Corticomuscular Coherence and Its Applications: A Review

Hebbian plasticity induced by temporally coincident BCI enhances post-stroke motor recovery

Functional electrical stimulation (FES) can support functional restoration of a paretic limb post-stroke. Hebbian plasticity depends on temporally coinciding pre- and post-synaptic activity. A tight temporal relationship between motor cortical (MC) activity associated with attempted movement and FES-generated visuo-proprioceptive feedback is hypothesized to enhance motor recovery. Using a brain-computer interface (BCI) to classify MC spectral power in electroencephalographic (EEG) signals to trigger FES-delivery with detection of movement attempts improved motor outcomes in chronic stroke patients. We hypothesized that heightened neural plasticity earlier post-stroke would further enhance corticomuscular functional connectivity and motor recovery. We compared subcortical non-dominant hemisphere stroke patients in BCI-FES and Random-FES (FES temporally independent of MC movement attempt detection) groups. The primary outcome measure was the Fugl-Meyer Assessment, Upper Extremity (FMA-UE). We recorded high-density EEG and transcranial magnetic stimulation-induced motor evoked potentials before and after treatment. The BCI group showed greater: FMA-UE improvement; motor evoked potential amplitude; beta oscillatory power and long-range temporal correlation reduction over contralateral MC; and corticomuscular coherence with contralateral MC. These changes are consistent with enhanced post-stroke motor improvement when movement is synchronized with MC activity reflecting attempted movement.

Identifying alterations in hand movement coordination from chronic stroke survivors using a wearable high-density EMG sleeve

Objective.Non-invasive, high-density electromyography (HD-EMG) has emerged as a useful tool to collect a range of neurophysiological motor information. Recent studies have demonstrated changes in EMG features that occur after stroke, which correlate with functional ability, highlighting their potential use as biomarkers. However, previous studies have largely explored these EMG features in isolation with individual electrodes to assess gross movements, limiting their potential clinical utility. This study aims to predict hand function of stroke survivors by combining interpretable features extracted from a wearable HD-EMG forearm sleeve.Approach.Here, able-bodied (N= 7) and chronic stroke subjects (N= 7) performed 12 functional hand and wrist movements while HD-EMG was recorded using a wearable sleeve. A variety of HD-EMG features, or views, were decomposed to assess alterations in motor coordination.Main Results.Stroke subjects, on average, had higher co-contraction and reduced muscle coupling when attempting to open their hand and actuate their thumb. Additionally, muscle synergies decomposed in the stroke population were relatively preserved, with a large spatial overlap in composition of matched synergies. Alterations in synergy composition demonstrated reduced coupling between digit extensors and muscles that actuate the thumb, as well as an increase in flexor activity in the stroke group. Average synergy activations during movements revealed differences in coordination, highlighting overactivation of antagonist muscles and compensatory strategies. When combining co-contraction and muscle synergy features, the first principal component was strongly correlated with upper-extremity Fugl Meyer hand sub-score of stroke participants (R2= 0.86). Principal component embeddings of individual features revealed interpretable measures of motor coordination and muscle coupling alterations.Significance.These results demonstrate the feasibility of predicting motor function through features decomposed from a wearable HD-EMG sleeve, which could be leveraged to improve stroke research and clinical care.

Brain (EEG) and muscle (EMG) activity related to 3D sit-to-stand kinematics in healthy adults and in central neurological pathology - A systematic review

BACKGROUND

The sit-to-stand transfer is a fundamental functional movement during normal activities of daily living. Central nervous system disorders can negatively impact the execution of sit-to-stand transfers, often impeding successful completion. Despite its importance, the neurophysiological basis at muscle (electromyography (EMG)) and brain (electroencephalography (EEG)) level as related to the kinematic movement is not well understood.

OBJECTIVES

This review synthesises the published literature addressing central and peripheral neural activity during 3D kinematic capture of sit-to-stand transfers.

METHODS

A pre-registered systematic review was conducted. Electronic databases (PubMed, CINAHL Plus, Web of Science, Scopus and EMBASE) were searched from inception using search operators that included sit-to-stand, kinematics and EMG and/or EEG. The search was not limited by study type but was limited to populations comprising of healthy individuals or individuals with a central neurological pathology.

RESULTS

From a total of 28,770 identified papers, 59 were eligible for inclusion. Ten of these 59 studies received a moderate quality rating; with the remainder rated as weak using the Effective Public Health Practice Project tool. Fifty-eight studies captured kinematic data of sit-to-stand with associated EMG activity only and one study captured kinematics with co-registered EMG and EEG data. Fifty-six studies examined sit-to-stand transfer in healthy individuals, reporting four dynamic movement phases and three muscle synergies commonly used by most individuals to stand-up. Pre-movement EEG activity was reported in one study with an absence of data during execution. Eight studies examined participants following stroke and two examined participants with Parkinson's disease, both reporting no statistically significant differences between their kinematics and muscle activity and those of healthy controls.

SIGNIFICANCE

Little is known about the neural basis of the sit-to-stand transfer at brain level with limited focus in central neurological pathology. This poses a barrier to targeted mechanistic-based rehabilitation of the sit-to-stand movement in neurological populations.

The effect of inherent and incidental constraints on bimanual force control in simulated Martian gravity

The ability to coordinate actions between the limbs is important for many operationally relevant tasks associated with space exploration. A future milestone in space exploration is sending humans to Mars. Therefore, an experiment was designed to examine the influence of inherent and incidental constraints on the stability characteristics associated with the bimanual control of force in simulated Martian gravity. A head-up tilt (HUT)/head-down tilt (HDT) paradigm was used to simulate gravity on Mars (22.3° HUT). Right limb dominant participants (N = 11) were required to rhythmically coordinate patterns of isometric forces in 1:1 in-phase and 1:2 multifrequency patterns by exerting force with their right and left limbs. Lissajous displays were provided to guide task performance. Participants performed 14 twenty-second practice trials at 90° HUT (Earth). Following a 30-min rest period, participants performed 2 test trials for each coordination pattern in both Earth and Mars conditions. Performance during the test trials were compared. Results indicated very effective temporal performance of the goal coordination tasks in both gravity conditions. However, results indicated differences associated with the production of force between Earth and Mars. In general, participants produced less force in simulated Martian gravity than in the Earth condition. In addition, force production was more harmonic in Martian gravity than Earth gravity for both limbs, indicating that less force distortions (adjustments, hesitations, and/or perturbations) occurred in the Mars condition than in the Earth condition. The force coherence analysis indicated significantly higher coherence in the 1:1 task than in the 1:2 task for all force frequency bands, with the highest level of coherence in the 1-4 Hz frequency band for both gravity conditions. High coherence in the 1-4 Hz frequency band is associated with a common neural drive that activates the two arms simultaneously and is consistent with the requirements of the two tasks. The results also support the notion that neural crosstalk stabilizes the performance of the 1:1 in-phase task. In addition, significantly higher coherence in the 8-12 Hz frequency bands were observed for the Earth condition than the Mars condition. Force coherence in the 8-12 Hz bands is associated with the processing of sensorimotor information, suggesting that participants were better at integrating visual, proprioceptive, and/or tactile feedback in Earth than for the Mars condition. Overall, the results indicate less neural interference in Martian gravity; however, participants appear to be more effective at using the Lissajous displays to guide performance under Earth's gravity.

