Abstract

The neurobehavioral mechanisms of human motor-control and learning evolved in free behaving, real-life settings, yet this is studied mostly in reductionistic lab-based experiments. Here we take a step towards a more real-world motor neuroscience using wearables for naturalistic full-body motion-tracking and the sports of pool billiards to frame a real-world skill learning experiment. First, we asked if well-known features of motor learning in lab-based experiments generalize to a real-world task. We found similarities in many features such as multiple learning rates, and the relationship between task-related variability and motor learning. Our data-driven approach reveals the structure and complexity of movement, variability, and motor learning, enabling an in-depth understanding of the structure of motor learning in three ways: First, while expecting most of the movement learning is done by the cue-wielding arm, we find that motor learning affects the whole body, changing motor-control from head to toe. Second, during learning, all subjects decreased their movement variability and their variability in the outcome. Subjects who were initially more variable were also more variable after learning. Lastly, when screening the link across subjects between initial variability in individual joints and learning, we found that only the initial variability in the right forearm supination shows a significant correlation to the subjects’ learning rates. This is in-line with the relationship between learning and variability: while learning leads to an overall reduction in movement variability, only initial variability in specific task-relevant dimensions can facilitate faster learning.

Highlights

  • The neurobehavioral mechanisms of human motor-control and learning evolved in free behaving, real-life settings, yet this is studied mostly in reductionistic lab-based experiments

  • While laboratory-tasks play an important role in our understanding of sensorimotor control and learning, they address a very restricted range of behaviours that do not capture the full complexity of real-world motor control and may overlook fundamental principles of motor control and learning in real-life[14,15]

  • Neurobehavioral mechanisms are subject to evolutionary selection pressures and survive only if they are relevant in natural tasks

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Summary

Introduction

The neurobehavioral mechanisms of human motor-control and learning evolved in free behaving, real-life settings, yet this is studied mostly in reductionistic lab-based experiments. Others moved away from the computer screen but were still highly constrained; e.g. throwing a frisbee while the subject’s trunk is strapped to the chair to prevent trunk ­movement[23] Another line of inquiry used free-behaviour in real-world tasks such as tool-making or ­juggling[17,24,25,26,27]. Subjects had to do a pool shot to put the ball in the pocket using unconstrained full-body, self-paced movement, with as many preparatory movements as the subject needs for each shoot, the only constraints arose from the placement of the white cue ball which the subjects shoot with the cue stick and the red target ball (that needs to go into the pocket) We implemented this as a real-world experiment, effectively only adding sensors to the subject and the pool table, i.e. subjects use the normal pool cue, balls, and pool table they would in a leisure setting and carry out natural motor commands, receive the natural somatosensory feedback and experience the same satisfaction (rewards) when they put the ball in the pocket as this is a real-world task. The skill of subjects in putting the ball into the pocket is learnable in the time course of 1–2 h, allowing us to record and analyse the experiments as one session

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