Multiple processes independently predict motor learning

Abstract

Background Our ability to acquire, refine and adapt skilled limb movements is a hallmark of human motor learning that allows us to successfully perform many daily activities. The capacity to acquire, refine and adapt other features of motor performance, such as visual search, eye-hand coordination and visuomotor decisions, may also contribute to motor learning. However, the extent to which refinements of multiple behavioral features and their underlying neural processes independently contribute to motor learning remains unknown. In the current study, we used an ethological approach to test the hypothesis that practice-related refinements of multiple behavioral features would be independently predictive of motor learning. Methods Eighteen healthy, young adults used an upper-limb robot with eye-tracking to practice six trials of a continuous, visuomotor task once a week for six consecutive weeks. Participants used virtual paddles to hit away 200 “Targets” and avoid hitting 100 “Distractors” that continuously moved towards them from the back of the workspace. Motor learning was inferred from trial-by-trial acquisition and week-by-week retention of improvements on two measures of task performance related to motor execution and motor inhibition. Adaptations involving underlying neural processes were inferred from trial-by-trial acquisition and week-by-week retention of refinements on measures of skilled limb movement, visual search, eye-hand coordination and visuomotor decisions. We tested our hypothesis by quantifying the extent to which refinements on measures of multiple behavioral features (predictors) were independently predictive of improvements on our two measures of task performance (outcomes) after removing all shared variance between predictors. Results We found that refinements on measures of skilled limb movement, visual search and eye-hand coordination were independently predictive of improvements on our measure of task performance related to motor execution. In contrast, only refinements of eye-hand coordination were independently predictive of improvements on our measure of task performance related to motor inhibition. Conclusion Our results provide indirect evidence that refinements involving multiple, neural processes may independently contribute to motor learning, and distinct neural processes may underlie improvements in task performance related to motor execution and motor inhibition. This also suggests that refinements involving multiple, neural processes may contribute to motor recovery after stroke, and rehabilitation interventions should be designed to produce refinements of all behavioral features that may contribute to motor recovery.

Don’t watch your step: gaze behavior adapts with practice of a target stepping task

“…Therefore, they could shift their overall average fixation distance despite not changing their fixation timing by changing where they directed their fixations in the middle of swing phase, though they would still make a final confirmatory fixation back at their foot to confirm accurate foot placement. It may be that participants became more efficient confirming where their foot is in space or they became more proficient at using peripheral vision to guide target stepping (as seen during reaching by Perry et al 2020). Either change would allow participants to look farther ahead without reducing their ability to perform a feedback-driven motor control strategy.…”

“…The primary limitation is that while the present study measured where individuals look, it did not quantify any cognitive processing being done with that information. While it is likely that processing follows foveal vision, this is not a requirement (Perry et al 2020) . Stepping behavior is often relatively automatic and therefore gaze may be directed for other purposes (such as looking at someone while you talk to them).…”

Motor learning alters vision, but vision does not alter motor learning

“…The correlational relationship between visual information and motor control strategies is well documented in a variety of motor learning tasks. Whether people are controlling a cursor on a computer (Sailer et al 2005), playing video games (Vickers et al 2010), reaching for a target (Perry et al 2020), or stepping on (Cates and Gordon 2022) or avoiding (Kopiske et al 2021) targets on the ground, a progression from fixating on the object being manipulated to fixating on the target is characteristic of motor learning. This gaze shift also occurs whether the task consists of intermittent targets (Sailer et al 2005, Kopiske et al 2021 or a continuous stream of targets for the individual to navigate (Vickers et al 2010, Perry et al 2020, Cates and Gordon 2022 suggesting neither the type of motor task nor muscle groups used affect the relationship.…”

“…Whether people are controlling a cursor on a computer (Sailer et al 2005), playing video games (Vickers et al 2010), reaching for a target (Perry et al 2020), or stepping on (Cates and Gordon 2022) or avoiding (Kopiske et al 2021) targets on the ground, a progression from fixating on the object being manipulated to fixating on the target is characteristic of motor learning. This gaze shift also occurs whether the task consists of intermittent targets (Sailer et al 2005, Kopiske et al 2021 or a continuous stream of targets for the individual to navigate (Vickers et al 2010, Perry et al 2020, Cates and Gordon 2022 suggesting neither the type of motor task nor muscle groups used affect the relationship. For the motor control strategy to change, previous literature generally assumes that first a person's motor performance changes, then their visual behavior changes to support the new motor control strategy (Figure 1 Research on visual occlusion during motor learning suggests that visual sampling strategies may need to change before motor performance can improve.…”