A computational model for rhythmic and discrete movements in uni- and bimanual coordination

Immediate Effects of a Single Session of Cervical Spine Manipulation on Cervical Movement Patterns in People With Nonspecific Neck Pain: A Randomized Controlled Trial

OBJECTIVE

The aim of the present study was to assess the immediate effects of a single session of cervical spine manipulation on cervical movement patterns, disability, and the patient's perceived improvement in people with nonspecific neck pain.

METHODS

A single-blinded, randomized, sham-controlled trial was carried out at a biomechanics institute. Fifty participants diagnosed with acute and chronic nonspecific neck pain (minimum duration of the symptoms being 1 month) were randomized to an experimental group (EG, n = 25) or a sham-control group (CG, n = 25, 23 of whom completed the study). EG received a single cervical spine manipulation session; CG received a single placebo intervention. Both groups received manipulation or sham from the same physiotherapist. Main outcome measures were neck kinematics (ie, range of motion and movement harmony) during cyclic movements, self-reported neck disability, and impression of change assessed before and 5 minutes after treatment.

RESULTS

The EG showed no significant improvements (P > .05) in any of the studied biomechanical variables, except for right-side bending and left rotation, in which we found a range of motion significant mean difference of 1.97° and 1.95°, respectively (P < .05). The CG showed enhanced harmonic motion during flexion (P < .05). Both groups showed a significant decrease in self-reported neck disability after treatment (P < .05), and EG participants perceived a significantly larger improvement after manipulation compared with the CG (P < .05).

CONCLUSIONS

A single session of cervical manipulation provided by a physiotherapist had no impact on cervical motion during cyclic movements, but rather induced self-reported perceived improvement in neck disability and impression of change after treatment in people with nonspecific neck pain.

Hopf Bifurcations in Complex Multiagent Activity: The Signature of Discrete to Rhythmic Behavioral Transitions

Most human actions are composed of two fundamental movement types, discrete and rhythmic movements. These movement types, or primitives, are analogous to the two elemental behaviors of nonlinear dynamical systems, namely, fixed-point and limit cycle behavior, respectively. Furthermore, there is now a growing body of research demonstrating how various human actions and behaviors can be effectively modeled and understood using a small set of low-dimensional, fixed-point and limit cycle dynamical systems (differential equations). Here, we provide an overview of these dynamical motorprimitives and detail recent research demonstrating how these dynamical primitives can be used to model the task dynamics of complex multiagent behavior. More specifically, we review how a task-dynamic model of multiagent shepherding behavior, composed of rudimentary fixed-point and limit cycle dynamical primitives, can not only effectively model the behavior of cooperating human co-actors, but also reveals how the discovery and intentional use of optimal behavioral coordination during task learning is marked by a spontaneous, self-organized transition between fixed-point and limit cycle dynamics (i.e., via a Hopf bifurcation).

Separating neural influences from peripheral mechanics: the speed-curvature relation in mechanically constrained actions

While the study of unconstrained movements has revealed important features of neural control, generalizing those insights to more sophisticated object manipulation is challenging. Humans excel at physical interaction with objects, even when those objects introduce complex dynamics and kinematic constraints. This study examined humans turning a horizontal planar crank (radius 10.29 cm) at their preferred and three instructed speeds (with visual feedback), both in clockwise and counterclockwise directions. To explore the role of neuromechanical dynamics, the instructed speeds covered a wide range: fast (near the limits of performance), medium (near preferred speed), and very slow (rendering dynamic effects negligible). Because kinematically constrained movements involve significant physical interaction, disentangling neural control from the influences of biomechanics presents a challenge. To address it, we modeled the interactive dynamics to "subtract off" peripheral biomechanics from observed force and kinematic data, thereby estimating aspects of underlying neural action that may be expressed in terms of motion. We demonstrate the value of this method: remarkably, an approximately elliptical path emerged, and speed minima coincided with curvature maxima, similar to what is seen in unconstrained movements, even though the hand moved at nearly constant speed along a constant-curvature path. These findings suggest that the neural controller takes advantage of peripheral biomechanics to simplify physical interaction. As a result, patterns seen in unconstrained movements persist even when physical interaction prevents their expression in hand kinematics. The reemergence of a speed-curvature relation indicates that it is due, at least in part, to neural processes that emphasize smoothness and predictability.NEW & NOTEWORTHY Physically interacting with kinematic constraints is commonplace in everyday actions. We report a study of humans turning a crank, a circular constraint that imposes constant hand path curvature and hence should suppress variations of hand speed due to the power-law speed-curvature relation widely reported for unconstrained motions. Remarkably, we found that, when peripheral biomechanical factors are removed, a speed-curvature relation reemerges, indicating that it is, at least in part, of neural origin.

