Acquisition of Novel and Complex Motor Skills: Stable Solutions Where Intrinsic Noise Matters Less

Abstract

Most experimental paradigms in motor neuroscience have used relatively focal and experimentally constrained tasks to allow precise measurement and experimental control. Therefore, practice-induced improvements and learning have been confined to relatively simple changes or adaptations to external perturbations. Here, we propose an approach to study more complex skills that are novel and require more extensive practice, leading to quantitative and qualitative changes in overt performance. Central to these skills is that they have extrinsic redundancy that allows exploration and exploitation of dynamic properties of the task. We hypothesize that in such skills, humans seek stable solutions that are robust to perturbations that make their intrinsic noise matter less. Three experimental paradigms exemplify our model-based and hypothesis-driven approach to skill acquisition: discrete throwing, rhythmic ball bouncing, and complex object manipulation. In skittles, a throwing skill, results show that actors are sensitive to the error tolerance afforded by the task. In ball bouncing, we show that subjects exploit the dynamic stability of the task, where small errors and noise self-stabilize without explicit corrections. In manipulating a “cup of coffee,” subjects learn to optimize the safety or energy margins and scale it to their intrinsic variability. This research presents new experimental paradigms that characterize the behavioral correlates of neuroplasticity in more complex skill acquisition. This fundamental work is a platform for future work to develop behavioral interventions for clinical applications.