Decomposition of variability in the execution of goal-oriented tasks: three components of skill improvement

From neural noise to co-adaptability: Rethinking the multifaceted architecture of motor variability

In the last decade, the source and the functional meaning of motor variability have attracted considerable attention in behavioral and brain sciences. This construct classically combined different levels of description, variable internal robustness or coherence, and multifaceted operational meanings. We provide here a comprehensive review of the literature with the primary aim of building a precise lexicon that goes beyond the generic and monolithic use of motor variability. In the pars destruens of the work, we model three domains of motor variability related to peculiar computational elements that influence fluctuations in motor outputs. Each domain is in turn characterized by multiple sub-domains. We begin with the domains of noise and differentiation. However, the main contribution of our model concerns the domain of adaptability, which refers to variation within the same exact motor representation. In particular, we use the terms learning and (social)fitting to specify the portions of motor variability that depend on our propensity to learn and on our largely constitutive propensity to be influenced by external factors. A particular focus is on motor variability in the context of the sub-domain named co-adaptability. Further groundbreaking challenges arise in the modeling of motor variability. Therefore, in a separate pars construens, we attempt to characterize these challenges, addressing both theoretical and experimental aspects as well as potential clinical implications for neurorehabilitation. All in all, our work suggests that motor variability is neither simply detrimental nor beneficial, and that studying its fluctuations can provide meaningful insights for future research.

Beyond simple laboratory studies: Developing sophisticated models to study rich behavior

Psychology and neuroscience are concerned with the study of behavior, of internal cognitive processes, and their neural foundations. However, most laboratory studies use constrained experimental settings that greatly limit the range of behaviors that can be expressed. While focusing on restricted settings ensures methodological control, it risks impoverishing the object of study: by restricting behavior, we might miss key aspects of cognitive and neural functions. In this article, we argue that psychology and neuroscience should increasingly adopt innovative experimental designs, measurement methods, analysis techniques and sophisticated computational models to probe rich, ecologically valid forms of behavior, including social behavior. We discuss the challenges of studying rich forms of behavior as well as the novel opportunities offered by state-of-the-art methodologies and new sensing technologies, and we highlight the importance of developing sophisticated formal models. We exemplify our arguments by reviewing some recent streams of research in psychology, neuroscience and other fields (e.g., sports analytics, ethology and robotics) that have addressed rich forms of behavior in a model-based manner. We hope that these "success cases" will encourage psychologists and neuroscientists to extend their toolbox of techniques with sophisticated behavioral models - and to use them to study rich forms of behavior as well as the cognitive and neural processes that they engage.

Reflecting on what is "skill" in human motor skill learning

Humans have an exceptional ability to execute a variety of skilled movements. Researchers have been long interested in understanding behavioral and neurophysiological basis of human motor skill learning for advancing both fundamental neuroscientific knowledge and clinical outcomes. However, despite decades of work in this field there is a lack of consensus about what is meant by "skill" in skill learning. With an advent of various task paradigms testing human motor behavior and increasing heterogeneity in motor learning assessments methods, it is very crucial to identify key features of skill in order to avoid any ambiguity that may result in misinterpretation or over-generalization of findings, which could have serious implications for replication and translational research. In this review, we attempt to highlight the features of skill following a historical approach, considering the seminal work that led to the first definitions of skill and including some contemporary concepts emerging from human motor learning research. Overall, based on this literature, we emphasize that skill has some fundamental characteristics, such as- (i) optimal movement selection and execution, (ii) improved movement speed and accuracy, and (iii) reduced movement variability and error. These features of skill can emerge as a consequence of extensive practice/training/learning, thus resulting in an improved performance state beyond baseline levels. Finally we provide some examples of model tasks that can appropriately capture these features of skill, and conclude that any neuroscientific endeavor aimed at understanding the essence of skill in human motor skill learning should focus on these aspects.

Kinematic coordinations capture learning during human-exoskeleton interaction

Human-exoskeleton interactions have the potential to bring about changes in human behavior for physical rehabilitation or skill augmentation. Despite significant advances in the design and control of these robots, their application to human training remains limited. The key obstacles to the design of such training paradigms are the prediction of human-exoskeleton interaction effects and the selection of interaction control to affect human behavior. In this article, we present a method to elucidate behavioral changes in the human-exoskeleton system and identify expert behaviors correlated with a task goal. Specifically, we observe the joint coordinations of the robot, also referred to as kinematic coordination behaviors, that emerge from human-exoskeleton interaction during learning. We demonstrate the use of kinematic coordination behaviors with two task domains through a set of three human-subject studies. We find that participants (1) learn novel tasks within the exoskeleton environment, (2) demonstrate similarity of coordination during successful movements within participants, (3) learn to leverage these coordination behaviors to maximize success within participants, and (4) tend to converge to similar coordinations for a given task strategy across participants. At a high level, we identify task-specific joint coordinations that are used by different experts for a given task goal. These coordinations can be quantified by observing experts and the similarity to these coordinations can act as a measure of learning over the course of training for novices. The observed expert coordinations may further be used in the design of adaptive robot interactions aimed at teaching a participant the expert behaviors.

Shaping Exploration: How Does the Constraint-Induced Movement Therapy Helps Patients Finding a New Movement Solution

Despite the relative success of constraint-induced movement therapy in the recovery of injury-/trauma-related populations, the mechanisms by which it promotes its results are still unknown. From a dynamical systems approach, we investigated whether the induced exploratory patterns within and between trials during an exercise in Shaping (the therapy's practice) could shed light on this process. We analyzed data from four chronic spinal-cord injury patients during a task of placing and removing their feet from a step. We assessed the within and between trial dynamics through recurrent quantification analyses and task-space analyses, respectively. From our results, individuals found movement patterns directed to modulate foot height (to accomplish the task). Additionally, when the task was manipulated (increasing step height), individuals increased coupling and coupling variability in the ankle, hip, and knee over trials. This pattern of findings is in consonance with the idea of Shaping inducing exploration of different movements. Such exploration might be an important factor affording the positive changes observed in the literature.

Assessment of human expertise and movement kinematics in first-person shooter games

In contrast to traditional professional sports, there are few standardized metrics in professional esports (competitive multiplayer video games) for assessing a player's skill and ability. We assessed the performance of professional-level players in Aim LabTM, a first-person shooter training and assessment game, with two target-shooting tasks. These tasks differed primarily in target size: the task with large targets provided an incentive to be fast but imprecise and the task with large targets provided an incentive to be precise but slow. Each player's motor acuity was measured by characterizing the speed-accuracy trade-off in shot behavior: shot time (elapsed time for a player to shoot at a target) and shot spatial error (distance from center of a target). We also characterized the fine-grained kinematics of players' mouse movements. Our findings demonstrate that: 1) movement kinematics depended on task demands; 2) individual differences in motor acuity were significantly correlated with kinematics; and 3) performance, combined across the two target sizes, was poorly characterized by Fitts Law. Our approach to measuring motor acuity has widespread applications not only in esports assessment and training, but also in basic (motor psychophysics) and clinical (gamified rehabilitation) research.

