Rectification and non-linear pre-processing of EMG signals for cortico-muscular analysis

Machine learning for hand pose classification from phasic and tonic EMG signals during bimanual activities in virtual reality

Myoelectric prostheses have recently shown significant promise for restoring hand function in individuals with upper limb loss or deficiencies, driven by advances in machine learning and increasingly accessible bioelectrical signal acquisition devices. Here, we first introduce and validate a novel experimental paradigm using a virtual reality headset equipped with hand-tracking capabilities to facilitate the recordings of synchronized EMG signals and hand pose estimation. Using both the phasic and tonic EMG components of data acquired through the proposed paradigm, we compare hand gesture classification pipelines based on standard signal processing features, convolutional neural networks, and covariance matrices with Riemannian geometry computed from raw or xDAWN-filtered EMG signals. We demonstrate the performance of the latter for gesture classification using EMG signals. We further hypothesize that introducing physiological knowledge in machine learning models will enhance their performances, leading to better myoelectric prosthesis control. We demonstrate the potential of this approach by using the neurophysiological integration of the "move command" to better separate the phasic and tonic components of the EMG signals, significantly improving the performance of sustained posture recognition. These results pave the way for the development of new cutting-edge machine learning techniques, likely refined by neurophysiology, that will further improve the decoding of real-time natural gestures and, ultimately, the control of myoelectric prostheses.

Muscle Recruitment Strategies in a Redundant Task: Age Differences Through Network Analyses

There are numerous studies comparing young and old adults in terms of muscle coordination in standard tasks (e.g., walking, reaching) and small variations of them. These tasks might hide differences: individuals would converge to similar behavior as they practice these throughout life. Also, we are unaware of studies that considered the muscle recruitment nested dynamics. For this reason, our study evaluated how young and old women coordinate and control the movement system while performing an unusual redundant motor control task through the network physiology approach. We acquired electromyographic signals from nine leg muscles of the dominant and non-dominant limbs during maximum voluntary isometric contractions (knee extension and flexion) and co-contraction bouts. Our results showed that young participants presented higher peak torque output, with similar EMG variability, compared to older participants. Considering firing rate frequencies, old and young women demonstrated different traits for network clustering and efficiency for the task. Age seems to affect muscle coordination at higher frequencies, even with a similar number of muscle synergies, indicating that younger women might have more integrated synergies than older women. The findings also point to differential muscle coordination adaptability.

Negative Myoclonus: Neurophysiological Study and Clinical Impact in Progressive Myoclonus Ataxia

INTRODUCTION

Negative myoclonus (NM) is an involuntary movement caused by a sudden interruption of muscular activity, resulting in gait problems and falls.

OBJECTIVE

To establish frequency, clinical impact, and neurophysiology of NM in progressive myoclonus ataxia (PMA) patients.

METHODS

Clinical, neurophysiological, and genetic data of 14 PMA individuals from University Medical Centre Groningen (UMCG) Expertise Center Movement Disorder Groningen were retrospectively collected. Neurophysiological examination included video-electromyography-accelerometry assessment in all patients and electroencephalography (EEG) examination in 13 individuals. Jerk-locked (or silent period-locked) back-averaging and cortico-muscular coherence (CMC) analysis aided the classification of myoclonus.

RESULTS

NM was present in 6 (NM+) and absent in 8 (NM-) PMA patients. NM+ individuals have more frequent falls (100% vs. 37.5%) and higher scores on the Gross Motor Function Classification System (GMFCS) (4.3 ±0.74 vs. 2.5 ±1.2) than NM- individuals. Genetic background of NM+ included GOSR2 and SEMA6B, while that of NM- included ATM, KCNC3, NUS1, STPBN2, and GOSR2. NM was frequently preceded by positive myoclonus (PM) and silent-period length was between 88 and 194 ms. EEG epileptiform discharges were associated with NM in 2 cases. PM was classified as cortical in 5 NM+ and 2 NM- through EEG inspection, jerk-locked back-averaging, or CMC analysis.

DISCUSSION

Neurophysiological examination is crucial for detecting NM that could be missed on clinical examination due to a preceding PM. Evidence points to a cortical origin of NM, an association with more severe motor phenotype, and suggests the presence of genetic disorders causing either a PMA or progressive myoclonus epilepsy, rather than pure PMA phenotype. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

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.

Vertebral level specific modulation of paraspinal muscle activity based on vestibular signals during walking

Evoking muscle responses by electrical vestibular stimulation (EVS) may help to understand the contribution of the vestibular system to postural control. Although paraspinal muscles play a role in postural stability, the vestibulo-muscular coupling of these muscles during walking has rarely been studied. This study aimed to investigate how vestibular signals affect paraspinal muscle activity at different vertebral levels during walking with preferred and narrow step width. Sixteen healthy participants were recruited. Participants walked on a treadmill for 8 min at 78 steps/min and 2.8 km/h, at two different step width, either with or without EVS. Bipolar electromyography was recorded bilaterally from the paraspinal muscles at eight vertebral levels from cervical to lumbar. Coherence, gain, and delay of EVS and EMG responses were determined. Significant EVS-EMG coupling (P < 0.01) was found at ipsilateral and/or contralateral heel strikes. This coupling was mirrored between left and right relative to the midline of the trunk and between the higher and lower vertebral levels, i.e. a peak occurred at ipsilateral heel strike at lower levels, whereas it occurred at contralateral heel strike at higher levels. EVS-EMG coupling only partially coincided with peak muscle activity. EVS-EMG coherence slightly, but not significantly, increased when walking with narrow steps. No significant differences were found in gain and phase between the vertebral levels or step width conditions. In summary, vertebral level specific modulation of paraspinal muscle activity based on vestibular signals might allow a fast, synchronized, and spatially co-ordinated response along the trunk during walking. KEY POINTS: Mediolateral stabilization of gait requires an estimate of the state of the body, which is affected by vestibular afference. During gait, the heavy trunk segment is controlled by phasic paraspinal muscle activity and in rodents the medial and lateral vestibulospinal tracts activate these muscles. To gain insight in vestibulospinal connections in humans and their role in gait, we recorded paraspinal surface EMG of cervical to lumbar paraspinal muscles, and characterized coherence, gain and delay between EMG and electrical vestibular stimulation, during slow walking. Vestibular stimulation caused phasic, vertebral level specific modulation of paraspinal muscle activity at delays of around 40 ms, which was mirrored between left, lower and right, upper vertebral levels. Our results indicate that vestibular afference causes fast, synchronized, and spatially co-ordinated responses of the paraspinal muscles along the trunk, that simultaneously contribute to stabilizing the centre of mass trajectory and to keeping the head upright.

