A critical evaluation of the force control hypothesis in motor control

Evaluation of generic EMG-Torque models across two Upper-Limb joints

Advanced single-use dynamic EMG-torque models require burdensome subject-specific calibration contractions and have historically been assumed to produce lower error than generic models (i.e., models that are identical across subjects and muscles). To investigate this assumption, we studied generic one degree of freedom (DoF) models derived from the ensemble median of subject-specific models, evaluated across subject, DoF and joint. We used elbow (N = 64) and hand-wrist (N = 9) datasets. Subject-specific elbow models performed statistically better [5.79 ± 1.89 %MVT (maximum voluntary torque) error] than generic elbow models (6.21 ± 1.85 %MVT error). However, there were no statistical differences between subject-specific vs. generic models within each hand-wrist DoF. Next, we evaluated generic models across joints. The best hand-wrist generic model had errors of 6.29 ± 1.85 %MVT when applied to the elbow. The elbow generic model had errors of 7.04 ± 2.29 %MVT when applied to the hand-wrist. The generic elbow model was statistically better in both joints, compared to the generic hand-wrist model. Finally, we tested Butterworth filter models (a simpler generic model), finding no statistical differences between optimum Butterworth and subject-specific models. Overall, generic models simplified EMG-torque training without substantive performance degradation and provided the possibility of transfer learning between joints.

The Role of Imitation, Primitives, and Spatial Referent Coordinates in Motor Control: Implications for Writing and Reading

We review a body of literature related to the drawing and recognition of geometrical two-dimensional linear drawings including letters. Handwritten letters are viewed not as two-dimensional geometrical objects but as one-dimensional trajectories of the tip of the implement. Handwritten letters are viewed as composed of a small set of kinematic primitives. Recognition of objects is mediated by processes of their creation (actual or imagined)-the imitation principle, a particular example of action-perception coupling. The concept of spatial directional field guiding the trajectories is introduced and linked to neuronal population vectors. Further, we link the kinematic description to the theory of control with spatial referent coordinates. This framework allows interpreting a number of experimental observations and clinical cases of agnosia. It also allows formulating predictions for new experimental studies of writing.

Sensory weighting of position and force feedback during pinching

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.

Measuring complexity of muscle force control: Theoretical principles and clinical relevance in musculoskeletal research and practice

Musculoskeletal conditions affect bones, joints, and muscles of the locomotor system and are a leading cause of disability worldwide. This suggests that current musculoskeletal rehabilitation techniques fail to target the characteristics (e.g., physiological/physical/psychological) most influential for long-term musculoskeletal health. To identify whether a physiological characteristic is impaired, it must be measured. In neuromuscular control, traditional research approaches use magnitude-based measurements (e.g., peak force/standard deviation of force/coefficient of variation of force). However, magnitude-based measurements miss 'hidden information' regarding a physiological system's status across time. To better identify physiological characteristics that are clinically-important for long-term musculoskeletal health, other measurement approaches currently less applied in musculoskeletal research may be helpful. The purpose of this article is to present an introduction to technical and measurement principles for quantifying the 'complexity' of muscle force control as one representation of peripheral joint neuromuscular control. Complexity measurements are time-based and consider the irregular temporal structure of physiological signals. We review theoretical principles underlying measuring complexity of muscle force control and explain its clinical relevance for musculoskeletal scientists and clinicians. The principles include sensorimotor control of peripheral joints, muscle force signal construction and features, muscle force control measurement procedures, and variability and complexity variables. We propose the potential utility of measuring the complexity of muscle force control for diagnosing sensorimotor system impairment and prognosis following musculoskeletal disease or injury. This article will serve as an educational asset and a scientific resource that will inform future research directions to optimise rehabilitation for people with peripheral joint disease and injury.

Optimum trajectory learning in musculoskeletal systems with model predictive control and deep reinforcement learning

From the computational point of view, musculoskeletal control is the problem of controlling high degrees of freedom and dynamic multi-body system that is driven by redundant muscle units. A critical challenge in the control perspective of skeletal joints with antagonistic muscle pairs is finding methods robust to address this ill-posed nonlinear problem. To address this computational problem, we implemented a twofold optimization and learning framework to be specialized in addressing the redundancies in the muscle control . In the first part, we used model predictive control to obtain energy efficient skeletal trajectories to mimick human movements. The second part is to use deep reinforcement learning to obtain a sequence of stimulus to be given to muscles in order to obtain the skeletal trajectories with muscle control. We observed that the desired stimulus to muscles is only efficiently constructed by integrating the state and control input in a closed-loop setting as it resembles the proprioceptive integration in the spinal cord circuits. In this work, we showed how a variety of different reference trajectories can be obtained with optimal control and how these reference trajectories are mapped to the musculoskeletal control with deep reinforcement learning. Starting from the characteristics of human arm movement to obstacle avoidance experiment, our simulation results confirm the capabilities of our optimization and learning framework for a variety of dynamic movement trajectories. In summary, the proposed framework is offering a pipeline to complement the lack of experiments to record human motion-capture data as well as study the activation range of muscles to replicate the specific trajectory of interest. Using the trajectories from optimal control as a reference signal for reinforcement learning implementation has allowed us to acquire optimum and human-like behaviour of the musculoskeletal system which provides a framework to study human movement in-silico experiments. The present framework can also allow studying upper-arm rehabilitation with assistive robots given that one can use healthy subject movement recordings as reference to work on the control architecture of assistive robotics in order to compensate behavioural deficiencies. Hence, the framework opens to possibility of replicating or complementing labour-intensive, time-consuming and costly experiments with human subjects in the field of movement studies and digital twin of rehabilitation.

The legacy of Gerald L. Gottlieb in human movement neuroscience

In this paper, we review the legacy of Gerald (Gerry) Gottlieb in various fields related to the neural control of human movement. His studies on the myotatic (stretch) reflex and postmyotatic responses to ankle joint perturbations paved the way for current explorations of long-loop reflexes and their role in the control of movement. The dual-strategy hypothesis introduced order into a large body of literature on the triphasic muscle activation patterns seen over a variety of voluntary movements in healthy persons. The dual-strategy hypothesis continues to be important for understanding the performance of subjects with disordered motor control. The principle of linear synergy (covariance of joint torques) was an attempt to solve one of the notorious problems of motor redundancy, which remains an important topic in the field. Gerry's attitude toward the equilibrium-point hypothesis varied between rejection and using it to explore patterns of hypothetical control variables and movement variability. The discovery of reciprocal excitation in healthy neonates fostered other studies of changes in spinal cord physiology as motor skills develop. In addition, studies of people with spasticity and the effects of treatment with intrathecal baclofen were crucial in demonstrating the possibility of unmasking voluntary movements after suppression of the hyperreflexia of spasticity. Gerry Gottlieb contributed a significant body of knowledge that formed a solid foundation from which to study a variety of neurological diseases and their treatments, and a more comprehensive and parsimonious foundation to describe the neural control of human movement.