The primacy of rhythm: how discrete actions merge into a stable rhythmic pattern

This study examined how humans spontaneously merge a sequence of discrete actions into a rhythmic pattern, even when periodicity is not required. Two experiments used a virtual throwing task, in which subjects performed a long sequence of discrete throwing movements, aiming to hit a virtual target. In experiment 1, subjects performed the task for 11 sessions. Although there was no instruction to perform rhythmically, the variability of the interthrow intervals decreased to a level comparable to that of synchronizing with a metronome; furthermore, dwell times shortened or even disappeared with practice. Floquet multipliers and decreasing variability of the arm trajectories estimated in state space indicated an increasing degree of dynamic stability. Subjects who achieved a higher level of periodicity and stability also displayed higher accuracy in the throwing task. To directly test whether rhythmicity affected performance, experiment 2 disrupted the evolving continuity and periodicity by enforcing a pause between successive throws. This discrete group performed significantly worse and with higher variability in their arm trajectories than the self-paced group. These findings are discussed in the context of previous neuroimaging results showing that rhythmic movements involve significantly fewer cortical and subcortical activations than discrete movements and therefore may pose a computationally more parsimonious solution. Such emerging stable rhythms in neuromotor subsystems may serve as building blocks or dynamic primitives for complex actions. The tendency for humans to spontaneously fall into a rhythm in voluntary movements is consistent with the ubiquity of rhythms at all levels of the physiological system. NEW & NOTEWORTHY When performing a series of throws to hit a target, humans spontaneously merged successive actions into a continuous approximately periodic pattern. The degree of rhythmicity and stability correlated with hitting accuracy. Enforcing irregular pauses between throws to disrupt the rhythm deteriorated performance. Stable rhythmic patterns may simplify control of movement and serve as dynamic primitives for more complex actions. This observation reveals that biological systems tend to exhibit rhythmic behavior consistent with a plethora of physiological processes.

Rhythmic robotic training enhances motor skills of both rhythmic and discrete upper-limb movements after stroke: a longitudinal pilot study

Discrete and rhythmic movements are two fundamental motor primitives being, at least partially, controlled by separate neural circuitries. After a stroke, both primitives may be impaired in the upper limb. Currently, intensive functional movement therapy is recommended after stroke, but it is mainly composed of discrete movements. No recommendation is made for the specific training of rhythmic movements. However, if they form two different primitives, both should receive a specific training to recover the complete motor repertoire, as many daily live movements integrate both of them. This paper reports the effects of a pure unilateral rhythmic movement therapy on motor performance, after stroke. Thirteen patients with chronic stroke participated in this longitudinal pilot study. They were assessed twice before the therapy to validate their chronic state, and twice after the last session to establish the short-term and long-term effects of the therapy. The therapy itself was composed of 12 sessions spread over 1 month. The exercises consisted in performing straight or circular rhythmic movements, while receiving assistance as need through a robotic device. Short-term and long-term improvements were observed in rhythmic movements regarding smoothness, velocity, and harmonicity. More surprisingly, some transfer occurred to the untrained discrete movements. This finding disputes previous studies that reported no transfer from rhythmic to discrete movements with healthy participants.

