Human Motor Skill Learning Research Articles

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.

A preliminary examination of the contextual interference effect on trained trick retention in domestic dogs.

This study sought to enhance current dog training practices by determining whether a finding from human motor skill learning research, the contextual interference (CI) effect, could be replicated in a trick-training paradigm with companion dogs. In humans, research shows that practicing skills in random order, as compared with blocked order, improves learning of those skills. To test this question in dogs, we randomly allocated 17 dogs to blocked training (low CI) or random training (high CI). The dogs performed three behaviors of varying difficulty. After training, we conducted a retention test in which half of the dogs in each group performed the tasks in blocked order and the other half in random order. We scored each trick, measured duration, and measured whether dogs required one or two tries to perform a behavior. We found no significant differences between dogs who practiced three tricks in random or in blocked order during training and during a retention test. This study is the first to apply the CI effect to dog trick training. Although no evidence of the CI effect was found, the current research provides a preliminary framework for future studies with potential implications for increasing retention of trained skills.

Mechanisms of offline motor learning at a microscale of seconds in large-scale crowdsourced data

Performance improvements during early human motor skill learning are suggested to be driven by short periods of rest during practice, at the scale of seconds. To reveal the unknown mechanisms behind these “micro-offline” gains, we leveraged the sampling power offered by online crowdsourcing (cumulative N over all experiments = 951). First, we replicated the original in-lab findings, demonstrating generalizability to subjects learning the task in their daily living environment (N = 389). Second, we show that offline improvements during rest are equivalent when significantly shortening practice period duration, thus confirming that they are not a result of recovery from performance fatigue (N = 118). Third, retroactive interference immediately after each practice period reduced the learning rate relative to interference after passage of time (N = 373), indicating stabilization of the motor memory at a microscale of several seconds. Finally, we show that random termination of practice periods did not impact offline gains, ruling out a contribution of predictive motor slowing (N = 71). Altogether, these results demonstrate that micro-offline gains indicate rapid, within-seconds consolidation accounting for early skill learning.

Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control.

Human motor skill learning is driven by the necessity to adapt to new situations. While supportive contacts are essential for many tasks, little is known about their impact on motor learning. To study the effect of contacts an innovative full-body experimental paradigm was established. The task of the subjects was to reach for a distant target while postural stability could only be maintained by establishing an additional supportive hand contact. To examine adaptation, non-trivial postural perturbations of the subjects’ support base were systematically introduced. A novel probabilistic trajectory model approach was employed to analyze the correlation between the motions of both arms and the trunk. We found that subjects adapted to the perturbations by establishing target dependent hand contacts. Moreover, we found that the trunk motion adapted significantly faster than the motion of the arms. However, the most striking finding was that observations of the initial phase of the left arm or trunk motion (100–400 ms) were sufficient to faithfully predict the complete movement of the right arm. Overall, our results suggest that the goal-directed arm movements determine the supportive arm motions and that the motion of heavy body parts adapts faster than the light arms.

Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems

A salient feature of human motor skill learning is the ability to exploit similarities across related tasks. In biological motor control, it has been hypothesized that muscle synergies, coherent activations of groups of muscles, allow for exploiting shared knowledge. Recent studies have shown that a rich set of complex motor skills can be generated by a combination of a small number of muscle synergies. In robotics, dynamic movement primitives are commonly used for motor skill learning. This machine learning approach implements a stable attractor system that facilitates learning and it can be used in high-dimensional continuous spaces. However, it does not allow for reusing shared knowledge, i.e., for each task an individual set of parameters has to be learned. We propose a novel movement primitive representation that employs parametrized basis functions, which combines the benefits of muscle synergies and dynamic movement primitives. For each task a superposition of synergies modulates a stable attractor system. This approach leads to a compact representation of multiple motor skills and at the same time enables efficient learning in high-dimensional continuous systems. The movement representation supports discrete and rhythmic movements and in particular includes the dynamic movement primitive approach as a special case. We demonstrate the feasibility of the movement representation in three multi-task learning simulated scenarios. First, the characteristics of the proposed representation are illustrated in a point-mass task. Second, in complex humanoid walking experiments, multiple walking patterns with different step heights are learned robustly and efficiently. Finally, in a multi-directional reaching task simulated with a musculoskeletal model of the human arm, we show how the proposed movement primitives can be used to learn appropriate muscle excitation patterns and to generalize effectively to new reaching skills.

Reward Improves Long-Term Retention of a Motor Memory through Induction of Offline Memory Gains

In humans, training in which good performance is rewarded or bad performance punished results in transient behavioral improvements. The relative effects of reward and punishment on consolidation and long-term retention, critical behavioral stages for successful learning, are not known. Here, we investigated the effects of reward and punishment on these different stages of human motor skill learning. We studied healthy subjects who trained on a motor task under rewarded, punished, or neutral control conditions. Performance was tested before and immediately, 6 hr, 24 hr, and 30 days after training in the absence of reward or punishment. Performance improvements immediately after training were comparable in the three groups. At 6 hr, the rewarded group maintained performance gains, whereas the other two groups experienced significant forgetting. At 24 hr, the reward group showed significant offline (posttraining) improvements, whereas the other two groups did not. At 30 days, the rewarded group retained the gains identified at 24 hr, whereas the other two groups experienced significant forgetting. We conclude that training under rewarded conditions is more effective than training under punished or neutral conditions in eliciting lasting motor learning, an advantage driven by offline memory gains that persist over time.

Developmental contributions to human motor skill learning

Event Abstract Back to Event Developmental contributions to human motor skill learning Virginia Penhune1* 1 Department of Psychology, Concordia University, Canada Motor skills are ubiquitous in everyday life. While certain skills, such as walking, are largely innate, most, such as writing and playing the piano, are acquired through practice. In the past decade, numerous studies have investigated the behavioural and neural underpinnings of motor skill learning in adults; however, very little is known about how children acquire new motor skills. Recent evidence from paediatric structural neuroimaging research shows on-going changes in brain systems important for motor learning. Thus, maturational changes in the brain coincide with and likely underlie changes in motor abilities across development. This talk will consider two types of developmental contributions to skill learning. First, I will discuss recent work examining developmental changes in the ability to learn motor skills in school-age children. Overall, results showed a developmental progression in motor sequence learning within and across days of practice. Second, I will review a series of experiments examining the effect of early musical training (before age seven) on motor learning and performance later in life. The results of these experiments show that early-trained musicians show better sensorimotor synchronization than late-trained musicians matched for years of experience. Taken together, these studies suggest that there may be a sensitive period for motor learning in childhood, similar to that for language learning. Conference: Tuning the Brain for Music, Helsinki, Finland, 5 Feb - 6 Feb, 2009. Presentation Type: Oral Presentation Topic: Key Note Talks Citation: Penhune V (2009). Developmental contributions to human motor skill learning. Conference Abstract: Tuning the Brain for Music. doi: 10.3389/conf.neuro.09.2009.02.001 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 23 Jan 2009; Published Online: 23 Jan 2009. * Correspondence: Virginia Penhune, Department of Psychology, Concordia University, Québec, Canada, University.penhunelab@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Virginia Penhune Google Virginia Penhune Google Scholar Virginia Penhune PubMed Virginia Penhune Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Festina lente: evidences for fast and slow learning processes and a role for sleep in human motor skill learning.

Festina lente: evidences for fast and slow learning processes and a role for sleep in human motor skill learning.