Motor control beyond reach-how humans hit a target with a whip

Humans are strikingly adept at manipulating complex objects, from tying shoelaces to cracking a bullwhip. These motor skills have highly nonlinear interactive dynamics that defy reduction into parts. Yet, despite advances in data recording and processing, experiments in motor neuroscience still prioritize experimental reduction over realistic complexity. This study embraced the fully unconstrained behaviour of hitting a target with a 1.6-m bullwhip, both in rhythmic and discrete fashion. Adopting an object-centered approach to test the hypothesis that skilled movement simplifies the whip dynamics, the whip's evolution was characterized in relation to performance error and hand speed. Despite widely differing individual strategies, both discrete and rhythmic styles featured a cascade-like unfolding of the whip. Whip extension and orientation at peak hand speed predicted performance error, at least in the rhythmic style, suggesting that humans accomplished the task by setting initial conditions. These insights may inform further studies on human and robot control of complex objects.

Beyond task-space exploration: On the role of variance for motor control and learning

This conceptual analysis on the role of variance for motor control and learning should be taken as a call to: (a) overcome the classic motor-action controversy by identifying converging lines and mutual synergies in the explanation of motor behavior phenomena, and (b) design more empirical research on low-level operational aspects of motor behavior rather than on high-level theoretical terms. Throughout the paper, claim (a) is exemplified by deploying the well-accepted task-space landscape metaphor. This approach provides an illustration not only of a dynamical sensorimotor system but also of a structure of internal forward models, as they are used in more cognitively rooted frameworks such as the theory of optimal feedback control. Claim (b) is put into practice by, mainly theoretically, substantiating a number of predictions for the role of variance in motor control and learning that can be derived from a convergent perspective. From this standpoint, it becomes obvious that variance is neither generally “good” nor generally “bad” for sensorimotor learning. Rather, the predictions derived suggest that specific forms of variance cause specific changes on permanent performance. In this endeavor, Newell’s concept of task-space exploration is identified as a fundamental learning mechanism. Beyond, we highlight further predictions regarding the optimal use of variance for learning from a converging view. These predictions regard, on the one hand, additional learning mechanisms based on the task-space landscape metaphor—namely task-space formation, task-space differentiation and task-space (de-)composition—and, on the other hand, mechanisms of meta-learning that refer to handling noise as well as learning-to-learn and learning-to-adapt. Due to the character of a conceptual-analysis paper, we grant ourselves the right to be highly speculative on some issues. Thus, we would like readers to see our call mainly as an effort to stimulate both a meta-theoretical discussion on chances for convergence between classically separated lines of thought and, on an empirical level, future research on the role of variance in motor control and learning.

The role of ball backspin alignment and variability in basketball shooting accuracy

Interaction between the shooting hand and ball at the moment a basketball is released generates a three-dimensional backspin of the ball. This study is the first to investigate how characteristics of the backspin alignment and variability contribute to lateral shooting accuracy. Spin axis (SA) direction and backspin magnitude were measured on 25 shot attempts for 26 collegiate basketball players (male: n = 16, female: n = 10). The mean SA alignment, as viewed from the shooting hand side, was found to be tipped down and towards the target (p < 0.001). Standard deviations (SD) in the SA alignment were strong predictors of lateral accuracy (vertical SD: r = 0.80, p < 0.001, forward-backward SD: r = 0.51, p = 0.01), with variation in the vertical alignment being the best predictor. No significant correlation between mean SA misalignment and lateral accuracy was observed. However, intra-individual relationships between SA misalignment and lateral error revealed that individuals tended to have 0.17 degrees more misalignment for each cm of lateral error (p < 0.001, 95% CI: 0.24-0.09). These indicate that while an individual's mean alignment may not predict lateral accuracy, improving one's SA alignment and reducing alignment variability may increase lateral accuracy.

General variability leads to specific adaptation toward optimal movement policies

Our nervous systems can learn optimal control policies in response to changes to our bodies, tasks, and movement contexts. For example, humans can learn to adapt their control policy in walking contexts where the energy-optimal policy is shifted along variables such as step frequency or step width. However, it is unclear how the nervous system determines which ways to adapt its control policy. Here, we asked how human participants explore through variations in their control policy to identify more optimal policies in new contexts. We created new contexts using exoskeletons that apply assistive torques to each ankle at each walking step. We analyzed four variables that spanned the levels of the whole movement, the joint, and the muscle: step frequency, ankle angle range, total soleus activity, and total medial gastrocnemius activity. We found that, across all of these analyzed variables, variability increased upon initial exposure to new contexts and then decreased with experience. This led to adaptive changes in the magnitude of specific variables, and these changes were correlated with reduced energetic cost. The timescales by which adaptive changes progressed and variability decreased were faster for some variables than others, suggesting a reduced search space within which the nervous system continues to optimize its policy. These collective findings support the principle that exploration through general variability leads to specific adaptation toward optimal movement policies.

Always Pay Attention to Which Model of Motor Learning You Are Using

This critical review considers the epistemological and historical background of the theoretical construct of motor learning for a more differentiated understanding. More than simply reflecting critically on the models that are used to solve problems-whether they are applied in therapy, physical education, or training practice-this review seeks to respond constructively to the recent discussion caused by the replication crisis in life sciences. To this end, an in-depth review of contemporary motor learning approaches is provided, with a pragmatism-oriented clarification of the researcher's intentions on fundamentals (what?), subjects (for whom?), time intervals (when?), and purpose (for what?). The complexity in which the processes of movement acquisition, learning, and refinement take place removes their predictable and linear character and therefore, from an applied point of view, invites a great deal of caution when trying to make generalization claims. Particularly when we attempt to understand and study these phenomena in unpredictable and dynamic contexts, it is recommended that scientists and practitioners seek to better understand the central role that the individual and their situatedness plays in the system. In this way, we will be closer to making a meaningful and authentic contribution to the advancement of knowledge, and not merely for the sake of renaming inventions.

Long-Term Motor Learning in the "Wild" With High Volume Video Game Data

Motor learning occurs over long periods of practice during which motor acuity, the ability to execute actions more accurately, precisely, and in less time, improves. Laboratory-based studies of motor learning are typically limited to a small number of participants and a time frame of minutes to several hours per participant. There is a need to assess the generalizability of theories and findings from lab-based motor learning studies on larger samples and time scales. In addition, laboratory-based studies of motor learning use relatively simple motor tasks which participants are unlikely to be intrinsically motivated to learn, limiting the interpretation of their findings in more ecologically valid settings ("in the wild"). We studied the acquisition and longitudinal refinement of a complex sensorimotor skill embodied in a first-person shooter video game scenario, with a large sample size (N = 7174, 682,564 repeats of the 60 s game) over a period of months. Participants voluntarily practiced the gaming scenario for up to several hours per day up to 100 days. We found improvement in performance accuracy (quantified as hit rate) was modest over time but motor acuity (quantified as hits per second) improved considerably, with 40-60% retention from 1 day to the next. We observed steady improvements in motor acuity across multiple days of video game practice, unlike most motor learning tasks studied in the lab that hit a performance ceiling rather quickly. Learning rate was a non-linear function of baseline performance level, amount of daily practice, and to a lesser extent, number of days between practice sessions. In addition, we found that the benefit of additional practice on any given day was non-monotonic; the greatest improvements in motor acuity were evident with about an hour of practice and 90% of the learning benefit was achieved by practicing 30 min per day. Taken together, these results provide a proof-of-concept in studying motor skill acquisition outside the confines of the traditional laboratory, in the presence of unmeasured confounds, and provide new insights into how a complex motor skill is acquired in an ecologically valid setting and refined across much longer time scales than typically explored.

