these signals. In our study, we utilized three datasets: NinaPro Database 1, CapgMyo Database A, and CapgMyo Database B. These datasets were chosen for their open-source availability and established role in evaluating surface electromyography classifiers. Hand gesture recognition using surface electromyography signals draws inspiration from image classification algorithms, leading to the introduction and development of the Novel Signal Transformer. We systematically investigated two feature extraction techniques for surface electromyography signals: the Fast Fourier Transform and wavelet-based feature extraction. Our study demonstrated significant advancements in surface electromyography signal classification, particularly in the Ninapro database 1 and CapgMyo dataset A, surpassing existing results in the literature. The newly introduced Signal Transformer outperformed traditional Convolutional Neural Networks by excelling in capturing structural details and incorporating global information from image-like signals through robust basis functions. Additionally, the inclusion of an attention mechanism within the Signal Transformer highlighted the significance of electrode readings, improving classification accuracy. These findings underscore the potential of the Signal Transformer as a powerful tool for precise and effective surface electromyography signal classification, promising applications in prosthetic control and rehabilitation.

EMG-projected MEG High-Resolution Source Imaging of Human Motor Execution: Brain-Muscle Coupling above Movement Frequencies

Magnetoencephalography (MEG) is a non-invasive functional imaging technique for pre-surgical mapping. However, movement-related MEG functional mapping of primary motor cortex (M1) has been challenging in presurgical patients with brain lesions and sensorimotor dysfunction due to the large numbers of trails needed to obtain adequate signal to noise. Moreover, it is not fully understood how effective the brain communication is with the muscles at frequencies above the movement frequency and its harmonics. We developed a novel Electromyography (EMG)-projected MEG source imaging technique for localizing M1 during ~1 minute recordings of left and right self-paced finger movements (~1 Hz). High-resolution MEG source images were obtained by projecting M1 activity towards the skin EMG signal without trial averaging. We studied delta (1-4 Hz), theta (4-7 Hz), alpha (8-12 Hz), beta (15-30 Hz), and gamma (30-90 Hz) bands in 13 healthy participants (26 datasets) and two presurgical patients with sensorimotor dysfunction. In healthy participants, EMG-projected MEG accurately localized M1 with high accuracy in delta (100.0%), theta (100.0%), and beta (76.9%) bands, but not alpha (34.6%) and gamma (0.0%) bands. Except for delta, all other frequency bands were above the movement frequency and its harmonics. In both presurgical patients, M1 activity in the affected hemisphere was also accurately localized, despite highly irregular EMG movement patterns in one patient. Altogether, our EMG-projected MEG imaging approach is highly accurate and feasible for M1 mapping in presurgical patients. The results also provide insight into movement related brain-muscle coupling above the movement frequency and its harmonics.

Recurrent inhibition contribution to corticomuscular coherence modulation between contraction types

Recent findings provided evidence that spinal regulatory mechanisms were involved in corticomuscular coherence (CMC) modulation between contraction types. Although their relative contributions could not be precisely identified, it was suggested that recurrent inhibition (RI) could modulate CMC by regulating the synchronization of spinal motoneuron activity. To confirm this hypothesis, concurrent modulations of RI and CMC for the soleus (SOL) were compared during submaximal isometric, shortening and lengthening plantar flexions. Submaximal contraction intensity was set at 50% of the maximal SOL EMG activity. CMC was computed in the time-frequency domain between the Cz EEG electrode signal and the nonrectified SOL EMG signal. The RI was quantified through the paired Hoffmann (H) reflex technique by comparing the modulations of the test and conditioning H-reflexes (H' and H1 , respectively). Both beta-band CMC and the ratio between H' and H1 amplitudes were significantly lower in SOL during lengthening compared with isometric and shortening contractions. Furthermore, we observed a negative linear correlation between the RI and beta-band CMC. Finally, a higher RI increase during lengthening contractions compared to either isometric or shortening ones was correlated with a larger decrease in CMC. Collectively, these novel findings provide robust evidence that the RI acts as a neural "filter" that contributes to the modulation of corticomuscular interactions between contraction types, possibly by disrupting the oscillatory muscle activation.

Combined effect of contraction type and intensity on corticomuscular coherence during isokinetic plantar flexions

During isometric contractions, corticomuscular coherence (CMC) may be modulated along with the contraction intensity. Furthermore, CMC may also vary between contraction types due to the contribution of spinal inhibitory mechanisms. However, the interaction between the effect of the contraction intensity and of the contraction type on CMC remains hitherto unknown. Therefore, CMC and spinal excitability modulations were compared during submaximal isometric, shortening and lengthening contractions of plantar flexor muscles at 25, 50, and 70% of the maximal soleus (SOL) EMG activity. CMC was computed in the time-frequency domain between the Cz EEG electrode signal and the SOL or medial gastrocnemius (MG) EMG signals. The results indicated that beta-band CMC was decreased in the SOL only between 25 and 50-70% contractions for both isometric and anisometric contractions, but remained similar for all contraction intensities in the MG. Spinal excitability was similar for all contraction intensities in both muscles. Meanwhile a divergence of the EEG and the EMG signals mean frequency was observed only in the SOL and only between 25 and 50-70% contractions, independently from the contraction type. Collectively, these findings confirm an effect of the contraction intensity on beta-band CMC, although it was only measured in the SOL, between low-level and high-level contraction intensities. Furthermore, the current findings provide new evidence that the observed modulations of beta-band CMC with the contraction intensity does not depend on the contraction type or on spinal excitability variations.

Aging-induced alterations in EEG spectral power associated with graded force motor tasks

BACKGROUND

It has been demonstrated that in young and healthy individuals, there is a strong association between the amplitude of EEG-derived motor activity-related cortical potential or EEG spectral power (ESP) and voluntary muscle force. This association suggests that the motor-related ESP may serve as an index of central nervous system function in controlling voluntary muscle activation Therefore, it may potentially be used as an objective marker to track changes in functional neuroplasticity due to neurological disorders, aging, and following rehabilitation therapies. To this end, the relationship between the band-specific ESP-combined spectral power of EEG oscillatory and aperiodic (noise) components-and voluntary elbow flexion (EF) force has been analyzed in elder and young individuals.

METHODS

20 young (22.6 ± 0.87 year) and 28 elderly (74.79 ± 1.37 year) participants performed EF contractions at 20%, 50%, and 80% of maximum voluntary contraction (MVC) while high-density EEG signals were recorded. Both the absolute and relative ESPs were computed for the EEG frequency bands of interest.

RESULTS

The MVC force generated by the elderly was foreseeably lower than that of the young participants. Compared to young, the elderly cohort's (1) total ESP was significantly lower for the high (80% MVC) force task; (2) relative ESP in beta band was significantly elevated for the low and moderate (20% MVC and 50% MVC) force tasks; (3) absolute ESP failed to have a positive trend with force for EEG frequency bands of interest; and (4) beta-band relative ESP did not exhibit a significant decrease with increasing force levels.