Improvements in motor control are associated with improved quality of life following an at-home muscle biofeedback program for chronic stroke

Introduction

Chronic stroke survivors with severe arm impairment have limited options for effective rehabilitation. High intensity, repetitive task practice (RTP) is known to improve upper limb function among stroke survivors who have some volitional muscle activation. However, clients without volitional movement of their arm are ineligible for RTP-based interventions and require hands-on facilitation from a clinician or robotic therapy to simulate task practice. Such approaches can be expensive, burdensome, and have marginal effects. Alternatively, supervised at-home telerehabilitation using muscle biofeedback may provide a more accessible, affordable, and effective rehabilitation option for stroke survivors with severe arm impairment, and could potentially help people with severe stroke regain enough volitional activation to be eligible for RTP-types of therapies. Feedback of muscle activity via electromyography (EMG) has been previously used with clients who have minimal or no movement to improve functional performance. Specifically, training to reduce unintended co-contractions of the impaired hand using EMG biofeedback may modestly improve motor control in people with limited movement. Importantly, these modest and covert functional changes may influence the perceived impact of stroke-related disability in daily life. In this manuscript, we examine whether physical changes following use of a portable EMG biofeedback system (Tele-REINVENT) for severe upper limb hemiparesis also relate to perceived quality of life improvements. Secondarily, we examined the effects of Tele-REINVENT, which uses EMG to quantify antagonistic muscle activity during movement attempt trials and transform individuated action into computer game control, on several different domains of stroke recovery.

Methods

For this pilot study, nine stroke survivors (age = 37-73 years) with chronic impairment (Fugl-Meyer = 14-40/66) completed 30 1-hour sessions of home-based training, consisting of six weeks of gaming that reinforced wrist extensor muscle activity while attenuating coactivation of flexor muscles. To assess motor control and performance, we measured changes in active wrist ranges of motion, the Fugl-Meyer Assessment, and Action Research Arm Test. We also collected an EMG-based test of muscle control to examine more subtle changes. To examine changes in perceived quality of life, we utilized the Stroke Impact Scale along with participant feedback.

Results

Results from our pilot data suggest that 30 sessions of remote training can induce modest changes on clinical and functional assessments, showing a statistically significant improvement of active wrist ranges of motion at the group level, changes that could allow some people with severe stroke to be eligible for other therapeutic approaches, such as RTP. Additionally, changes in motor control were correlated with the perceived impact of stroke on participation and impairment after training. We also report changes in corticomuscular coherence, which showed a laterality change from the ipsilesional motor cortex towards the contralesional hemisphere during wrist extension attempts. Finally, all participants showed high adherence to the protocol and reported enjoying using the system.

Conclusion

Overall, Tele-REINVENT represents a promising telerehabilitation intervention that might improve sensorimotor outcomes in severe chronic stroke, and that improving sensorimotor abilities even modestly may improve quality of life. We propose that Tele-REINVENT may be used as a precursor to help participants gain enough active movement to participate other occupational therapy interventions, such as RTP. Future work is needed to examine if home-based telerehabilitation to provide feedback of individuated muscle activity could increase meaningful rehabilitation accessibility and outcomes for underserved populations.

Dopamine improves defective cortical and muscular connectivity during bilateral control of gait in Parkinson's disease

Parkinson's Disease (PD)-typical declines in gait coordination are possibly explained by weakness in bilateral cortical and muscular connectivity. Here, we seek to determine whether this weakness and consequent decline in gait coordination is affected by dopamine levels. To this end, we compare cortico-cortical, cortico-muscular, and intermuscular connectivity and gait outcomes between body sides in people with PD under ON and OFF medication states, and in older adults. In our study, participants walked back and forth along a 12 m corridor. Gait events (heel strikes and toe-offs) and electrical cortical and muscular activities were measured and used to compute cortico-cortical, cortico-muscular, and intermuscular connectivity (i.e., coherences in the alpha, beta, and gamma bands), as well as features characterizing gait performance (e.g., the step-timing coordination, length, and speed). We observe that people with PD, mainly during the OFF medication, walk with reduced step-timing coordination. Additionally, our results suggest that dopamine intake in PD increases the overall cortico-muscular connectivity during the stance and swing phases of gait. We thus conclude that dopamine corrects defective feedback caused by impaired sensory-information processing and sensory-motor integration, thus increasing cortico-muscular coherences in the alpha bands and improving gait.

Automatic sleep-wake classification and Parkinson's disease recognition using multifeature fusion with support vector machine

AIMS

Sleep disturbance is a prevalent nonmotor symptom of Parkinson's disease (PD), however, assessing sleep conditions is always time-consuming and labor-intensive. In this study, we performed an automatic sleep-wake state classification and early diagnosis of PD by analyzing the electrocorticography (ECoG) and electromyogram (EMG) signals of both normal and PD rats.

METHODS

The study utilized ECoG power, EMG amplitude, and corticomuscular coherence values extracted from normal and PD rats to construct sleep-wake scoring models based on the support vector machine algorithm. Subsequently, we incorporated feature values that could act as diagnostic markers for PD and then retrained the models, which could encompass the identification of vigilance states and the diagnosis of PD.

RESULTS

Features extracted from occipital ECoG signals were more suitable for constructing sleep-wake scoring models than those from frontal ECoG (average Cohen's kappa: 0.73 vs. 0.71). Additionally, after retraining, the new models demonstrated increased sensitivity to PD and accurately determined the sleep-wake states of rats (average Cohen's kappa: 0.79).

CONCLUSION

This study accomplished the precise detection of substantia nigra lesions and the monitoring of sleep-wake states. The integration of circadian rhythm monitoring and disease state assessment has the potential to improve the efficacy of therapeutic strategies considerably.

Effects of non-invasive cervical spinal cord neuromodulation by trans-spinal electrical stimulation on cortico-muscular descending patterns in upper extremity of chronic stroke

Background: Trans-spinal electrical stimulation (tsES) to the intact spinal cord poststroke may modulate the cortico-muscular control in stroke survivors with diverse lesions in the brain. This work aimed to investigate the immediate effects of tsES on the cortico-muscular descending patterns during voluntary upper extremity (UE) muscle contractions by analyzing cortico-muscular coherence (CMCoh) and electromyography (EMG) in people with chronic stroke. Methods: Twelve chronic stroke participants were recruited to perform wrist-hand extension and flexion tasks at submaximal levels of voluntary contraction for the corresponding agonist flexors and extensors. During the tasks, the tsES was delivered to the cervical spinal cord with rectangular biphasic pulses. Electroencephalography (EEG) data were collected from the sensorimotor cortex, and the EMG data were recorded from both distal and proximal UE muscles. The CMCoh, laterality index (LI) of the peak CMCoh, and EMG activation level parameters under both non-tsES and tsES conditions were compared to evaluate the immediate effects of tsES on the cortico-muscular descending pathway. Results: The CMCoh and LI of peak CMCoh in the agonist distal muscles showed significant increases (p < 0.05) during the wrist-hand extension and flexion tasks with the application of tsES. The EMG activation levels of the antagonist distal muscle during wrist-hand extension were significantly decreased (p < 0.05) with tsES. Additionally, the proximal UE muscles exhibited significant decreases (p < 0.05) in peak CMCoh and EMG activation levels by applying tsES. There was a significant increase (p < 0.05) in LI of peak CMCoh of proximal UE muscles during tsES. Conclusion: The cervical spinal cord neuromodulation via tsES enhanced the residual descending excitatory control, activated the local inhibitory circuits within the spinal cord, and reduced the cortical and proximal muscular compensatory effects. These results suggested the potential of tsES as a supplementary input for improving UE motor functions in stroke rehabilitation.

Assessing Cognitive Workload in Motor Decision-Making through Functional Connectivity Analysis: Towards Early Detection and Monitoring of Neurodegenerative Diseases

Neurodegenerative diseases (NDs), such as Alzheimer's, Parkinson's, amyotrophic lateral sclerosis, and frontotemporal dementia, among others, are increasingly prevalent in the global population. The clinical diagnosis of these NDs is based on the detection and characterization of motor and non-motor symptoms. However, when these diagnoses are made, the subjects are often in advanced stages where neuromuscular alterations are frequently irreversible. In this context, we propose a methodology to evaluate the cognitive workload (CWL) of motor tasks involving decision-making processes. CWL is a concept widely used to address the balance between task demand and the subject's available resources to complete that task. In this study, multiple models for motor planning during a motor decision-making task were developed by recording EEG and EMG signals in n=17 healthy volunteers (9 males, 8 females, age 28.66±8.8 years). In the proposed test, volunteers have to make decisions about which hand should be moved based on the onset of a visual stimulus. We computed functional connectivity between the cortex and muscles, as well as among muscles using both corticomuscular and intermuscular coherence. Despite three models being generated, just one of them had strong performance. The results showed two types of motor decision-making processes depending on the hand to move. Moreover, the central processing of decision-making for the left hand movement can be accurately estimated using behavioral measures such as planning time combined with peripheral recordings like EMG signals. The models provided in this study could be considered as a methodological foundation to detect neuromuscular alterations in asymptomatic patients, as well as to monitor the process of a degenerative disease.