Effect of Object Texture and Weight on Ipsilateral Corticospinal Influences During Bimanual Holding in Humans

We tested the hypothesis that the ipsilateral corticospinal system, like the contralateral corticospinal system, controls the threshold muscle length at which wrist muscles and the stretch reflex begin to act during holding tasks. Transcranial magnetic stimulation was applied over the right primary motor cortex in 21 healthy subjects holding a smooth or coarse block between the hands. Regardless of the lifting force, motor evoked potentials in right wrist flexors were larger for the smooth block. This result was explained based on experimental evidence that motor actions are controlled by shifting spatial stretch reflex thresholds. Thus, the ipsilateral corticospinal system is involved in threshold position control by modulating facilitatory influences of hand skin afferents on motoneurons of wrist muscles during bimanual object manipulation.

Motor learning in neurological rehabilitation

While most upper limb training interventions in neurological rehabilitation are based on established principles of motor learning and neural plasticity, recovery potential may be improved if the focus includes remediating an individual's specific motor impairment within the framework of a motor control theory. This paper reviews current theories of motor control and motor learning and describes how they can be incorporated into training programs to enhance sensorimotor recovery in patients with neurological lesions. An emphasis is placed on dynamical systems theory and the use of new technologies such as virtual, augmented and mixed reality applications for rehabilitation to facilitate learning.Implications for RehabilitationKinematic abundance allows the healthy nervous system to produce different combinations of joint rotations to perform a desired task.The structure of practice to improve the movement repertoire in rehabilitation should take into account the kinematic abundance of the system.Learning can be enhanced by varied practice with feedback about key movement elements.Virtual reality environments provide opportunities to manipulate the structure and schedule of practice and feedback.

Understanding and Synergy: A Single Concept at Different Levels of Analysis?

Biological systems differ from the inanimate world in their behaviors ranging from simple movements to coordinated purposeful actions by large groups of muscles, to perception of the world based on signals of different modalities, to cognitive acts, and to the role of self-imposed constraints such as laws of ethics. Respectively, depending on the behavior of interest, studies of biological objects based on laws of nature (physics) have to deal with different salient sets of variables and parameters. Understanding is a high-level concept, and its analysis has been linked to other high-level concepts such as "mental model" and "meaning". Attempts to analyze understanding based on laws of nature are an example of the top-down approach. Studies of the neural control of movements represent an opposite, bottom-up approach, which starts at the interface with classical physics of the inanimate world and operates with traditional concepts such as forces, coordinates, etc. There are common features shared by the two approaches. In particular, both assume organizations of large groups of elements into task-specific groups, which can be described with only a handful of salient variables. Both assume optimality criteria that allow the emergence of families of solutions to typical tasks. Both assume predictive processes reflected in anticipatory adjustments to actions (motor and non-motor). Both recognize the importance of generating dynamically stable solutions. The recent progress in studies of the neural control of movements has led to a theory of hierarchical control with spatial referent coordinates for the effectors. This theory, in combination with the uncontrolled manifold hypothesis, allows quantifying the stability of actions with respect to salient variables. This approach has been used in the analysis of motor learning, changes in movements with typical and atypical development and with aging, and impaired actions by patients with various neurological disorders. It has been developed to address issues of kinesthetic perception. There seems to be hope that the two counter-directional approaches will meet and result in a single theoretical scheme encompassing biological phenomena from figuring out the best next move in a chess position to activating motor units appropriate for implementing that move on the chessboard.

Unintentional Force Drifts as Consequences of Indirect Force Control with Spatial Referent Coordinates

We explored the phenomenon of unintentional force drifts in the absence of visual feedback. Based on the idea of direct force control with internal models and on the idea of indirect force control with referent coordinates to the involved muscle groups, contrasting predictions were drawn for changes in the drift magnitude when acting against external spring loads. Fifteen young subjects performed typical accurate force production tasks by pressing with the Index finger at 20% of maximal voluntary contraction (MVC) in isometric conditions and while acting against one of the three external springs with different stiffness. The visual feedback on the force was turned off after 5 s. At the end of each 20-s trial, the subjects relaxed and then tried to reproduce the final force level. The force drifts were significantly smaller in the spring conditions, particularly when acting against more compliant springs. The subjects were unaware of the force drifts and, during force matching, produced forces close to the initial force magnitude, which were not different across the conditions. There was a trend toward larger drifts during performance by the dominant hand. We view these observations as strong arguments in favor of the theory of control with spatial referent coordinates. In particular, force drifts were likely consequences of drifts of referent coordinates to both agonist and antagonist muscles. The lack of drift effects on both perception-to-report and perception-to-act fit the scheme of kinesthetic perception based on the interaction of efferent (referent coordinate) and afferent processes.

Central pattern generator and human locomotion in the context of referent control of motor actions

Unperturbed human locomotion presumably results from feedforward shifts in stable body equilibrium in the environment, thus avoiding falling and subsequent catching considered in alternative theories of locomotion. Such shifts are achieved by relocation of the referent body configuration at which multiple muscle recruitment begins. Rather than being directly specified by a central pattern generator, multiple muscles are activated depending on the extent to which the body is deflected from the referent, threshold body configuration, as confirmed in previous studies. Based on the referent control theory of action and perception, solutions to classical problems in motor control are offered, including the previously unresolved problem of the integration of central and reflex influences on motoneurons and the problem of how posture and movement are related. The speed of locomotion depends on the rate of shifts in the referent body configuration. The transition from walking to running results from increasing the rate of referent shifts. It is emphasised that there is a certain hierarchy between reciprocal and co-activation of agonist and antagonist muscles during locomotion and other motor actions, which is also essential for the understanding of how locomotor speed is regulated. The analysis opens a new avenue in neurophysiological approaches to human locomotion with clinical implications.

One more time about motor (and non-motor) synergies

We revisit the concept of synergy based on the recently translated classical book by Nikolai Bernstein (On the construction of movements, Medgiz, Moscow 1947; Latash, Bernstein's Construction of Movements, Routledge, Abingdon 2020b) and progress in understanding the physics and neurophysiology of biological action. Two aspects of synergies are described: organizing elements into stable groups (modes) and ensuring dynamical stability of salient performance variables. The ability of the central nervous system to attenuate synergies in preparation for a quick action-anticipatory synergy adjustments-is emphasized. Recent studies have demonstrated synergies at the level of hypothetical control variables associated with spatial referent coordinates for effectors. Overall, the concept of synergies fits naturally the hierarchical scheme of control with referent coordinates with an important role played by back-coupling loops within the central nervous system and from peripheral sensory endings. Further, we review studies showing non-trivial changes in synergies with development, aging, fatigue, practice, and a variety of neurological disorders. Two aspects of impaired synergic control-impaired stability and impaired agility-are introduced. The recent generalization of the concept of synergies for non-motor domains, including perception, is discussed. We end the review with a list of unresolved and troubling issues.