Cortico-muscular connectivity is modulated by passive and active Lokomat-assisted Gait

The effects of robotic-assisted gait (RAG) training, besides conventional therapy, on neuroplasticity mechanisms and cortical integration in locomotion are still uncertain. To advance our knowledge on the matter, we determined the involvement of motor cortical areas in the control of muscle activity in healthy subjects, during RAG with Lokomat, both with maximal guidance force (100 GF-passive RAG) and without guidance force (0 GF-active RAG) as customary in rehabilitation treatments. We applied a novel cortico-muscular connectivity estimation procedure, based on Partial Directed Coherence, to jointly study source localized EEG and EMG activity during rest (standing) and active/passive RAG. We found greater cortico-cortical connectivity, with higher path length and tendency toward segregation during rest than in both RAG conditions, for all frequency bands except for delta. We also found higher cortico-muscular connectivity in distal muscles during swing (0 GF), and stance (100 GF), highlighting the importance of direct supraspinal control to maintain balance, even when gait is supported by a robotic exoskeleton. Source-localized connectivity shows that this control is driven mainly by the parietal and frontal lobes. The involvement of many cortical areas also in passive RAG (100 GF) justifies the use of the 100 GF RAG training for neurorehabilitation, with the aim of enhancing cortical-muscle connections and driving neural plasticity in neurological patients.

Intermuscular Coherence during Quiet Standing in Sub-Acute Patients after Stroke: An Exploratory Study

Asymmetrically impaired standing control is a prevalent disability among stroke patients; however, most of the neuromuscular characteristics are unclear. Therefore, the main purpose of this study was to investigate between-limb differences in intermuscular coherence during quiet standing. Consequently, 15 patients who had sub-acute stroke performed a quiet standing task without assistive devices, and electromyography was measured on the bilateral tibialis anterior (TA), soleus (SL), and medial gastrocnemius (MG). The intermuscular coherence of the unilateral synergistic (SL-MG) pair and unilateral antagonist (TA-SL and TA-MG) pairs in the delta (0-5 Hz) and beta (15-35 Hz) bands were calculated and compared between the paretic and non-paretic limbs. The unilateral synergistic SL-MG coherence in the beta band was significantly greater in the non-paretic limb than in the paretic limb (p = 0.017), while unilateral antagonist TA-MG coherence in the delta band was significantly greater in the paretic limb than in the non-paretic limb (p < 0.01). During quiet standing, stroke patients showed asymmetry in the cortical control of the plantar flexor muscles, and synchronous control between the antagonistic muscles was characteristic of the paretic limb. This study identified abnormal muscle activity patterns and asymmetrical cortical control underlying impaired standing balance in patients with sub-acute stroke using an intermuscular coherence analysis.

Beat encoding at mistuned octaves within single electrosensory neurons

Beats are slow periodic amplitude modulations resulting from the superposition of two spectrally close periodic signals. The difference frequency between the signals sets the frequency of the beat. A field study in the electric fish Apteronotus rostratus showed the behavioral relevance of very high difference frequencies. Contrary to expectations from previous studies, our electrophysiological data show strong responses of p-type electroreceptor afferents whenever the difference frequency approaches integer multiples (mistuned octaves) of the fish's own electric field frequency (carrier). Mathematical reasoning and simulations show that common approaches to extract amplitude modulations, such as Hilbert transform or half-wave rectification, are not sufficient to explain the responses at carrier octaves. Instead, half-wave rectification needs to be smoothed out, for example by a cubic function. Because electroreceptive afferents share many properties with auditory nerve fibers, these mechanisms may underly the human perception of beats at mistuned octaves as described by Ohm and Helmholtz.

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.

Muscle activation patterns and muscle synergies reflect different modes of coordination during upper extremity movement

A core issue in motor control is how the central nervous system generates and selects the muscle activation patterns necessary to achieve a variety of behaviors and movements. Extensive studies have verified that it is the foundation to induce a complex movement by the modular combinations of several muscles with a synergetic relationship. However, a few studies focus on the synergetic similarity and dissimilarity among different types of movements, especially for the upper extremity movements. In this study, we introduced the non-negative matrix factorization (NMF) method to explore the muscle activation patterns and synergy structure under 6 types of movements, involving the hand open (HO), hand close (HC), wrist flexion (WF), wrist extension (WE), supination (SU), and pronation (PR). For this, we enrolled 10 healthy subjects to record the electromyography signal for NMF calculation. The results showed a highly modular similarity of the muscle synergy among subjects under the same movement. Furthermore, Spearman's correlation analysis indicated significant similarities among HO-WE, HO-SU, and WE-SU (p < 0.001). Additionally, we also found shared synergy and special synergy in activation patterns among different movements. This study confirmed the theory of modular structure in the central nervous system, which yields a stable synergetic pattern under the same movement. Our findings on muscle synergy will be of great significance to motor control and even to clinical assessment techniques.

Modulation of lower limb muscles and trajectory correction in the bipedal stance during visual perturbation

The ability to actively track posture using visual targets as indicators is important for improving impairments in whole-body coordination, and accurate visual feedback on tasks is considered effective in promoting sensory-motor integration and behavioral success. In the present study, we examined inter- and intramuscular modulation between the two lower limbs in response to visual perturbation. Sixteen healthy young subjects (age: 21.3 ± 0.7 years) were asked to move their weight back and forth while tracking a visual target displayed on a monitor in front of them for 30 s. Three types of target movements were examined: a sinusoidal wave (i.e., a predictable pattern), more complex patterns (random), and no movement (stationary). Electromyography (EMG) was used to assess intra- and intermuscular coherence modulation of the plantar flexor muscles (right and left soleus and right and left medial gastrocnemius). The ability to adjust posture to follow the target signal was assessed using a stabilometer. Inter- and intramuscular coherence increased during the visual perturbation task compared to the stationary task. In addition, left-right differences in lower limb modulation were observed during the visual perturbation task. Furthermore, interlimb coherence was related to the motor accuracy of tracking. The muscles of both lower limbs cooperated in response to visual perturbation, suggesting that these muscles control visually induced anteroposterior postural sway. Since such visual perturbations promote coordination between both lower extremities, this relationship may indicate the potential for rehabilitation training to help individuals acquire and improve the motor functions necessary to efficiently and stably perform activities of daily living.

Sensorimotor recalibration of postural control strategies occurs after whole body vibration

Efficient postural control results from an effective interplay between sensory feedbacks integration and muscle modulation and can be affected by ageing and neuromuscular injuries. With this study, we investigated the effect of whole-body vibratory stimulation on postural control strategies employed to maintain an upright posture. We explored both physiological and posturography metrics, through corticomuscular and intramuscular coherence, and muscle networks analyses. The stimulation disrupts balance in the short term, but leads to a greater contribution of cortical activity, necessary to modulate muscle activation via the formation of (new) synergies. We also observed a reconfiguration of muscle recruitment patterns that returned to pre-stimulation levels after few minutes, accompanied by a slight improvement of balance in the anterior-posterior direction. Our results suggest that, in the context of postural control, appropriate mechanical stimulation is capable of triggering a recalibration of the sensorimotor set and might offer new perspectives for motor re-education.

Neuromuscular adaptations after osseointegration of a bone-anchored prosthesis in a unilateral transfemoral amputee - a case study

PURPOSE

Many individuals with a lower limb amputation experience problems with the fitting of the socket of their prosthesis, leading to dissatisfaction or device rejection. Osseointegration (OI)- the implantation of a shaft directly interfacing with the remaining bone- is an alternative for these patients. In this observational study, we investigated how bone anchoring influences neuromuscular parameters during balance control in a patient with a unilateral transfemoral amputation.

MATERIAL AND METHODS

Center of pressure (CoP) and electromyography (EMG) signals from muscles controlling the hip and the ankle of the intact leg were recorded during quiet standing six months before and one and a half years after this patient underwent an OI surgery. Results were compared to a control group of nine able-bodied individuals.

