The gradient of the reinforcement landscape influences sensorimotor learning

PLoS Comput Biol. 2019 Mar 4;15(3):e1006839. doi: 10.1371/journal.pcbi.1006839. eCollection 2019 Mar.


Consideration of previous successes and failures is essential to mastering a motor skill. Much of what we know about how humans and animals learn from such reinforcement feedback comes from experiments that involve sampling from a small number of discrete actions. Yet, it is less understood how we learn through reinforcement feedback when sampling from a continuous set of possible actions. Navigating a continuous set of possible actions likely requires using gradient information to maximize success. Here we addressed how humans adapt the aim of their hand when experiencing reinforcement feedback that was associated with a continuous set of possible actions. Specifically, we manipulated the change in the probability of reward given a change in motor action-the reinforcement gradient-to study its influence on learning. We found that participants learned faster when exposed to a steep gradient compared to a shallow gradient. Further, when initially positioned between a steep and a shallow gradient that rose in opposite directions, participants were more likely to ascend the steep gradient. We introduce a model that captures our results and several features of motor learning. Taken together, our work suggests that the sensorimotor system relies on temporally recent and spatially local gradient information to drive learning.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Hand / physiology
  • Humans
  • Learning*
  • Motor Skills*
  • Probability
  • Reinforcement, Psychology*
  • Task Performance and Analysis

Grants and funding

This work was funded through the Natural Sciences and Engineering Research Council of Canada (RGPIN 238338, awarded to PLG. This work was funded through the Canadian Institute of Health Research (PJT-153447, awarded to PLG. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.