Simplified Optimal Estimation of Time-Varying Electromyogram Standard Deviation (EMGσ): Evaluation on Two Datasets

To facilitate the broader use of EMG signal whitening, we studied four whitening procedures of various complexities, as well as the roles of sampling rate and noise correction. We separately analyzed force-varying and constant-force contractions from 64 subjects who completed constant-posture tasks about the elbow over a range of forces from 0% to 50% maximum voluntary contraction (MVC). From the constant-force tasks, we found that noise correction via the root difference of squares (RDS) method consistently reduced EMG recording noise, often by a factor of 5-10. All other primary results were from the force-varying contractions. Sampling at 4096 Hz provided small and statistically significant improvements over sampling at 2048 Hz (~3%), which, in turn, provided small improvements over sampling at 1024 Hz (~4%). In comparing equivalent processing variants at a sampling rate of 4096 Hz, whitening filters calibrated to the EMG spectrum of each subject generally performed best (4.74% MVC EMG-force error), followed by one universal whitening filter for all subjects (4.83% MVC error), followed by a high-pass filter whitening method (4.89% MVC error) and then a first difference whitening filter (4.91% MVC error)-but none of these statistically differed. Each did significantly improve from EMG-force error without whitening (5.55% MVC). The first difference is an excellent whitening option over this range of contraction forces since no calibration or algorithm decisions are required.

Efference copy in kinesthetic perception: a copy of what is it?

A number of notions in the fields of motor control and kinesthetic perception have been used without clear definitions. In this review, we consider definitions for efference copy, percept, and sense of effort based on recent studies within the physical approach, which assumes that the neural control of movement is based on principles of parametric control and involves defining time-varying profiles of spatial referent coordinates for the effectors. The apparent redundancy in both motor and perceptual processes is reconsidered based on the principle of abundance. Abundance of efferent and afferent signals is viewed as the means of stabilizing both salient action characteristics and salient percepts formalized as stable manifolds in high-dimensional spaces of relevant elemental variables. This theoretical scheme has led recently to a number of novel predictions and findings. These include, in particular, lower accuracy in perception of variables produced by elements involved in a multielement task compared with the same elements in single-element tasks, dissociation between motor and perceptual effects of muscle coactivation, force illusions induced by muscle vibration, and errors in perception of unintentional drifts in performance. Taken together, these results suggest that participation of efferent signals in perception frequently involves distorted copies of actual neural commands, particularly those to antagonist muscles. Sense of effort is associated with such distorted efferent signals. Distortions in efference copy happen spontaneously and can also be caused by changes in sensory signals, e.g., those produced by muscle vibration.

Seeing motion of controlled object improves grip timing in adults with autism spectrum condition: evidence for use of inverse dynamics in motor control

Previous studies (Haswell et al. in Nat Neurosci 12:970-972, 2009; Marko et al. in Brain J Neurol 138:784-797, 2015) reported that people with autism rely less on vision for learning to reach in a force field. This suggested a possibility that they have difficulties in extracting force information from visual motion signals, a process called inverse dynamics computation. Our recent study (Takamuku et al. in J Int Soc Autism Res 11:1062-1075, 2018) examined the ability of inverse computation with two perceptual tasks and found similar performances in typical and autistic adults. However, this tested the computation only in the context of sensory perception while it was possible that the suspected disability is specific to the motor domain. Here, in order to address the concern, we tested the use of inverse dynamics computation in the context of motor control by measuring changes in grip timing caused by seeing/not seeing a controlled object. The motion of the object was informative of its inertial force and typical participants improved their grip timing based on the visual feedback. Our interest was on whether the autism participants show the same improvement. While some autism participants showed atypical hand slowing when seeing the controlled object, we found no evidence of abnormalities in the inverse computation in our grip timing task or in a replication of the perceptual task. This suggests that the ability of inverse dynamics computation is preserved not only for sensory perception but also for motor control in adults with autism.

Embodied skillful performance: where the action is

When someone masters a skill, their performance looks to us like second nature: it looks as if their actions are smoothly performed without explicit, knowledge-driven, online monitoring of their performance. Contemporary computational models in motor control theory, however, are instructionist: that is, they cast skillful performance as a knowledge-driven process. Optimal motor control theory (OMCT), as representative par excellence of such approaches, casts skillful performance as an instruction, instantiated in the brain, that needs to be executed-a motor command. This paper aims to show the limitations of such instructionist approaches to skillful performance. We specifically address the question of whether the assumption of control-theoretic models is warranted. The first section of this paper examines the instructionist assumption, according to which skillful performance consists of the execution of theoretical instructions harnessed in motor representations. The second and third sections characterize the implementation of motor representations as motor commands, with a special focus on formulations from OMCT. The final sections of this paper examine predictive coding and active inference-behavioral modeling frameworks that descend, but are distinct, from OMCT-and argue that the instructionist, control-theoretic assumptions are ill-motivated in light of new developments in active inference.

Simplified Optimal Estimation of Time-Varying Electromyogram Standard Deviation (EMGσ)

Previous works have shown that whitening improves the processed electromyogram (EMG) signal for use in end applications such as EMG to torque modelling. Traditional whitening methods fit each subject from calibration contractions, which is a hindrance to their widespread use. To eliminate this cumbersome calibration, a universal whitening filter was developed using the whitening filters from a pre-existing data set (64 subjects, 8 electrodes/subject). Since the shape of each subject-specific whitening filter was observed to be relatively consistent across subjects, the universal whitening filter was formed as their ensemble average. The processed EMG was then used to model surface EMG to torque about the elbow. Traditional and universal whitening provided the same EMG-torque benefit, each improving statistically over unwhitened processing by ~14% during dynamic contractions. We further studied the use of root difference of squares (RDS) post-processing to attenuate additive measurement noise in EMG channels. With and without whitening, RDS processing (vs. no RDS processing) better attenuated additive noise, reducing it from 2-4% (on average) of the processed EMG from a 50% contraction down to < 1%. The combined use of universal whitening filters and RDS processing should be a particular benefit in real-time applications such as prosthesis control.