RESULTS

Muscle co-activation and EMG intensity decreased after bone anchoring, approaching the levels of able-bodied individuals. Muscle co-activation controlling the ankle decreased in the high-frequency range, and the EMG intensity spectrum decreased in the lower-frequency range for all muscles when vision was allowed. With eyes closed, the ankle extensor muscle showed an increased EMG intensity in the high-frequency range post-surgery. CoP length increased in the mediolateral direction of the amputated leg.

CONCLUSIONS

These findings point to shifts in the patient's neuromuscular profile towards the one of able-bodied individuals.

Lateralised dynamic modulations of corticomuscular coherence associated with bimanual learning of rhythmic patterns

Human movements are spontaneously attracted to auditory rhythms, triggering an automatic activation of the motor system, a central phenomenon to music perception and production. Cortico-muscular coherence (CMC) in the theta, alpha, beta and gamma frequencies has been used as an index of the synchronisation between cortical motor regions and the muscles. Here we investigated how learning to produce a bimanual rhythmic pattern composed of low- and high-pitch sounds affects CMC in the beta frequency band. Electroencephalography (EEG) and electromyography (EMG) from the left and right First Dorsal Interosseus and Flexor Digitorum Superficialis muscles were concurrently recorded during constant pressure on a force sensor held between the thumb and index finger while listening to the rhythmic pattern before and after a bimanual training session. During the training, participants learnt to produce the rhythmic pattern guided by visual cues by pressing the force sensors with their left or right hand to produce the low- and high-pitch sounds, respectively. Results revealed no changes after training in overall beta CMC or beta oscillation amplitude, nor in the correlation between the left and right sides for EEG and EMG separately. However, correlation analyses indicated that left- and right-hand beta EEG-EMG coherence were positively correlated over time before training but became uncorrelated after training. This suggests that learning to bimanually produce a rhythmic musical pattern reinforces lateralised and segregated cortico-muscular communication.

A Waveform-Independent Measure of Recurrent Neural Activity

Rhythmic neural activity, so-called oscillations, plays a key role in neural information transmission, processing, and storage. Neural oscillations in distinct frequency bands are central to physiological brain function, and alterations thereof have been associated with several neurological and psychiatric disorders. The most common methods to analyze neural oscillations, e.g., short-time Fourier transform or wavelet analysis, assume that measured neural activity is composed of a series of symmetric prototypical waveforms, e.g., sinusoids. However, usually, the models generating the signal, including waveform shapes of experimentally measured neural activity are unknown. Decomposing asymmetric waveforms of nonlinear origin using these classic methods may result in spurious harmonics visible in the estimated frequency spectra. Here, we introduce a new method for capturing rhythmic brain activity based on recurrences of similar states in phase-space. This method allows for a time-resolved estimation of amplitude fluctuations of recurrent activity irrespective of or specific to waveform shapes. The algorithm is derived from the well-established field of recurrence analysis, which, in comparison to Fourier-based analysis, is still very uncommon in neuroscience. In this paper, we show its advantages and limitations in comparison to short-time Fourier transform and wavelet convolution using periodic signals of different waveform shapes. Furthermore, we demonstrate its application using experimental data, i.e., intracranial and noninvasive electrophysiological recordings from the human motor cortex of one epilepsy patient and one healthy adult, respectively.

Inter-muscular coherence and functional coordination in the human upper extremity after stroke

Muscle coordination and motor function of stroke patients are weakened by stroke-related motor impairments. Our earlier studies have determined alterations in inter-muscular coordination patterns (muscle synergies). However, the functional connectivity of these synergistically paired or unpaired muscles is still unclear in stroke patients. The goal of this study is to quantify the alterations of inter-muscular coherence (IMC) among upper extremity muscles that have been shown to be synergistically or non-synergistically activated in stroke survivors. In a three-dimensional isometric force matching task, surface EMG signals are collected from 6 age-matched, neurologically intact healthy subjects and 10 stroke patients, while the target force space is divided into 8 subspaces. According to the results of muscle synergy identification with non-negative matrix factorization algorithm, muscle pairs are classified as synergistic and non-synergistic. In both control and stroke groups, IMC is then calculated for all available muscle pairs. The results show that synergistic muscle pairs have higher coherence in both groups. Furthermore, anterior and middle deltoids, identified as synergistic muscles in both groups, exhibited significantly weaker IMC at alpha band in stroke patients. The anterior and posterior deltoids, identified as synergistic muscles only in stroke patients, revealed significantly higher IMC in stroke group at low gamma band. On the contrary, anterior deltoid and pectoralis major, identified as synergistic muscles in control group only, revealed significantly higher IMC in control group in alpha band. The results of muscle synergy and IMC analyses provide congruent and complementary information for investigating the mechanism that underlies post-stroke motor recovery.

Unilateral transfemoral amputees exhibit altered strength and dynamics of muscular co-activation modulated by visual feedback

OBJECTIVE

Somatosensory perception is disrupted in patients with a lower limb amputation. This increases the difficulty to maintain balance and leads to the development of neuromuscular adjustments. We investigated how these adjustments are reflected in the co-activation of lower body muscles and are modulated by visual feedback.

APPROACH

We measured electromyography (EMG) signals of muscles from the trunk (erector spinae and obliquus external), and the lower intact/dominant leg (tibialis anterior and medial gastrocnemius) in eleven unilateral transfemoral amputees and eleven age-matched able-bodied controls during 30 seconds of upright standing with and without visual feedback. Muscle synergies involved in balance control were investigated using wavelet coherence analysis. We focused on 7 frequencies grouped in three frequency bands, a low-frequency band (7.56 and 19.86 Hz) representing more sub-cortical and spinal inputs to the muscles, a mid-frequency band (38.26 and 62.63 Hz) representing more cortical inputs, and a high-frequency band (92.90, 129 and 170.90 Hz) associated with synchronizing motor unit action potentials. Further, the dynamics of changes in intermuscular coupling over time were quantified using the Entropic Half-Life.

MAIN RESULTS

Amputees exhibited lower coherency values when vision was removed at 7.56 Hz for the muscle pair of the lower leg. At this frequency, the coherency values of the amputee group also differed from controls for the eyes closed condition. Controls and amputees exhibited opposite coherent behaviors with visual feedback at 7.56 Hz. For the eyes open condition at 129 Hz, the coherency values of amputees and controls differed for the muscle pair of the trunk, and at 170.90 Hz for the muscle pair of the lower leg. Amputees exhibited different dynamics of muscle co-activation at the low frequency band when vision was available.

SIGNIFICANCE

Altogether, these findings point to the development of neuromuscular adaptations reflected in the strength and dynamics of muscular co-activation.