Bio-inspired controller achieving forward speed modulation with a 3D bipedal walker

Despite all the effort devoted to generating locomotion algorithms for bipedal walkers, robots are still far from reaching the impressive human walking capabilities, for instance regarding robustness and energy consumption. In this paper, we have developed a bio-inspired torque-based controller supporting the emergence of a new generation of robust and energy-efficient walkers. It recruits virtual muscles driven by reflexes and a central pattern generator, and thus requires no computationally intensive inverse kinematics or dynamics modeling. This controller is capable of generating energy-efficient and human-like gaits (both regarding kinematics and dynamics) across a large range of forward speeds, in a 3D environment. After a single off-line optimization process, the forward speed can be continuously commanded within this range by changing high-level parameters, as linear or quadratic functions of the target speed. Sharp speed transitions can then be achieved with no additional tuning, resulting in immediate adaptations of the step length and frequency. In this paper, we particularly embodied this controller on a simulated version of COMAN, a 95 cm tall humanoid robot. We reached forward speed modulations between 0.4 and 0.9 m/s. This covers normal human walking speeds once scaled to the robot size. Finally, the walker demonstrated significant robustness against a large spectrum of unpredicted perturbations: facing external pushes or walking on altered environments, such as stairs, slopes, and irregular ground.

The visual encoding of purely proprioceptive intermanual tasks is due to the need of transforming joint signals, not to their interhemispheric transfer

To perform goal-oriented hand movement, humans combine multiple sensory signals (e.g., vision and proprioception) that can be encoded in various reference frames (body centered and/or exo-centered). In a previous study (Tagliabue M, McIntyre J. PLoS One 8: e68438, 2013), we showed that, when aligning a hand to a remembered target orientation, the brain encodes both target and response in visual space when the target is sensed by one hand and the response is performed by the other, even though both are sensed only through proprioception. Here we ask whether such visual encoding is due 1) to the necessity of transferring sensory information across the brain hemispheres, or 2) to the necessity, due to the arms' anatomical mirror symmetry, of transforming the joint signals of one limb into the reference frame of the other. To answer this question, we asked subjects to perform purely proprioceptive tasks in different conditions: Intra, the same arm sensing the target and performing the movement; Inter/Parallel, one arm sensing the target and the other reproducing its orientation; and Inter/Mirror, one arm sensing the target and the other mirroring its orientation. Performance was very similar between Intra and Inter/Mirror (conditions not requiring joint-signal transformations), while both differed from Inter/Parallel. Manipulation of the visual scene in a virtual reality paradigm showed visual encoding of proprioceptive information only in the latter condition. These results suggest that the visual encoding of purely proprioceptive tasks is not due to interhemispheric transfer of the proprioceptive information per se, but to the necessity of transforming joint signals between mirror-symmetric limbs.NEW & NOTEWORTHY Why does the brain encode goal-oriented, intermanual tasks in a visual space, even in the absence of visual feedback about the target and the hand? We show that the visual encoding is not due to the transfer of proprioceptive signals between brain hemispheres per se, but to the need, due to the mirror symmetry of the two limbs, of transforming joint angle signals of one arm in different joint signals of the other.

Can discrete joint action be synergistic? Studying the stabilization of interpersonal hand coordination

The human perceptual-motor system is tightly coupled to the physical and informational dynamics of a task environment. These dynamics operate to constrain the high-dimensional order of the human movement system into low-dimensional, task-specific synergies-functional groupings of structural elements that are temporarily constrained to act as a single coordinated unit. The aim of the current study was to determine whether synergistic processes operate when coacting individuals coordinate to perform a discrete joint-action task. Pairs of participants sat next to each other and each used 1 arm to complete a pointer-to-target task. Using the uncontrolled manifold (UCM) analysis for the first time in a discrete joint action, the structure of joint-angle variance was examined to determine whether there was synergistic organization of the degrees of freedom employed at the interpersonal or intrapersonal levels. The results revealed that the motor actions performed by coactors were synergistically organized at both the interpersonal and intrapersonal levels. More importantly, however, the interpersonal synergy was found to be significantly stronger than the intrapersonal synergies. Accordingly, the results provide clear evidence that coacting individuals can become temporarily organized to form single synergistic 2-person systems during performance of a discrete joint action.