Multiscale Canonical Coherence for Functional Corticomuscular Coupling Analysis

Functional corticomuscular coupling (FCMC) probes multi-level information communication in the sensorimotor system. The canonical Coherence (caCOH) method has been leveraged to measure the FCMC between two multivariate signals within the single scale. In this paper, we propose the concept of multiscale canonical Coherence (MS-caCOH) to disentangle complex multi-layer information and extract coupling features in multivariate spaces from multiple scales. Then, we verified the reliability and effectiveness of MS-caCOH on two types of data sets, i.e., a synthetic multivariate data set and a real-world multivariate data set. Our simulation results showed that compared with caCOH, MS-caCOH enhanced coupling detection and achieved lower pattern recovery errors at multiple frequency scales. Further analysis on experimental data demonstrated that the proposed MS-caCOH method could also capture detailed multiscale spatial-frequency characteristics. This study leverages the multiscale analysis framework and multivariate method to give a new insight into corticomuscular coupling analysis.

cTBS over primary motor cortex increased contralateral corticomuscular coupling and interhemispheric functional connection

Objective.Transcranial magnetic stimulation is a non-invasive brain stimulation technique that changes the activity of the cerebral cortex. Contralesional continuous theta burst stimulation (cTBS) has been proposed and verified beneficial to stroke motor recovery. However, the underlying mechanism is still unclear.Approach.20 healthy right-handed subjects were recruited in this study, receiving real-cTBS over their left primary motor cortex or sham-cTBS. We designed the finger tapping task (FTT) before and after stimulation and recorded the accuracy and reaction time (RT) of the task. The electroencephalogram and surface electromyogram signals were recorded during the left finger pinching task (FPT) before and after stimulation. We calculated cortico-muscular coherence (CMC) in the contralateral hemisphere and cortico-cortical coherence (CCC) in the bilateral hemisphere. The two-way repeated measures analysis of variance was used to analyze the effect of cTBS.Main results.In the FTT, there was a significant main effect of 'time' on RT (F(1, 38) = 24.739,p< 0.001). In the FPT, the results showed that there was a significant interaction effect on the CMC peak and area in the beta band (peak:F(1, 38) = 8.562,p= 0.006; area:F(1, 38) = 5.273,p= 0.027), on the CCC peak in the alpha band (F(1, 38) = 4.815,p= 0.034) and area in the beta band (F(1, 38) = 4.822,p= 0.034). The post hoc tests showed that the CMC peak (W= 20,p= 0.002), the CMC area (W= 13,p= 0.003) and the CCC peak (t= -2.696,p= 0.014) increased significantly after real-cTBS. However, there was no significant decrease or increase after sham-cTBS.Significance.Our study found that cTBS can improve CMC of contralateral hemisphere and CCC of bilateral hemisphere, indicating that cTBS can strengthen cortico-muscular and cortico-cortical coupling.

Clinical neurophysiology of REM parasomnias: Diagnostic aspects and insights into pathophysiology

Parasomnias are due to a transient unstable state dissociation during entry into sleep, within sleep, or during arousal from sleep, and manifest with abnormal sleep related behaviors, perceptions, emotions, dreams, and autonomic nervous system activity. Rapid eye movement (REM) parasomnias include REM sleep behavior disorder (RBD), isolated recurrent sleep paralysis and nightmare disorder. Neurophysiology is key for diagnosing these disorders and provides insights into their pathophysiology. RBD is very well characterized from a neurophysiological point of view, also thank to the fact that polysomnography is needed for the diagnosis. Diagnostic criteria are provided by the American Academy of Sleep Medicine and video-polysomnography guidelines for the diagnosis by the International REM Sleep Behavior Disorder Study Group. Differences between the two sets of criteria are presented and discussed. Availability of polysomnography in RBD provides data on sleep electroencephalography (EEG), electrooculography (EOG) and electromyography (EMG). Sleep EEG in RBD shows e.g. changes in delta and theta power, in sleep spindles and K complexes. EMG during REM sleep is essential for RBD diagnosis and is an important neurodegeneration biomarker. RBD patients present alterations also in wake EEG, autonomic function, evoked potentials, and transcranial magnetic stimulation. Clinical neurophysiological data on recurrent isolated sleep paralysis and nightmare disorder are scant. The few available data provide insights into the pathophysiology of these disorders, demonstrating a state dissociation in recurrent isolated sleep paralysis and suggesting alterations in sleep macro- and microstructure as well as autonomic changes in nightmare disorder.

Effects of sling exercises on pain, function, and corticomuscular functional connectivity in individuals with chronic low back pain- preliminary study

BACKGROUND

Individuals with chronic low back pain (CLBP) exhibit altered brain function and trunk muscle activation.

AIM

This study examined the effects of sling exercises on pain, function, and corticomuscular coherence (CMC) in healthy adults and individuals with CLBP.

METHODS

Eight individuals with CLBP and 15 healthy adults received sling exercise training for 6 weeks. Before and after training, participants performed two motor tasks: rapid arm lifts and repeated trunk flexion-extension tasks, and electromyography of the trunk muscles and electroencephalography of the sensorimotor cortex were recorded. Chi-squared test and Mann-Whitney U tests were used for between group comparison, and Wilcoxon signed-rank tests were used for pre- and post-training comparison. Spearman's Rank Correlation Coefficient (Rs) was used to identify for the relationship between motor performance and Corticomuscular coherence.

RESULTS

Sling exercises significantly improved pain (median from 3 to 1, p = .01) and Oswestry Disability Index scores (median from 2.5 to 2, p = .03) in the CLBP group. During rapid arm lifts, individuals with CLBP showed lower beta CMC of the transverse abdominis and internal oblique (Tra/IO) (0.8 vs. 0.49, p = .01) and lumbar erector spinae (0.70 vs. 0.38, p = .04) than the control group at baseline. During trunk flexion-extension, the CLBP group showed higher gamma CMC of the left Tra/IO than the control group at baseline (0.28 vs. 0.16 , p = .001). After training, all CMC became statistically non-significant between groups. The training induced improvement in anticipatory activation of the Tra/IO was positively correlated with the beta CMC (rs = 0.7851, p = .02).

CONCLUSION

A 6-week sling exercises diminished pain and disability in patients with CLBP and improved the anticipatory activation and CMC in some trunk muscles. These improvements were associated with training induced changes in corticomuscular connectivity in individuals with CLBP.

Hook Fabric Electroencephalography Electrode for Brain Activity Measurement without Shaving the Head

In this research, novel electroencephalogram (EEG) electrodes were developed to detect high-quality EEG signals without the requirement of conductive gels, skin treatments, or head shaving. These electrodes were created using electrically conductive hook fabric with a resistance of 1 Ω/sq. The pointed hooks of the conductive fabric establish direct contact with the skin and can penetrate through hair. To ensure excellent contact between the hook fabric electrode and the scalp, a knitted-net EEG bridge cap with a bridging effect was employed. The results showed that the hook fabric electrode exhibited lower skin-to-electrode impedance compared to the dry Ag/AgCl comb electrode. Additionally, it collected high-quality signals on par with the standard wet gold cups and commercial dry Ag/AgCl comb electrodes. Moreover, the hook fabric electrode displayed a higher signal-to-noise ratio (33.6 dB) with a 4.2% advantage over the standard wet gold cup electrode. This innovative electrode design eliminates the need for conductive gel and head shaving, offering enhanced flexibility and lightweight characteristics, making it ideal for integration into textile structures and facilitating convenient long-term monitoring.