CONCLUSIONS

As opposed to young subjects, the beta-band relative ESP in elderly did not significantly decrease with increasing EF force values. This observation suggests the use of beta-band relative ESP as a potential biomarker for age-related motor control degeneration.

Sparse representation of brain signals offers effective computation of cortico-muscular coupling value to predict the task-related and non-task sEMG channels: A joint hdEEG-sEMG study

Cortico-muscular interactions play important role in sensorimotor control during motor task and are commonly studied by cortico-muscular coherence (CMC) method using joint electroencephalogram-surface electromyogram (EEG-sEMG) signals. As noise and time delay between the two signals weaken the CMC value, coupling difference between non-task sEMG channels is often undetectable. We used sparse representation of EEG channels to compute CMC and detect coupling for task-related and non-task sEMG signals. High-density joint EEG-sEMG (53 EEG channels, 4 sEMG bipolar channels) signals were acquired from 15 subjects (30.26 ± 4.96 years) during four specific hand and foot contraction tasks (2 dynamic and 2 static contraction). Sparse representations method was applied to detect projection of EEG signals on each sEMG channel. Bayesian optimization was employed to select best-fitted method with tuned hyperparameters on the input feeding data while using 80% data as the train set and 20% as test set. K-fold (K = 5) cross-validation method was used for evaluation of trained model. Two models were trained separately, one for CMC data and the other from sparse representation of EEG channels on each sEMG channel. Sensitivity, specificity, and accuracy criteria were obtained for test dataset to evaluate the performance of task-related and non-task sEMG channels detection. Coupling values were significantly different between grand average of task-related compared to the non-task sEMG channels (Z = -6.33, p< 0.001, task-related median = 2.011, non-task median = 0.112). Strong coupling index was found even in single trial analysis. Sparse representation approach (best fitted model: SVM, Accuracy = 88.12%, Sensitivity = 83.85%, Specificity = 92.45%) outperformed CMC method (best fitted model: KNN, Accuracy = 50.83%, Sensitivity = 52.17%, Specificity = 49.47%). Sparse representation approach offers high performance to detect CMC for discerning the EMG channels involved in the contraction tasks and non-tasks.

Neurophysiological features in spinocerebellar ataxia type 2: Prospects for novel biomarkers

Electrophysiological biomarkers are useful to assess the degeneration and progression of the nervous system in pre-ataxic and ataxic stages of the Spinocerebellar Ataxia Type 2 (SCA2). These biomarkers are essentially defined by their clinical significance, discriminating patients and/or preclinical subjects from healthy controls in cross-sectional studies, their significant changes over time in longitudinal studies, and their correlation with the cytosine-guanine-adenine (CAG) repeat expansion and/or clinical ataxia scores, time of evolution and time to ataxia onset. We classified electrophysiological biomarkers into three main types: (1) preclinical, (2) disease progression and (3) genetic damage. We review the data that identify sural nerve potential amplitude, maximum saccadic velocity, sleep efficiency, rapid eye movement (REM) sleep percentage, K-complex density, REM sleep without atonia percentage, corticomuscular coherence, central motor conduction time, visual P300 latency, and antisaccadic error correction latency as reliable preclinical, progression and/or genetic damage biomarkers of SCA2. These electrophysiological biomarkers will facilitate the conduction of clinical trials that test the efficacy of emerging treatments in SCA2.

Dynamic Modulation of Beta Band Cortico-Muscular Coupling Induced by Audio-Visual Rhythms

Human movements often spontaneously fall into synchrony with auditory and visual environmental rhythms. Related behavioral studies have shown that motor responses are automatically and unintentionally coupled with external rhythmic stimuli. However, the neurophysiological processes underlying such motor entrainment remain largely unknown. Here, we investigated with electroencephalography (EEG) and electromyography (EMG) the modulation of neural and muscular activity induced by periodic audio and/or visual sequences. The sequences were presented at either 1 or 2 Hz, while participants maintained constant finger pressure on a force sensor. The results revealed that although there was no change of amplitude in participants' EMG in response to the sequences, the synchronization between EMG and EEG recorded over motor areas in the beta (12-40 Hz) frequency band was dynamically modulated, with maximal coherence occurring about 100 ms before each stimulus. These modulations in beta EEG-EMG motor coherence were found for the 2-Hz audio-visual sequences, confirming at a neurophysiological level the enhancement of motor entrainment with multimodal rhythms that fall within preferred perceptual and movement frequency ranges. Our findings identify beta band cortico-muscular coupling as a potential underlying mechanism of motor entrainment, further elucidating the nature of the link between sensory and motor systems in humans.

Specific modulation of corticomuscular coherence during submaximal voluntary isometric, shortening and lengthening contractions

During voluntary contractions, corticomuscular coherence (CMC) is thought to reflect a mutual interaction between cortical and muscle oscillatory activities, respectively measured by electroencephalography (EEG) and electromyography (EMG). However, it remains unclear whether CMC modulation would depend on the contribution of neural mechanisms acting at the spinal level. To this purpose, modulations of CMC were compared during submaximal isometric, shortening and lengthening contractions of the soleus (SOL) and the medial gastrocnemius (MG) with a concurrent analysis of changes in spinal excitability that may be reduced during lengthening contractions. Submaximal contractions intensity was set at 50% of the maximal SOL EMG activity. CMC was computed in the time-frequency domain between the Cz EEG electrode signal and the unrectified SOL or MG EMG signal. Spinal excitability was quantified through normalized Hoffmann (H) reflex amplitude. The results indicate that beta-band CMC and normalized H-reflex were significantly lower in SOL during lengthening compared with isometric contractions, but were similar in MG for all three muscle contraction types. Collectively, these results highlight an effect of contraction type on beta-band CMC, although it may differ between agonist synergist muscles. These novel findings also provide new evidence that beta-band CMC modulation may involve spinal regulatory mechanisms.

Wavelet coherence analysis of muscle coupling during reaching movement in stroke

Agonist-antagonist coordination is essential to ensure the accuracy and stability of voluntary movement, which can be presented by time-varying coupling between agonist-antagonist electromyographic (EMG) signals. To discover the stroke-induced neurological change in paretic muscles, the wavelet coherence is firstly compared with coherence by simulated data and is utilized to represent the time-varying coupling of experimental data during elbow-tracking tasks. The simulation in this study demonstrates that the wavelet coherence is superior to coherence in the detection of short-time coupling between simulated signals. In addition, the experiment in this study is designed to explore the coupling between agonist-antagonist activations during the dynamic process. In the experiment, 10 post-stroke patients and 10 age-matched adults serving as controls were recruited and asked to perform elbow sinusoidal trajectory tracking tasks. Both the elbow angle and EMG signals of biceps and triceps were recorded simultaneously. Experimental results showed that wavelet coherence could represent the time-varying coupling between two EMG signals in the time-frequency domain, and its dynamic character was appropriate in the dynamic process to discover the functional coupling. According to the time and frequency analysis, the lower functional coupling in the post-stroke group and the obvious wavelet coherence difference between the two groups in the lower frequency range suggested a possible hypothesis mechanism that the weakening of coupling between agonist-antagonist muscles in the affected sides might in fact be stroke-induced damage in the direct corticospinal pathways.

