Proprioceptive recalibration following implicit visuomotor adaptation is preserved in Parkinson's disease

Slower rates of prism adaptation but intact aftereffects in patients with early to mid-stage Parkinson's disease

There is currently mixed evidence on the effect of Parkinson's disease on motor adaptation. Some studies report that patients display adaptation comparable to age-matched controls, while others report a complete inability to adapt to novel sensory perturbations. Here, early to mid-stage Parkinson's patients were recruited to perform a prism adaptation task. When compared to controls, patients showed slower rates of initial adaptation but intact aftereffects. These results support the suggestion that patients with early to mid-stage Parkinson's disease display intact adaptation driven by sensory prediction errors, as shown by the intact aftereffect. But impaired facilitation of performance through cognitive strategies informed by task error, as shown by the impaired initial adaptation. These results support recent studies that suggest that patients with Parkinson's disease retain the ability to perform visuomotor adaptation, but display altered use of cognitive strategies to aid performance and generalises these previous findings to the classical prism adaptation task.

A Serious Game for the Assessment of Visuomotor Adaptation Capabilities during Locomotion Tasks Employing an Embodied Avatar in Virtual Reality

The study of visuomotor adaptation (VMA) capabilities has been encompassed in various experimental protocols aimed at investigating human motor control strategies and/or cognitive functions. VMA-oriented frameworks can have clinical applications, primarily in the investigation and assessment of neuromotor impairments caused by conditions such as Parkinson's disease or post-stroke, which affect the lives of tens of thousands of people worldwide. Therefore, they can enhance the understanding of the specific mechanisms of such neuromotor disorders, thus being a potential biomarker for recovery, with the aim of being integrated with conventional rehabilitative programs. Virtual Reality (VR) can be entailed in a framework targeting VMA since it allows the development of visual perturbations in a more customizable and realistic way. Moreover, as has been demonstrated in previous works, a serious game (SG) can further increase engagement thanks to the use of full-body embodied avatars. Most studies implementing VMA frameworks have focused on upper limb tasks and have utilized a cursor as visual feedback for the user. Hence, there is a paucity in the literature about VMA-oriented frameworks targeting locomotion tasks. In this article, the authors present the design, development, and testing of an SG-based framework that addresses VMA in a locomotion activity by controlling a full-body moving avatar in a custom VR environment. This workflow includes a set of metrics to quantitatively assess the participants' performance. Thirteen healthy children were recruited to evaluate the framework. Several quantitative comparisons and analyses were run to validate the different types of introduced visuomotor perturbations and to evaluate the ability of the proposed metrics to describe the difficulty caused by such perturbations. During the experimental sessions, it emerged that the system is safe, easy to use, and practical in a clinical setting. Despite the limited sample size, which represents the main limitation of the study and can be compensated for with future recruitment, the authors claim the potential of this framework as a useful instrument for quantitatively assessing either motor or cognitive impairments. The proposed feature-based approach gives several objective parameters as additional biomarkers that can integrate the conventional clinical scores. Future studies might investigate the relation between the proposed biomarkers and the clinical scores for specific disorders such as Parkinson's disease and cerebral palsy.

Implicit sensorimotor adaptation is preserved in Parkinson's disease

Our ability to enact successful goal-directed actions involves multiple learning processes. Among these processes, implicit motor adaptation ensures that the sensorimotor system remains finely tuned in response to changes in the body and environment. Whether Parkinson's disease impacts implicit motor adaptation remains a contentious area of research: whereas multiple reports show impaired performance in this population, many others show intact performance. While there is a range of methodological differences across studies, one critical issue is that performance in many of the studies may reflect a combination of implicit adaptation and strategic re-aiming. Here, we revisited this controversy using a visuomotor task designed to isolate implicit adaptation. In two experiments, we found that adaptation in response to a wide range of visual perturbations was similar in Parkinson's disease and matched control participants. Moreover, in a meta-analysis of previously published and unpublished work, we found that the mean effect size contrasting Parkinson's disease and controls across 16 experiments involving over 200 participants was not significant. Together, these analyses indicate that implicit adaptation is preserved in Parkinson's disease, offering a fresh perspective on the role of the basal ganglia in sensorimotor learning.

