Neural coupling between the central nervous system and the periphery is essential for the neural control of movement. Corticomuscular coherence is a popular linear technique to assess synchronised ...oscillatory activity in the sensorimotor system. This oscillatory coupling originates from ascending somatosensory feedback and descending motor commands. However, corticomuscular coherence cannot separate this bidirectionality. Furthermore, the sensorimotor system is nonlinear, resulting in cross‐frequency coupling. Cross‐frequency oscillations cannot be assessed nor exploited by linear measures. Here, we emphasise the need of novel coupling measures, which provide directionality and acknowledge nonlinearity, to unveil neural coupling in the sensorimotor system. We highlight recent advances in the field and argue that assessing directionality and nonlinearity of neural coupling will break new ground in the study of the control of movement in healthy and neurologically impaired individuals.
Coherence is a standard linear technique to investigate corticomuscular interaction. Advanced signal analyses revealed nonlinearity in the sensorimotor system, showing cross‐frequency coupling between brain oscillations and muscle activity (Yang et al., 2016, Front. Comput. Neurosci.). We argue that nonlinear neural analyses will open new ground to study healthy and pathological control of movement.
The simultaneous modulation of joint torque and stiffness enables humans to perform large repertoires of movements, while versatilely adapting to external mechanical demands. Multi-muscle force ...control is key for joint torque and stiffness modulation. However, the inability to directly measure muscle force in the intact moving human prevents understanding how muscle force causally links to joint torque and stiffness. Joint stiffness is predominantly estimated via joint perturbation-based experiments in combination with system identification techniques. However, these techniques provide joint-level stiffness estimations with no causal link to the underlying muscle forces. Moreover, the need for joint perturbations limits the generalizability and applicability to study natural movements. Here, we present an electromyography (EMG)-driven musculoskeletal modeling framework that can be calibrated to match reference joint torque and stiffness profiles simultaneously via a multi-term objective function. EMG-driven models calibrated on <2 s of reference torque and stiffness data could blindly estimate reference profiles across 100 s of data not used for calibration. Model calibrations using an objective function comprising torque and stiffness terms always provided less feasible solutions than an objective function comprising solely a torque term, thereby reducing the space of feasible muscle–tendon parameters. Results also showed the proposed framework’s ability to estimate joint stiffness in unperturbed conditions, while capturing differences against stiffness profiles derived during perturbed conditions. The proposed framework may provide new ways for studying causal relationships between muscle force and joint torque and stiffness during movements in interaction with the environment, with broad implications across biomechanics, rehabilitation and robotics.
The contributions of the cerebral cortex to human balance control are clearly demonstrated by the profound impact of cortical lesions on the ability to maintain standing balance. The cerebral cortex ...is thought to regulate subcortical postural centers to maintain upright balance and posture under varying environmental conditions and task demands. However, the cortical mechanisms that support standing balance remain elusive. Here, we present an EEG-based analysis of cortical oscillatory dynamics during the preparation and execution of balance responses with distinct postural demands. In our experiment, participants responded to backward movements of the support surface either with one forward step or by keeping their feet in place. To challenge the postural control system, we applied participant-specific high accelerations of the support surface such that the postural demand was low for stepping responses and high for feet-in-place responses. We expected that postural demand modulated the power of intrinsic cortical oscillations.
Independent component analysis and time-frequency domain statistics revealed stronger suppression of alpha (9–13 Hz) and low-gamma (31–34 Hz) rhythms in the supplementary motor area (SMA) when preparing for feet-in-place responses (i.e., high postural demand). Irrespective of the response condition, support-surface movements elicited broadband (3–17 Hz) power increase in the SMA and enhancement of the theta (3–7 Hz) rhythm in the anterior prefrontal cortex (PFC), anterior cingulate cortex (ACC), and bilateral sensorimotor cortices (M1/S1). Although the execution of reactive responses resulted in largely similar cortical dynamics, comparison between the bilateral M1/S1 showed that stepping responses corresponded with stronger suppression of the beta (13–17 Hz) rhythm in the M1/S1 contralateral to the support leg. Comparison between response conditions showed that feet-in-place responses corresponded with stronger enhancement of the theta (3–7 Hz) rhythm in the PFC. Our results provide novel insights into the cortical dynamics of SMA, PFC, and M1/S1 during the control of human balance.
•We evaluated the cortical control of balance from EEG-derived source-level activity.•We compared two distinct reactive balance responses with different postural demands.•Stronger preparatory SMA activity corresponded with higher postural demand.•Midfrontal theta activity may signify instability detection and/or motor inhibition.•Lateralized M1/S1 beta rhythm suggests contributions to support side stabilization.