Participation of ipsilateral cortical descending influences in bimanual wrist movements in humans

There are contralateral and less studied ipsilateral (i), indirect cortical descending projections to motoneurons (MNs). We compared ipsilateral cortical descending influences on MNs of wrist flexors by applying transcranial magnetic stimulation (TMS) over the right primary motor cortex at actively maintained flexion and extension wrist positions in uni- and bimanual tasks in right-handed participants (n = 23). The iTMS response includes a short latency (~ 25 ms) motor evoked potential (iMEP), a silent period (iSP) and a long latency (~ 60 ms) facilitation called rebound (iRB). We also investigated whether the interaction between the two hands while holding an object in a bimanual task involves ipsilateral cortical descending influences. In the unimanual task, iTMS responses in the right wrist flexors were unaffected by changes in wrist position. In the bimanual task with an object, iMEPs in the right wrist flexors were larger when the ipsilateral wrist was in flexion compared to extension. Without the object, only iRB were larger when the ipsilateral wrist was extended. Thus, ipsilateral cortical descending influences on MNs were modulated only in bimanual tasks and depended on how the two hands interacted. It is concluded that the left and right cortices cooperate in bimanual tasks involving holding an object with both hands, with possible involvement of oligo- and poly-synaptic, as well as transcallosal projections to MNs. The possible involvement of spinal and transcortical stretch and cutaneous reflexes in bimanual tasks when holding an object is discussed in the context of the well-established notion that indirect, referent control underlies motor actions.

Eye and head movements and vestibulo-ocular reflex in the context of indirect, referent control of motor actions

Conventional explanations of the vestibulo-ocular reflex (VOR) and eye and head movements are revisited by considering two alternative frameworks addressing the question of how the brain controls motor actions. Traditionally, biomechanical and/or computational frameworks reflect the views of several prominent scholars of the past, including Helmholtz and von Holst, who assumed that the brain directly specifies the desired motor outcome and uses efference copy to influence perception. However, empirical studies resulting in the theory of referent control of action and perception (an extension of the equilibrium-point hypothesis) revealed that direct specification of motor outcome is inconsistent with nonlinear properties of motoneurons and with the physical principle that the brain can control motor actions only indirectly, by changing or maintaining the values of neurophysiological parameters that influence, but can remain independent of, biomechanical variables. Some parameters are used to shift the origin (referent) points of spatial frames of reference (FRs) or system of coordinates in which motor actions emerge without being predetermined. Parameters are adjusted until the emergent motor actions meet the task demands. Several physiological parameters and spatial FRs have been identified, supporting the notion of indirect, referent control of movements. Instead of integration of velocity-dependent signals, position-dimensional referent signals underlying head motion can likely be transmitted to motoneurons of extraocular muscles. This would produce compensatory eye movement preventing shifts in gaze during head rotation, even after bilateral destruction of the labyrinths. The referent control framework symbolizes a shift in the paradigm for the understanding of VOR and eye and head movement production.

Effects of mechanical assistance on muscle activity and motor performance during isometric elbow flexion

Mechanical assistance on joint movement is generally beneficial; however, its effects on cooperative performance and muscle activity needs to be further explored. This study examined how motor performance and muscle activity are altered when mechanical assistance is provided during isometric force control of ramp-down and hold phases. Thirteen right-handed participants (age: 24.7 ± 1.8 years) performed trajectory tracking tasks. Participants were asked to maintain the reference magnitude of 47 N (REF) during isometric elbow flexion. The force was released to a step-down magnitude of either 75% REF or 50% REF and maintained, with and without mechanical assistance. The ramp-down durations of force release were set to 0.5, 2.5, or 5.0 s. Throughout the experiment, we measured the following: (1) the force output using load cells to compute force variability and overshoot ratio; (2) peak perturbation on the elbow movement using an accelerometer; (3) the surface electromyography (sEMG) from biceps brachii and triceps brachii muscles; and (4) EMG oscillation from the biceps brachii muscle in the bandwidth of 15-45 Hz. Our results indicated that mechanical assistance, which involved greater peak perturbation, demonstrated lower force variability than non-assistance (p < 0.01), while EMG oscillation in the biceps brachii muscle from 15 to 45 Hz was increased (p < 0.05). These findings imply that if assistive force is provided during isometric force control, the central nervous system actively tries to stabilize motor performance by controlling specific motor unit activity in the agonist muscle.

Optimal Estimation of EMG Standard Deviation (EMG σ ) in Additive Measurement Noise: Model-Based Derivations and Their Implications

Typical electromyogram (EMG) processors estimate EMG signal standard deviation (EMG σ ) via moving average root mean square (RMS) or mean absolute value (MAV) filters, whose outputs are used in force estimation, prosthesis/orthosis control, etc. In the inevitable presence of additive measurement noise, some processors subtract the noise standard deviation from EMG RMS (or MAV). Others compute a root difference of squares (RDS)-subtract the noise variance from the square of EMG RMS (or MAV), all followed by taking the square root. Herein, we model EMG as an amplitude-modulated random process in additive measurement noise. Assuming a Gaussian (or, separately, Laplacian) distribution, we derive analytically that the maximum likelihood estimate of EMG σ requires RDS processing. Whenever that subtraction would provide a negative-valued result, we show that EMG σ should be set to zero. Our theoretical models further show that during rest, approximately 50% of EMG σ estimates are non-zero. This result is problematic when EMG σ is used for real-time control, explaining the common use of additional thresholding. We tested our model results experimentally using biceps and triceps EMG from 64 subjects. Experimental results closely followed the Gaussian model. We conclude that EMG processors should use RDS processing and not noise standard deviation subtraction.

Force and electromyography responses during isometric force release of different rates and step-down magnitudes

This study investigated motor responses of force release during isometric elbow flexion by comparing effects of different ramp durations and step-down magnitudes. Twelve right-handed participants (age: 23.1 ± 1.1) performed trajectory tracking tasks. Participants were instructed to release their force from the reference magnitude (REF; 40% of maximal voluntary contraction force) to a step-down magnitude of 67% REF or 33% REF and maintain the released magnitude. Force release was guided by ramp durations of either 1 s or 5 s. Electromyography of the biceps brachii and triceps brachii was performed during the experimental task, and the co-contraction ratio was evaluated. Force output was recorded to evaluate the parameters of motor performance, such as force variability and overshoot ratio. Although a longer ramp duration of 5 s decreased the force variability and overshoot ratio than did shorter ramp duration of 1 s, higher perceived exertion and co-contraction ratio were followed. Force variability was greater when force was released to the step-down magnitude of 33% REF than that when the magnitude was 67% REF, however, the overshoot ratio showed opposite results. This study provided evidence proving that motor control strategies adopted for force release were affected by both duration and step-down magnitude. In particular, it implies that different control strategies are required according to the level of step-down magnitude with a relatively short ramp duration.