Body Weight Control Is a Key Element of Motor Control for Toddlers' Walking

New-borns can step when supported for about 70-80% of their own body weight. Gravity-related sensorimotor information might be an important factor in developing the ability to walk independently. We explored how body weight support alters motor control in toddlers during the first independent steps and in toddlers with about half a year of walking experience. Sixteen different typically developing children were assessed during (un)supported walking on a running treadmill. Electromyography of 18-24 bilateral leg and back muscles and vertical ground reaction forces were recorded. Strides were grouped into four levels of body weight support ranging from no (<10%), low (10-35%), medium (35-55%), and high (55-95%) support. We constructed muscle synergies and muscle networks and assessed differences between levels of support and between groups. In both groups, muscle activities could be described by four synergies. As expected, the mean activity decreased with body weight support around foot strikes. The younger first-steps group showed changes in the temporal pattern of the synergies when supported for more than 35% of their body weight. In this group, the muscle network was dense with several interlimb connections. Apparently, the ability to process gravity-related information is not fully developed at the onset of independent walking causing motor control to be fairly disperse. Synergy-specific sensitivity for unloading implies distinct neural mechanisms underlying (the emergence of) these synergies.

Establishing the Role of Elbow Muscles by Evaluating Muscle Activation and Co-contraction Levels at Maximal External Rotation in Fastball Pitching

Background: Baseball pitching is associated with a high prevalence of ulnar collateral ligament injuries, potentially due to the high external valgus load on the medial side of the elbow at the instant of maximal shoulder external rotation (MER). In-vitro studies show that external valgus torque is resisted by the ulnar collateral ligament but could also be compensated by elbow muscles. As the potential active contribution of these muscles in counteracting external valgus load during baseball pitching is unknown, the aim of this study is to determine whether and to what extent the elbow muscles are active at and around MER during a fastball pitch in baseball.

Methods: Eleven uninjured pitchers threw 15 fastball pitches. Surface electromyography of six muscles crossing the elbow were measured at 2000 Hz. Electromyography signals were normalized to maximal activity values. Co-contraction index (CCI) was calculated between two pairs of the flexor and extensor elbow muscles. Confidence intervals were calculated at the instant of MER. Four ranges of muscle activity were considered; 0–20% was considered low; 21–40% moderate; 41–60% high and over 60% as very high. To determine MER, the pitching motion was captured with a highspeed camera at 240 Hz.

Results: The flexor pronator mass, pronator teres, triceps brachii, biceps brachii, extensor supinator mass and anconeus show moderate activity at MER. Considerable variation between participants was found in all muscles. The CCI revealed co-contraction of the two flexor-extensor muscle pairs at MER.

Interpretation: The muscle activation of the flexor and pronator muscles at MER indicates a direct contribution of forearm muscles crossing the medial side of the elbow in counteracting the external valgus load during fastball pitching. The activation of both flexor and extensor muscles indicates an in-direct contributory effect as the combined activity of these muscles counteract opening of the humeroulnar joint space. We believe that active muscular contributions counteracting the elbow valgus torque can be presumed to relieve the ulnar collateral ligament from maximal stress and are thus of importance in injury risk assessment in fastball pitching in baseball.

Input Zone-Selective Dysrhythmia in Motor Thalamus after Dopamine Depletion

The cerebral cortex, basal ganglia and motor thalamus form circuits important for purposeful movement. In Parkinsonism, basal ganglia neurons often exhibit dysrhythmic activity during, and with respect to, the slow (∼1 Hz) and beta-band (15-30 Hz) oscillations that emerge in cortex in a brain state-dependent manner. There remains, however, a pressing need to elucidate the extent to which motor thalamus activity becomes similarly dysrhythmic after dopamine depletion relevant to Parkinsonism. To address this, we recorded single-neuron and ensemble outputs in the basal ganglia-recipient zone (BZ) and cerebellar-recipient zone (CZ) of motor thalamus in anesthetized male dopamine-intact rats and 6-OHDA-lesioned rats during two brain states, respectively defined by cortical slow-wave activity and activation. Two forms of thalamic input zone-selective dysrhythmia manifested after dopamine depletion: (1) BZ neurons, but not CZ neurons, exhibited abnormal phase-shifted firing with respect to cortical slow oscillations prevalent during slow-wave activity; and (2) BZ neurons, but not CZ neurons, inappropriately synchronized their firing and engaged with the exaggerated cortical beta oscillations arising in activated states. These dysrhythmias were not accompanied by the thalamic hypoactivity predicted by canonical firing rate-based models of circuit organization in Parkinsonism. Complementary recordings of neurons in substantia nigra pars reticulata suggested that their altered activity dynamics could underpin the BZ dysrhythmias. Finally, pharmacological perturbations demonstrated that ongoing activity in the motor thalamus bolsters exaggerated beta oscillations in motor cortex. We conclude that BZ neurons are selectively primed to mediate the detrimental influences of abnormal slow and beta-band rhythms on circuit information processing in Parkinsonism.SIGNIFICANCE STATEMENT Motor thalamus neurons mediate the influences of basal ganglia and cerebellum on the cerebral cortex to govern movement. Chronic depletion of dopamine from the basal ganglia causes some symptoms of Parkinson's disease. Here, we elucidate how dopamine depletion alters the ways motor thalamus neurons engage with two distinct oscillations emerging in cortico-basal ganglia circuits in vivo We discovered that, after dopamine depletion, neurons in the thalamic zone receiving basal ganglia inputs are particularly prone to becoming dysrhythmic, changing the phases and/or synchronization (but not rate) of their action potential firing. This bolsters cortical dysrhythmia. Our results provide important new insights into how aberrant rhythmicity in select parts of motor thalamus could detrimentally affect neural circuit dynamics and behavior in Parkinsonism.

An Objective, Information-Based Approach for Selecting the Number of Muscle Synergies to be Extracted via Non-Negative Matrix Factorization

Muscle synergy analysis is a useful tool for the evaluation of the motor control strategies and for the quantification of motor performance. Among the parameters that can be extracted, most of the information is included in the rank of the modular control model (i.e. the number of muscle synergies that can be used to describe the overall muscle coordination). Even though different criteria have been proposed in literature, an objective criterion for the model order selection is needed to improve reliability and repeatability of MSA results. In this paper, we propose an Akaike Information Criterion (AIC)-based method for model order selection when extracting muscle synergies via the original Gaussian Non-Negative Matrix Factorization algorithm. The traditional AIC definition has been modified based on a correction of the likelihood term, which includes signal dependent noise on the neural commands, and a Discrete Wavelet decomposition method for the proper estimation of the number of degrees of freedom of the model, reduced on a synergy-by-synergy and event-by-event basis. We tested the performance of our method in comparison with the most widespread ones, proving that our criterion is able to yield good and stable performance in selecting the correct model order in simulated EMG data. We further evaluated the performance of our AIC-based technique on two distinct experimental datasets confirming the results obtained with the synthetic signals, with performances that are stable and independent from the nature of the analysed task, from the signal quality and from the subjective EMG pre-processing steps.

Can Corticomuscular Coherence Differentiate between REM Sleep Behavior Disorder with or without Parkinsonism?