A Narrative Review on Multi-Domain Instrumental Approaches to Evaluate Neuromotor Function in Rehabilitation

In clinical scenarios, the use of biomedical sensors, devices and multi-parameter assessments is fundamental to provide a comprehensive portrait of patients' state, in order to adapt and personalize rehabilitation interventions and support clinical decision-making. However, there is a huge gap between the potential of the multidomain techniques available and the limited practical use that is made in the clinical scenario. This paper reviews the current state-of-the-art and provides insights into future directions of multi-domain instrumental approaches in the clinical assessment of patients involved in neuromotor rehabilitation. We also summarize the main achievements and challenges of using multi-domain approaches in the assessment of rehabilitation for various neurological disorders affecting motor functions. Our results showed that multi-domain approaches combine information and measurements from different tools and biological signals, such as kinematics, electromyography (EMG), electroencephalography (EEG), near-infrared spectroscopy (NIRS), and clinical scales, to provide a comprehensive and objective evaluation of patients' state and recovery. This multi-domain approach permits the progress of research in clinical and rehabilitative practice and the understanding of the pathophysiological changes occurring during and after rehabilitation. We discuss the potential benefits and limitations of multi-domain approaches for clinical decision-making, personalized therapy, and prognosis. We conclude by highlighting the need for more standardized methods, validation studies, and the integration of multi-domain approaches in clinical practice and research.

Task-dependent alteration of beta-band intermuscular coherence is associated with ipsilateral corticospinal tract excitability

Beta-band (15-30 Hz) synchronization between the EMG signals of active limb muscles can serve as a non-invasive assay of corticospinal tract integrity. Tasks engaging a single limb often primarily utilize one corticospinal pathway, although bilateral neural circuits can participate in goal-directed actions involving multi-muscle coordination and utilization of feedback. Suboptimal utilization of such circuits after CNS injury can result in unintended mirror movements and activation of pathological synergies. Accordingly, it is important to understand how the actions of one limb (e.g., a less-affected limb after strokes) influence the opposite corticospinal pathway for the rehabilitation target. Certain unimanual actions decrease the excitability of the "unengaged" corticospinal tract, presumably to prevent mirror movement, but there is no direct way to predict the extent to which this will occur. In this study, we tested the hypothesis that task-dependent changes in beta-band drives to muscles of one hand will inversely correlate with changes in the opposite corticospinal tract excitability. Ten participants completed spring pinching tasks known to induce differential 15-30 Hz drive to muscles. During compressions, transcranial magnetic stimulation single pulses to the ipsilateral M1 were delivered to generate motor-evoked potentials in the unengaged hand. The task-induced changes in ipsilateral corticospinal excitability were inversely correlated with associated changes in EMG-EMG coherence of the task hand. These results demonstrate a novel connection between intermuscular coherence and the excitability of the "unengaged" corticospinal tract and provide a springboard for further mechanistic studies of unimanual tasks of varying difficulty and their effects on neural pathways relevant to rehabilitation.

Corticomuscular Coherence in Children with Unilateral Cerebral Palsy: A Feasibility and Preliminary Protocol Study

Objective This study assessed the feasibility of corticomuscular coherence measurement during a goal-directed task in children with unilateral cerebral palsy while establishing optimal experimental parameters. Methods Participants (Manual Ability Classification System levels I-III) completed a submaximal isometric goal-directed grip task during simultaneous electroencephalography and electromyography (EMG) acquisition. Results All participants (n = 11, 6 females, mean age 11.3 ±2.4 years) completed corticomuscular coherence procedures. Of the 40 trials obtained per extremity, an average of 29 (n = 9) and 27 (n = 10) trials were retained from the more- and less-affected extremities, respectively. Obtaining measurement stability required an average of 28 trials per extremity. Conclusion Findings from this work support the feasibility of corticomuscular coherence measurement in children with unilateral cerebral palsy. Acquiring 28 to 40 corticomuscular coherence trials per extremity is ideal. The experimental parameters established in this work will inform future corticomuscular coherence application in pediatric unilateral cerebral palsy.

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.

Effects of Muscle Fatigue and Recovery on the Neuromuscular Network after an Intermittent Handgrip Fatigue Task: Spectral Analysis of Electroencephalography and Electromyography Signals

Mechanisms underlying exercise-induced muscle fatigue and recovery are dependent on peripheral changes at the muscle level and improper control of motoneurons by the central nervous system. In this study, we analyzed the effects of muscle fatigue and recovery on the neuromuscular network through the spectral analysis of electroencephalography (EEG) and electromyography (EMG) signals. A total of 20 healthy right-handed volunteers performed an intermittent handgrip fatigue task. In the prefatigue, postfatigue, and postrecovery states, the participants contracted a handgrip dynamometer with sustained 30% maximal voluntary contractions (MVCs); EEG and EMG data were recorded. A considerable decrease was noted in EMG median frequency in the postfatigue state compared with the findings in other states. Furthermore, the EEG power spectral density of the right primary cortex exhibited a prominent increase in the gamma band. Muscle fatigue led to increases in the beta and gamma bands of contralateral and ipsilateral corticomuscular coherence, respectively. Moreover, a decrease was noted in corticocortical coherence between the bilateral primary motor cortices after muscle fatigue. EMG median frequency may serve as an indicator of muscle fatigue and recovery. Coherence analysis revealed that fatigue reduced the functional synchronization among bilateral motor areas but increased that between the cortex and muscle.

Artificial Neural Network-Assisted Classification of Hearing Prognosis of Sudden Sensorineural Hearing Loss With Vertigo

This study aimed to determine the impact on hearing prognosis of the coherent frequency with high magnitude-squared wavelet coherence (MSWC) in video head impulse test (vHIT) among patients with sudden sensorineural hearing loss with vertigo (SSNHLV) undergoing high-dose steroid treatment. This study was a retrospective cohort study. SSNHLV patients treated at our referral center from December 2016 to December 2020 were examined. The cohort comprised 64 patients with SSNHLV undergoing high-dose steroid treatment. MSWC was measured by calculating the wavelet coherence analysis (WCA) at various frequencies from a vHIT. The hearing prognosis were analyzed using a multivariable Cox regression model and convolution neural network (CNN) of WCA. There were 64 patients with a male-to-female ratio of 1:1.67. The greater highest coherent frequency of the posterior semicircular canal (SCC) was associated with the complete recovery (CR) of hearing. After adjustment for other factors, the result remained robust (hazard ratio [HR] 2.11, 95% confidence interval [CI] 1.86-2.35). In the feature extraction with Resnet-50 and proceeding SVM in the horizontal image cropping style, the classification accuracy [STD] for (CR vs. partial + no recovery [PR + NR]), (over-sampling of CR vs. PR + NR), (extensive data extraction of CR vs. PR + NR), and (interpolation of time series of CR vs. PR + NR) were 83.6% [7.4], 92.1% [6.8], 88.9% [7.5], and 91.6% [6.4], respectively. The high coherent frequency of the posterior SCC was a significantly independent factor that was associated with good hearing prognosis in the patients who have SSNHLV. WCA may be provided with comprehensive ability in vestibulo-ocular reflex (VOR) evaluation. CNN could be utilized to classify WCA, predict treatment outcomes, and facilitate vHIT interpretation. Feature extraction in CNN with proceeding SVM and horizontal cropping style of wavelet coherence plot performed better accuracy and offered more stable model for hearing outcomes in patients with SSNHLV than pure CNN classification. Clinical and Translational Impact Statement-High coherent frequency in vHIT results in good hearing outcomes in SSNHLV and facilitates AI classification.

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.

