Kinematic signatures of learning that emerge in a real-world motor skill task

Abstract

The neurobehavioral mechanisms of human motor-control and learning evolved in free behaving, real-life settings, yet to date is studied in simplified lab-based settings. We demonstrate the feasibility of real-world neuroscience, using wearables for naturalistic full-body motion-tracking and mobile brain-imaging, to study motor-learning in billiards. We highlight the similarities between motor-learning in-the-wild and classic toy-tasks in well-known features, such as multiple learning rates, and the relationship between task-related variability and motor learning. Studying in-the-wild learning enable looking at global observables of motor learning, as well as relating learning to mechanisms deduced from reductionist models. The analysis of the velocity profiles of all joints enabled in depth understanding of the structure of learning across the body. First, while most of the movement was done by the right arm, the entire body learned the task, as evident by the decrease in both inter- and intra-trial variabilities of various joints across the body over learning. Second, while over learning all subjects decreased their movement variability and the variability in the outcome (ball direction), subjects who were initially more variable were also more variable after learning, supporting the notion that movement variability is an individual trait. Lastly, when exploring the link between variability and learning over joints we found that only the variability in the right elbow supination shows significant correlation to learning. This demonstrates the relation between learning and variability: while learning leads to overall reduction in movement variability, only initial variability in specific task relevant dimensions can facilitate faster learning.