Effects of the amount of practice and time interval between practice sessions on the retention of internal models

The amount of practice and time interval between practice sessions are important factors that influence motor learning efficiency. Here, we aimed to reveal the relationship between the retention and consolidation of a new internal model, and the amount of practice and time interval between practice sessions. We employed a visuomotor rotation tracking task to test the hypotheses that (1) a new internal model consolidates owing to extensive practice after reaching a task performance plateau and (2) a longer time interval between practice sessions makes it difficult to activate a new internal model. The participants were assigned to one of the four groups that differed in terms of the amount of practice and the time interval between practice sessions. They performed a tracking task in which they experienced 120° clockwise visuomotor rotation and were required to track a moving target on a computer display using a mouse cursor. To evaluate the retention and consolidation of a new internal model, we calculated the aftereffects and savings as measures of motor learning. To the best our knowledge, this is the first study to manipulate both the amount of practice and the time interval between practice sessions simultaneously in one experiment using a visuomotor tracking task. Our results support the previously reported idea that extensive practice is necessary for the consolidation of a new internal model.

Two degrees of freedom, dynamic, hand-wrist EMG-force using a minimum number of electrodes

Few studies have related the surface electromyogram (EMG) of forearm muscles to two degree of freedom (DoF) hand-wrist forces; ones that have, used large high-density electrode arrays that are impractical for most applied biomechanics research. Hence, we researched EMG-force in two DoFs-hand open-close paired with one wrist DoF-using as few as four conventional electrodes, comparing equidistant placement about the forearm to optimized site selection. Nine subjects produced 1-DoF and 2-DoF uniformly distributed random forces (bandlimited to 0.75 Hz) up to 30% maximum voluntary contraction (MVC). EMG standard deviation (EMGσ) was related to force offline using linear dynamic regression models. For 1-DoF forces, average RMS errors using two optimally-sited electrodes ranged from 8.3 to 9.0 %MVC, depending on the DoF. For 2-DoFs, overall performance was best when training from both 1- and 2-DoF trials, giving average RMS errors using four optimally-sited electrodes of 9.2 %MVC for each DoF pair (hand open-close paired with one wrist DoF). For each model, additional optimally-sited electrodes showed little statistical improvement. Electrodes placed equidistant performed noticeably poorer than an equal number of electrodes that were optimally sited. The results suggest that reliable 2-DoF hand-wrist EMG-force with a small number of electrodes may be feasible.

Indirect, referent control of motor actions underlies directional tuning of neurons

Many neurons of the primary motor cortex (M1) are maximally sensitive to "preferred" hand movement directions and generate progressively less activity with movements away from these directions. M1 activity also correlates with other biomechanical variables. These findings are predominantly interpreted in a framework in which the brain preprograms and directly specifies the desired motor outcome. This approach is inconsistent with the empirically derived equilibrium-point hypothesis, in which the brain can control motor actions only indirectly, by changing neurophysiological parameters that may influence, but remain independent of, biomechanical variables. The controversy is resolved on the basis of experimental findings and theoretical analysis of how sensory and central influences are integrated in the presence of the fundamental nonlinearity of neurons: electrical thresholds. In the presence of sensory inputs, electrical thresholds are converted into spatial thresholds that predetermine the position of the body segments at which muscles begin to be activated. Such thresholds may be considered as referent points of respective spatial frames of reference (FRs) in which neurons, including motoneurons, are centrally predetermined to work. By shifting the referent points of respective FRs, the brain elicits intentional actions. Pure involuntary reactions to perturbations are accomplished in motionless FRs. Neurons are primarily sensitive to shifts in referent directions, i.e., shifts in spatial FRs, whereas emergent neural activity may or may not correlate with different biomechanical variables depending on the motor task and external conditions. Indirect, referent control of posture and movement symbolizes a departure from conventional views based on direct preprogramming of the motor outcome.

Down regulation of vestibular balance stabilizing mechanisms to enable transition between motor states

The neural control of transition between posture and movement encompasses the regulation of reflex-stabilizing mechanisms to enable motion. Optimal feedback theory suggests that such transitions require the disengagement of one motor control policy before the implementation of another. To test this possibility, we investigated the continuity of the vestibular control of balance during transitions between quiet standing and locomotion and between two standing postures. Healthy subjects initiated and terminated locomotion or shifted the distribution of their weight between their feet, while exposed to electrical vestibular stimuli (EVS). The relationship between EVS and ground reaction forces was quantified using time-frequency analyses. Discontinuities corresponding to null coherence periods were observed preceding the onset of movement initiation and during the step preceding locomotion termination. These results show humans interrupt the vestibular balance stabilizing mechanisms to transition between motor states, suggesting a discrete change between motor control policies, as predicted by optimal feedback theory.

Crossing Abbey Road is something of a paradox in neuroscientific terms. As you stand waiting to cross, tiny movements of your body – such as those due to breathing – cause you to sway by small amounts. To prevent you from falling over, your brain makes active corrections to your posture. These posture-correcting mechanisms oppose movements such as sway and keep you standing upright. But what happens when you want to cross the road?

To get you moving, your brain has two options. It could temporarily suppress the posture-correcting mechanisms. Or it could reconfigure them so that they work in a different way. The posture-correcting mechanisms rely upon sensory input from various sources. These include the vestibular system of the inner ear. The vestibular system tells the brain about the position and movement of the head in space and relative to gravity. Monitoring vestibular system activity as a person starts to move should thus reveal what is happening to the posture-correcting mechanisms.

Tisserand et al. asked healthy volunteers to transition between standing still and walking, or to shift their weight from one foot to the other. At the same time, small non-painful electric currents were applied to the bones behind the volunteers' ears. These currents induced small changes in vestibular system activity. Sensors in the floor measured the forces the volunteers generated while standing or walking, thereby revealing how they adjusted their balance. The results showed that the brain suppresses its posture-correcting mechanisms before people start or stop moving.

These findings have implications for robotics. They could make it easier to program robots to show smooth transitions into and out of movement. The findings are also relevant to movement disorders such as Parkinson's disease. One common symptom of this disorder is freezing of gait, in which patients suddenly feel as though their feet are glued to the ground. Understanding how the brain controls movement transitions may reveal how such symptoms arise.

Purkinje Cell Representations of Behavior: Diary of a Busy Neuron

Fundamental for understanding cerebellar function is determining the representations in Purkinje cell activity, the sole output of the cerebellar cortex. Up to the present, the most accurate descriptions of the information encoded by Purkinje cells were obtained in the context of motor behavior and reveal a high degree of heterogeneity of kinematic and performance error signals encoded. The most productive framework for organizing Purkinje cell firing representations is provided by the forward internal model hypothesis. Direct tests of this hypothesis show that individual Purkinje cells encode two different forward models simultaneously, one for effector kinematics and one for task performance. Newer results demonstrate that the timing of simple spike encoding of motor parameters spans an extend interval of up to ±2 seconds. Furthermore, complex spike discharge is not limited to signaling errors, can be predictive, and dynamically controls the information in the simple spike firing to meet the demands of upcoming behavior. These rich, diverse, and changing representations highlight the integrative aspects of cerebellar function and offer the opportunity to generalize the cerebellar computational framework over both motor and non-motor domains.