Intermuscular coherence between homologous muscles during dynamic and static movement periods of bipedal squatting

Coordination of functionally coupled muscles is a key aspect of movement execution. Demands on coordinative control increase with the number of involved muscles and joints, as well as with differing movement periods within a given motor sequence. While previous research has provided evidence concerning inter- and intramuscular synchrony in isolated movements, compound movements remain largely unexplored. With this study, we aimed to uncover neural mechanisms of bilateral coordination through intermuscular coherence (IMC) analyses between principal homologous muscles during bipedal squatting (BpS) at multiple frequency bands (alpha, beta, and gamma). For this purpose, participants performed bipedal squats without additional load, which were divided into three distinct movement periods (eccentric, isometric, and concentric). Surface electromyography (EMG) was recorded from four homologous muscle pairs representing prime movers during bipedal squatting. We provide novel evidence that IMC magnitudes differ between movement periods in beta and gamma bands, as well as between homologous muscle pairs across all frequency bands. IMC was greater in the muscle pairs involved in postural and bipedal stability compared with those involved in muscular force during BpS. Furthermore, beta and gamma IMC magnitudes were highest during eccentric movement periods, whereas we did not find movement-related modulations for alpha IMC magnitudes. This finding thus indicates increased integration of afferent information during eccentric movement periods. Collectively, our results shed light on intermuscular synchronization during bipedal squatting, as we provide evidence that central nervous processing of bilateral intermuscular functioning is achieved through task-dependent modulations of common neural input to homologous muscles.

NEW & NOTEWORTHY It is largely unexplored how the central nervous system achieves coordination of homologous muscles of the upper and lower body within a compound whole body movement, and to what extent this neural drive is modulated between different movement periods and muscles. Using intermuscular coherence analysis, we show that homologous muscle functions are mediated through common oscillatory input that extends over alpha, beta, and gamma frequencies with different synchronization patterns at different movement periods.

Beta-Range Corticomuscular Coupling Reflects Asymmetries in Hand Movement

Hand movement in humans is verified as asymmetries and lateralization, and two hemispheres make some distinct but complementary contributions in the control of hand movement. However, little research has been done on whether the information transfer of the motor system is different between left and right hand movement. Considering the importance of functional corticomuscular coupling (FCMC) between the motor cortex and contralateral muscle in movement assessment, this study aimed to explore the differences between left and right hand by investigating the interaction between muscle and brain activity. Here, we applied the transfer spectral entropy (TSE) algorithm to quantize the connection between electroencephalogram (EEG) over the brain scalp and electromyogram (EMG) from extensor digitorum (ED) and flexor digitorum superficialis (FDS) muscles recorded simultaneously during a gripping task. Eight healthy subjects were enrolled in this study. Results showed that left hand yielded narrower and lower beta synchronization compared to the right. Further analysis indicated coupling strength in EEG-EMG(FDS) combination was higher at beta band than that in EEG-EMG(ED) combination, and exhibited distinct differences between descending (EEG to EMG direction) and ascending (EMG to EEG direction) direction. This study presents the distinctions of beta-range FCMC between left and right hand, and confirms the importance of beta synchronization in understanding the mechanism of motor stability control. The cortex-muscle FCMC might be used as an evaluation approach to explore the difference between left and right movement system.

EMG Rectification Is Detrimental for Identifying Abnormalities in Corticomuscular and Intermuscular Coherence in Spinocerebellar Ataxia Type 2

Corticomuscular and intermuscular coherence (CMC, IMC) reflect connectivity between neuronal activity in the motor cortex measured by electroencephalography (EEG) and muscular activity measured by electromyography (EMG), or between activity in different muscles, respectively. There is an ongoing debate on the appropriateness of EMG rectification prior to coherence estimation. This work examines the effects of EMG rectification in CMC and IMC estimation in 20 spinocerebellar ataxia type 2 (SCA2) patients, 16 prodromal SCA2 gene mutation carriers, and 26 healthy controls during a repetitive upper or lower limb motor task. Coherence estimations were performed using the non-rectified raw EMG signal vs. the rectified EMG signal. EMG rectification decreases the level of significance of lower beta-frequency band CMC and IMC values in SCA2 patients and prodromal SCA2 mutation carriers vs. healthy controls, and also results in overall lower coherence values. EMG rectification is detrimental for beta-frequency band CMC and IMC estimation. One likely reason for this effect is distortion of coherence estimation in high-frequency signals, where the level of amplitude cancelation is high.

Canonical maximization of coherence: A novel tool for investigation of neuronal interactions between two datasets

Synchronization between oscillatory signals is considered to be one of the main mechanisms through which neuronal populations interact with each other. It is conventionally studied with mass-bivariate measures utilizing either sensor-to-sensor or voxel-to-voxel signals. However, none of these approaches aims at maximizing synchronization, especially when two multichannel datasets are present. Examples include cortico-muscular coherence (CMC), cortico-subcortical interactions or hyperscanning (where electroencephalographic EEG/magnetoencephalographic MEG activity is recorded simultaneously from two or more subjects). For all of these cases, a method which could find two spatial projections maximizing the strength of synchronization would be desirable. Here we present such method for the maximization of coherence between two sets of EEG/MEG/EMG (electromyographic)/LFP (local field potential) recordings. We refer to it as canonical Coherence (caCOH). caCOH maximizes the absolute value of the coherence between the two multivariate spaces in the frequency domain. This allows very fast optimization for many frequency bins. Apart from presenting details of the caCOH algorithm, we test its efficacy with simulations using realistic head modelling and focus on the application of caCOH to the detection of cortico-muscular coherence. For this, we used diverse multichannel EEG and EMG recordings and demonstrate the ability of caCOH to extract complex patterns of CMC distributed across spatial and frequency domains. Finally, we indicate other scenarios where caCOH can be used for the extraction of neuronal interactions.