Neurophysiologic correlates of motor learning that can be monitored during neurorehabilitation interventions can facilitate the development of more effective learning methods. Previous studies have ...focused on the role of the beta band (14–30 Hz) because of its clear response during motor activity. However, it is difficult to discriminate between beta activity related to learning a movement and performing the movement. In this study, we analysed differences in the electroencephalography (EEG) power spectra of complex and simple explicit sequential motor tasks in healthy young subjects. The complex motor task (CMT) allowed EEG measurement related to motor learning. In contrast, the simple motor task (SMT) made it possible to control for EEG activity associated with performing the movement without significant motor learning. Source reconstruction of the EEG revealed task-related activity from 5 clusters covering both primary motor cortices (M1) and 3 clusters localised to different parts of the cingulate cortex (CC). We found no association between M1 beta power and learning, but the CMT produced stronger bilateral beta suppression compared to the SMT. However, there was a positive association between contralateral M1 theta (5–8 Hz) and alpha (8–12 Hz) power and motor learning, and theta and alpha power in the posterior mid-CC and posterior CC were positively associated with greater motor learning. These findings suggest that the theta and alpha bands are more related to motor learning than the beta band, which might merely relate to the level of perceived difficulty during learning.
Human hands are complex biomechanical systems that allow for dexterous tasks with many degrees of freedom. Coordination of the fingers is essential for many activities of daily living and involves ...integrating sensory signals. During this sensory integration, the central nervous system deals with the uncertainty of sensory signals. When handling compliant objects, force and position are related. Interactions with stiff objects result in reduced position changes and increased force changes compared to compliant objects. Literature has shown sensory integration of force and position at the shoulder. Nevertheless, differences in sensory requirements between proximal and distal joints may lead to different proprioceptive representations, hence findings at proximal joints cannot be directly transferred to distal joints, such as the digits. Here, we investigate the sensory integration of force and position during pinching. A haptic manipulator rendered a virtual spring with adjustable stiffness between the index finger and the thumb. Participants had to blindly reproduce a force against the spring. In both visual reference trials and blind reproduction trials, the relation between pinch force and spring compression was constant. However, by covertly changing the spring characteristics in catch trials into an adjusted force-position relation, the participants’ weighting of force and position could be revealed. In agreement with previous studies on the shoulder, participants relied more on force sense in trials with higher stiffness. This study demonstrated stiffness-dependent sensory integration of force and position feedback during pinching.
Human stance involves multiple segments, including the legs and trunk, and requires coordinated actions of both. A novel method was developed that reliably estimates the contribution of the left and ...right leg (i.e., the ankle and hip joints) to the balance control of individual subjects.
The method was evaluated using simulations of a double-inverted pendulum model and the applicability was demonstrated with an experiment with seven healthy and one Parkinsonian participant. Model simulations indicated that two perturbations are required to reliably estimate the dynamics of a double-inverted pendulum balance control system. In the experiment, two multisine perturbation signals were applied simultaneously. The balance control system dynamic behaviour of the participants was estimated by Frequency Response Functions (FRFs), which relate ankle and hip joint angles to joint torques, using a multivariate closed-loop system identification technique.
In the model simulations, the FRFs were reliably estimated, also in the presence of realistic levels of noise. In the experiment, the participants responded consistently to the perturbations, indicated by low noise-to-signal ratios of the ankle angle (0.24), hip angle (0.28), ankle torque (0.07), and hip torque (0.33). The developed method could detect that the Parkinson patient controlled his balance asymmetrically, that is, the right ankle and hip joints produced more corrective torque.
The method allows for a reliable estimate of the multisegmental feedback mechanism that stabilizes stance, of individual participants and of separate legs.
There is no objective gold standard to detect tremors. This concerns not only the choice of the algorithm and sensors, but methods are often designed to detect tremors in one specific group of ...patients during the performance of a specific task. Therefore, the aim of this study is twofold. First, an objective quantitative method to detect tremor windows (TWs) in accelerometer and electromyography recordings is introduced. Second, the tremor stability index (TSI) is determined to indicate the advantage of detecting TWs prior to analysis. Ten Parkinson's disease (PD) patients, ten essential tremor (ET) patients, and ten healthy controls (HC) performed a resting, postural and movement task. Data was split into 3-s windows, and the power spectral density was calculated for each window. The relative power around the peak frequency with respect to the power in the tremor band was used to classify the windows as either tremor or non-tremor. The method yielded a specificity of 96.45%, sensitivity of 84.84%, and accuracy of 90.80% of tremor detection. During tremors, significant differences were found between groups in all three parameters. The results suggest that the introduced method could be used to determine under which conditions and to which extent undiagnosed patients exhibit tremors.