Age and sex differences in force steadiness and intermuscular coherence of lower leg muscles during isometric plantar flexion

Age- and sex-related alterations in the control of multiple muscles during contractions are not well understood. The purpose of the present study was to examine the age and sex differences in force steadiness and intermuscular coherence (IMC), and thereby to clarify the functional role of IMC during plantar flexion. Twenty-six young (YNG, 23-34 years), thirty middle-aged (MID, 35-64 years) and twenty-four older adults (OLD, 65-82 years) performed submaximal isometric contractions of plantar flexion, while electromyography was recorded from the soleus (SOL), gastrocnemius lateralis/medialis (GL/GM) and tibialis anterior (TA) muscles. Coefficient of variation (CV) of torque and IMC in the alpha, beta and gamma bands was calculated. We found that OLD demonstrated significantly higher torque CV than YNG and MID, and males demonstrated significantly higher torque CV than females (both p < 0.05). The IMC in the gamma band (five out of the six pairs) was significantly higher in YNG than MID and/or OLD (p < 0.05), while the gamma band IMC between GL and SOL was significantly higher in females. However, age or sex differences were not detected in the alpha or beta band. Moreover, the gamma band IMC between SOL and TA had a weak (r =  - 0.229) but significant (p < 0.05) negative correlation with torque CV. These results suggest that force steadiness differs with age and sex, and that the higher gamma band IMC may contribute to more stable force control during plantar flexion.

A sequential learning model with GNN for EEG-EMG-based stroke rehabilitation BCI

Introduction

Brain-computer interfaces (BCIs) have the potential in providing neurofeedback for stroke patients to improve motor rehabilitation. However, current BCIs often only detect general motor intentions and lack the precise information needed for complex movement execution, mainly due to insufficient movement execution features in EEG signals.

Methods

This paper presents a sequential learning model incorporating a Graph Isomorphic Network (GIN) that processes a sequence of graph-structured data derived from EEG and EMG signals. Movement data are divided into sub-actions and predicted separately by the model, generating a sequential motor encoding that reflects the sequential features of the movements. Through time-based ensemble learning, the proposed method achieves more accurate prediction results and execution quality scores for each movement.

Results

A classification accuracy of 88.89% is achieved on an EEG-EMG synchronized dataset for push and pull movements, significantly outperforming the benchmark method's performance of 73.23%.

Discussion

This approach can be used to develop a hybrid EEG-EMG brain-computer interface to provide patients with more accurate neural feedback to aid their recovery.

Short report presenting preliminary evidence of impaired corticomuscular coherence in an individual with Developmental Coordination Disorder

BACKGROUND

It has been suggested that developmental coordination disorder (DCD) could be caused by a 'dysconnection' in brain and skeletal muscle communication. To date no previous work has examined the integrity of this neuromuscular process in individuals with DCD.

AIMS

To conduct a feasibility study for measuring functional connectivity of the brain and muscle in an individual with DCD using corticomuscular coherence (CMC).

METHODS AND PROCEDURES

An individual with DCD and a typically developing (TD) participant completed a series of sustained 5-second voluntary isometric hand contractions (15 ± 5 % MVC) on a handheld dynamometer under both single and dual task (i.e., counting backwards) conditions. EEG, EMG and force data were collected.

OUTCOMES AND RESULTS

The participant with DCD displayed poorer force steadiness and higher mental demand compared to the TD participant and in dual task conditions. The TD participant displayed a commonly observed pattern of CMC that was highly localised over the contralateral hand area, the DCD participant displayed a less localised CMC across cortical regions.

CONCLUSIONS AND IMPLICATIONS

These findings support the feasibility of measuring CMC in DCD populations and offer some, albeit preliminary, evidence of impaired communication between the brain and muscles in these individuals.

Corticospinal Responses Following Gait-Specific Training in Stroke Survivors: A Systematic Review

Corticospinal excitability is subject to alterations after stroke. While the reversal of these alterations has been proposed as an underlying mechanism for improved walking capacity after gait-specific training, this has not yet been clearly demonstrated. Therefore, the objective of this review is to evaluate the effect of gait-specific training on corticospinal excitability in stroke survivors. We conducted an electronic database search in four databases (i.e., Medline, Embase, CINAHL and Web of Science) in June 2022. Two authors screened in an independent way all the studies and selected those that investigated the effect of gait-specific training on variables such as motor-evoked potential amplitude, motor threshold, map size, latency, and corticospinal silent period in stroke survivors. Nineteen studies investigating the effect of gait-specific training on corticospinal excitability were included. Some studies showed an increased MEP amplitude (7/16 studies), a decreased latency (5/7studies), a decreased motor threshold (4/8 studies), an increased map size (2/3 studies) and a decreased cortical silent period (1/2 study) after gait-specific training. No change has been reported in terms of short interval intracortical inhibition after training. Five studies did not report any significant effect after gait-specific training on corticospinal excitability. The results of this systematic review suggest that gait-specific training modalities can drive neuroplastic adaptation among stroke survivors. However, given the methodological disparity of the included studies, additional clinical trials of better methodological quality are needed to establish conclusions. The results of this review can therefore be used to develop future studies to better understand the effects of gait-specific training on the central nervous system.

Cortico-muscular coupling to control a hybrid brain-computer interface for upper limb motor rehabilitation: A pseudo-online study on stroke patients

Brain-Computer Interface (BCI) systems for motor rehabilitation after stroke have proven their efficacy to enhance upper limb motor recovery by reinforcing motor related brain activity. Hybrid BCIs (h-BCIs) exploit both central and peripheral activation and are frequently used in assistive BCIs to improve classification performances. However, in a rehabilitative context, brain and muscular features should be extracted to promote a favorable motor outcome, reinforcing not only the volitional control in the central motor system, but also the effective projection of motor commands to target muscles, i.e., central-to-peripheral communication. For this reason, we considered cortico-muscular coupling (CMC) as a feature for a h-BCI devoted to post-stroke upper limb motor rehabilitation. In this study, we performed a pseudo-online analysis on 13 healthy participants (CTRL) and 12 stroke patients (EXP) during executed (CTRL, EXP unaffected arm) and attempted (EXP affected arm) hand grasping and extension to optimize the translation of CMC computation and CMC-based movement detection from offline to online. Results showed that updating the CMC computation every 125 ms (shift of the sliding window) and accumulating two predictions before a final classification decision were the best trade-off between accuracy and speed in movement classification, independently from the movement type. The pseudo-online analysis on stroke participants revealed that both attempted and executed grasping/extension can be classified through a CMC-based movement detection with high performances in terms of classification speed (mean delay between movement detection and EMG onset around 580 ms) and accuracy (hit rate around 85%). The results obtained by means of this analysis will ground the design of a novel non-invasive h-BCI in which the control feature is derived from a combined EEG and EMG connectivity pattern estimated during upper limb movement attempts.

Functional and neuromuscular changes induced via a low-cost, muscle-computer interface for telerehabilitation: A feasibility study in chronic stroke

Stroke is a leading cause of adult disability in the United States. High doses of repeated task-specific practice have shown promising results in restoring upper limb function in chronic stroke. However, it is currently challenging to provide such doses in clinical practice. At-home telerehabilitation supervised by a clinician is a potential solution to provide higher-dose interventions. However, telerehabilitation systems developed for repeated task-specific practice typically require a minimum level of active movement. Therefore, severely impaired people necessitate alternative therapeutic approaches. Measurement and feedback of electrical muscle activity via electromyography (EMG) have been previously implemented in the presence of minimal or no volitional movement to improve motor performance in people with stroke. Specifically, muscle neurofeedback training to reduce unintended co-contractions of the impaired hand may be a targeted intervention to improve motor control in severely impaired populations. Here, we present the preliminary results of a low-cost, portable EMG biofeedback system (Tele-REINVENT) for supervised and unsupervised upper limb telerehabilitation after stroke. We aimed to explore the feasibility of providing higher doses of repeated task-specific practice during at-home training. Therefore, we recruited 5 participants (age = 44-73 years) with chronic, severe impairment due to stroke (Fugl-Meyer = 19-40/66). They completed a 6-week home-based training program that reinforced activity of the wrist extensor muscles while avoiding coactivation of flexor muscles via computer games. We used EMG signals to quantify the contribution of two antagonistic muscles and provide biofeedback of individuated activity, defined as a ratio of extensor and flexor activity during movement attempt. Our data suggest that 30 1-h sessions over 6 weeks of at-home training with our Tele-REINVENT system is feasible and may improve individuated muscle activity as well as scores on standard clinical assessments (e.g., Fugl-Meyer Assessment, Action Research Arm Test, active wrist range of motion) for some individuals. Furthermore, tests of neuromuscular control suggest modest changes in the synchronization of electroencephalography (EEG) and EMG signals within the beta band (12-30 Hz). Finally, all participants showed high adherence to the training protocol and reported enjoying using the system. These preliminary results suggest that using low-cost technology for home-based telerehabilitation after severe chronic stroke is feasible and may be effective in improving motor control via feedback of individuated muscle activity.