Standing task difficulty related increase in agonist-agonist and agonist-antagonist common inputs are driven by corticospinal and subcortical inputs respectively

In standing, coordinated activation of lower extremity muscles can be simplified by common neural inputs to muscles comprising a functional synergy. We examined the effect of task difficulty on common inputs to agonist-agonist (AG-AG) pairs supporting direction specific reciprocal muscle control and agonist-antagonist (AG-ANT) pairs supporting stiffness control. Since excessive stiffness is energetically costly and limits the flexibility of responses to perturbations, compared to AG-ANT, we expected greater AG-AG common inputs and a larger increase with increasing task difficulty. We used coherence analysis to examine common inputs in three frequency ranges which reflect subcortical/spinal (0–5 and 6–15 Hz) and corticospinal inputs (6–15 and 16–40 Hz). Coherence was indeed higher in AG-AG compared to AG-ANT muscles in all three frequency bands, indicating a predilection for functional synergies supporting reciprocal rather than stiffness control. Coherence increased with increasing task difficulty, only in AG-ANT muscles in the low frequency band (0–5 Hz), reflecting subcortical inputs and only in AG-AG group in the high frequency band (16–40 Hz), reflecting corticospinal inputs. Therefore, common neural inputs to both AG-AG and AG-ANT muscles increase with difficulty but are likely driven by different sources of input to spinal alpha motor neurons.

Optimization of relative parameters in transfer entropy estimation and application to corticomuscular coupling in humans

BACKGROUND

As a non-modeled information theoretical measure, the transfer entropy (TE) could be applied to quantitatively analyze the linear and nonlinear coupling characteristics between two observations. However, the parameters selection of TE (the parameters used in state space reconstruction and estimating Shannon entropy) has a serious influence on the accuracy of its results.

NEW METHOD

In this study, the hybrid particle swarm optimization (HPSO) was applied to improve the accuracy of TE by optimizing its parameters. In HPSO, the TE calculation and significant analysis were integrated into the fitness function, and the optimal parameters group within the parameter space could be automatically found through an iteration process.

RESULTS

The TE results computed under the parameters optimized by HPSO (HPSO-TE), was assessed with a numerical non-linear model, the neural mass model and the recorded electroencephalogram (EEG) and electromyogram (EMG) signals. Compared with TE, HPSO-TE could reduce the 'false positive' in non-linear model, and 'spurious coupling', i.e. two nonzero TEs for unidirectionally coupled systems, especially when coupling strength was weak. The robustness against noise and long time-delay was improved. Moreover, the experimental data analysis showed HPSO-TE revealed the dominant direction (EEG → EMG) in corticomuscular coupling, and had higher values than TE which showed the same dominant direction.

COMPARISON WITH EXISTING METHOD

The implication of HPSO improved the accuracy of TE in estimating the coupling strength and direction.

CONCLUSIONS

The efficiency of TE could be improved by HPSO for estimating coupling relationships, especially for weakly coupled, strong noisy and long time-delay series.

Multiscale Information Transfer in Functional Corticomuscular Coupling Estimation Following Stroke: A Pilot Study

Recently, functional corticomuscular coupling (FCMC) between the cortex and the contralateral muscle has been used to evaluate motor function after stroke. As we know, the motor-control system is a closed-loop system that is regulated by complex self-regulating and interactive mechanisms which operate in multiple spatial and temporal scales. Multiscale analysis can represent the inherent complexity. However, previous studies in FCMC for stroke patients mainly focused on the coupling strength in single-time scale, without considering the changes of the inherently directional and multiscale properties in sensorimotor systems. In this paper, a multiscale-causal model, named multiscale transfer entropy, was used to quantify the functional connection between electroencephalogram over the scalp and electromyogram from the flexor digitorum superficialis (FDS) recorded simultaneously during steady-state grip task in eight stroke patients and eight healthy controls. Our results showed that healthy controls exhibited higher coupling when the scale reached up to about 12, and the FCMC in descending direction was stronger at certain scales (1, 7, 12, and 14) than that in ascending direction. Further analysis showed these multi-time scale characteristics mainly focused on the beta1 band at scale 11 and beta2 band at scale 9, 11, 13, and 15. Compared to controls, the multiscale properties of the FCMC for stroke were changed, the strengths in both directions were reduced, and the gaps between the descending and ascending directions were disappeared over all scales. Further analysis in specific bands showed that the reduced FCMC mainly focused on the alpha2 at higher scale, beta1 and beta2 across almost the entire scales. This study about multi-scale confirms that the FCMC between the brain and muscles is capable of complex and directional characteristics, and these characteristics in functional connection for stroke are destroyed by the structural lesion in the brain that might disrupt coordination, feedback, and information transmission in efferent control and afferent feedback. The study demonstrates for the first time the multiscale and directional characteristics of the FCMC for stroke patients, and provides a preliminary observation for application in clinical assessment following stroke.

Abnormal functional corticomuscular coupling after stroke

Motor dysfunction is a major consequence after stroke and it is generally believed that the loss of motor ability is caused by the impairments in neural network that controls movement. To explore the abnormal mechanisms how the brain controls shoulder abduction and elbow flexion in "flexion synergy" following stroke, we used the functional corticomuscular coupling (FCMC) between the brain and the muscles as a tool to identify the temporal evolution of corticomuscular interaction between the synkinetic and separate phases. 59-channel electroencephalogram (EEG) over brain scalp and 2-channel electromyogram (EMG) from biceps brachii (BB)/deltoid (DT) were recorded in sixteen stroke patients with motor dysfunction and eight healthy controls during a task of uplifting the arm (stage 1) and maintaining up to the chest (stage 2). As a result, compared to healthy controls, stroke patients had abnormally reduced coherence in EEG-BB combination and increased coherence in EEG-DT combination. Compared to synkinetic stroke patients, separate ones exhibited higher coupling at gamma-band during stage 1 and higher at beta-band during stage 2 in EEG-BB combination, but lower at beta-band during stage 2 in EEG-DT combination. Therefore, we infer that the disorders of efferent control and afferent proprioception in sensorimotor system for stroke patients effect on the oscillation at beta and gamma bands. Patients need integrate more information for shoulder abduction to compensate for the functional loss of elbow flexion in the recovery process, so that partial cortical cortex controlling on the elbow flexion may work on the shoulder abduction during "flexion synergy". Such researches could provide new perspective on the temporal evolution of corticomuscular interaction after stroke and add to our understanding of possible pathomechanisms how the brain abnormally controls shoulder abduction and elbow flexion in "flexion synergy".

Nonlinear Coupling between Cortical Oscillations and Muscle Activity during Isotonic Wrist Flexion

Coupling between cortical oscillations and muscle activity facilitates neuronal communication during motor control. The linear part of this coupling, known as corticomuscular coherence, has received substantial attention, even though neuronal communication underlying motor control has been demonstrated to be highly nonlinear. A full assessment of corticomuscular coupling, including the nonlinear part, is essential to understand the neuronal communication within the sensorimotor system. In this study, we applied the recently developed n:m coherence method to assess nonlinear corticomuscular coupling during isotonic wrist flexion. The n:m coherence is a generalized metric for quantifying nonlinear cross-frequency coupling as well as linear iso-frequency coupling. By using independent component analysis (ICA) and equivalent current dipole source localization, we identify four sensorimotor related brain areas based on the locations of the dipoles, i.e., the contralateral primary sensorimotor areas, supplementary motor area (SMA), prefrontal area (PFA) and posterior parietal cortex (PPC). For all these areas, linear coupling between electroencephalogram (EEG) and electromyogram (EMG) is present with peaks in the beta band (15–35 Hz), while nonlinear coupling is detected with both integer (1:2, 1:3, 1:4) and non-integer (2:3) harmonics. Significant differences between brain areas is shown in linear coupling with stronger coherence for the primary sensorimotor areas and motor association cortices (SMA, PFA) compared to the sensory association area (PPC); but not for the nonlinear coupling. Moreover, the detected nonlinear coupling is similar to previously reported nonlinear coupling of cortical activity to somatosensory stimuli. We suggest that the descending motor pathways mainly contribute to linear corticomuscular coupling, while nonlinear coupling likely originates from sensory feedback.