REM sleep behavior disorder (RBD) could be a predictor of Parkinsonism even before development of typical motor symptoms. This study aims to characterize clinical features and corticomuscular and corticocortical coherence (CMC and CCC, respectively) during sleep in RBD patients with or without Parkinsonism. We enrolled a total of 105 subjects, including 20 controls, 54 iRBD, and 31 RBD+P patients, patients who were diagnosed as idiopathic RBD (iRBD) and RBD with Parkinsonism (RBD+P) in our neurology department. We analyzed muscle atonia index (MAI) and CMC between EEG and chin/limb muscle electromyography (EMG) and CCC during different sleep stages. Although differences in the CMC of iRBD group were observed only during REM sleep, MAI differences between groups were noted during both REM and NREM N2 stage sleep. During REM sleep, CMC was higher and MAI was reduced in iRBD patients compared to controls (p = 0.001, p < 0.001, respectively). Interestingly, MAI was more reduced in RBD+P compared to iRBD patients. In comparison, CCC was higher in iRBD patients compared to controls whereas CCC was lower in RBD+P groups compared to control and iRBD groups in various frequency bands during both NREM N2 and REM sleep stages. Among them, increased CMC during REM sleep revealed correlation between clinical severities of RBD symptoms. Our findings indicate that MAI, CMC, and CCC showed distinctive features in iRBD and RBD+P patients compared to controls, suggesting potential usefulness to understand possible links between these diseases.

Disrupted cortico-peripheral interactions in motor disorders

Motor disorders may arise from neurological damage or diseases at different levels of the hierarchical motor control system and side-loops. Altered cortico-peripheral interactions might be essential characteristics indicating motor dysfunctions. By integrating cortical and peripheral responses, top-down and bottom-up cortico-peripheral coupling measures could provide new insights into the motor control and recovery process. This review first discusses the neural bases of cortico-peripheral interactions, and corticomuscular coupling and corticokinematic coupling measures are addressed. Subsequently, methodological efforts are summarized to enhance the modeling reliability of neural coupling measures, both linear and nonlinear approaches are introduced. The latest progress, limitations, and future directions are discussed. Finally, we emphasize clinical applications of cortico-peripheral interactions in different motor disorders, including stroke, neurodegenerative diseases, tremor, and other motor-related disorders. The modified interaction patterns and potential changes following rehabilitation interventions are illustrated. Altered coupling strength, modified coupling directionality, and reorganized cortico-peripheral activation patterns are pivotal attributes after motor dysfunction. More robust coupling estimation methodologies and combination with other neurophysiological modalities might more efficiently shed light on motor control and recovery mechanisms. Future studies with large sample sizes might be necessary to determine the reliabilities of cortico-peripheral interaction measures in clinical practice.

A novel delay estimation method for improving corticomuscular coherence in continuous synchronization events

OBJECTIVE

While the corticomuscular coupling between motor cortex and muscle tissue has received considerable attention, which is typically quantitative measure to evaluate neural signals synchronization in the motor control system, little work has been published regarding the effect of underlying delay of two coupled physiological signals on coherence.

METHODS

In this study, we developed a novel delay estimation method, named rate of voxels change (RVC), detecting time delay in two coupled physiological signals. Based on RVC framework, delay compensation was used to adjust magnitude squared coherence (MSC) image. To illustrate the effectiveness of the RVC method, we compared the estimated delays and the adjusted MSC results based on RVC method and corticomuscular coherence with time lag (CMCTL) method.

RESULTS

The simulation results suggested that RVC method was not only superior to the CMCTL method in estimating different time delays, but also has better optimization effect on MSC image. The experimental results further confirmed that delay estimated by the proposed RVC method was more in line with the underlying physiology (controls: 22.8 ms vs patients: 34.5 ms). Meanwhile, RVC-based delay compensation could significantly optimize the MSC of specific regions.

SIGNIFICANCE

This study proved that RVC has remarkably higher reliability in detecting time delay between coupled neurophysiological signals, and the application of RVC was an improvement on the previous studies that mainly focused on biased MSC estimation.

Context-Dependent Modulation of Corticomuscular Coherence in a Series of Motor Initiation and Maintenance of Voluntary Contractions

For our precise motor control, we should consider "motor context," which involves the flow from feedforward to feedback control. The present study focused on corticomuscular coherence (CMC) to physiologically evaluate how the sensorimotor integration is modulated in a series of movements depending on the motor context. We evaluated CMC between electroencephalograms over the sensorimotor cortex and rectified electromyograms from the tibialis anterior muscle during intermittent contractions with 2 contraction intensities in 4 experiments. Although sustained contractions with weak-to-moderate intensities led to no difference in CMC between intensities, intermittent ballistic-and-hold contractions with 2 intensities (10% and 15% or 25% of the maximal voluntary contraction, MVC) presented in a randomized order resulted in greater magnitude of CMC for the weaker intensity. Moreover, the relative amount of initial error was larger for trials with 10% of MVC, which indicated that initial motor output was inaccurate during weaker contractions. However, this significant difference in CMC vanished in the absence of trial randomization or the application of intermittent ramp-and-hold contractions with slower torque developments. Overall, CMC appears to be modulated context-dependently and is especially enhanced when active sensorimotor integration is required in feedback control periods because of the complexity and inaccuracy of preceding motor control.

Electroencephalogram-Electromyogram Functional Coupling and Delay Time Change Based on Motor Task Performance

Synchronous correlation brain and muscle oscillations during motor task execution is termed as functional coupling. Functional coupling between two signals appears with a delay time which can be used to infer the directionality of information flow. Functional coupling of brain and muscle depends on the type of muscle contraction and motor task performance. Although there have been many studies of functional coupling with types of muscle contraction and force level, there has been a lack of investigation with various motor task performances. Motor task types play an essential role that can reflect the amount of functional interaction. Thus, we examined functional coupling under four different motor tasks: real movement, intention, motor imagery and movement observation tasks. We explored interaction of two signals with linear and nonlinear information flow. The aim of this study is to investigate the synchronization between brain and muscle signals in terms of functional coupling and delay time. The results proved that brain–muscle functional coupling and delay time change according to motor tasks. Quick synchronization of localized cortical activity and motor unit firing causes good functional coupling and this can lead to short delay time to oscillate between signals. Signals can flow with bidirectionality between efferent and afferent pathways.

Dynamic modulation of cortico-muscular coupling during real and imagined sensorimotor synchronisation

People have a natural and intrinsic ability to coordinate body movements with rhythms surrounding them, known as sensorimotor synchronisation. This can be observed in daily environments, when dancing or singing along with music, or spontaneously walking, talking or applauding in synchrony with one another. However, the neurophysiological mechanisms underlying accurately synchronised movement with selected rhythms in the environment remain unclear. Here we studied real and imagined sensorimotor synchronisation with interleaved auditory and visual rhythms using cortico-muscular coherence (CMC) to better understand the processes underlying the preparation and execution of synchronised movement. Electroencephalography (EEG), electromyography (EMG) from the finger flexors, and continuous force signals were recorded in 20 participants during tapping and imagined tapping with discrete stimulus sequences consisting of alternating auditory beeps and visual flashes. The results show that the synchronisation between cortical and muscular activity in the beta (14-38 Hz) frequency band becomes time-locked to the taps executed in synchrony with the visual and auditory stimuli. Dynamic modulation in CMC also occurred when participants imagined tapping with the visual stimuli, but with lower amplitude and a different temporal profile compared to real tapping. These results suggest that CMC does not only reflect changes related to the production of the synchronised movement, but also to its preparation, which appears heightened under higher attentional demands imposed when synchronising with the visual stimuli. These findings highlight a critical role of beta band neural oscillations in the cortical-muscular coupling underlying sensorimotor synchronisation.

