title: Reward feedback accelerates motor learning.
abstract: Recent findings have demonstrated that reward feedback alone can drive motor learning. However, it is not yet clear whether reward feedback alone can lead to learning when a perturbation is introduced abruptly, or how a reward gradient can modulate learning. In this study, we provide reward feedback that decays continuously with increasing error. We asked whether it is possible to learn an abrupt visuomotor rotation by reward alone, and if the learning process could be modulated by combining reward and sensory feedback and/or by using different reward landscapes. We designed a novel visuomotor learning protocol during which subjects experienced an abruptly introduced rotational perturbation. Subjects received either visual feedback or reward feedback, or a combination of the two. Two different reward landscapes, where the reward decayed either linearly or cubically with distance from the target, were tested. Results demonstrate that it is possible to learn from reward feedback alone and that the combination of reward and sensory feedback accelerates learning. An analysis of the underlying mechanisms reveals that although reward feedback alone does not allow for sensorimotor remapping, it can nonetheless lead to broad generalization, highlighting a dissociation between remapping and generalization. Also, the combination of reward and sensory feedback accelerates learning without compromising sensorimotor remapping. These findings suggest that the use of reward feedback is a promising approach to either supplement or substitute sensory feedback in the development of improved neurorehabilitation techniques. More generally, they point to an important role played by reward in the motor learning process.
authors.affiliation: Department of Integrative Physiology, University of Colorado Boulder, Boulder, Colorado.
authors.forename: Ali A
authors.initials: AA
authors.lastname: Nikooyan
authors.affiliation: Department of Integrative Physiology, University of Colorado Boulder, Boulder, Colorado alaa@colorado.edu.
authors.forename: Alaa A
authors.initials: AA
authors.lastname: Ahmed
mesh_terms: D001132:Arm; D030141:Feedback, Psychological; D056228:Feedback, Sensory; D005793:Generalization, Psychological; D006801:Humans; D007858:Learning; D016014:Linear Models; D008959:Models, Neurological; D011597:Psychomotor Performance; D012201:Reward; D012399:Rotation; D014796:Visual Perception
keywords: decision-making; dopaminergic; reinforcement learning; sensorimotor mapping; temporal-difference model