Detecting a Cortical Fingerprint of Parkinson's Disease for Closed-Loop Neuromodulation

Recent evidence suggests that deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD) mediates its clinical effects by modulating cortical oscillatory activity, presumably via a direct cortico-subthalamic connection. This observation might pave the way for novel closed-loop approaches comprising a cortical sensor. Enhanced beta oscillations (13-35 Hz) have been linked to the pathophysiology of PD and may serve as such a candidate marker to localize a cortical area reliably modulated by DBS. However, beta-oscillations are widely distributed over the cortical surface, necessitating an additional signal source for spotting the cortical area linked to the pathologically synchronized cortico-subcortical motor network. In this context, both cortico-subthalamic coherence and cortico-muscular coherence (CMC) have been studied in PD patients. Whereas, the former requires invasive recordings, the latter allows for non-invasive detection, but displays a rather distributed cortical synchronization pattern in motor tasks. This distributed cortical representation may conflict with the goal of detecting a cortical localization with robust biomarker properties which is detectable on a single subject basis. We propose that this limitation could be overcome when recording CMC at rest. We hypothesized that-unlike healthy subjects-PD would show CMC at rest owing to the enhanced beta oscillations observed in PD. By performing source space analysis of beta CMC recorded during resting-state magnetoencephalography, we provide preliminary evidence in one patient for a cortical hot spot that is modulated most strongly by subthalamic DBS. Such a spot would provide a prominent target region either for direct neuromodulation or for placing a potential sensor in closed-loop DBS approaches, a proposal that requires investigation in a larger cohort of PD patients.

Phasic stabilization of motor output after auditory and visual distractors

To maintain steady motor output, distracting sensory stimuli need to be blocked. To study the effects of brief auditory and visual distractors on the human primary motor (M1) cortex, we monitored magnetoencephalographic (MEG) cortical rhythms, electromyogram (EMG) of finger flexors, and corticomuscular coherence (CMC) during right-hand pinch (force 5-7% of maximum) while 1-kHz tones and checkerboard patterns were presented for 100 ms once every 3.5-5 s. Twenty-one subjects (out of twenty-two) showed statistically significant ∼20-Hz CMC. Both distractors elicited a covert startle-like response evident in changes of force and EMG (∼50% of the background variation) but without any visible movement, followed by ∼1-s enhancement of CMC (auditory on average by 75%, P < 0.001; visual by 33%, P < 0.05) and rolandic ∼20-Hz rhythm (auditory by 14%, P < 0.05; visual by 11%, P < 0.01). Directional coupling of coherence from muscle to the M1 cortex (EMG→MEG) increased for ∼0.5 s at the onset of the CMC enhancement, but only after auditory distractor (by 105%; P < 0.05), likely reflecting startle-related proprioceptive afference. The 20-Hz enhancements occurred in the left M1 cortex and were for the auditory stimuli preceded by an early suppression (by 7%, P < 0.05). Task-unrelated distractors modulated corticospinal coupling at ∼20 Hz. We propose that the distractors triggered covert startle-like responses, resulting in proprioceptive afference to the cortex, and that they also transiently disengaged the subject's attention from the fine-motor task. As a result, the corticospinal output was readjusted to keep the contraction force stable.

A Fuzzy Inference System for Closed-Loop Deep Brain Stimulation in Parkinson's Disease

Parkinsons disease is a complex neurodegenerative disorder for which patients present many symptoms, tremor being the main one. In advanced stages of the disease, Deep Brain Stimulation is a generalized therapy which can significantly improve the motor symptoms. However despite its beneficial effects on treating the symptomatology, the technique can be improved. One of its main limitations is that the parameters are fixed, and the stimulation is provided uninterruptedly, not taking into account any fluctuation in the patients state. A closed-loop system which provides stimulation by demand would adjust the stimulation to the variations in the state of the patient, stimulating only when it is necessary. It would not only perform a more intelligent stimulation, capable of adapting to the changes in real time, but also extending the devices battery life, thereby avoiding surgical interventions. In this work we design a tool that learns to recognize the principal symptom of Parkinsons disease and particularly the tremor. The goal of the designed system is to detect the moments the patient is suffering from a tremor episode and consequently to decide whether stimulation is needed or not. For that, local field potentials were recorded in the subthalamic nucleus of ten Parkinsonian patients, who were diagnosed with tremor-dominant Parkinsons disease and who underwent surgery for the implantation of a neurostimulator. Electromyographic activity in the forearm was simultaneously recorded, and the relation between both signals was evaluated using two different synchronization measures. The results of evaluating the synchronization indexes on each moment represent the inputs to the designed system. Finally, a fuzzy inference system was applied with the goal of identifying tremor episodes. Results are favourable, reaching accuracies of higher 98.7% in 70% of the patients.

Spatial variability in cortex-muscle coherence investigated with magnetoencephalography and high-density surface electromyography

Cortex-muscle coherence (CMC) reflects coupling between magnetoencephalography (MEG) and surface electromyography (sEMG), being strongest during isometric contraction but absent, for unknown reasons, in some individuals. We used a novel nonmagnetic high-density sEMG (HD-sEMG) electrode grid (36 mm × 12 mm; 60 electrodes separated by 3 mm) to study effects of sEMG recording site, electrode derivation, and rectification on the strength of CMC. Monopolar sEMG from right thenar and 306-channel whole-scalp MEG were recorded from 14 subjects during 4-min isometric thumb abduction. CMC was computed for 60 monopolar, 55 bipolar, and 32 Laplacian HD-sEMG derivations, and two derivations were computed to mimic "macroscopic" monopolar and bipolar sEMG (electrode diameter 9 mm; interelectrode distance 21 mm). With unrectified sEMG, 12 subjects showed statistically significant CMC in 91-95% of the HD-sEMG channels, with maximum coherence at ∼25 Hz. CMC was about a fifth stronger for monopolar than bipolar and Laplacian derivations. Monopolar derivations resulted in most uniform CMC distributions across the thenar and in tightest cortical source clusters in the left rolandic hand area. CMC was 19-27% stronger for HD-sEMG than for "macroscopic" monopolar or bipolar derivations. EMG rectification reduced the CMC peak by a quarter, resulted in a more uniformly distributed CMC across the thenar, and provided more tightly clustered cortical sources than unrectifed sEMGs. Moreover, it revealed CMC at ∼12 Hz. We conclude that HD-sEMG, especially with monopolar derivation, can facilitate detection of CMC and that individual muscle anatomy cannot explain the high interindividual CMC variability.