Alterations in Muscle Networks in the Upper Extremity of Chronic Stroke Survivors

Muscle networks describe the functional connectivity between muscles quantified through the decomposition of intermuscular coherence (IMC) to identify shared frequencies at which certain muscles are co-modulated by common neural input. Efforts have been devoted to characterizing muscle networks in healthy subjects but stroke-linked alterations to muscle networks remain unexplored. Muscle networks were assessed for eight key upper extremity muscles during isometric force generation in stroke survivors with mild, moderate, and severe impairment and compared against healthy controls to identify stroke-specificalterations in muscle connectivity. Coherence matrices were decomposed using non-negative matrix factorization. The variance accounted for thresholding was then assessed to identify the number of muscle networks. Results showed that the number of muscle networks decreased in stroke survivors compared to age-matched healthy controls (four networks in the healthy control group) as the severity of post-stroke motor impairment increased (three in the mild- and two in the moderate- and severe-strokegroups). Statistically significant reductions of IMC in the synergistic deltoid muscles in the alpha-band in stroke patients versus healthy controls ( p < 0.05) were identified. This study represents the first effort, to the best of our knowledge, to assess stroke-linked alterations in functional intermuscular connectivity using muscle network analysis. The findings revealed a pattern of alterations to muscle networks in stroke survivors compared to healthy controls, as a result of the loss of brain function associated with the stroke. These alterations in muscle networks reflected underlying pathophysiology. These findings can help better understand the motor impairment and motor control in stroke and may advance rehabilitation efforts for stroke by identifying the impaired neuromuscular coordination among multiple muscles in the frequency domain.

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.

Review on electromyography signal acquisition and processing

Electromyography (EMG) is a technique for recording biomedical electrical signals obtained from the neuromuscular activities. These signals are used to monitor medical abnormalities and activation levels, and also to analyze the biomechanics of any animal movements. In this article, we provide a short review of EMG signal acquisition and processing techniques. The average efficiency of capture of EMG signals with current technologies is around 70%. Once the signal is captured, signal processing algorithms then determine the recognition accuracy, with which signals are decoded for their corresponding purpose (e.g., moving robotic arm, speech recognition, gait analysis). The recognition accuracy can go as high as 99.8%. The accuracy with which the EMG signal is decoded has already crossed 99%, and with improvements in deep learning technology, there is a large scope for improvement in the design hardware that can efficiently capture EMG signals.

Desflurane and sevoflurane differentially affect activity of the subthalamic nucleus in Parkinson's disease

BACKGROUND

Desflurane and sevoflurane are commonly used during inhalational anaesthesia, but few studies have investigated their effects on deep cerebral neuronal activity. In addition, the association between subthalamic nucleus (STN) neurophysiology and general anaesthesia induced by volatile anaesthetics are not yet identified. This study aimed to identify differences in neurophysiological characteristics of the STN during comparable minimal alveolar concentration (MAC) desflurane and sevoflurane anaesthesia for deep brain stimulation (DBS) in patients with Parkinson's disease.

METHODS

Twelve patients with similar Parkinson's disease severity received desflurane (n=6) or sevoflurane (n=6) during DBS surgery. We obtained STN spike firing using microelectrode recording at 0.5-0.6 MAC and compared firing rate, power spectral density, and coherence.

RESULTS

Neuronal firing rate was lower with desflurane (47.4 [26.7] Hz) than with sevoflurane (63.9 [36.5] Hz) anaesthesia (P<0.001). Sevoflurane entrained greater gamma oscillation power than desflurane (62.9% [0.9%] vs 57.0% [1.5%], respectively; P=0.002). There was greater coherence in the theta band of the desflurane group compared with the sevoflurane group (13% vs 6%, respectively). Anaesthetic choice did not differentially influence STN mapping accuracy or the clinical outcome of DBS electrode implantation.

CONCLUSIONS

Desflurane and sevoflurane produced distinct neurophysiological profiles in humans that may be associated with their analgesic and hypnotic actions.

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.

Muscle Synergies and Coherence Networks Reflect Different Modes of Coordination During Walking

When walking speed is increased, the frequency ratio between the arm and leg swing switches spontaneously from 2:1 to 1:1. We examined whether these switches are accompanied by changes in functional connectivity between multiple muscles. Subjects walked on a treadmill with their arms swinging along their body while kinematics and surface electromyography (EMG) of 26 bilateral muscles across the body were recorded. Walking speed was varied from very slow to normal. We decomposed EMG envelopes and intermuscular coherence spectra using non-negative matrix factorization (NMF), and the resulting modes were combined into multiplex networks and analyzed for their community structure. We found five relevant muscle synergies that significantly differed in activation patterns between 1:1 and 2:1 arm-leg coordination and the transition period between them. The corresponding multiplex network contained a single module indicating pronounced muscle co-activation patterns across the whole body during a gait cycle. NMF of the coherence spectra distinguished three EMG frequency bands: 4-8, 8-22, and 22-60 Hz. The community structure of the multiplex network revealed four modules, which clustered functional and anatomical linked muscles across modes of coordination. Intermuscular coherence at 4-22 Hz between upper and lower body and within the legs was particularly pronounced for 1:1 arm-leg coordination and was diminished when switching between modes of coordination. These findings suggest that the stability of arm-leg coordination is associated with modulations in long-distant neuromuscular connectivity.

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.

Independently together: subthalamic theta and beta opposite roles in predicting Parkinson's tremor

Tremor is a core feature of Parkinson’s disease and the most easily recognized Parkinsonian sign. Nonetheless, its pathophysiology remains poorly understood. Here, we show that multispectral spiking activity in the posterior-dorso-lateral oscillatory (motor) region of the subthalamic nucleus distinguishes resting tremor from the other Parkinsonian motor signs and strongly correlates with its severity. We evaluated microelectrode-spiking activity from the subthalamic dorsolateral oscillatory region of 70 Parkinson’s disease patients who underwent deep brain stimulation surgery (114 subthalamic nuclei, 166 electrode trajectories). We then investigated the relationship between patients’ clinical Unified Parkinson’s Disease Rating Scale score and their peak theta (4–7 Hz) and beta (13–30 Hz) powers. We found a positive correlation between resting tremor and theta activity (r = 0.41, P < 0.01) and a non-significant negative correlation with beta activity (r = −0.2, P = 0.5). Hypothesizing that the two neuronal frequencies mask each other’s relationship with resting tremor, we created a non-linear model of their proportional spectral powers and investigated its relationship with resting tremor. As hypothesized, patients’ proportional scores correlated better than either theta or beta alone (r = 0.54, P < 0.001). However, theta and beta oscillations were frequently temporally correlated (38/70 patients manifested significant positive temporal correlations and 1/70 exhibited significant negative correlation between the two frequency bands). When comparing theta and beta temporal relationship (r θ β) to patients’ resting tremor scores, we found a significant negative correlation between the two (r = −0.38, P < 0.01). Patients manifesting a positive correlation between the two bands (i.e. theta and beta were likely to appear simultaneously) were found to have lower resting tremor scores than those with near-zero correlation values (i.e. theta and beta were likely to appear separately). We therefore created a new model incorporating patients’ proportional theta–beta power and r θ βscores to obtain an improved neural correlate of resting tremor (r = 0.62, P < 0.001). We then used the Akaike and Bayesian information criteria for model selection and found the multispectral model, incorporating theta–beta proportional power and their correlation, to be the best fitting model, with 0.96 and 0.89 probabilities, respectively. Here we found that as theta increases, beta decreases and the two appear separately—resting tremor is worsened. Our results therefore show that theta and beta convey information about resting tremor in opposite ways. Furthermore, the finding that theta and beta coactivity is negatively correlated with resting tremor suggests that theta–beta non-linear scale may be a valuable biomarker for Parkinson’s resting tremor in future adaptive deep brain stimulation techniques.