Motor Memory Consolidation after Augmented Variability Depends on the Space in which Variability is Introduced

Motor memories undergo a period of consolidation before they become resistant to the practice of another task. Although movement variability is important in motor memory consolidation, its role is not fully understood in redundant tasks where variability can exist along two orthogonal subspaces (the 'task space' and the 'null space') that have different effects on task performance. Here, we used haptic perturbations to augment variability in these different spaces and examined their effect on motor memory consolidation. Participants learned a shuffleboard task, where they held a bimanual manipulandum and made a discrete throwing motion to slide a virtual puck towards a target. The task was redundant because the distance travelled by the puck was determined by the sum of the left and right hand speeds at release. After participants practiced the task, we used haptic perturbations to introduce motor variability in the task space or null space and examined consolidation of the original task on the next day. We found that regardless of the amplitude, augmenting variability in the task space resulted in significantly better consolidation relative to augmenting variability in the null space, but was not different from a control group that practiced with no variability. This benefit of increasing task space variability relative to increasing null space variability was likely due to the fact that it did not disrupt the pre-existing coordination strategy. These results suggest that the effects of variability on motor memory consolidation depend on the interplay between the induced variability and the pre-existing coordination strategy.

Optimization in Manual Aiming: Relating Inherent Variability and Target Size, and Its Influence on Tendency

For manual aiming, the optimized submovement model predicts a tendency toward target-center of primary movement endpoints (probabilistic strategy), while the minimization model predicts target undershooting ("play-it-safe" strategy). The spatial variability of primary movement endpoints directed toward a cross-hair (400-500 ms) (Session 1) were scaled by a multiplicative factor (x1 - 4) to form circular targets of different sizes (Session 2). In recognition of both models, it was predicted that the more that inherent variability exceeded the target size, the greater the tendency to shift from target-center aiming to target undershooting. The central tendency of primary movement endpoints was not influenced by the targets, while it neared target-center. These findings concur with a probabilistic strategy, although we speculate on factors that might otherwise foster a "play-it-safe" strategy.

Clarifying the Biomechanical Concept of Coordination Through Comparison With Coordination in Motor Control

Coordination is a multidisciplinary concept in human movement science, particularly in the field of biomechanics and motor control. However, the term is not used synonymously by researchers and has substantially different meanings depending on the studies. Therefore, it is necessary to clarify the meaning of coordination to avoid confusion. The meaning of coordination in motor control from computational and ecological perspectives has been clarified, and the meanings differed between them. However, in biomechanics, each study has defined the meaning of the term and the meanings are diverse, and no study has attempted to bring together the diversity of the meanings of the term. Therefore, the purpose of this study is to provide a summary of the different meanings of coordination across the theoretical landscape and clarify the meaning of coordination in biomechanics. We showed that in biomechanics, coordination generally means the relation between elements that act toward the achievement of a motor task, which we call biomechanical coordination. We also showed that the term coordination used in computational and ecological perspectives has two different meanings, respectively. Each one had some similarities with biomechanical coordination. The findings of this study lead to an accurate understanding of the concept of coordination, which would help researchers formulate their empirical arguments for coordination in a more transparent manner. It would allow for accurate interpretation of data and theory development. By comprehensively providing multiple perspectives on coordination, this study intends to promote coordination studies in biomechanics.

Motor Variability Prior to Learning does not Facilitate the Ability to Adopt new Movement Solutions

Many contexts in motor learning require a learner to change from an existing movement solution to a novel movement solution to perform the same task. Recent evidence has pointed to motor variability prior to learning as a potential marker for predicting individual differences in motor learning. However, it is not known if this variability is predictive of the ability to adopt a new movement solution for the same task. Here, we examined this question in the context of a redundant precision task requiring control of motor variability. Fifty young adults learned a precision task that involved throwing a virtual puck toward a target using both hands. Because the speed of the puck depended on the sum of speeds of both hands, this task could be achieved using multiple solutions. Participants initially performed a baseline task where there was no constraint on the movement solution, and then performed a novel task where they were constrained to adopt a specific movement solution requiring asymmetric left and right hand speeds. Results showed that participants were able to learn the new solution, and this change was associated with changes in both the amount and structure of variability. However, increased baseline motor variability did not facilitate initial or final task performance when using the new solution - in fact, greater variability was associated with higher errors. These results suggest that motor variability is not necessarily indicative of flexibility and highlight the role of the task context in determining the relation between motor variability and learning.

Effects of motor skill level and speed on movement variability during running

Variability in movement is an informative biological feature. This study aimed to examine the effects of motor skill level and running speed on movement variability. Twenty-nine male college students (fourteen athletes and fifteen non-athletes) participated in this study. All participants performed three motor tasks: 3 m/s running, 5 m/s running, and sprint running. Lower-limb kinematic data were acquired using a 16-camera infrared motion capture system. Lower-limb coordination during the stance phase was quantified using a continuous relative phase (CRP) method for interlimb (hip-hip, knee-knee, ankle-ankle) and intralimb (hip-knee, knee-ankle). The variabilities of stride length, stride cadence, joint angles, intralimb CRP, and interlimb CRP were calculated as standard deviations of each measurement. The results revealed that there were significant interaction effects between motor skill level and speed on movement variability for stride length (p = 0.047), ankle angle during propulsive phase (p = 0.001), knee-ankle CRP during propulsive phase (p = 0.007) and knee-knee CRP during propulsive phase (p = 0.009). Athletes showed greater angle variability, coordination variability and lower stride length variability during sprinting (all p < 0.05). In contrast, no between groups variability difference was observed when jogging at fixed lower speeds (all p > 0.05). Movement variability was greater for sprinting compared to jogging. Skill level was found to differentially affect the role of coordination variability in sprint performance. For athletes, hip-knee deviation phase and hip-hip deviation phase during braking phase were negatively correlated with sprinting speed (r = -0.563 and -0.642, respectively; both p < 0.05). For non-athletes, hip-knee deviation phase was positively correlated with sprinting speed (r = 0.581, p = 0.023). In conclusion, stride length become more stable, joint angle and coordination become more variable with long-term training. Results of this study also suggest that the relationship between coordination variability and performance is complicated and may depend on motor skill level. More longitudinal studies are needed to definitively determine the relationship between movement variability and performance.

The road towards understanding embodied decisions

Most current decision-making research focuses on classical economic scenarios, where choice offers are prespecified and where action dynamics play no role in the decision. However, our brains evolved to deal with different choice situations: "embodied decisions". As examples of embodied decisions, consider a lion that has to decide which gazelle to chase in the savannah or a person who has to select the next stone to jump on when crossing a river. Embodied decision settings raise novel questions, such as how people select from time-varying choice options and how they track the most relevant choice attributes; but they have long remained challenging to study empirically. Here, we summarize recent progress in the study of embodied decisions in sports analytics and experimental psychology. Furthermore, we introduce a formal methodology to identify the relevant dimensions of embodied choices (present and future affordances) and to map them into the attributes of classical economic decisions (probabilities and utilities), hence aligning them. Studying embodied decisions will greatly expand our understanding of what decision-making is.