Corticomotor Plasticity Underlying Priming Effects of Motor Imagery on Force Performance

The neurophysiological processes underlying the priming effects of motor imagery (MI) on force performance remain poorly understood. Here, we tested whether the priming effects of embedded MI practice involved short-term changes in corticomotor connectivity. In a within-subjects counterbalanced experimental design, participants (n = 20) underwent a series of experimental sessions consisting of successive maximal isometric contractions of elbow flexor muscles. During inter-trial rest periods, we administered MI, action observation (AO), and a control passive recovery condition. We collected electromyograms (EMG) from both agonists and antagonists of the force task, in addition to electroencephalographic (EEG) brain potentials during force trials. Force output was higher during MI compared to AO and control conditions (both p < 0.01), although fatigability was similar across experimental conditions. We also found a weaker relationship between triceps brachii activation and force output during MI and AO compared to the control condition. Imaginary coherence topographies of alpha (8−12 Hz) oscillations revealed increased connectivity between EEG sensors from central scalp regions and EMG signals from agonists during MI, compared to AO and control. Present results suggest that the priming effects of MI on force performance are mediated by a more efficient cortical drive to motor units yielding reduced agonist/antagonist coactivation.

Normalized compression distance to measure cortico-muscular synchronization

The neuronal functional connectivity is a complex and non-stationary phenomenon creating dynamic networks synchronization determining the brain states and needed to produce tasks. Here, as a measure that quantifies the synchronization between the neuronal electrical activity of two brain regions, we used the normalized compression distance (NCD), which is the length of the compressed file constituted by the concatenated two signals, normalized by the length of the two compressed files including each single signal. To test the NCD sensitivity to physiological properties, we used NCD to measure the cortico-muscular synchronization, a well-known mechanism to control movements, in 15 healthy volunteers during a weak handgrip. Independently of NCD compressor (Huffman or Lempel Ziv), we found out that the resulting measure is sensitive to the dominant-non dominant asymmetry when novelty management is required (p = 0.011; p = 0.007, respectively) and depends on the level of novelty when moving the non-dominant hand (p = 0.012; p = 0.024). Showing lower synchronization levels for less dexterous networks, NCD seems to be a measure able to enrich the estimate of functional two-node connectivity within the neuronal networks that control the body.

Effects of auditory feedback on fine motor output and corticomuscular coherence during a unilateral finger pinch task

Auditory feedback is important to reduce movement error and improve motor performance during a precise motor task. Accurate motion guided by auditory feedback may rely on the neural muscle transmission pathway between the sensorimotor area and the effective muscle. However, it remains unclear how neural activities and sensorimotor loops play a role in enhancing performance. The present study uses an auditory feedback system by simultaneously recording electroencephalogram (EEG), electromyography (EMG), and exert force information to measure corticomuscular coherence (CMC), neural activity, and motor performance during precise unilateral right-hand pinch by using the thumb and the index finger with and without auditory feedback. This study confirms three results. First, compared with no auditory feedback, auditory feedback decreases movement errors. Second, compared with no auditory feedback, auditory feedback decreased the power spectrum in the beta band in the bimanual sensorimotor cortex and the alpha band in the ipsilateral sensorimotor cortex. Finally, CMC was computed between effector muscle of right hand and contralateral sensorimotor cortex. Analyses reveals that the CMC of beta band significantly decreases in auditory feedback condition compared with no auditory feedback condition. The results indicate that auditory feedback decreases the power spectral in the alpha and beta bands and decreases corticospinal connection in the beta band during precise hand control. This study provides a new perspective on the effect of auditory feedback on behavior and brain activity and offers a new idea for designing more suitable and effective rehabilitation and training strategies to improve fine motor performance.

A Semi-Supervised Progressive Learning Algorithm for Brain-Computer Interface

Brain-computer interface (BCI) usually suffers from the problem of low recognition accuracy and large calibration time, especially when identifying motor imagery tasks for subjects with indistinct features and classifying fine grained motion control tasks by electroencephalogram (EEG)-electromyogram (EMG) fusion analysis. To fill the research gap, this paper presents an end-to-end semi-supervised learning framework for EEG classification and EEG-EMG fusion analysis. Benefiting from the proposed metric learning based label estimation strategy, sampling criterion and progressive learning scheme, the proposed framework efficiently extracts distinctive feature embedding from the unlabeled EEG samples and achieves a 5.40% improvement on BCI Competition IV Dataset IIa with 80% unlabeled samples and an average 3.35% improvement on two public BCI datasets. By employing synchronous EMG features as pseudo labels for the unlabeled EEG samples, the proposed framework further extracts deep level features of the synergistic complementarity between the EEG signals and EMG features based on the deep encoders, which improves the performance of hybrid BCI (with a 5.53% improvement for the Upper Limb Motion Dataset and an average 4.34% improvement on two hybrid datasets). Moreover, the ablation experiments show that the proposed framework can substantially improve the performance of the deep encoders (with an average 5.53% improvement). The proposed framework not only largely improves the performance of deep networks in the BCI system, but also significantly reduces the calibration time for EEG-EMG fusion analysis, which shows great potential for building an efficient and high-performance hybrid BCI for the motor rehabilitation process.

Learning neural decoders without labels using multiple data streams

OBJECTIVE

Recent advances in neural decoding have accelerated the development of brain-computer interfaces aimed at assisting users with everyday tasks such as speaking, walking, and manipulating objects. However, current approaches for training neural decoders commonly require large quantities of labeled data, which can be laborious or infeasible to obtain in real-world settings. Alternatively, self-supervised models that share self-generated pseudo-labels between two data streams have shown exceptional performance on unlabeled audio and video data, but it remains unclear how well they extend to neural decoding.

APPROACH

We learn neural decoders without labels by leveraging multiple simultaneously recorded data streams, including neural, kinematic, and physiological signals. Specifically, we apply cross-modal, self-supervised deep clustering to train decoders that can classify movements from brain recordings. After training, we then isolate the decoders for each input data stream and compare the accuracy of decoders trained using cross-modal deep clustering against supervised and unimodal, self-supervised models.

MAIN RESULTS

We find that sharing pseudo-labels between two data streams during training substantially increases decoding performance compared to unimodal, self-supervised models, with accuracies approaching those of supervised decoders trained on labeled data. Next, we extend cross-modal decoder training to three or more modalities, achieving state-of-the-art neural decoding accuracy that matches or slightly exceeds the performance of supervised models. Significance: We demonstrate that cross-modal, self-supervised decoding can be applied to train neural decoders when few or no labels are available and extend the cross-modal framework to share information among three or more data streams, further improving self-supervised training.