What drives the perceptual change resulting from speech motor adaptation? Evaluation of hypotheses in a Bayesian modeling framework

Shifts in perceptual boundaries resulting from speech motor learning induced by perturbations of the auditory feedback were taken as evidence for the involvement of motor functions in auditory speech perception. Beyond this general statement, the precise mechanisms underlying this involvement are not yet fully understood. In this paper we propose a quantitative evaluation of some hypotheses concerning the motor and auditory updates that could result from motor learning, in the context of various assumptions about the roles of the auditory and somatosensory pathways in speech perception. This analysis was made possible thanks to the use of a Bayesian model that implements these hypotheses by expressing the relationships between speech production and speech perception in a joint probability distribution. The evaluation focuses on how the hypotheses can (1) predict the location of perceptual boundary shifts once the perturbation has been removed, (2) account for the magnitude of the compensation in presence of the perturbation, and (3) describe the correlation between these two behavioral characteristics. Experimental findings about changes in speech perception following adaptation to auditory feedback perturbations serve as reference. Simulations suggest that they are compatible with a framework in which motor adaptation updates both the auditory-motor internal model and the auditory characterization of the perturbed phoneme, and where perception involves both auditory and somatosensory pathways.

Real-time muscle state estimation from EMG signals during isometric contractions using Kalman filters

State-space control of myoelectric devices and real-time visualization of muscle forces in virtual rehabilitation require measuring or estimating muscle dynamic states: neuromuscular activation, tendon force and muscle length. This paper investigates whether regular (KF) and extended Kalman filters (eKF), derived directly from Hill-type muscle mechanics equations, can be used as real-time muscle state estimators for isometric contractions using raw electromyography signals (EMG) as the only available measurement. The estimators' amplitude error, computational cost, filtering lags and smoothness are compared with usual EMG-driven analysis, performed offline, by integrating the nonlinear Hill-type muscle model differential equations (offline simulations-OS). EMG activity of the three triceps surae components (soleus, gastrocnemius medialis and gastrocnemius lateralis), in three torque levels, was collected for ten subjects. The actualization interval (AI) between two updates of the KF and eKF was also varied. The results show that computational costs are significantly reduced (70x for KF and 17[Formula: see text] for eKF). The filtering lags presented sharp linear relationships with the AI (0-300 ms), depending on the state and activation level. Under maximum excitation, amplitude errors varied in the range 10-24% for activation, 5-8% for tendon force and 1.4-1.8% for muscle length, reducing linearly with the excitation level. Smoothness, measured by the ratio between the average standard variations of KF/eKF and OS estimations, was greatly reduced for activation but converged exponentially to 1 for the other states by increasing AI. Compared to regular KF, extended KF does not seem to improve estimation accuracy significantly. Depending on the particular application requirements, the most appropriate KF actualization interval can be selected.

An Extended Passive Motion Paradigm for Human-Like Posture and Movement Planning in Redundant Manipulators

A major challenge in robotics and computational neuroscience is relative to the posture/movement problem in presence of kinematic redundancy. We recently addressed this issue using a principled approach which, in conjunction with nonlinear inverse optimization, allowed capturing postural strategies such as Donders' law. In this work, after presenting this general model specifying it as an extension of the Passive Motion Paradigm, we show how, once fitted to capture experimental postural strategies, the model is actually able to also predict movements. More specifically, the passive motion paradigm embeds two main intrinsic components: joint damping and joint stiffness. In previous work we showed that joint stiffness is responsible for static postures and, in this sense, its parameters are regressed to fit to experimental postural strategies. Here, we show how joint damping, in particular its anisotropy, directly affects task-space movements. Rather than using damping parameters to fit a posteriori task-space motions, we make the a priori hypothesis that damping is proportional to stiffness. This remarkably allows a postural-fitted model to also capture dynamic performance such as curvature and hysteresis of task-space trajectories during wrist pointing tasks, confirming and extending previous findings in literature.

Task-space separation principle: a force-field approach to motion planning for redundant manipulators

In this work, we address human-like motor planning in redundant manipulators. Specifically, we want to capture postural synergies such as Donders' law, experimentally observed in humans during kinematically redundant tasks, and infer a minimal set of parameters to implement similar postural synergies in a kinematic model. For the model itself, although the focus of this paper is to solve redundancy by implementing postural strategies derived from experimental data, we also want to ensure that such postural control strategies do not interfere with other possible forms of motion control (in the task-space), i.e. solving the posture/movement problem. The redundancy problem is framed as a constrained optimization problem, traditionally solved via the method of Lagrange multipliers. The posture/movement problem can be tackled via the separation principle which, derived from experimental evidence, posits that the brain processes static torques (i.e. posture-dependent, such as gravitational torques) separately from dynamic torques (i.e. velocity-dependent). The separation principle has traditionally been applied at a joint torque level. Our main contribution is to apply the separation principle to Lagrange multipliers, which act as task-space force fields, leading to a task-space separation principle. In this way, we can separate postural control (implementing Donders' law) from various types of tasks-space movement planners. As an example, the proposed framework is applied to the (redundant) task of pointing with the human wrist. Nonlinear inverse optimization (NIO) is used to fit the model parameters and to capture motor strategies displayed by six human subjects during pointing tasks. The novelty of our NIO approach is that (i) the fitted motor strategy, rather than raw data, is used to filter and down-sample human behaviours; (ii) our framework is used to efficiently simulate model behaviour iteratively, until it converges towards the experimental human strategies.

Referent control and motor equivalence of reaching from standing

Motor actions may result from central changes in the referent body configuration, defined as the body posture at which muscles begin to be activated or deactivated. The actual body configuration deviates from the referent configuration, particularly because of body inertia and environmental forces. Within these constraints, the system tends to minimize the difference between these configurations. For pointing movement, this strategy can be expressed as the tendency to minimize the difference between the referent trajectory (R_T) and actual trajectory (Q_T) of the effector (hand). This process may underlie motor equivalent behavior that maintains the pointing trajectory regardless of the number of body segments involved. We tested the hypothesis that the minimization process is used to produce pointing in standing subjects. With eyes closed, 10 subjects reached from a standing position to a remembered target located beyond arm length. In randomly chosen trials, hip flexion was unexpectedly prevented, forcing subjects to take a step during pointing to prevent falling. The task was repeated when subjects were instructed to intentionally take a step during pointing. In most cases, reaching accuracy and trajectory curvature were preserved due to adaptive condition-specific changes in interjoint coordination. Results suggest that referent control and the minimization process associated with it may underlie motor equivalence in pointing.