Handlebar Robotic System for Bimanual Motor Control and Learning Research

Robotic devices can be used for motor control and learning research. In this work, we present the construction, modeling and experimental validation of a bimanual robotic device. We tested some hypotheses that may help to better understand the motor learning processes involved in the interlimb coordination function. The system emulates a bicycle handlebar with rotational motion, thus requiring bilateral upper limb control and a coordinated sequence of joint sub-movements. The robotic handlebar is compact and portable and can register in a fast rate both position and forces independently from arms, including prehension forces. An impedance control system was implemented in order to promote a safer environment for human interaction and the system is able to generate force fields, suitable for implementing motor learning paradigms. The novelty of the system is the decoupling of prehension and manipulation forces of each hand, thus paving the way for the investigation of hand dominance function in a bimanual task. Experiments were conducted with ten healthy subjects, kinematic and dynamic variables were measured during a rotational set of movements. Statistical analyses showed that movement velocity decreased with practice along with an increase in reaction time. This suggests an increase of the task planning time. Prehension force decreased with practice. However, an unexpected result was that the dominant hand did not lead the bimanual task, but helped to correct the movement, suggesting different roles for each hand during a cooperative bimanual task.

A Hessian-based decomposition characterizes how performance in complex motor skills depends on individual strategy and variability

In complex real-life motor skills such as unconstrained throwing, performance depends on how accurate is on average the outcome of noisy, high-dimensional, and redundant actions. What characteristics of the action distribution relate to performance and how different individuals select specific action distributions are key questions in motor control. Previous computational approaches have highlighted that variability along the directions of first order derivatives of the action-to-outcome mapping affects performance the most, that different mean actions may be associated to regions of the actions space with different sensitivity to noise, and that action covariation in addition to noise magnitude matters. However, a method to relate individual high-dimensional action distribution and performance is still missing. Here we introduce a decomposition of performance into a small set of indicators that compactly and directly characterize the key performance-related features of the distribution of high-dimensional redundant actions. Central to the method is the observation that, if performance is quantified as a mean score, the Hessian (second order derivatives) of the action-to-score function determines how the noise of the action distribution affects performance. We can then approximate the mean score as the sum of the score of the mean action and a tolerance-variability index which depends on both Hessian and action covariance. Such index can be expressed as the product of three terms capturing noise magnitude, noise sensitivity, and alignment of the most variable and most noise sensitive directions. We apply this method to the analysis of unconstrained throwing actions by non-expert participants and show that, consistently across four different throwing targets, each participant shows a specific selection of mean action score and tolerance-variability index as well as specific selection of noise magnitude and alignment indicators. Thus, participants with different strategies may display the same performance because they can trade off suboptimal mean action for better tolerance-variability and higher action variability for better alignment with more tolerant directions in action space.

Task and Informational Constraints on Search Strategies: Testing the Idea of Convergence to Tolerant Regions

The experiment reported was designed to investigate the interaction of information and force variability on the evolving search strategy, specifically testing the hypothesis of convergence to tolerant regions. Participants were required to produce proportional bimanual isometric force output over three days of practice, with no prespecified force target and where performance was more tolerant to force variability at higher forces. The duration of intermittent visual feedback was manipulated to test the effects of information and force variability on the search process and the resulting sensitivity to tolerant regions of the task space. The findings showed that just under half of the participants exploited more tolerant regions and that this was predicted by the initial force conditions. Different characterizations of the individual search patterns were also predicted by inherent force-dependent variability and initial force conditions. Visual intermittency feedback did not affect the time-dependent properties of the search process but did influence the within-trial variability. Our findings suggest that the attraction to tolerant regions needs to be considered within the interactions of the different categories of constraints on the search process.

Stride-to-Stride Variability of the Center of Mass in Male Trained Runners After an Exhaustive Run: A Three Dimensional Movement Variability Analysis With a Subject-Specific Anthropometric Model

The motion of the human body can be described by the motion of its center of mass (CoM). Since the trajectory of the CoM is a crucial variable during running, one can assume that trained runners would try to keep their CoM trajectory constant from stride to stride. However, when exposed to fatigue, runners might have to adapt certain biomechanical parameters. The Uncontrolled Manifold approach (UCM) and the Tolerance, Noise, and Covariation (TNC) approach are used to analyze changes in movement variability while considering the overall task of keeping a certain task relevant variable constant. The purpose of this study was to investigate if and how runners adjust their CoM trajectory during a run to fatigue at a constant speed on a treadmill and how fatigue affects the variability of the CoM trajectory. Additionally, the results obtained with the TNC approach were compared to the results obtained with the UCM analysis in an earlier study on the same dataset. Therefore, two TNC analyses were conducted to assess effects of fatigue on the CoM trajectory from two viewpoints: one analyzing the CoM with respect to a lab coordinate system (PVlab) and another one analyzing the CoM with respect to the right foot (PVfoot). Full body kinematics of 13 healthy young athletes were captured in a rested and in a fatigued state and an anthropometric model was used to calculate the CoM based on the joint angles. Variability was quantified by the coefficient of variation of the length of the position vector of the CoM and by the components Tolerance, Noise, and Covariation which were analyzed both in 3D and the projections in the vertical, anterior-posterior and medio-lateral coordinate axes. Concerning PVlab we found that runners increased their stride-to-stride variability in medio-lateral direction (1%). Concerning PVfoot we found that runners lowered their CoM (4 mm) and increased their stride-to-stride variability in the absorption phase in both 3D and in the vertical direction. Although we identified statistically relevant differences between the two running states, we have to point out that the effects were small (CV ≤ 1%) and must be interpreted cautiously.

Relevance of Predictive and Postdictive Error Information in the Course of Motor Learning

The prediction of the sensory consequences of physical movements is a fundamental feature of the human brain. This function is attributed to a forward model, which generates predictions based on sensory and efferent information. The neural processes underlying such predictions have been studied using the error-related negativity (ERN) as a fronto-central event-related potential in electroencephalogram (EEG) tracings. In this experiment, 16 participants practiced a novel motor task for 4000 trials over ten sessions. Neural correlates of error processing were recorded in sessions one, five, and ten. Along with significant improvements in task performance, the ERN amplitude increased over the sessions. Simultaneously, the feedback-related negativity (FRN), a neural marker corresponding to the processing of movement-outcome feedback, attenuated with learning. The findings suggest that early in learning, the motor control system relies more on information from external feedback about terminal outcome. With increasing task performance, the forward model is able to generate more accurate outcome predictions, which, as a result, increasingly contributes to error processing. The data also suggests a complementary relationship between the ERN and the FRN over motor learning.

Perceptual-motor styles

Even for a stereotyped task, sensorimotor behavior is generally variable due to noise, redundancy, adaptability, learning or plasticity. The sources and significance of different kinds of behavioral variability have attracted considerable attention in recent years. However, the idea that part of this variability depends on unique individual strategies has been explored to a lesser extent. In particular, the notion of style recurs infrequently in the literature on sensorimotor behavior. In general use, style refers to a distinctive manner or custom of behaving oneself or of doing something, especially one that is typical of a person, group of people, place, context, or period. The application of the term to the domain of perceptual and motor phenomenology opens new perspectives on the nature of behavioral variability, perspectives that are complementary to those typically considered in the studies of sensorimotor variability. In particular, the concept of style may help toward the development of personalised physiology and medicine by providing markers of individual behaviour and response to different stimuli or treatments. Here, we cover some potential applications of the concept of perceptual-motor style to different areas of neuroscience, both in the healthy and the diseased. We prefer to be as general as possible in the types of applications we consider, even at the expense of running the risk of encompassing loosely related studies, given the relative novelty of the introduction of the term perceptual-motor style in neurosciences.