Temporally stable beta sensorimotor oscillations and cortico-muscular coupling underlie force steadiness

As humans, we seamlessly hold objects in our hands, and may even lose consciousness of these objects. This phenomenon raises the unsettled question of the involvement of the cerebral cortex, the core area for voluntary motor control, in dynamically maintaining steady muscle force. To address this issue, we measured magnetoencephalographic brain activity from healthy adults who maintained a steady pinch grip. Using a novel analysis approach, we uncovered fine-grained temporal modulations in the beta sensorimotor brain rhythm and its coupling with muscle activity, with respect to several aspects of muscle force (rate of increase/decrease or plateauing high/low). These modulations preceded changes in force features by ∼40 ms and possessed behavioral relevance, as less salient or absent modulation predicted a more stable force output. These findings have consequences for the existing theories regarding the functional role of cortico-muscular coupling, and suggest that steady muscle contractions are characterized by a stable rather than fluttering involvement of the sensorimotor cortex.

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.

A Review and Meta-Analysis of Interactive Metronome Training: Positive Effects for Motor Functioning

Interactive metronome training may be effective for improving motor performances through timing. In this systematic review and meta-analysis, 18 prospective studies met our eligibility criteria, and we summarized the effects of interactive metronome training protocols on motor functioning. We estimated effect sizes by quantifying differences in altered motor functions between participants in interactive metronome training and control groups. Two additional subgroup analyses determined whether the positive effects on motor function improvements were different among (a) three types of participants (i.e., athletes, healthy individuals, and patients with neurological disorders) and (b) two different training protocols (i.e., interactive metronome training only and interactive metronome training combined with an additional motor program). Random-effects model meta-analysis revealed moderate positive effects of interactive metronome training on motor function, with interactive metronome treatment effects significant across athletes, healthy individuals, and patients with neurological disorders. Interactive metronome training combined with additional motor programs showed comparable effects to those obtained after interactive metronome training alone. These findings suggest motor improvement benefits to strengthening or capitalizing on an individual's motor timing.

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.

Enhancement of functional corticomuscular coupling after transcranial ultrasound stimulation in mice

OBJECTIVE

Transcranial ultrasound stimulation (TUS), a large penetration depth and high spatial resolution technology, has developed rapidly in recent years. This study aimed to explore and evaluate the neuromodulation effects of TUS on mouse motor neural circuits under different parameters.

APPROACH

Our study used functional corticomuscular coupling (FCMC) as an index to explore the modulation mechanism for movement control under different TUS parameters (intensity [Isppa] and stimulation duration [SD]). We collected local field potential (LFP) and tail electromyographic (EMG) data under TUS in healthy mice and then introduced the time-frequency coherence method to analyze the FCMC before and after TUS in the time-frequency domain. After that, we defined the relative coherence area (RCA) to quantify the coherence between LFP and EMG under TUS.

MAIN RESULTS

The FCMC at theta, alpha, beta, and gamma bands was enhanced after TUS, and the neuromodulation efficacy mainly occurred in the lower frequency band (theta and alpha band). After TUS with different parameters, the FCMC in all selected frequency bands showed a tendency of increasing first and then decreasing. Further analysis showed that the maximum coupling value of theta band appeared from 0.2 to 0.4 s, and that the maximum coupling value in alpha and gamma band appeared from 0 to 0.2 s.

SIGNIFICANCE

The aforementioned results demonstrate that FCMC in the motor cortex could be modulated by TUS. We provide a theoretical basis for further exploring the modulation mechanism of TUS parameters and clinical application.

Corticomuscular integrated representation of voluntary motor effort in robotic control for wrist-hand rehabilitation after stroke

OBJECTIVE

The central-to-peripheral voluntary motor effort (VME) in physical practice of the paretic limb is a dominant force for driving functional neuroplasticity on motor restoration post-stroke. However, current rehabilitation robots isolated the central and peripheral involvements in the control design, resulting in limited rehabilitation effectiveness. The purpose of this study was to design a corticomuscular coherence (CMC) and electromyography (EMG)-driven (CMC-EMG-driven) system with central-and-peripheral integrated representation of VME for wrist-hand rehabilitation after stroke.

APPROACH

The CMC-EMG-driven control was developed in a neuromuscular electrical stimulation (NMES)-robot system, i.e., CMC-EMG-driven NMES-robot system, to instruct and assist the wrist-hand extension and flexion in persons after stroke. A pilot single-group trial of 20 training sessions was conducted with the developed system to assess the feasibility for wrist-hand practice on the chronic strokes (n=16). The rehabilitation effectiveness was evaluated through clinical assessments, CMC, and EMG activation levels.

MAIN RESULTS

The trigger success rate and laterality index (LI) of CMC were significantly increased in wrist-hand extension across training sessions (p<0.05). After the training, significant improvements in the target wrist-hand joints and suppressed compensation from the proximal shoulder-elbow joints were observed through the clinical scores and EMG activation levels (p<0.05). The central-to-peripheral VME distribution across upper extremity (UE) muscles was also significantly improved, as revealed by the CMC values (p<0.05).

SIGNIFICANCE

Precise wrist-hand rehabilitation was achieved by the developed system, presenting suppressed cortical and muscular compensation from the contralesional hemisphere and the proximal UE, and improved distribution of the central-and-peripheral VME on UE muscles.

Low-Frequency Oscillations and Force Control Capabilities as a Function of Force Level in Older Women

Force variability is potentially related to altered low-frequency oscillations in motor outputs. This study examines the contributions of low-frequency oscillations in force to altered force control performances from lower to higher targeted force levels in older women. Fourteen older women executed unilateral hand-grip force control tasks at 10% and 40% of maximum voluntary contraction (MVC). Force control performances were estimated by calculating force accuracy (root-mean-square-error), force variability (standard deviation), and force regularity (approximate entropy). We additionally quantified low-frequency oscillations in force using absolute powers across four different frequency bands: (a) 0–0.5 Hz, (b) 0.5–1.0 Hz, (c) 1.0–1.5 Hz, and (d) 1.5–2.0 Hz. The findings reveal that from lower to higher targeted force level older women show greater force error, force variability, and force regularity with increased values of absolute power in force across the four frequency bands. The multiple regression models identified a significant relationship between greater force frequency power below 0.5 Hz and more impairments in force control performances. These findings suggest that force frequency oscillation below 0.5 Hz is a key predictor indicating altered stability of task performances across different targeted force levels in older women.

Steadiness training improves the quadriceps strength and self-reported outcomes in persistent quadriceps weakness following nine months of anterior cruciate ligament reconstruction and failed conventional physiotherapy

Background Persistent quadriceps weakness may occur after anterior cruciate ligament reconstruction, limiting the strength gain. However, steadiness strengthening might change the inability to gain strength. Hence, we determined whether strength training with force steadiness and visual biofeedback can improve knee quadriceps torque, self-reported pain and knee stability in patients with persistent quadriceps weakness after knee anterior cruciate ligament reconstruction. Methods Twenty-five patients (aged 43.7 ± 12.2 years) with persistent quadriceps weakness following knee anterior cruciate ligament reconstruction and 34-weeks of physiotherapy performed unilateral strength training for both lower limbs. Four-weeks of conventional physiotherapy at week-30 were given, confirming the inability to gain torque. Then, steadiness training (isometric knee extension with visual biofeedback) was given for 7-weeks. Knee quadriceps peak torque, strength improvement, determination of responders to the intervention, coherence of strength gain between limbs, and self-reported outcomes (pain and knee stability) were obtained. Descriptive statistics and data inference using mixed-ANOVA, McNemar test, and χ² test were described. Findings Quadriceps torque in the reconstructed knee improved (98.2 ± 47.2-155.2 ± 78.9 Nm; p = 0.031) for most patients (84%). Nevertheless, the torque was lower than the healthy side maintaining asymmetry (155.2 ± 78.9 vs. 209.5 ± 101.8 Nm; p = 0.026). There was high (20%) and medium coherence (80%) between limbs. Knee stability and pain improved in 72% of the patients (p < 0.001). Interpretations Steadiness training after anterior cruciate ligament reconstruction followed 9 months of surgery and failed conventional physiotherapy, improves the persistent weakness and self-reported outcomes, but gain strength was dissimilar between limbs.