Quantification of Interictal Neuromagnetic Activity in Absence Epilepsy with Accumulated Source Imaging

Aberrant brain activity in childhood absence epilepsy (CAE) during seizures has been well recognized as synchronous 3 Hz spike-and-wave discharges on electroencephalography. However, brain activity from low- to very high-frequency ranges in subjects with CAE between seizures (interictal) has rarely been studied. Using a high-sampling rate magnetoencephalography (MEG) system, we studied ten subjects with clinically diagnosed but untreated CAE in comparison with age- and gender-matched controls. MEG data were recorded from all subjects during the resting state. MEG sources were assessed with accumulated source imaging, a new method optimized for localizing and quantifying spontaneous brain activity. MEG data were analyzed in nine frequency bands: delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-30 Hz), low-gamma (30-55 Hz), high-gamma (65-90 Hz), ripple (90-200 Hz), high-frequency oscillation (HFO, 200-1,000 Hz), and very high-frequency oscillation (VHFO, 1,000-2,000 Hz). MEG source imaging revealed that subjects with CAE had higher odds of interictal brain activity in 200-1,000 and 1,000-2,000 Hz in the parieto-occipito-temporal junction and the medial frontal cortices as compared with controls. The strength of the interictal brain activity in these regions was significantly elevated in the frequency bands of 90-200, 200-1,000 and 1,000-2,000 Hz for subjects with CAE as compared with controls. The results indicate that CAE has significantly aberrant brain activity between seizures that can be noninvasively detected. The measurements of high-frequency neuromagnetic oscillations may open a new window for investigating the cerebral mechanisms of interictal abnormalities in CAE.

Rectification is required to extract oscillatory envelope modulation from surface electromyographic signals

Rectification of surface electromyographic (EMG) recordings prior to their correlation with other signals is a widely used form of preprocessing. Recently this practice has come into question, elevating the subject of EMG rectification to a topic of much debate. Proponents for rectifying suggest it accentuates the EMG spike timing information, whereas opponents indicate it is unnecessary and its nonlinear distortion of data is potentially destructive. Here we examine the necessity of rectification on the extraction of muscle responses, but for the first time using a known oscillatory input to the muscle in the form of electrical vestibular stimulation. Participants were exposed to sinusoidal vestibular stimuli while surface and intramuscular EMG were recorded from the left medial gastrocnemius. We compared the unrectified and rectified surface EMG to single motor units to determine which method best identified stimulus-EMG coherence and phase at the single-motor unit level. Surface EMG modulation at the stimulus frequency was obvious in the unrectified surface EMG. However, this modulation was not identified by the fast Fourier transform, and therefore stimulus coherence with the unrectified EMG signal failed to capture this covariance. Both the rectified surface EMG and single motor units displayed significant coherence over the entire stimulus bandwidth (1–20 Hz). Furthermore, the stimulus-phase relationship for the rectified EMG and motor units shared a moderate correlation ( r = 0.56). These data indicate that rectification of surface EMG is a necessary step to extract EMG envelope modulation due to motor unit entrainment to a known stimulus.

Quantification of dexterity as the dynamical regulation of instabilities: comparisons across gender, age, and disease

Dexterous manipulation depends on using the fingertips to stabilize unstable objects. The Strength-Dexterity paradigm consists of asking subjects to compress a slender and compliant spring prone to buckling. The maximal level of compression [requiring low fingertip forces <300 grams force (gf)] quantifies the neural control capability to dynamically regulate fingertip force vectors and motions for a dynamic manipulation task. We found that finger dexterity is significantly affected by age (p = 0.017) and gender (p = 0.021) in 147 healthy individuals (66F, 81M, 20-88 years). We then measured finger dexterity in 42 hands of patients following treatment for osteoarthritis of the base of the thumb (CMC OA, 33F, 65.8 ± 9.7 years), and 31 hands from patients being treated for Parkinson's disease (PD, 6F, 10M, 67.68 ± 8.5 years). Importantly, we found no differences in finger compression force among patients or controls. However, we did find stronger age-related declines in performance in the patients with PD (slope -2.7 gf/year, p = 0.002) than in those with CMC OA (slope -1.4 gf/year, p = 0.015), than in controls (slope -0.86 gf/year). In addition, the temporal variability of forces during spring compression shows clearly different dynamics in the clinical populations compared to the controls (p < 0.001). Lastly, we compared dexterity across extremities. We found stronger age (p = 0.005) and gender (p = 0.002) effects of leg compression force in 188 healthy subjects who compressed a larger spring with the foot of an isolated leg (73F, 115M, 14-92 years). In 81 subjects who performed the tests with all four limbs separately, we found finger and leg compression force to be significantly correlated (females ρ = 0.529, p = 0.004; males ρ = 0.403, p = 0.003; 28F, 53M, 20-85 years), but surprisingly found no differences between dominant and non-dominant limbs. These results have important clinical implications, and suggest the existence - and compel the investigation - of systemic versus limb-specific mechanisms for dexterity.

High-density surface electromyography improves the identification of oscillatory synaptic inputs to motoneurons

Many studies have addressed corticomuscular coherence (CMC), but broad applications are limited by low coherence values and the variability across subjects and recordings. Here, we investigated how the use of high-density surface electromyography (HDsEMG) can improve the detection of CMC. Sixteen healthy subjects performed isometric contractions at six low-force levels using a pinch-grip, while HDsEMG of the adductor pollicis transversus and flexor and abductor pollicis brevis and whole-head magnetoencephalography were recorded. Different configurations were constructed from the HDsEMG grid, such as a bipolar and Laplacian montage, as well as a montage based on principal component analysis (PCA). CMC was estimated for each configuration, and the strength of coherence was compared across configurations. As expected, performance of the precision-grip task resulted in significant CMC in the β-frequency band (16-26 Hz). Compared with a bipolar EMG montage, all multichannel configurations obtained from the HDsEMG grid revealed a significant increase in CMC. The configuration, based on PCA, showed the largest (37%) increase. HDsEMG did not reduce the between-subject variability; rather, many configurations showed an increased coefficient of variation. Increased CMC presumably reflects the ability of HDsEMG to counteract inherent EMG signal factors-such as amplitude cancellation-which impact the detection of oscillatory inputs. In contrast, the between-subject variability of CMC most likely has a cortical origin.

Tibialis Anterior muscle coherence during controlled voluntary activation in patients with spinal cord injury: diagnostic potential for muscle strength, gait and spasticity

Background

Coherence estimation has been used as an indirect measure of voluntary neurocontrol of residual motor activity following spinal cord injury (SCI). Here intramuscular Tibialis Anterior (TA) coherence estimation was performed within specific frequency bands for the 10-60 Hz bandwidth during controlled ankle dorsiflexion in subjects with incomplete SCI with and without spasticity.