Increased motor variability facilitates motor learning in weight shift toward the paretic side during walking in individuals post-stroke

The purpose of this study was to determine whether applying "varied" versus constant pelvis assistance force mediolaterally toward the paretic side of stroke survivors during walking would result in short-term improvement in weight shift toward the paretic side. Twelve individuals post-stroke (60.4 ± 6.2 years; gait speed: 0.53 ± 0.19 m/s) were tested under two conditions (varied vs. constant). Each condition was conducted in a single separate session, which consisted of (a) treadmill walking with no assistance force for 1 min (baseline), pelvis assistance toward the paretic side for 9 min (adaptation), and then no force for additional 1 min (post-adaptation), and (b) overground walking. In the "varied" condition, the magnitude of force was randomly changed across steps between 30% and 100% of the predetermined amount. In the abrupt condition, the magnitude of force was kept constant at 100% of the predetermined amount. Participants exhibited greater improvements in weight shift toward the paretic side (p < 0.01) and in muscle activity of plantar flexors and hip adductors of the paretic leg (p = 0.02) from baseline to late post-adaptation period for the varied condition than for the constant condition. Motor variability of the peak pelvis displacement at baseline was correlated with improvement in weight shift toward the paretic side after training for the varied (R²  = 0.64, p = 0.01) and the constant condition (R²  = 0.39, p = 0.03). These findings suggest that increased motor variability, induced by applying the varied pelvis assistance, may facilitate motor learning in weight shift and gait symmetry during walking in individuals post-stroke.

Neural Encoding and Representation of Time for Sensorimotor Control and Learning

The ability to perceive and produce movements in the real world with precise timing is critical for survival in animals, including humans. However, research on sensorimotor timing has rarely considered the tight interrelation between perception, action, and cognition. In this review, we present new evidence from behavioral, computational, and neural studies in humans and nonhuman primates, suggesting a pivotal link between sensorimotor control and temporal processing, as well as describing new theoretical frameworks regarding timing in perception and action. We first discuss the link between movement coordination and interval-based timing by addressing how motor training develops accurate spatiotemporal patterns in behavior and influences the perception of temporal intervals. We then discuss how motor expertise results from establishing task-relevant neural manifolds in sensorimotor cortical areas and how the geometry and dynamics of these manifolds help reduce timing variability. We also highlight how neural dynamics in sensorimotor areas are involved in beat-based timing. These lines of research aim to extend our understanding of how timing arises from and contributes to perceptual-motor behaviors in complex environments to seamlessly interact with other cognitive processes.

Promoting Motor Variability During Robotic Assistance Enhances Motor Learning of Dynamic Tasks

Despite recent advances in robot-assisted training, the benefits of haptic guidance on motor (re)learning are still limited. While haptic guidance may increase task performance during training, it may also decrease participants' effort and interfere with the perception of the environment dynamics, hindering somatosensory information crucial for motor learning. Importantly, haptic guidance limits motor variability, a factor considered essential for learning. We propose that Model Predictive Controllers (MPC) might be good alternatives to haptic guidance since they minimize the assisting forces and promote motor variability during training. We conducted a study with 40 healthy participants to investigate the effectiveness of MPCs on learning a dynamic task. The task consisted of swinging a virtual pendulum to hit incoming targets with the pendulum ball. The environment was haptically rendered using a Delta robot. We designed two MPCs: the first MPC-end-effector MPC-applied the optimal assisting forces on the end-effector. A second MPC-ball MPC-applied its forces on the virtual pendulum ball to further reduce the assisting forces. The participants' performance during training and learning at short- and long-term retention tests were compared to a control group who trained without assistance, and a group that trained with conventional haptic guidance. We hypothesized that the end-effector MPC would promote motor variability and minimize the assisting forces during training, and thus, promote learning. Moreover, we hypothesized that the ball MPC would enhance the performance and motivation during training but limit the motor variability and sense of agency (i.e., the feeling of having control over their movements), and therefore, limit learning. We found that the MPCs reduce the assisting forces compared to haptic guidance. Training with the end-effector MPC increases the movement variability and does not hinder the pendulum swing variability during training, ultimately enhancing the learning of the task dynamics compared to the other groups. Finally, we observed that increases in the sense of agency seemed to be associated with learning when training with the end-effector MPC. In conclusion, training with MPCs enhances motor learning of tasks with complex dynamics and are promising strategies to improve robotic training outcomes in neurological patients.

Embodied virtual reality for the study of real-world motor learning

Motor-learning literature focuses on simple laboratory-tasks due to their controlled manner and the ease to apply manipulations to induce learning and adaptation. Recently, we introduced a billiards paradigm and demonstrated the feasibility of real-world-neuroscience using wearables for naturalistic full-body motion-tracking and mobile-brain-imaging. Here we developed an embodied virtual-reality (VR) environment to our real-world billiards paradigm, which allows to control the visual feedback for this complex real-world task, while maintaining sense of embodiment. The setup was validated by comparing real-world ball trajectories with the trajectories of the virtual balls, calculated by the physics engine. We then ran our short-term motor learning protocol in the embodied VR. Subjects played billiard shots when they held the physical cue and hit a physical ball on the table while seeing it all in VR. We found comparable short-term motor learning trends in the embodied VR to those we previously reported in the physical real-world task. Embodied VR can be used for learning real-world tasks in a highly controlled environment which enables applying visual manipulations, common in laboratory-tasks and rehabilitation, to a real-world full-body task. Embodied VR enables to manipulate feedback and apply perturbations to isolate and assess interactions between specific motor-learning components, thus enabling addressing the current questions of motor-learning in real-world tasks. Such a setup can potentially be used for rehabilitation, where VR is gaining popularity but the transfer to the real-world is currently limited, presumably, due to the lack of embodiment.

Quantitative Assessment of Learning and Retention in Virtual Vocal Function Exercises

Purpose Successful voice therapy requires the patient to learn new vocal behaviors, but little is currently known regarding how vocal motor skills are improved and retained. To quantitatively characterize the motor learning process in a clinically meaningful context, a virtual task was developed based on the Vocal Function Exercises. In the virtual task, subjects control a computational model of a ball floating on a column of airflow via modifications to mean airflow (L/s) and intensity (dB-C) to keep the ball within a target range representing a normative ratio (dB × s/L). Method One vocally healthy female and one female with nonphonotraumatic vocal hyperfunction practiced the task for 11 days and completed retention testing 1 and 6 months later. The mapping between the two execution variables (airflow and intensity) and one error measure (proximity to the normative ratio) was evaluated by quantifying distributional variability (tolerance cost and noise cost) and temporal variability (scaling index of detrended fluctuation analysis). Results Both subjects reduced their error over practice and retained their performance 6 months later. Tolerance cost and noise cost were positively correlated with decreases in error during early practice and late practice, respectively. After extended practice, temporal variability was modulated to align with the task's solution manifold. Conclusions These case studies illustrated, in a healthy control and a patient with nonphonotraumatic vocal hyperfunction, that the virtual floating ball task produces quantitative measures characterizing the learning process. Future work will further investigate the task's potential to enhance clinical assessment and treatments involving voice control. Supplemental Material https://doi.org/10.23641/asha.13322891.