Smaller muscle mass is associated with increase in EMG-EMG coherence of the leg muscle during unipedal stance in elderly adults

Age-induced decline in the ability to perform daily activities is associated with a deterioration of physical parameters. Changes occur in neuromuscular system with age; however, the relationship between these changes and physical parameters has not been fully elucidated. Therefore, in this study, we aimed to determine the relationship between neuromuscular system evaluated using a coherence analysis of the leg muscles and physical parameters in community-dwelling healthy elderly adults. The participants were required to stand still in bipedal and unipedal stances on a force plate. Then, electromyography (EMG) was recorded from the tibialis anterior (TA) and medial and lateral gastrocnemius (MG/LG) muscles, and intermuscular coherence was calculated between the following pairs: TA and MG (TA-MG), TA and LG (TA-LG), and MG and LG (MG-LG). Furthermore, gait speed, unipedal stance time, and muscle mass were measured. EMG-EMG coherence for the MG-LG pair was significantly greater in the unipedal stance task than in the bipedal one (p = .001). Multiple linear regression analysis revealed that the muscle mass of the leg was negatively correlated with the change in the β-band coherence for the MG-LG pair from bipedal to unipedal stance (R² = 0.067, standard β = -0.345, p = .044). As the β-band coherence could reflect the corticospinal activity, the increased β-band coherence may be a compensation for the smaller muscle mass, or alternatively may be a sign of changes in the nervous system resulting in the loss of muscle mass.

Sevoflurane and Parkinson’s Disease

Background

General anesthetics-induced changes of electrical oscillations in the basal ganglia may render the identification of the stimulation targets difficult. The authors hypothesized that while sevoflurane anesthesia entrains coherent lower frequency oscillations, it does not affect the identification of the subthalamic nucleus and clinical outcome.

Methods

A cohort of 19 patients with Parkinson’s disease with comparable disability underwent placement of electrodes under either sevoflurane general anesthesia (n = 10) or local anesthesia (n = 9). Microelectrode recordings during targeting were compared for neuronal spiking characteristics and oscillatory dynamics. Clinical outcomes were compared at 5-yr follow-up.

Results

Under sevoflurane anesthesia, subbeta frequency oscillations predominated (general vs. local anesthesia, mean ± SD; delta: 13 ± 7.3% vs. 7.8 ± 4.8%; theta: 8.4 ± 4.1% vs. 3.9 ± 1.6%; alpha: 8.1 ± 4.1% vs. 4.8 ± 1.5%; all P &lt; 0.001). In addition, distinct dorsolateral beta and ventromedial gamma oscillations were detected in the subthalamic nucleus solely in awake surgery (mean ± SD; dorsal vs. ventral beta band power: 20.5 ± 6.6% vs. 15.4 ± 4.3%; P &lt; 0.001). Firing properties of subthalamic neurons did not show significant difference between groups. Clinical outcomes with regard to improvement in motor and psychiatric symptoms and adverse effects were comparable for both groups. Tract numbers of microelectrode recording, active contact coordinates, and stimulation parameters were also equivalent.

Conclusions

Sevoflurane general anesthesia decreased beta-frequency oscillations by inducing coherent lower frequency oscillations, comparable to the pattern seen in the scalp electroencephalogram. Nevertheless, sevoflurane-induced changes in electrical activity patterns did not reduce electrode placement accuracy and clinical effect. These observations suggest that microelectrode-guided deep brain stimulation under sevoflurane anesthesia is a feasible clinical option.

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Corticomuscular control of walking in older people and people with Parkinson's disease

Changes in human gait resulting from ageing or neurodegenerative diseases are multifactorial. Here we assess the effects of age and Parkinson’s disease (PD) on corticospinal activity recorded during treadmill and overground walking. Electroencephalography (EEG) from 10 electrodes and electromyography (EMG) from bilateral tibialis anterior muscles were acquired from 22 healthy young, 24 healthy older and 20 adults with PD. Event-related power, corticomuscular coherence (CMC) and inter-trial coherence were assessed for EEG from bilateral sensorimotor cortices and EMG during the double-support phase of the gait cycle. CMC and EMG power at low beta frequencies (13–21 Hz) was significantly decreased in older and PD participants compared to young people, but there was no difference between older and PD groups. Older and PD participants spent shorter time in the swing phase than young individuals. These findings indicate age-related changes in the temporal coordination of gait. The decrease in low-beta CMC suggests reduced cortical input to spinal motor neurons in older people during the double-support phase. We also observed multiple changes in electrophysiological measures at low-gamma frequencies during treadmill compared to overground walking, indicating task-dependent differences in corticospinal locomotor control. These findings may be affected by artefacts and should be interpreted with caution.

Maturation of feedforward toe walking motor program is impaired in children with cerebral palsy

Voluntary toe walking in adults is characterized by feedforward control of ankle muscles in order to ensure optimal stability of the ankle joint at ground impact. Toe walking is frequently observed in children with cerebral palsy, but the mechanisms involved have not been clarified. Here, we investigated maturation of voluntary toe walking in typically-developing children and typically-developed adults and compared it to involuntary toe walking in children with cerebral palsy. Twenty-eight children with cerebral palsy (age 3-14 years), 24 typically-developing children (age 2-14 years) and 15 adults (mean age 30.7 years) participated in the study. EMG activity was measured from the tibialis anterior and soleus muscles together with knee and ankle joint position during treadmill walking. In typically-developed adults, low step-to-step variability of the drop of the heel after ground impact was correlated with low tibialis anterior and high soleus EMG with no significant coupling between the antagonist muscle EMGs. Typically-developing children showed a significant age-related decline in EMG amplitude reaching an adult level at 10-12 years of age. The youngest typically-developing children showed a broad peak EMG-EMG synchronization (>100 ms) associated with large 5-15 Hz coherence between antagonist muscle activities. EMG coherence declined with age and at the age of 10-12 years no correlation was observed similar to adults. This reduction in coherence was closely related to improved step-to-step stability of the ankle joint position. Children with cerebral palsy generally showed lower EMG levels than typically-developing children and larger step-to-step variability in ankle joint position. In contrast to typically-developing children, children with cerebral palsy showed no age-related decline in tibialis anterior EMG amplitude. Motor unit synchronization and 5-15 Hz coherence between antagonist EMGs was observed more frequently in children with cerebral palsy when compared to typically-developing children and in contrast to typically-developing participants there was no age-related decline. We conclude that typically-developing children develop mature feedforward control of ankle muscle activity as they age, such that at age 10-12 years there is little agonist-antagonist muscle co-contraction around the time of foot-ground contact during toe walking. Children with cerebral palsy, in contrast, continue to co-contract agonist and antagonist ankle muscles when toe walking. We speculate that children with cerebral palsy maintain a co-contraction activation pattern when toe walking due to weak muscles and insufficient motor and sensory signalling necessary for optimization of feedforward motor programs. These findings are important for understanding of the pathophysiology and treatment of toe walking.