Implicit guidance to stable performance in a rhythmic perceptual-motor skill

Feedback about error or reward is regarded essential for aiding learners to acquire a perceptual-motor skill. Yet, when a task has redundancy and the mapping between execution and performance outcome is unknown, simple error feedback does not suffice in guiding the learner toward the optimal solutions. The present study developed and tested a new means of implicitly guiding learners to acquire a perceptual-motor skill, rhythmically bouncing a ball on a racket. Due to its rhythmic nature, this task affords dynamically stable solutions that are robust to small errors and noise, a strategy that is independent from actively correcting error. Based on the task model implemented in a virtual environment, a time-shift manipulation was designed to shift the range of ball-racket contacts that achieved dynamically stable solutions. In two experiments, subjects practiced with this manipulation that guided them to impact the ball with more negative racket accelerations, the indicator for the strategy with dynamic stability. Subjects who practiced under normal conditions took longer time to acquire this strategy, although error measures were identical between the control and experimental groups. Unlike in many other haptic guidance or adaptation studies, the experimental groups not only learned, but also maintained the stable solution after the manipulation was removed. These results are a first demonstration that more subtle ways to guide the learner to better performance are needed especially in tasks with redundancy, where error feedback may not be sufficient.

The effect of stereotype threat on performance of a rhythmic motor skill

Many studies using cognitive tasks have found that stereotype threat, or concern about confirming a negative stereotype about one's group, debilitates performance. The few studies that documented similar effects on sensorimotor performance have used only relatively coarse measures to quantify performance. This study tested the effect of stereotype threat on a rhythmic ball bouncing task, where previous analyses of the task dynamics afforded more detailed quantification of the effect of threat on motor control. In this task, novices hit the ball with positive racket acceleration, indicative of unstable performance. With practice, they learn to stabilize error by changing their ball-racket impact from positive to negative acceleration. Results showed that for novices, stereotype threat potentiated hitting the ball with positive racket acceleration, leading to poorer performance of stigmatized females. However, when the threat manipulation was delivered after having acquired some skill, reflected by negative racket acceleration, the stigmatized females performed better. These findings are consistent with the mere effort account that argues that stereotype threat potentiates the most likely response on the given task. The study also demonstrates the value of identifying the control mechanisms through which stereotype threat has its effects on outcome measures.

Different corticospinal control between discrete and rhythmic movement of the ankle

We investigated differences in corticospinal and spinal control between discrete and rhythmic ankle movements. Motor evoked potentials (MEPs) in the tibialis anterior and soleus muscles and soleus H-reflex were elicited in the middle of the plantar flexion phase during discrete ankle movement or in the initial or later cycles of rhythmic ankle movement. The H-reflex was evoked at an intensity eliciting a small M-wave and MEPs were elicited at an intensity of 1.2 times the motor threshold of the soleus MEPs. Only trials in which background EMG level, ankle angle, and ankle velocity were similar among the movement conditions were included for data analysis. In addition, only trials with a similar M-wave were included for data analysis in the experiment evoking H-reflexes. Results showed that H reflex and MEP amplitudes in the soleus muscle during discrete movement were not significantly different from those during rhythmic movement. MEP amplitude in the tibialis anterior muscle during the later cycles of rhythmic movement was significantly larger than that during the initial cycle of the rhythmic movement or during discrete movement. Higher corticospinal excitability in the tibialis anterior muscle during the later cycles of rhythmic movement may reflect changes in corticospinal control from the initial cycle to the later cycles of rhythmic movement.