NEW & NOTEWORTHY

Motor actions may result from minimization of the deflection of the actual body configuration from the centrally specified referent body configuration, in the limits of neuromuscular and environmental constraints. The minimization process may maintain reaching trajectory and accuracy regardless of the number of body segments involved (motor equivalence), as confirmed in this study of reaching from standing in young healthy individuals. Results suggest that the referent control process may underlie motor equivalence in reaching.

Biomechanics as a window into the neural control of movement

Biomechanics and motor control are discussed as parts of a more general science, physics of living systems. Major problems of biomechanics deal with exact definition of variables and their experimental measurement. In motor control, major problems are associated with formulating currently unknown laws of nature specific for movements by biological objects. Mechanics-based hypotheses in motor control, such as those originating from notions of a generalized motor program and internal models, are non-physical. The famous problem of motor redundancy is wrongly formulated; it has to be replaced by the principle of abundance, which does not pose computational problems for the central nervous system. Biomechanical methods play a central role in motor control studies. This is illustrated with studies with the reconstruction of hypothetical control variables and those exploring motor synergies within the framework of the uncontrolled manifold hypothesis. Biomechanics and motor control have to merge into physics of living systems, and the earlier this process starts the better.

Active sensing without efference copy: referent control of perception

Although action and perception are different behaviors, they are likely to be interrelated, as implied by the notions of perception-action coupling and active sensing. Traditionally, it has been assumed that the nervous system directly preprograms motor commands required for actions and uses a copy of them called efference copy (EC) to also influence our senses. This review offers a critical analysis of the EC concept by identifying its limitations. An alternative to the EC concept is based on the experimentally confirmed notion that sensory signals from receptors are perceived relative to referent signals specified by the brain. These referents also underlie the control of motor actions by predetermining where, in the spatial domain, muscles can work without preprogramming how they should work in terms of motor commands or EC. This approach helps solve several problems of action and explain several sensory experiences, including position sense and the sense that the world remains stationary despite changes in its retinal image during eye or body motion (visual space constancy). The phantom limb phenomenon and other kinesthetic illusions are also explained within this framework.

Unsteady steady-states: central causes of unintentional force drift

We applied the theory of synergies to analyze the processes that lead to unintentional decline in isometric fingertip force when visual feedback of the produced force is removed. We tracked the changes in hypothetical control variables involved in single fingertip force production based on the equilibrium-point hypothesis, namely the fingertip referent coordinate (R _FT) and its apparent stiffness (C _FT). The system's state is defined by a point in the {R _FT; C _FT} space. We tested the hypothesis that, after visual feedback removal, this point (1) moves along directions leading to drop in the output fingertip force, and (2) has even greater motion along directions that leaves the force unchanged. Subjects produced a prescribed fingertip force using visual feedback and attempted to maintain this force for 15 s after the feedback was removed. We used the "inverse piano" apparatus to apply small and smooth positional perturbations to fingers at various times after visual feedback removal. The time courses of R _FT and C _FT showed that force drop was mostly due to a drift in R _FT toward the actual fingertip position. Three analysis techniques, namely hyperbolic regression, surrogate data analysis, and computation of motor-equivalent and non-motor-equivalent motions, suggested strong covariation in R _FT and C _FT stabilizing the force magnitude. Finally, the changes in the two hypothetical control variables {R _FT; C _FT} relative to their average trends also displayed covariation. On the whole, the findings suggest that unintentional force drop is associated with (a) a slow drift of the referent coordinate that pulls the system toward a low-energy state and (b) a faster synergic motion of R _FT and C _FT that tends to stabilize the output fingertip force about the slowly drifting equilibrium point.

What you feel is what you see: inverse dynamics estimation underlies the resistive sensation of a delayed cursor

How our central nervous system (CNS) learns and exploits relationships between force and motion is a fundamental issue in computational neuroscience. While several lines of evidence have suggested that the CNS predicts motion states and signals from motor commands for control and perception (forward dynamics), it remains controversial whether it also performs the 'inverse' computation, i.e. the estimation of force from motion (inverse dynamics). Here, we show that the resistive sensation we experience while moving a delayed cursor, perceived purely from the change in visual motion, provides evidence of the inverse computation. To clearly specify the computational process underlying the sensation, we systematically varied the visual feedback and examined its effect on the strength of the sensation. In contrast to the prevailing theory that sensory prediction errors modulate our perception, the sensation did not correlate with errors in cursor motion due to the delay. Instead, it correlated with the amount of exposure to the forward acceleration of the cursor. This indicates that the delayed cursor is interpreted as a mechanical load, and the sensation represents its visually implied reaction force. Namely, the CNS automatically computes inverse dynamics, using visually detected motions, to monitor the dynamic forces involved in our actions.

Effect of Resistance Training of the Wrist Joint Muscles on Multi-Digit Coordination

This study investigated the effects of a specific regimen of resistance training on coordinated actions of human hand digits during grasping. Participants were instructed to hold a rectangular object with all five digits and to maintain the orientation of the object against transient perturbation. Indices of co-varied actions (i.e., synergies) among multi-digit grasping and rotational actions were quantified. The index of anticipatory changes of co-varied actions among digit forces (i.e., anticipatory synergy adjustment) was also quantified, which represents the controller's ability to predict an upcoming perturbation. The synergies of both grasping force and moment stabilization increased with the training. No change in the index of anticipatory synergy adjustment with training was observed. The current results suggest that the resistance training on the wrist could be an effective way to enhance both voluntary muscle force/torque production capability and ability to stabilize task performances during multi-digit prehensile tasks.

Should the Equilibrium Point Hypothesis (EPH) be Considered a Scientific Theory?

The purpose of this commentary is to discuss factors that limit consideration of the equilibrium point hypothesis as a scientific theory. The EPH describes control of motor neuron threshold through the variable lambda, which corresponds to a unique referent configuration for a muscle, joint, or combination of joints. One of the most compelling features of the equilibrium point hypothesis is the integration of posture and movement control into a single mechanism. While the essential core of the hypothesis is based upon spinal circuitry interacting with peripheral mechanics, the proponents have extended the theory to include the higher-level processes that generate lambda, and in doing so, imposed an injunction against the supraspinal nervous system modeling, computing, or predicting dynamics. This limitation contradicts evidence that humans take account of body and environmental dynamics in motor selection, motor control, and motor adaptation processes. A number of unresolved limitations to the EPH have been debated in the literature for many years, including whether muscle resistance to displacement, measured during movement, is adequate to support this form of control, violations in equifinality predictions, spinal circuits that alter the proposed invariant characteristic for muscles, and limitations in the description of how the complexity of spinal circuitry might be integrated to yield a unique and stable equilibrium position for a given motor neuron threshold. In addition, an important empirical limitation of EPH is the measurement of the invariant characteristic, which needs to be done under a constant central state. While there is no question that the EPH is an elegant and generative hypothesis for motor control research, the claim that this hypothesis has reached the status of a scientific theory is premature.