Back to reality: differences in learning strategy in a simplified virtual and a real throwing task

Virtual environments have been widely used in motor neuroscience and rehabilitation, as they afford tight control of sensorimotor conditions and readily afford visual and haptic manipulations. However, typically, studies have only examined performance in the virtual testbeds, without asking how the simplified and controlled movement in the virtual environment compares to behavior in the real world. To test whether performance in the virtual environment was a valid representation of corresponding behavior in the real world, this study compared throwing in a virtual set-up with realistic throwing, where the task parameters were precisely matched. Even though the virtual task only required a horizontal single-joint arm movement, similar to many simplified movement assays in motor neuroscience, throwing accuracy and precision were significantly worse than in the real task that involved all degrees of freedom of the arm; only after 3 practice days did success rate and error reach similar levels. To gain more insight into the structure of the learning process, movement variability was decomposed into deterministic and stochastic contributions. Using the tolerance-noise-covariation decomposition method, distinct stages of learning were revealed: While tolerance was optimized first in both environments, it was higher in the virtual environment, suggesting that more familiarization and exploration was needed in the virtual task. Covariation and noise showed more contributions in the real task, indicating that subjects reached the stage of fine-tuning of variability only in the real task. These results showed that while the tasks were precisely matched, the simplified movements in the virtual environment required more time to become successful. These findings resonate with the reported problems in transfer of therapeutic benefits from virtual to real environments and alert that the use of virtual environments in research and rehabilitation needs more caution.NEW & NOTEWORTHY This study compared human performance of the same throwing task in a real and a matched virtual environment. With 3 days' practice, subjects improved significantly faster in the real task, even though the arm and hand movements were more complex. Decomposing variability revealed that performance in the virtual environment, despite its simplified hand movements, required more exploration. Additionally, due to fewer constraints in the real task, subjects could modify the geometry of the solution manifold, by shifting the release position, and thereby simplify the task.

Consistent Hand Dynamics Are Achieved by Controlling Variabilities Among Joint Movements During Fastball Pitching

This study aimed to determine whether covariations among joint movements are utilized to stabilize hand orientation and movement and to determine which of the upper or lower extremities make effective use of the covariation. Joint angles during pitching were measured in 12 skilled baseball pitchers, using a motion capture system. The joint angles in 10 successful trials were used for the reconstructed motions. The reconstructed motion in the first condition was the same as for the measured motion. In the second condition, the reconstructed motion was generated with joint angles that were pseudo-randomly selected to artificially break off covariation in the measured joint-angle combination. In the third and fourth conditions, the reconstructed motions were generated with the same joint-angle combinations as the measured angles in the throwing arm and the stride leg, respectively, but pseudo-randomly selected in the other joint angles. Ten reconstructed motions were generated for each condition. Standard deviations (SDs) of hand orientation and movement direction were calculated and compared among the conditions. All SDs for the first condition were the smallest among the conditions, indicating that the movements in the measured condition used the covariation in joint angles to make the hand movement stable. The results also illustrated that some SDs in the fourth condition were smaller than those in the third condition, suggesting that the lower extremity made effective use of the covariation. These results imply that it is necessary not only to reduce variability in each joint but also to regulate joint movements to stabilize hand orientation and movement.

Motor learning in real-world pool billiards

The neurobehavioral mechanisms of human motor-control and learning evolved in free behaving, real-life settings, yet this is studied mostly in reductionistic lab-based experiments. Here we take a step towards a more real-world motor neuroscience using wearables for naturalistic full-body motion-tracking and the sports of pool billiards to frame a real-world skill learning experiment. First, we asked if well-known features of motor learning in lab-based experiments generalize to a real-world task. We found similarities in many features such as multiple learning rates, and the relationship between task-related variability and motor learning. Our data-driven approach reveals the structure and complexity of movement, variability, and motor learning, enabling an in-depth understanding of the structure of motor learning in three ways: First, while expecting most of the movement learning is done by the cue-wielding arm, we find that motor learning affects the whole body, changing motor-control from head to toe. Second, during learning, all subjects decreased their movement variability and their variability in the outcome. Subjects who were initially more variable were also more variable after learning. Lastly, when screening the link across subjects between initial variability in individual joints and learning, we found that only the initial variability in the right forearm supination shows a significant correlation to the subjects' learning rates. This is in-line with the relationship between learning and variability: while learning leads to an overall reduction in movement variability, only initial variability in specific task-relevant dimensions can facilitate faster learning.

Brain Activity Reveals Multiple Motor-Learning Mechanisms in a Real-World Task

Many recent studies found signatures of motor learning in neural beta oscillations (13-30 Hz), and specifically in the post-movement beta rebound (PMBR). All these studies were in controlled laboratory-tasks in which the task designed to induce the studied learning mechanism. Interestingly, these studies reported opposing dynamics of the PMBR magnitude over learning for the error-based and reward-based tasks (increase vs. decrease, respectively). Here, we explored the PMBR dynamics during real-world motor-skill-learning in a billiards task using mobile-brain-imaging. Our EEG recordings highlight the opposing dynamics of PMBR magnitudes (increase vs. decrease) between different subjects performing the same task. The groups of subjects, defined by their neural dynamics, also showed behavioral differences expected for different learning mechanisms. Our results suggest that when faced with the complexity of the real-world different subjects might use different learning mechanisms for the same complex task. We speculate that all subjects combine multi-modal mechanisms of learning, but different subjects have different predominant learning mechanisms.

A real-time feedback method to reduce loading rate during running: Effect of combining direct and indirect feedback

Impact loading plays a key role in the pathophysiology of running-related injuries. Providing real-time feedback may be an effective strategy to reduce impact loading; however, it is currently unclear what an effective training method to help runners achieve a habitual low loading rate is. We subjected 20 healthy non-runners to a structured sequence of direct and indirect biofeedback designed to facilitate broader exploration of neuro-mechanical workspace for potential movement solutions (indirect feedback on cadence and foot-strike angle) and to refine and converge upon an optimal sub-set of that space to match the task goal (direct feedback on loading rate). While indirect biofeedback on foot-strike angle yielded a lower impact load than providing direct biofeedback on loading rate, compared to indirect biofeedback on foot-strike angle, providing direct feedback on loading rate statistically increased (+58%, p = 0.007) the range of goal-relevant solutions participants used to lower their impact loading. Results showed that structured feedback was effective in increasing the range of input parameters that match the task goal, hence expanding the size of goal-relevant solutions, which may benefit running performance under changing environmental constraints.

Compensation of stochastic time-continuous perturbations during walking in healthy young adults: An analysis of the structure of gait variability

BACKGROUND

During everyday locomotion, we cope with various internal or external perturbations (e.g. uneven surface). Uncertainty exists on how unpredictable external perturbations increase noise within the motor system and if they are compensated by employing covariation of the limb joints or rather due to decreased sensitivity of an altered posture.