A survey on CPG-inspired control models and system implementation

This paper surveys the developments of the last 20 years in the field of central pattern generator (CPG) inspired locomotion control, with particular emphasis on the fast emerging robotics-related applications. Functioning as a biological neural network, CPGs can be considered as a group of coupled neurons that generate rhythmic signals without sensory feedback; however, sensory feedback is needed to shape the CPG signals. The basic idea in engineering endeavors is to replicate this intrinsic, computationally efficient, distributed control mechanism for multiple articulated joints, or multi-DOF control cases. In terms of various abstraction levels, existing CPG control models and their extensions are reviewed with a focus on the relative advantages and disadvantages of the models, including ease of design and implementation. The main issues arising from design, optimization, and implementation of the CPG-based control as well as possible alternatives are further discussed, with an attempt to shed more light on locomotion control-oriented theories and applications. The design challenges and trends associated with the further advancement of this area are also summarized.

Dynamic primitives in the control of locomotion

Humans achieve locomotor dexterity that far exceeds the capability of modern robots, yet this is achieved despite slower actuators, imprecise sensors, and vastly slower communication. We propose that this spectacular performance arises from encoding motor commands in terms of dynamic primitives. We propose three primitives as a foundation for a comprehensive theoretical framework that can embrace a wide range of upper- and lower-limb behaviors. Building on previous work that suggested discrete and rhythmic movements as elementary dynamic behaviors, we define submovements and oscillations: as discrete movements cannot be combined with sufficient flexibility, we argue that suitably-defined submovements are primitives. As the term “rhythmic” may be ambiguous, we define oscillations as the corresponding class of primitives. We further propose mechanical impedances as a third class of dynamic primitives, necessary for interaction with the physical environment. Combination of these three classes of primitive requires care. One approach is through a generalized equivalent network: a virtual trajectory composed of simultaneous and/or sequential submovements and/or oscillations that interacts with mechanical impedances to produce observable forces and motions. Reliable experimental identification of these dynamic primitives presents challenges: identification of mechanical impedances is exquisitely sensitive to assumptions about their dynamic structure; identification of submovements and oscillations is sensitive to their assumed form and to details of the algorithm used to extract them. Some methods to address these challenges are presented. Some implications of this theoretical framework for locomotor rehabilitation are considered.

Dynamic primitives of motor behavior

We present in outline a theory of sensorimotor control based on dynamic primitives, which we define as attractors. To account for the broad class of human interactive behaviors-especially tool use-we propose three distinct primitives: submovements, oscillations, and mechanical impedances, the latter necessary for interaction with objects. Owing to the fundamental features of the neuromuscular system-most notably, its slow response-we argue that encoding in terms of parameterized primitives may be an essential simplification required for learning, performance, and retention of complex skills. Primitives may simultaneously and sequentially be combined to produce observable forces and motions. This may be achieved by defining a virtual trajectory composed of submovements and/or oscillations interacting with impedances. Identifying primitives requires care: in principle, overlapping submovements would be sufficient to compose all observed movements but biological evidence shows that oscillations are a distinct primitive. Conversely, we suggest that kinematic synergies, frequently discussed as primitives of complex actions, may be an emergent consequence of neuromuscular impedance. To illustrate how these dynamic primitives may account for complex actions, we briefly review three types of interactive behaviors: constrained motion, impact tasks, and manipulation of dynamic objects.

On the Kinematic Motion Primitives (kMPs) - Theory and Application

Human neuromotor capabilities guarantee a wide variety of motions. A full understanding of human motion can be beneficial for rehabilitation or performance enhancement purposes, or for its reproduction on artificial systems like robots. This work aims at describing the complexity of human motion in a reduced dimensionality, by means of kinematic Motion Primitives (kMPs). A set of five invariant kMPs are identified for periodic motions, and a set of two kMPs for discrete motions. It is shown how these two sets of kMPs can be combined to synthesize more complex motion as the simultaneous execution of the periodic and the discrete motions. The results reported are an evidence of the theory of Central Pattern Generators (CPG), showing its effects on the kinematics, and are related to what presented in the literature on the Motor Primitives extracted from EMG signals. Experimental tests with the COmpliant huMANoid (COMAN) were performed to show that the kMPs extracted from human subjects can be used to transfer the features of human locomotion to the gait of a robot.