Tool use ability depends on understanding of functional dynamics and not specific joint contribution profiles

Researchers in cognitive neuroscience have become increasingly interested in how different aspects of tool use are integrated and represented by the brain. Comparatively less attention has been directed toward tool use actions themselves and how effective tool use behaviors are coordinated. In response, we take this opportunity to consider the mechanical principles of tool use actions and their relationship to motor learning. Using kinematic analysis, we examine both functional dynamics and joint contribution profiles of subjects with different levels of experience in a primordial percussive task. Our results show that the ability to successfully produce stone flakes using the Oldowan method did not correspond with any particular joint contribution profile. Rather, expertise in this tool use action was principally associated with the subject's ability to regulate the functional parameters that define the task itself.

Neural representation of muscle dynamics in voluntary movement control

Several theories of motor control posit that the nervous system has access to a neural representation of muscle dynamics. Yet, this has not been tested experimentally. Should such a representation exist, it was hypothesized that subjects who learned to control a virtual limb using virtual muscles would improve performance faster and show greater generalization than those who learned with a less dynamically complex virtual force generator. Healthy adults practiced using their biceps brachii activity to move a myoelectrically controlled virtual limb from rest to a standard target position with maximum speed and accuracy. Throughout practice, generalization was assessed with untrained target trials and sensitivity to actuator dynamics was probed by unexpected actuator model switches. In a muscle model subject group (n = 10), the biceps electromyographic signal activated a virtual muscle that pulled on the virtual limb with a force governed by muscle dynamics, defined by a nonlinear force-length-velocity relation and series elastic stiffness. A force generator group (n = 10) performed the same task, but the actuation force was a linear function of the biceps activation signal. Both groups made significant errors with unexpected actuator dynamics switches, supporting task sensitivity to actuator dynamics. The muscle model group improved performance as fast as the force generator group and showed greater generalization in early practice, despite using an actuator with more complex dynamics. These results are consistent with a preexisting neural representation of muscle dynamics, which may have offset any learning challenges associated with the more dynamically complex virtual muscle model.

The distributed lambda (λ) model (DLM): a 3-D, finite-element muscle model based on Feldman's λ model; assessment of orofacial gestures

PURPOSE

The authors aimed to design a distributed lambda model (DLM), which is well adapted to implement three-dimensional (3-D), finite-element descriptions of muscles.

METHOD

A muscle element model was designed. Its stress-strain relationships included the active force-length characteristics of the λ model along the muscle fibers, together with the passive properties of muscle tissues in the 3-D space. The muscle element was first assessed using simple geometrical representations of muscles in the form of rectangular bars. It was then included in a 3-D face model, and its impact on lip protrusion was compared with the impact of a Hill-type muscle model.

RESULTS

The force-length characteristic associated with the muscle elements matched well with the invariant characteristics of the λ model. The impact of the passive properties was assessed. Isometric force variation and isotonic displacements were modeled. The comparison with a Hill-type model revealed strong similarities in terms of global stress and strain.

CONCLUSION

The DLM accounted for the characteristics of the λ model. Biomechanically, no clear differences were found between the DLM and a Hill-type model. Accurate evaluations of the λ model, based on the comparison between data and simulations, are now possible with 3-D biomechanical descriptions of the speech articulators because of the DLM.

Electromyogram bandwidth requirements when the signal is whitened

Whitening the surface electromyogram (EMG) improves EMG amplitude (EMGσ) and EMG-torque estimation. Laboratory studies utilizing contraction levels up to maximum voluntary contraction (MVC) show that whitening is useful over a frequency band extending to 1000-2000 Hz. However, EMG electrode systems with such wide bandwidth are uncommon, particularly in real-time applications; and these contraction levels are also not common. Thus, we studied the influence of the frequency band over which whitening was performed versus the resulting performance. Low-level, torque-varying contractions (average torque level of 18.5% flexion MVC) of the elbow were contrasted with medium-level 50% MVC constant-torque contractions. For each, the maximum whitening bandwidth was varied between 30-2000 Hz. The low-level contractions (which incorporate the contraction range of most daily tasks) showed that performance utilizing frequencies out to 400-500 Hz was not statistically different than results out to the full available frequency (2000 Hz). For the medium-level (50% MVC) contractions, frequencies out to 800-900 Hz were statistically equivalent to the full bandwidth. These results suggest that conventional electrodes with a typical passband of ∼ 500 Hz are appropriate when whitening data from contraction levels typically experienced in many applications. Wider bandwidths may be advantageous for strenuous activities.

Action-perception coupling in kinesthesia: a new approach

According to recent findings, intentional motor actions are controlled by resetting the referent position, R, at which neuromuscular elements, including reflexes, begin to act. It is suggested that somatosensory afferents inform the brain about the deviation (P) of body segments from the centrally set referent position. To perceive the actual position (Q) of body segments and form the position sense (PS), the central and afferent signals are combined: Q=R+P. In previous studies, the R has been shown to remain invariant during involuntary changes in the wrist position elicited by sudden unloading of muscles, suggesting that only the afferent component is responsible for the PS during this reflex. In contrast, the central PS component, R, is predominantly responsible for PS during intentional motion in isotonic conditions. We tested the hypothesis that the R and P are interchangeable PS components such that involuntary changes in wrist position elicited by the unloading reflex can easily be reproduced by making intentional changes in wrist position in isotonic conditions, in the absence of vision. The PS rule also suggests that PS is independent of sense of effort, which was tested by asking subjects to reproduce elbow joint angles under different constant loads. We also tested the hypothesis that tendon vibration may elicit motion that may not be perceived by subjects (no-motion illusion). These hypotheses were confirmed in three experiments. It is concluded that the R and P are additive components of PS and that, contrary to the conventional view, PS is independent of the sense of effort or efference copy. The PS rule also explains kinesthetic illusions and the phantom limb phenomenon. This study advances the understanding of action-perception coupling in kinesthesia.

Flexibility of movement organization in piano performance

Piano performance involves a large repertoire of highly skilled movements. The acquisition of these exceptional skills despite innate neural and biomechanical constraints requires a sophisticated interaction between plasticity of the neural system and organization of a redundant number of degrees of freedom (DOF) in the motor system. Neuroplasticity subserving virtuosity of pianists has been documented in neuroimaging studies investigating effects of long-term piano training on structure and function of the cortical and subcortical regions. By contrast, recent behavioral studies have advanced the understanding of neuromuscular strategies and biomechanical principles behind the movement organization that enables skilled piano performance. Here we review the motor control and biomechanics literature, introducing the importance of describing motor behaviors not only for understanding mechanisms responsible for skillful motor actions in piano playing, but also for advancing diagnosis and rehabilitation of movement disorders caused by extensive piano practice.