Objective: Accurate estimation of stiffness across anatomical levels (i.e., joint, muscle, and tendon) in vivo has long been a challenge in biomechanics. Recent advances in electromyography ...(EMG)-driven musculoskeletal modeling have allowed the non-invasive estimation of stiffness during dynamic joint rotations. Nevertheless, validation has been limited to the joint level due to a lack of simultaneous in vivo experimental measurements of muscle and tendon stiffness. Methods: With a focus on the triceps surae, we employed a novel perturbation-based experimental technique informed by dynamometry and ultrasonography to derive reference stiffness at the joint, muscle, and tendon levels simultaneously. Here, we propose a new EMG-driven model-based approach that does not require external joint perturbation, nor ultrasonography, to estimate multi-level stiffness. We present a novel set of closed-form equations that enables the person-specific tuning of musculoskeletal parameters dictating biological stiffness, including passive force-length relationships in modeled muscles and tendons. Results: Calibrated EMG-driven musculoskeletal models estimated the reference data with average normalized root-mean-square error <inline-formula><tex-math notation="LaTeX">\approx</tex-math></inline-formula> 20%. Moreover, only when calibrated tendons were approximately four times more compliant than typically modeled, our approach could estimate multi-level reference stiffness. Conclusion: EMG-driven musculoskeletal models can be calibrated on a larger set of reference data to provide more realistic values for the biomechanical variables across multiple anatomical levels. Moreover, the tendon models that are typically used in musculoskeletal modeling are too stiff. Significance: Calibrated musculoskeletal models informed by experimental measurements give access to an augmented range of biomechanical variables that might not be easily measured with sensors alone.
Knowledge on joint impedance during walking in various conditions is relevant for clinical decision-making and the development of robotic gait trainers, leg prostheses, leg orthotics and wearable ...exoskeletons. Whereas ankle impedance during walking has been experimentally assessed, knee and hip joint impedance during walking have not been identified yet. Here we developed and evaluated a lower limb perturbator to identify hip, knee and ankle joint impedance during treadmill walking. The lower limb perturbator (LOPER) consists of an actuator connected to the thigh via rods. The LOPER allows to apply force perturbations to a free-hanging leg, while standing on the contralateral leg, with a bandwidth of up to 39 Hz. While walking in minimal impedance mode, the interaction forces between LOPER and the thigh were low (<5N) and the effect on the walking pattern was smaller than the within-subject variability during normal walking. Using a non-linear multibody dynamical model of swing leg dynamics, the hip, knee and ankle joint impedance were estimated at three time points during the swing phase for nine subjects walking at a speed of 0.5 m/s. The identified model was well able to predict the experimental responses for the hip and knee, since the mean variance accounted (VAF) for was 99% and 96%, respectively. The ankle lacked a consistent response and the mean VAF of the model fit was only 77%, and therefore the estimated ankle impedance was not reliable. The averaged across-subjects stiffness varied between the three time points within 34-66 and 0-3.5 Nm/rad Nm/rad for the hip and knee joint respectively. The damping varied between 1.9-4.6 and 0.02-0.14 Nms/rad Nms/rad for hip and knee respectively. The developed LOPER has a negligible effect on the unperturbed walking pattern and allows to identify hip and knee impedance during the swing phase.
Impaired postural control in Parkinson's disease (PD) seriously compromises life quality. Although balance training improves mobility and postural stability, lack of quantitative studies on the ...neurophysiological mechanisms of balance training in PD impedes the development of patient-specific therapies. We evaluated the effects of a balance-training program using functional balance and mobility tests, posturography, and a postural control model.
Center-of-pressure (COP) data of 40 PD patients before and after a 12-session balance-training program, and 20 healthy control subjects were recorded in four conditions with two tasks on a rigid surface (R-tasks) and two on foam. A postural control model was fitted to describe the posturography data. The model comprises a neuromuscular controller, a time delay, and a gain scaling the internal disturbance torque.
Patients' axial rigidity before training resulted in slower COP velocity in R-tasks; which was reflected as lower internal torque gain. Furthermore, patients exhibited poor stability on foam, remarked by abnormal higher sway amplitude. Lower control parameters as well as higher time delay were responsible for patients' abnormal high sway amplitude. Balance training improved all clinical scores on functional balance and mobility. Consistently, improved 'flexibility' appeared as enhanced sway velocity (increased internal torque gain). Balance training also helped patients to develop the 'stability degree' (increase control parameters), and to respond more quickly in unstable condition of stance on foam.
Projection of the common posturography measures on a postural control model provided a quantitative framework for unraveling the neurophysiological factors and different recovery mechanisms in impaired postural control in PD.
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