Separate representations of dynamics in rhythmic and discrete movements: evidence from motor learning

Rhythmic and discrete arm movements occur ubiquitously in everyday life, and there is a debate as to whether these two classes of movements arise from the same or different underlying neural mechanisms. Here we examine interference in a motor-learning paradigm to test whether rhythmic and discrete movements employ at least partially separate neural representations. Subjects were required to make circular movements of their right hand while they were exposed to a velocity-dependent force field that perturbed the circularity of the movement path. The direction of the force-field perturbation reversed at the end of each block of 20 revolutions. When subjects made only rhythmic or only discrete circular movements, interference was observed when switching between the two opposing force fields. However, when subjects alternated between blocks of rhythmic and discrete movements, such that each was uniquely associated with one of the perturbation directions, interference was significantly reduced. Only in this case did subjects learn to corepresent the two opposing perturbations, suggesting that different neural resources were employed for the two movement types. Our results provide further evidence that rhythmic and discrete movements employ at least partially separate control mechanisms in the motor system.

Early switching between movement types: indication of predictive control?

In everyday life, we frequently alternate between performing discrete and rhythmic movements. When performing a periodic movement, two distinct movement types can be distinguished: highly harmonic vs. discrete-like. The harmonicity of the movement is used to classify it as one or the other. We asked: (1) whether the frequency at which a periodic movement is performed affects the harmonicity of the resultant movement; and (2) what underlies switching between these movement types. To answer these questions, we studied horizontal flexion/extension forearm movements in 13 young adults over a wide range of frequencies. Movements were performed either at a fixed frequency, or at gradually increasing or decreasing target frequencies. We found movement harmonicity to depend on the frequency of the movement. Furthermore, we found a reverse hysteresis behavior, where participants switched movement type in anticipation of the future-required frequency. These findings suggest that predictive control is employed in switching between movement types.

Modeling discrete and rhythmic movements through motor primitives: a review

Rhythmic and discrete movements are frequently considered separately in motor control, probably because different techniques are commonly used to study and model them. Yet the increasing interest in finding a comprehensive model for movement generation requires bridging the different perspectives arising from the study of those two types of movements. In this article, we consider discrete and rhythmic movements within the framework of motor primitives, i.e., of modular generation of movements. In this way we hope to gain an insight into the functional relationships between discrete and rhythmic movements and thus into a suitable representation for both of them. Within this framework we can define four possible categories of modeling for discrete and rhythmic movements depending on the required command signals and on the spinal processes involved in the generation of the movements. These categories are first discussed in terms of biological concepts such as force fields and central pattern generators and then illustrated by several mathematical models based on dynamical system theory. A discussion on the plausibility of theses models concludes the work.

Variance components in discrete force production tasks

The study addresses the relationships between task parameters and two components of variance, "good" and "bad", during multi-finger accurate force production. The variance components are defined in the space of commands to the fingers (finger modes) and refer to variance that does ("bad") and does not ("good") affect total force. Based on an earlier study of cyclic force production, we hypothesized that speeding-up an accurate force production task would be accompanied by a drop in the regression coefficient linking the "bad" variance and force rate such that variance of the total force remains largely unaffected. We also explored changes in parameters of anticipatory synergy adjustments with speeding-up the task. The subjects produced accurate ramps of total force over different times and in different directions (force-up and force-down) while pressing with the four fingers of the right hand on individual force sensors. The two variance components were quantified, and their normalized difference was used as an index of a total force stabilizing synergy. "Good" variance scaled linearly with force magnitude and did not depend on force rate. "Bad" variance scaled linearly with force rate within each task, and the scaling coefficient did not change across tasks with different ramp times. As a result, a drop in force ramp time was associated with an increase in total force variance, unlike the results of the study of cyclic tasks. The synergy index dropped 100-200 ms prior to the first visible signs of force change. The timing and magnitude of these anticipatory synergy adjustments did not depend on the ramp time. Analysis of the data within an earlier model has shown adjustments in the variance of a timing parameter, although these adjustments were not as pronounced as in the earlier study of cyclic force production. Overall, we observed qualitative differences between the discrete and cyclic force production tasks: Speeding-up the cyclic tasks was associated with better adjustments of the timing accuracy, which helps achieve comparable force variance in tasks with different rates of force production. This does not happen in discrete tasks. The lack of scaling of the anticipatory changes in the synergy index with ramp time is the first reported feature that distinguishes anticipatory synergy adjustments from anticipatory postural adjustments. We discuss the differences between the cyclic and discrete tasks within a hierarchical control scheme offered by Schöner.