Physiological tremor is suppressed and force steadiness is enhanced with increased availability of serotonin regardless of muscle fatigue

Although there is evidence that 5-HT acts as an excitatory neuromodulator to enhance maximal force generation, it is largely unknown how 5-HT activity influences the ability to sustain a constant force during steady-state contractions. A total of 22 healthy individuals participated in the study, where elbow flexion force was assessed during brief isometric contractions at 10% maximal voluntary contraction (MVC), 60% MVC, MVC, and during a sustained MVC. The selective serotonin reuptake inhibitor, paroxetine, suppressed physiological tremor and increased force steadiness when performing the isometric contractions. In particular, a main effect of drug was detected for peak power of force within the 8-12 Hz range (P = 0.004) and the coefficient of variation (CV) of force (P < 0.001). A second experiment was performed where intermittent isometric elbow flexions (20% MVC sustained for 2 min) were repeatedly performed so that serotonergic effects on physiological tremor and force steadiness could be assessed during the development of fatigue. Main effects of drug were once again detected for peak power of force in the 8-12 Hz range (P = 0.002) and CV of force (P = 0.003), where paroxetine suppressed physiological tremor and increased force steadiness when the elbow flexors were fatigued. The findings of this study suggest that enhanced availability of 5-HT in humans has a profound influence of maintaining constant force during steady-state contractions. The action of 5-HT appears to suppress fluctuations in force regardless of the fatigue state of the muscle.NEW & NOTEWORTHY Converging lines of research indicate that enhanced serotonin availability increases maximal force generation. However, it is largely unknown how serotonin influences the ability to sustain a constant force. We performed two experiments to assess physiological tremor and force steadiness in unfatigued and fatigued muscle when serotonin availability was enhanced in the central nervous system. Enhanced availability of serotonin reduced physiological tremor amplitude and improved steadiness regardless of muscle fatigue.

Event-Related Desynchronization and Corticomuscular Coherence Observed During Volitional Swallow by Electroencephalography Recordings in Humans

Swallowing in humans involves many cortical areas although it is partly mediated by a series of brainstem reflexes. Cortical motor commands are sent to muscles during swallow. Previous works using magnetoencephalography showed event-related desynchronization (ERD) during swallow and corticomuscular coherence (CMC) during tongue movements in the bilateral sensorimotor and motor-related areas. However, there have been few analogous works that use electroencephalography (EEG). We investigated the ERD and CMC in the bilateral sensorimotor, premotor, and inferior prefrontal areas during volitional swallow by EEG recordings in 18 healthy human subjects. As a result, we found a significant ERD in the beta frequency band and CMC in the theta, alpha, and beta frequency bands during swallow in those cortical areas. These results suggest that EEG can detect the desynchronized activity and oscillatory interaction between the cortex and pharyngeal muscles in the bilateral sensorimotor, premotor, and inferior prefrontal areas during volitional swallow in humans.

The strength of corticomotoneuronal drive underlies ALS split phenotypes and reflects early upper motor neuron dysfunction

BACKGROUND

Split phenotypes, (split hand, elbow, leg, and foot), are probably unique to ALS, and are characterized by having a shared peripheral input of both affected and unaffected muscles. This implies an anatomical origin rostral to the spinal cord, primarily within the cerebral cortex. Therefore, split phenotypes are a potential marker of ALS upper motor neuron pathology. However, to date, reports documenting upper motor neuron dysfunction in split phenotypes have been limited to using transcranial magnetic stimulation and cortical threshold tracking techniques. Here, we consider several other potential methodologies that could confirm a primary upper motor neuron pathology in split phenotypes.

METHODS

We review the potential of: 1. measuring the compound excitatory post-synaptic potential recorded from a single activated motor unit, 2. cortical-muscular coherence, and 3. new advanced modalities of neuroimaging (high-resolution imaging protocols, ultra-high field MRI platforms [7T], and novel Non-Gaussian diffusion models).

CONCLUSIONS

We propose that muscles involved in split phenotypes are those functionally involved in the human motor repertoire used particularly in complex activities. Their anterior horn cells receive the strongest corticomotoneuronal input. This is also true of the weakest muscles that are the earliest to be affected in ALS. Descriptions of split hand in non-ALS cases and proposals that peripheral nerve or muscle dysfunction may be causative are contentious. Only a few carefully controlled cases of each form of split phenotype, using upper motor neuron directed methodologies, are necessary to prove our postulate.

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.

Neuromechanical Biomarkers for Robotic Neurorehabilitation

One of the current challenges for translational rehabilitation research is to develop the strategies to deliver accurate evaluation, prediction, patient selection, and decision-making in the clinical practice. In this regard, the robot-assisted interventions have gained popularity as they can provide the objective and quantifiable assessment of the motor performance by taking the kinematics parameters into the account. Neurophysiological parameters have also been proposed for this purpose due to the novel advances in the non-invasive signal processing techniques. In addition, other parameters linked to the motor learning and brain plasticity occurring during the rehabilitation have been explored, looking for a more holistic rehabilitation approach. However, the majority of the research done in this area is still exploratory. These parameters have shown the capability to become the “biomarkers” that are defined as the quantifiable indicators of the physiological/pathological processes and the responses to the therapeutical interventions. In this view, they could be finally used for enhancing the robot-assisted treatments. While the research on the biomarkers has been growing in the last years, there is a current need for a better comprehension and quantification of the neuromechanical processes involved in the rehabilitation. In particular, there is a lack of operationalization of the potential neuromechanical biomarkers into the clinical algorithms. In this scenario, a new framework called the “Rehabilomics” has been proposed to account for the rehabilitation research that exploits the biomarkers in its design. This study provides an overview of the state-of-the-art of the biomarkers related to the robotic neurorehabilitation, focusing on the translational studies, and underlying the need to create the comprehensive approaches that have the potential to take the research on the biomarkers into the clinical practice. We then summarize some promising biomarkers that are being under investigation in the current literature and provide some examples of their current and/or potential applications in the neurorehabilitation. Finally, we outline the main challenges and future directions in the field, briefly discussing their potential evolution and prospective.

Individualized beta-band oscillatory transcranial direct current stimulation over the primary motor cortex enhances corticomuscular coherence and corticospinal excitability in healthy individuals

BACKGROUND

Simultaneously modulating individual neural oscillation and cortical excitability may be important for enhancing communication between the primary motor cortex and spinal motor neurons, which plays a key role in motor control. However, it is unknown whether individualized beta-band oscillatory transcranial direct current stimulation (otDCS) enhances corticospinal oscillation and excitability.

OBJECTIVE

This study investigated the effects of individualized beta-band otDCS on corticomuscular coherence (CMC) and corticospinal excitability in healthy individuals.

METHODS

In total, 29 healthy volunteers participated in separate experiments. They received the following stimuli for 10 min on different days: 1) 2-mA otDCS with individualized beta-band frequencies, 2) 2-mA transcranial alternating current stimulation (tACS) with individualized beta-band frequencies, and 3) 2-mA transcranial direct current stimulation (tDCS). The changes in CMC between the vertex and tibialis anterior (TA) muscle and TA muscle motor-evoked potentials (MEPs) were assessed before and after (immediately, 10 min, and 20 min after) stimulation on different days. Additionally, 20-Hz otDCS for 10 min was applied to investigate the effects of a fixed beta-band frequency on CMC.

RESULTS

otDCS significantly increased CMC and MEPs immediately after stimulation, whereas tACS and tDCS had no effects. There was a significant negative correlation between normalized CMC changes in response to 20-Hz otDCS and the numerical difference between the 20-Hz and individualized CMC peak frequency before the stimulation.

CONCLUSIONS

These findings suggest that simultaneous modulation of neural oscillation and cortical excitability is critical for enhancing corticospinal communication. Individualized otDCS holds potential as a useful method in the field of neurorehabilitation.