RESEARCH QUESTION

Do continuous stochastic perturbations affect the structure of gait variability in young and healthy adults?

METHODS

In a cross-over study, gait kinematics of 21 healthy young sports students were registered during treadmill walking with and without continuous stochastic perturbations. Using the TNC method, the following aspects were analyzed: (a) the sensitivity of body posture to perturbations ('tolerance') decreasing gait variability, (b) the unstructured motor 'noise' increasing gait variability and (c) the amount of 'covariation' of the limb joints.

RESULTS

Compared to normal walking, gait variability was significantly increased (p < .001) during walking with perturbations. The negative effect of noise was partly compensated by improved 'covariation' of leg joints (p < .001). The aspect 'tolerance' had a small effect on increasing gait variability during stance phase (p < .001) and decreasing gait variability during swing phase (p < .001).

SIGNIFICANCE

Increased motor noise due to external perturbations is partly compensated by improved covariation of the limb joints. However, the effect of an altered posture slightly affects gait variability. Further studies should focus on different populations (e.g. older participants) to see if they use the same mechanism (improved covariation) to compensate for stochastic perturbations.

Assessment of a Cognitive-Motor Training Program in Adults at Risk for Developing Dementia

Background

With the prevalence of dementia increasing each year, pre-clinically implemented therapeutic interventions are needed. It has been suggested that cascading neural network failures may bring on behavioural deficits associated with Alzheimer’s disease.

Methods

Previously we have shown that cognitive-motor integration (CMI) training in adults with cognitive impairments generalized to improved global cognitive and activities of daily living scores. Here we employ a novel movement control–based training approach involving CMI rather than traditional cognition-only brain training. We hypothesized that such training would stimulate widespread neural networks and enhance rule-based visuomotor ability in at-risk individuals.

Results

We observed a significant improvement in bimanual coordination in the at-risk training group. We also observed significant decreases in movement variability for the most complex CMI condition in the at-risk and healthy training groups.

Conclusions

These data suggest that integrating cognition into action in a training intervention may be effective at strengthening vulnerable brain networks in asymptomatic adults at risk for developing dementia.

"Two sides of the same coin": constant motor learning speeds up, whereas variable motor learning stabilizes, speed-accuracy movements

PURPOSE

The aim of this study was to determine the time course of the trade-off between speed and accuracy, intraindividual variability, and movement transfer and retention (4 weeks after learning) of speed-accuracy tasks.

METHODS

The participants in this study were healthy adults randomly divided into three groups (control versus constant versus variable). They were aged 19-24 years, and 30 (15 men and 15 women) were in each group. Participants had to perform various tasks with the right dominant hand: (a) simple reaction test; (b) maximal velocity measurement; and (c) a speed-accuracy task.

RESULTS

During constant and variable learning, the trade-off in a speed-accuracy task in specific situations shifted toward improved motor planning and motor execution speed, and to reduced intraindividual variability. However, during variable learning, the maximal velocity and variability of motor planning time did not change. Constant learning effectively transferred into variable tasks in terms of reaction time, average velocity and maximal velocity, and these effects were greater than those associated with variable learning. However, the effects of constant learning did not transfer fully into the performance variability of variable movements. Variable learning effectively transferred into constant tasks for the coefficient of variation of the path of movement, average velocity, maximal velocity and reaction time. The retention effect depended neither on learning nor task specificity (constant versus variable tasks).

CONCLUSION

Constant learning speeds up but does not stabilize speed-accuracy movements in variable tasks; whereas, variable learning stabilizes but does not speed up speed-accuracy movements in constant tasks.

Surgeon-Centered Analysis of Robot-Assisted Needle Driving Under Different Force Feedback Conditions

Robotic assisted minimally invasive surgery (RAMIS) systems present many advantages to the surgeon and patient over open and standard laparoscopic surgery. However, haptic feedback, which is crucial for the success of many surgical procedures, is still an open challenge in RAMIS. Understanding the way that haptic feedback affects performance and learning can be useful in the development of haptic feedback algorithms and teleoperation control systems. In this study, we examined the performance and learning of inexperienced participants under different haptic feedback conditions in a task of surgical needle driving via a soft homogeneous deformable object-an artificial tissue. We designed an experimental setup to characterize their movement trajectories and the forces that they applied on the artificial tissue. Participants first performed the task in an open condition, with a standard surgical needle holder, followed by teleoperation in one of three feedback conditions: (1) no haptic feedback, (2) haptic feedback based on position exchange, and (3) haptic feedback based on direct recording from a force sensor, and then again with the open needle holder. To quantify the effect of different force feedback conditions on the quality of needle driving, we developed novel metrics that assess the kinematics of needle driving and the tissue interaction forces, and we combined our novel metrics with classical metrics. We analyzed the final teleoperated performance in each condition, the improvement during teleoperation, and the aftereffect of teleoperation on the performance when using the open needle driver. We found that there is no significant difference in the final performance and in the aftereffect between the 3 conditions. Only the two conditions with force feedback presented statistically significant improvement during teleoperation in several of the metrics, but when we compared directly between the improvements in the three different feedback conditions none of the effects reached statistical significance. We discuss possible explanations for the relative similarity in performance. We conclude that we developed several new metrics for the quality of surgical needle driving, but even with these detailed metrics, the advantage of state of the art force feedback methods to tasks that require interaction with homogeneous soft tissue is questionable.

Variability of running coordination in experts and novices: A 3D uncontrolled manifold analysis

The uncontrolled manifold (UCM) approach has been widely used in recent studies to examine variability in daily tasks; however, it has not yet been used to study running or the effects of expertise. Therefore, the aim of this study was to analyse the synergy structure stabilizing the centre of mass (CoM) trajectory in experts compared to novices during running at two different speeds using a subject-specific 3D model. A total of 25 healthy young adults (13 experts, 12 novices) participated in the study. All subjects ran at 10 and 15 km h^-1 on a treadmill. In each case, kinematics of 20 consecutive gait cycles were recorded and the effects of expertise and gait cycle phase on the synergy structure were investigated at both speeds. Specifically, the variance affecting the CoM ( U C M ⊥ ) , the variance not affecting the CoM ( U C M ∥ ) , and their ratio ( U C M R a t i o ) were analysed. Descriptively, in both groups there was a synergy stabilizing the CoM trajectory in running. However, the ANOVA showed no differences in U C M R a t i o between the two groups. In novices, U C M ⊥ and U C M ∥ were significantly higher compared to experts at the 15 km h^-1 condition. In both groups, there was more variability in the stance phase compared to the flight phase in the majority of cases. The results indicate that experts adopted a more consistent running style. The stride-to-stride variability was diminished but not abolished. This difference was only visible at the 15 km h^-1 condition. Furthermore, variability was less constrained in the stance phase compared to the flight phase.