Asymmetric transfer of visuomotor learning between discrete and rhythmic movements

As long as we only focus on kinematics, rhythmic movement appears to be a concatenation of discrete movements or discrete movement appears to be a truncated rhythmic movement. However, whether or not the neural control processes of discrete and rhythmic movements are distinct has not yet been clearly understood. Here, we address this issue by examining the motor learning transfer between these two types of movements testing the hypothesis that distinct neural control processes should lead to distinct motor learning and transfer. First, we found that the adaptation to an altered visuomotor condition was almost fully transferred from the discrete out-and-back movements to the rhythmic out-and-back movements; however, the transfer from the rhythmic to discrete movements was very small. Second, every time a new set of rhythmic movements was started, a considerable amount of movement error reappeared in the first and the following several cycles although the error converged to a small level by the end of each set. Last, we observed that when the discrete movement training was performed with intertrial intervals longer than 4 s, a significantly larger error appeared, specifically for the second and third cycles of the subsequent rhythmic movements, despite a seemingly full transfer to the first cycle. These results provide strong behavioral evidence that different neuronal control processes are involved in the two types of movements and that discrete control processes contribute to the generation of the first cycle of the rhythmic movement.

Optimal control of a hybrid rhythmic-discrete task: the bouncing ball revisited

Rhythmically bouncing a ball with a racket is a hybrid task that combines continuous rhythmic actuation of the racket with the control of discrete impact events between racket and ball. This study presents experimental data and a two-layered modeling framework that explicitly addresses the hybrid nature of control: a first discrete layer calculates the state to reach at impact and the second continuous layer smoothly drives the racket to this desired state, based on optimality principles. The testbed for this hybrid model is task performance at a range of increasingly slower tempos. When slowing the rhythm of the bouncing actions, the continuous cycles become separated into a sequence of discrete movements interspersed by dwell times and directed to achieve the desired impact. Analyses of human performance show increasing variability of performance measures with slower tempi, associated with a change in racket trajectories from approximately sinusoidal to less symmetrical velocity profiles. Matching results of model simulations give support to a hybrid control model based on optimality, and therefore suggest that optimality principles are applicable to the sensorimotor control of complex movements such as ball bouncing.

Open-loop, closed-loop and compensatory control: performance improvement under pressure in a rhythmic task

According to explicit monitoring theories, the phenomenon of choking under pressure is due to actors focusing their attention on the execution of the skill. This step-by-step perceptually guided control may then interfere with automatic execution. In order to examine the changes in control at the sensorimotor level, we examined the rhythmic task of ball bouncing which affords detailed quantification of indicators of control based on previous research. The hypothesis was that under psychological pressure perceptually guided control should lead to decreased performance due to over-emphasis on closed-loop control and decreased compensatory control. In two experiments of different difficulty psychological stress was induced via setting up a fake competition. Results showed that, contrary to the hypothesis, performance accuracy and consistency improved together with an increase in compensatory control. Indicators for open- and closed-loop processes did not change. Only under more challenging conditions in Experiment 2, enhanced performance under pressure was accompanied by more active, closed-loop and less passive control. The results are discussed in light of task demands and the continuous rhythmic nature of the task: in more challenging tasks, control appears to be more prone to disturbance due to psychological stress. The different control demands in continuous rhythmic tasks may be less prone to interference due to psychological stress than in discrete tasks.