Improved proprioception does not benefit visuomotor adaptation

Visuomotor adaptation arises when reaching in an altered visual environment, where one's seen hand position does not match their felt (i.e., proprioceptive) hand position in space. Here, we asked if proprioceptive training benefits visuomotor adaptation, and if these benefits arise due to implicit (unconscious) or explicit (conscious strategy) processes. Seventy-two participants were divided equally into 3 groups: proprioceptive training with feedback (PTWF), proprioceptive training no feedback (PTNF), and Control (CTRL). The PTWF and PTNF groups completed passive proprioceptive training, where a participant's hand was moved to an unknown reference location and they judged the felt position of their unseen hand relative to their body midline on every trial. The PTWF group received verbal feedback with respect to their response accuracy on the middle 60% of trials, whereas the PTNF did not receive any feedback during training. The CTRL group did not complete proprioceptive training and instead sat quietly during this time. Following proprioceptive training or time delay, all three groups reached when seeing a cursor that was rotated 30° clockwise relative to their hand motion. The experiment ended with participants completing a series of no-cursor reaches to assess implicit and explicit adaptation. Results indicated that the PTWF group improved the accuracy of their sense of felt hand position following proprioceptive training. However, this improved proprioceptive acuity (i.e., the accuracy of their sense of felt hand) did not benefit visuomotor adaptation, as all three groups showed similar visuomotor adaptation across rotated reach training trials. Visuomotor adaptation arose implicitly, with minimal explicit contribution for all three groups. Together, these results suggest that passive proprioceptive training does not benefit, nor hinder, the extent of implicit visuomotor adaptation established immediately following reach training with a 30° cursor rotation.

Mechanisms of Human Motor Learning Do Not Function Independently

Human motor learning is governed by a suite of interacting mechanisms each one of which modifies behavior in distinct ways and rely on different neural circuits. In recent years, much attention has been given to one type of motor learning, called motor adaptation. Here, the field has generally focused on the interactions of three mechanisms: sensory prediction error SPE-driven, explicit (strategy-based), and reinforcement learning. Studies of these mechanisms have largely treated them as modular, aiming to model how the outputs of each are combined in the production of overt behavior. However, when examined closely the results of some studies also suggest the existence of additional interactions between the sub-components of each learning mechanism. In this perspective, we propose that these sub-component interactions represent a critical means through which different motor learning mechanisms are combined to produce movement; understanding such interactions is critical to advancing our knowledge of how humans learn new behaviors. We review current literature studying interactions between SPE-driven, explicit, and reinforcement mechanisms of motor learning. We then present evidence of sub-component interactions between SPE-driven and reinforcement learning as well as between SPE-driven and explicit learning from studies of people with cerebellar degeneration. Finally, we discuss the implications of interactions between learning mechanism sub-components for future research in human motor learning.

Understanding implicit sensorimotor adaptation as a process of proprioceptive re-alignment

Multiple learning processes contribute to successful goal-directed actions in the face of changing physiological states, biomechanical constraints, and environmental contexts. Amongst these processes, implicit sensorimotor adaptation is of primary importance, ensuring that movements remain well-calibrated and accurate. A large body of work on reaching movements has emphasized how adaptation centers on an iterative process designed to minimize visual errors. The role of proprioception has been largely neglected, thought to play a passive role in which proprioception is affected by the visual error but does not directly contribute to adaptation. Here, we present an alternative to this visuo-centric framework, outlining a model in which implicit adaptation acts to minimize a proprioceptive error, the distance between the perceived hand position and its intended goal. This proprioceptive re-alignment model (PReMo) is consistent with many phenomena that have previously been interpreted in terms of learning from visual errors, and offers a parsimonious account of numerous unexplained phenomena. Cognizant that the evidence for PReMo rests on correlational studies, we highlight core predictions to be tested in future experiments, as well as note potential challenges for a proprioceptive-based perspective on implicit adaptation.

Novelty exposure induces stronger sensorimotor representations during a manual adaptation task

Active exploration of novel spatial environments enhances memory for subsequently presented explicit, declarative information in humans. These effects have been attributed to novelty promoting dopamine release via mesolimbic dopaminergic pathways in the brain. As procedural motor learning has been linked to dopamine as well, we predict that novelty effects extend to this domain. To test this hypothesis, the present study examined whether spatial novelty exploration benefits subsequent sensorimotor adaptation. Participants explored either two different virtual environments (i.e., novelty condition; n = 210) or two identical environments (i.e., familiar condition; n = 253). They then performed a manual adaptation task in which they had to adapt joystick movements to a visual perturbation. We assessed the rate of adaptation following the introduction of this perturbation, and the rate of deadaptation following its removal. While results showed reliable adaptation patterns and similar adaptation rates across both conditions, individuals in the novelty condition showed slower deadaptation. This suggests that exposure to spatial novelty induced stronger sensorimotor representations during adaptation, potentially through novelty-induced dopaminergic effects in mesocortical and/or nigrostriatal pathways. Novelty exposure may be employed to promote motor learning on tasks that require precision movements in altered sensory contexts, for example, in astronauts moving in microgravity or patients with impaired motor processing.