Playing Exergames Facilitates Central Drive to the Ankle Dorsiflexors During Gait in Older Adults; a Quasi-Experimental Investigation

Purpose

Gait training might be of particular importance to reduce fall risk in older adults. In the present study we explore the hypothesis that video game-based training will increase tibialis anterior (TA) muscle EMG-EMG coherence and relates to functional measures of lower limb control.

Methods

We focus on video game-based training performed in standing position, where the subjects have to lift their toes to place their feet on different target zones in order to successfully play the game. This type of training is hypothesized leading to progressive changes in the central motor drive to TA motor neurons and, consequently, improved control of ankle dorsiflexion during gait.

Results

Twenty older adults, 79 ± 8 years old, 13 females/7 males, participated. Results showed a significant difference against 0 in the experimental ΔPOST condition in dual-task walking and beta Frequency Of Interest (p = 0.002). Walking under dual task condition showed significant change over time in minimal Toe Clearance for both the left [χ²(2) = 7.46, p = 0.024, n = 20] and right [χ²(2) = 8.87, p = 0.012, n = 20] leg. No change in lower extremity function was detectable.

Conclusion

Overall we conclude that the initiation of an exergame-based training in upright standing position improves neural drive to the lower extremities in older adults, effects on minimal Toe Clearance and seems an acceptable form of physical exercise for this group.

Assisting Operators in Heavy Industrial Tasks: On the Design of an Optimized Cooperative Impedance Fuzzy-Controller With Embedded Safety Rules

Human-robot cooperation is increasingly demanded in industrial applications. Many tasks require the robot to enhance the capabilities of humans. In this scenario, safety also plays an important role in avoiding any accident involving humans, robots, and the environment. With this aim, the paper proposes a cooperative fuzzy-impedance control with embedded safety rules to assist human operators in heavy industrial applications while manipulating unknown weight parts. The proposed methodology is composed by four main components: (i) an inner Cartesian impedance controller (to achieve the compliant robot behavior), (ii) an outer fuzzy controller (to provide the assistance to the human operator), (iii) embedded safety rules (to limit force/velocity during the human-robot interaction enhancing safety), and (iv) a neural network approach (to optimize the control parameters for the human-robot collaboration on the basis of the target indexes of assistance performance defined for this purpose). The main achieved result refers to the capability of the controller to deal with uncertain payloads while assisting and empowering the human operator, both embedding in the controller safety features at force and velocity levels and minimizing the proposed performance indexes. The effectiveness of the proposed approach is verified with a KUKA iiwa 14 R820 manipulator in an experimental procedure where human subjects evaluate the robot performance in a collaborative lifting task of a 10 kg part.

Single channel surface electromyogram deconvolution to explore motor unit discharges

Interference surface electromyogram (EMG) reflects many bioelectric properties of active motor units (MU), which are however difficult to estimate due to the asynchronous summation of their discharges. This paper introduces a deconvolution technique to estimate the cumulative firings of MUs. Tests in simulations show that the power spectral density of the estimated MU firings has a low-frequency peak corresponding to the mean firing rate of MUs in the detection volume of the recording system, weighted by the amplitudes of MU action potentials. The peak increases in amplitude and its centroid shifts to a higher frequency when MU synchronization is simulated (mainly due to the shift of discharges of large MUs). The peak is found even at high force levels, when such a contribution does not emerge from the EMG. This result is also confirmed in preliminary applications to experimental data. Moreover, the simulated cumulative firings of MUs are estimated with a correlation above 90% (considering frequency contributions up to 150 Hz), for all force levels. The method requires a single EMG channel, thus being feasible even in applied studies using simple recording systems. It may open many potential applications, e.g., in the study of the modulation of MU firing rate induced by either fatigue or pathology and in coherency analysis. Graphical Abstract Examples of application of the deconvolution (Deconv) algorithm and comparison with the cumulative firings and the cumulated weighted firings (CWF, i.e., each firing pattern is weighted by the root mean squared amplitude of the corresponding MU action potential). Portions of data are shown on the left, the power spectral densities (PSD) on the right (Welch method applied to 3 s of data, sub-epochs of 0.5 s, mean value removed from each of them, 50% of overlap). A) Simulated signal (50% of maximal voluntary contraction, MVC) with random MU firings. B) Simulated signal (50% MVC) with a level of synchronization equal to 10%. C) Experimental data from vastus medialis at 40% MVC (data decomposed by the algorithm of Holobar and Zazula, IEEE Trans. Sig. Proc. 2007; PSD of the cumulated firings almost identical to that of CWF, as few MUs were identified).

How are Muscle Synergies Affected by Electromyography Pre-Processing?

Muscle synergies have been used for decades to explain a variety of motor behaviors, both in humans and animals and, more recently, to steer rehabilitation strategies. However, many sources of variability such as factorization algorithms, criteria for dimensionality reduction and data pre-processing constitute a major obstacle to the successful comparison of the results obtained by different research groups. Starting from the canonical EMG processing we determined how variations in filter cut-off frequencies and normalization methods, commonly found in literature, affect synergy weights and inter-subject similarity (ISS) using experimental data related to a 15-muscles upper-limb reaching task. Synergy weights were not significantly altered by either normalization (maximum voluntary contraction - MVC - or maximum amplitude of the signal - SELF) or band-pass filter ([20-500 Hz] or [50-500] Hz). Normalization did, however, alter the amount of variance explained by a set of synergies, which is a criterion often used for model order selection. Comparing different low-pass (LP) filters (0.5 Hz, 4 Hz, 10 Hz, 20 Hz cut-offs) we showed that increasing the low pass filter cut-off had the effect of decreasing the variance accounted for by a set number of synergies and affected individual muscle contributions. Extreme smoothing (i.e., LP cut-off 0.5 Hz) enhanced the contrast between active and inactive muscles but had an unpredictable effect on the ISS. The results presented here constitute a further step towards a thoughtful EMG pre-processing for the extraction of muscle synergies.

Neuromechanical Modelling of Articulatory Movements from Surface Electromyography and Speech Formants

Speech articulation is produced by the movements of muscles in the larynx, pharynx, mouth and face. Therefore speech shows acoustic features as formants which are directly related with neuromotor actions of these muscles. The first two formants are strongly related with jaw and tongue muscular activity. Speech can be used as a simple and ubiquitous signal, easy to record and process, either locally or on e-Health platforms. This fact may open a wide set of applications in the study of functional grading and monitoring neurodegenerative diseases. A relevant question, in this sense, is how far speech correlates and neuromotor actions are related. This preliminary study is intended to find answers to this question by using surface electromyographic recordings on the masseter and the acoustic kinematics related with the first formant. It is shown in the study that relevant correlations can be found among the surface electromyographic activity (dynamic muscle behavior) and the positions and first derivatives of the first formant (kinematic variables related to vertical velocity and acceleration of the joint jaw and tongue biomechanical system). As an application example, it is shown that the probability density function associated to these kinematic variables is more sensitive than classical features as Vowel Space Area (VSA) or Formant Centralization Ratio (FCR) in characterizing neuromotor degeneration in Parkinson’s Disease.