Methods

In the first cohort study 15 non-injured and 14 motor incomplete SCI subjects were recruited to evaluate TA coherence during controlled movement. Specifically 15-30 Hz EMG was recorded during dorsiflexion with: i) isometric activation at 50, 75 and 100% of maximal voluntary torque (MVT), ii) isokinetic activation at 60 and 120°/s and iii) isotonic dorsiflexion at 50% MVT. Following identification of the motor tasks necessary for measurement of optimal TA coherence a second cohort was analyzed within the 10-16 Hz, 15-30 Hz, 24-40 Hz and 40-60 Hz bandwidths from 22 incomplete SCI subjects, with and without spasticity.

Results

Intramuscular 40-60 Hz, but not 15-30 Hz TA, coherence calculated in SCI subjects during isometric activation at 100% of MVT was lower than the control group. In contrast only isometric activation at 100% of MVT 15-30 Hz TA coherence was higher in subjects with less severe SCI (AIS D vs. AIS C), and correlated functionally with dorsiflexion MVT. Higher TA coherence was observed for the SCI group during 120°/s isokinetic movement. In addition 15-30 Hz TA coherence calculated during isometric activation at 100% MVT or 120°/s isokinetic movement correlated moderately with walking function and time from SCI, respectively. Spasticity symptoms correlated negatively with coherence during isometric activation at 100% of MVT in all tested frequency bands, except for 15-30 Hz. Specifically, 10-16 Hz coherence correlated inversely with passive resistive torque to ankle dorsiflexion, while clinical measures of muscle hypertonia and spasm severity correlated inversely with 40-60 Hz.

Conclusion

Analysis of intramuscular 15-30 Hz TA coherence during isometric activation at 100% of MVT is related to muscle strength and gait function following incomplete SCI. In contrast several spasticity symptoms correlated negatively with 10-16 Hz and 40-60 Hz TA coherence during isometric activation at 100% MVT. Validation of the diagnostic potential of TA coherence estimation as a reliable and comprehensive measure of muscle strength, gait and spasticity should facilitate SCI neurorehabilation.

Reliability and agreement of intramuscular coherence in tibialis anterior muscle

Background

Neuroplasticity drives recovery of walking after a lesion of the descending tract. Intramuscular coherence analysis provides a way to quantify corticomotor drive during a functional task, like walking and changes in coherence serve as a marker for neuroplasticity. Although intramuscular coherence analysis is already applied and rapidly growing in interest, the reproducibility of variables derived from coherence is largely unknown. The purpose of this study was to determine the test-retest reliability and agreement of intramuscular coherence variables obtained during walking in healthy subjects.

Methodology/Principal Findings

Ten healthy participants walked on a treadmill at a slow and normal speed in three sessions. Area of coherence and peak coherence were derived from the intramuscular coherence spectra calculated using rectified and non-rectified M. tibialis anterior Electromyography (EMG). Reliability, defined as the ability of a measurement to differentiate between subjects and established by the intra-class correlation coefficient, was on the limit of good for area of coherence and peak coherence when derived from rectified EMG during slow walking. Yet, the agreement, defined as the degree to which repeated measures are identical, was low as the measurement error was relatively large. The smallest change to exceed the measurement error between two repeated measures was 66% of the average value. For normal walking and/or other EMG-processing settings, not rectifying the EMG and/or high-pass filtering with a high cutoff frequency (100 Hz) the reliability was only moderate to poor and the agreement was considerably lower.

Conclusions/significance

Only for specific conditions and EMG-processing settings, the derived coherence variables can be considered to be reliable measures. However, large changes (>66%) are needed to indicate a real difference. So, although intramuscular coherence is an easy to use and a sufficiently reliable tool to quantify intervention-induced neuroplasticity, the large effects needed to reveal a real change limit its practical use.

Oscillations in motor unit discharge are reflected in the low-frequency component of rectified surface EMG and the rate of change in force

Common drive to a motor unit (MU) pool manifests as low-frequency oscillations in MU discharge rate, producing fluctuations in muscle force. The aim of the study was to examine the temporal correlation between instantaneous MU discharge rate and rectified EMG in low frequencies. Additionally, we attempted to examine whether there is a temporal correlation between the low-frequency oscillations in MU discharge rate and the first derivative of force (dF/dt). Healthy young subjects produced steady submaximal force with their right finger as a single task or while maintaining a pinch-grip force with the left hand as a dual task. Surface EMG and fine-wire MU potentials were recorded from the first dorsal interosseous muscle in the right hand. Surface EMG was band-pass filtered (5-1,000 Hz) and full-wave rectified. Rectified surface EMG and the instantaneous discharge rate of MUs were smoothed by a Hann-window of 400 ms duration (equivalent to 2 Hz low-pass filtering). In each of the identified MUs, the smoothed MU discharge rate was positively correlated with the rectified-and-smoothed EMG as confirmed by the distinct peak in cross-correlation function with greater values in the dual task compared with the single task. Additionally, the smoothed MU discharge rate was temporally correlated with dF/dt more than with force and with rectified-and-smoothed EMG. The results indicated that the low-frequency component of rectified surface EMG and the first derivative of force provide temporal information on the low-frequency oscillations in the MU discharge rate.

Rectification of EMG in low force contractions improves detection of motor unit coherence in the beta-frequency band

Rectification of surface EMG before spectral analysis is a well-established preprocessing method used in the detection of motor unit firing patterns. A number of recent studies have called into question the need for rectification before spectral analysis, pointing out that there is no supporting experimental evidence to justify rectification. We present an analysis of 190 records from 13 subjects consisting of simultaneous recordings of paired single motor units and surface EMG from the extensor digitorum longus muscle during middle finger extension against gravity (unloaded condition) and against gravity plus inertial loading (loaded condition). We directly examine the hypothesis that rectified surface EMG is a better predictor of the frequency components of motor unit synchronization than the unrectified (or raw) EMG in the beta-frequency band (15-32 Hz). We use multivariate analysis and estimate the partial coherence between the paired single units using both rectified and unrectified surface EMG as a predictor. We use a residual partial correlation measure to quantify the difference between raw and rectified EMG as predictor and analyze unloaded and loaded conditions separately. The residual correlation for the unloaded condition is 22% with raw EMG and 3.5% with rectified EMG and for the loaded condition it is 5.2% with raw EMG and 1.4% with rectified EMG. We interpret these results as strong supporting experimental evidence in favor of using the preprocessing step of surface EMG rectification before spectral analysis.