Fast and specific: insights into the acquisition and generalization of motor acuity

Motor acuity is considered to be the outcome of prolonged practice and to involve morphological changes in the motor cortex. We have previously designed a curved pointing task, the arc pointing task (APT), to study motor acuity acquisition, defined as a change in the speed-accuracy tradeoff function (SAF) of the task. Here, we studied the generalization of motor acuity between hands and between tasks (drawing the arc in the opposite direction and with the untrained hand) and the effect of training duration on motor acuity. We report that training-induced motor acuity improvement did not generalize across hands and across tasks performed with the same hand, suggesting a task-specific representation of motor acuity. To our surprise, the largest gains in motor acuity, measured both by changes in SAF and by improvement in multiple kinematic variables, were seen following a short exposure to the task. Our results suggest that motor acuity training-induced improvement is task specific and that motor acuity starts to improve following a very short practice.NEW & NOTEWORTHY We report that training induced motor acuity improvement does not generalize from one hand to another or between movements that are performed with the same effector. Furthermore, significant improvements in acuity were found following a very short exposure to the task (∼20 trials). Therefore, our results suggest that the nervous system has the capacity to rapidly improve motor acuity.

Learning and transfer of complex motor skills in virtual reality: a perspective review

The development of more effective rehabilitative interventions requires a better understanding of how humans learn and transfer motor skills in real-world contexts. Presently, clinicians design interventions to promote skill learning by relying on evidence from experimental paradigms involving simple tasks, such as reaching for a target. While these tasks facilitate stringent hypothesis testing in laboratory settings, the results may not shed light on performance of more complex real-world skills. In this perspective, we argue that virtual environments (VEs) are flexible, novel platforms to evaluate learning and transfer of complex skills without sacrificing experimental control. Specifically, VEs use models of real-life tasks that afford controlled experimental manipulations to measure and guide behavior with a precision that exceeds the capabilities of physical environments. This paper reviews recent insights from VE paradigms on motor learning into two pressing challenges in rehabilitation research: 1) Which training strategies in VEs promote complex skill learning? and 2) How can transfer of learning from virtual to real environments be enhanced? Defining complex skills by having nested redundancies, we outline findings on the role of movement variability in complex skill acquisition and discuss how VEs can provide novel forms of guidance to enhance learning. We review the evidence for skill transfer from virtual to real environments in typically developing and neurologically-impaired populations with a view to understanding how differences in sensory-motor information may influence learning strategies. We provide actionable suggestions for practicing clinicians and outline broad areas where more research is required. Finally, we conclude that VEs present distinctive experimental platforms to understand complex skill learning that should enable transfer from therapeutic practice to the real world.

Adaptive Regulation of Motor Variability

Trial-to-trial movement variability can both drive motor learning and interfere with expert performance, suggesting benefits of regulating it in context-specific ways. Here we address whether and how the brain regulates motor variability as a function of performance by training rats to execute ballistic forelimb movements for reward. Behavioral datasets comprising millions of trials revealed that motor variability is regulated by two distinct processes. A fast process modulates variability as a function of recent trial outcomes, increasing it when performance is poor and vice versa. A slower process tunes the gain of the fast process based on the uncertainty in the task's reward landscape. Simulations demonstrated that this regulation strategy optimizes reward accumulation over a wide range of time horizons, while also promoting learning. Our results uncover a sophisticated algorithm implemented by the brain to adaptively regulate motor variability to improve task performance. VIDEO ABSTRACT.

Less noise during dual-task walking in healthy young adults: an analysis of different gait variability components

Dual-task costs of gait (variability) parameters are frequently used to probe the grade of automaticity of walking. However, recent studies reported contradicting dual-task costs for different gait variability measures within the same cohorts. The effects of a dual-task on the gait pattern are, thus, not fully understood. The aim of the current study was to analyze the different gait variability components ('Tolerance', 'Noise', and 'Covariation') during dual-task walking compared to single-task walking. In an experimental study, 21 young and healthy adults (11 males, 10 females, age: 24 ± 3 years) were included. The participants completed three experimental conditions: (a) single-task walking, (b) dual-task walking (serial-seven subtractions), and (c) cognitive single task in sitting position. To analyze different gait variability components, we applied a method which distinguishes the three components: 'Tolerance', 'Noise', and 'Covariation' (TNC). To test for differences, we used the statistical parametric mapping method. Compared to single-task walking, the results depict lower gait variability of the result parameters during the dual-task condition at 0-15% (p = 0.010) and 94-100% (p = 0.040) of the stance phase and 0-63% (p < 0.001) during the swing phase. The decreased result parameter variability was due to less (sensorimotor) 'Noise' (stance: 2-100%, p < 0.001; swing: 2-59%, p < 0.001) during the dual-task walking condition. In further studies, the sources of the reduced unstructured (sensorimotor) noise in the dual-task condition should be analyzed to better understand the effect of a cognitive dual task on the gait pattern.

A whole body characterization of individual strategies, gender differences, and common styles in overarm throwing

Overarm throwing is a fundamental human skill. Since paleolithic hunter-gatherer societies, the ability of throwing played a key role in brain and body co-evolution. For decades, throwing skill acquisition has been the subject of developmental and gender studies. However, due to its complex multijoint nature, whole body throwing has found little space in quantitative studies of motor behavior. In this study we examined how overarm throwing varies within and between individuals in a sample of untrained adults. To quantitatively compare whole body kinematics across throwing actions, we introduced a new combination of spatiotemporal principal component, linear discrimination, and clustering analyses. We found that the identity and gender of a thrower can be robustly inferred by the kinematics of a single throw, reflecting the characteristic features in individual throwing strategies and providing a quantitative ground for the well-known differences between males and females in throwing behavior. We also identified four main classes of throwing strategies, stable within individuals and resembling the main stages of throwing proficiency acquisition during motor development. These results support earlier proposals linking interindividual and gender differences in throwing, with skill acquisition interrupted at different stages of the typical developmental trajectory of throwing motor behavior.NEW & NOTEWORTHY Unconstrained throwing, because of its complexity, received little attention in quantitative motor control studies. By introducing a new approach to analyze whole body kinematics, we quantitatively characterized gender effects, interindividual differences, and common patterns in nontrained throwers. The four throwing styles identified across individuals resemble different stages in the acquisition of throwing skills during development. These results advance our understanding of complex motor skills, bridging the gap between motor control, motor development, and sport science.

Variability of upper body kinematics in a highly constrained task - sprint swimming

Before examining the effect of changing constraints on skill adaptation, it is useful to know the tolerable variability of a movement pattern for optimal performance. Tolerable variability may vary throughout the period of task performance as some parts of the movement pattern may be more important than others. The purpose of this study was to quantify the inter-trial variability of performance variables, and hand path as the task-relevant parameter, of skilled front crawl swimmers during 25 m sprints. It was hypothesised that the wrist paths would have smaller inter-trial variability during the below water phase than during the above water phase. Twelve skilled swimmers performed four 25 m front crawl sprints which were recorded by six phased locked video cameras for three-dimensional analysis. Standard deviations and time series repeatability (R ²) of the right and left wrist displacement were determined. On average, swimmers varied their sprint speed between trials by <1.5%. The spatio-temporal patterns of wrist paths varied by <3 cm in all directions (horizontal, vertical & lateral). There was no significant difference in inter-trial variability between above and below water phases. Swimmers increased wrist path consistency at the critical events of water entry in the horizontal and lateral directions and at exit for the horizontal direction. This study established levels of variability in spatio-temporal movement patterns of the paths of the wrist in sprint swimming and provided evidence that swimmers minimise variability for key events, in this case, the position of the wrists at water entry and exit.