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

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

The strength of the corticospinal coherence depends on the predictability of modulated isometric forces

Isometric compensation of predictably frequency-modulated low forces is associated with corticomuscular coherence (CMC) in beta and low gamma range. It remains unclear how the CMC is influenced by unpredictably modulated forces, which create a mismatch between expected and actual sensory feedback. We recorded electroencephalography from the contralateral hand motor area, electromyography (EMG), and the motor performance of 16 subjects during a visuomotor task in which they had to isometrically compensate target forces at 8% of the maximum voluntary contraction with their right index finger. The modulated forces were presented with predictable or unpredictable frequencies. We calculated the CMC, the cortical motor alpha-, beta-, and gamma-range spectral powers (SP), and the task-related desynchronization (TRD), as well as the EMG SP and the performance. We found that in the unpredictable condition the CMC was significantly lower and associated with lower cortical motor SP, stronger TRD, higher EMG SP, and worse performance. The findings suggest that due to the mismatch between predicted and actual sensory feedback leading to higher computational load and less stationary motor state, the unpredictable modulation of the force leads to a decrease in corticospinal synchrony, an increase in cortical and muscle activation, and a worse performance.

Rectification of SEMG as a tool to demonstrate synchronous motor unit activity during vibration

The use of surface electromyography (SEMG) in vibration studies is problematic since motion artifacts occupy the same frequency band with the SEMG signal containing information on synchronous motor unit activity. We hypothesize that using a harsher, 80-500 Hz band-pass filter and using rectification can help eliminate motion artifacts and provide a way to observe synchronous motor unit activity that is phase locked to vibration using SEMG recordings only. Multi Motor Unit (MMU) action potentials using intramuscular electrodes along with SEMG were recorded from the gastrocnemius medialis (GM) of six healthy male volunteers. Data were collected during whole body vibration, using vibration frequencies of 30 Hz, 35 Hz, 40 Hz or 50 Hz. A computer simulation was used to investigate the efficacy of filtering under different scenarios: with or without artifacts and/or motor unit synchronization. Our findings indicate that motor unit synchronization took place during WBV as verified by MMU recordings. A harsh filtering regimen along with rectification proved successful in demonstrating motor unit synchronization in SEMG recordings. Our findings were further supported by the results from the computer simulation, which indicated that filtering and rectification was efficient in discriminating motion artifacts from motor unit synchronization. We suggest that the proposed signal processing technique may provide a new methodology to evaluate the effects of vibration treatments using only SEMG. This is a major advantage, as this non-intrusive method is able to overcome movement artifacts and also indicate the synchronization of underlying motor units.

Essential tremor and tremor in Parkinson's disease are associated with distinct 'tremor clusters' in the ventral thalamus

Different tremor entities such as Essential Tremor (ET) or tremor in Parkinson's disease (PD) can be ameliorated by the implantation of electrodes in the ventral thalamus for Deep Brain Stimulation (DBS). The exact neural mechanisms underlying this treatment, as well as the specific pathophysiology of the tremor in both diseases to date remain elusive. Since tremor-related local field potentials (LFP) have been shown to cluster with a somatotopic representation in the subthalamic nucleus, we here investigated the neurophysiological correlates of tremor in the ventral thalamus in ET and PD using power and coherence analysis. Local field potentials (LFPs) at different recording depths and surface electromyographic signals (EMGs) from the extensor and flexor muscles of the contralateral forearm were recorded simultaneously in twelve ET and five PD patients. Data analysis revealed individual electrophysiological patterns of LFP-EMG coherence at single and double tremor frequency for each patient. Patterns observed varied in their spatial distribution within the Ventral lateral posterior nucleus of the thalamus (VLp), revealing a specific topography of 'tremor clusters' for PD and ET. The data strongly suggest that within VLp individual tremor-related electrophysiological signatures exist in ET and PD tremor.

Subthalamic nucleus stimulation restores the efferent cortical drive to muscle in parallel to functional motor improvement

Pathological synchronization in large-scale motor networks constitutes a pathophysiological hallmark of Parkinson's disease (PD). Corticomuscular synchronization in PD is pronounced in lower frequency bands (< 10 Hz), whereas efficient cortical motor integration in healthy persons is driven in the beta frequency range. Electroencephalogram and electromyogram recordings at rest and during an isometric precision grip task were performed in four perioperative sessions in 10 patients with PD undergoing subthalamic nucleus deep-brain stimulation: (i) 1 day before (D0); (ii) 1 day after (D1); (iii) 8 days after implantation of macroelectrodes with stimulation off (D8StimOff); and (iv) on (D8StimOn). Analyses of coherence and phase delays were performed in order to challenge the effects of microlesion and stimulation on corticomuscular coherence (CMC). Additionally, local field potentials recorded from the subthalamic nucleus on D1 allowed comprehensive mapping of motor-related synchronization in subthalamocortical and cerebromuscular networks. Motor performance improved at D8StimOn compared with D0 and D8StimOff paralleled by a reduction of muscular activity and CMC in the theta band (3.9-7.8 Hz) and by an increase of CMC in the low-beta band (13.7-19.5 Hz). Efferent motor cortical drives to muscle presented mainly below 10 Hz on D8StimOff that were suppressed on D8StimOn and occurred on higher frequencies from 13 to 45 Hz. On D1, coherence of the high-beta band (20.5-30.2 Hz) increased during movement compared with rest in subthalamomuscular and corticomuscular projections, whereas it was attenuated in subcorticocortical projections. The present findings lend further support to the concept of pathological network synchronization in PD that is beneficially modulated by stimulation.

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

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

Neural mechanisms of intermuscular coherence: implications for the rectification of surface electromyography

Oscillatory activity plays a crucial role in corticospinal control of muscle synergies and is widely investigated using corticospinal and intermuscular synchronization. However, the neurophysiological mechanisms that translate these rhythmic patterns into surface electromyography (EMG) are not well understood. This is underscored by the ongoing debate on the rectification of surface EMG before spectral analysis. Whereas empirical studies commonly rectify surface EMG, computational approaches have argued against it. In the present study, we employ a computational model to investigate the role of the motor unit action potential (MAUP) on the translation of oscillatory activity. That is, diverse MUAP shapes may distort the transfer of common input into surface EMG. We test this in a computational model consisting of two motor unit pools receiving common input and compare it to empirical results of intermuscular coherence between bilateral leg muscles. The shape of the MUAP was parametrically varied, and power and coherence spectra were investigated with and without rectification. The model shows that the effect of EMG rectification depends on the uniformity of MUAP shapes. When output spikes of different motor units are convolved with identical MUAPs, oscillatory input is evident in both rectified and nonrectified EMG. In contrast, a heterogeneous MAUP distribution distorts common input and oscillatory components are only manifest as periodic amplitude modulations, i.e., in rectified EMG. The experimental data showed that intermuscular coherence was mainly discernable in rectified EMG, hence providing empirical support for a heterogeneous distribution of MUAPs. These findings implicate that the shape of MUAPs is an essential parameter to reconcile experimental and computational approaches.

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.