Generating New Musical Preferences from Hierarchical Mapping of Predictions to Reward

Abstract

Much of what we know and love about music hinges on our ability to make successful predictions, which appears to be an intrinsically rewarding process. Yet the exact process by which learned predictions become pleasurable is unclear. Here, we created novel melodies in an alternative scale different from any established musical culture, to show how musical preference is generated de novo. Across nine studies (n=1185), participants learned to like more frequently-presented items that adhered to this rapidly-learned structure, suggesting that exposure and prediction errors both affected self-report liking ratings. Learning trajectories varied by music reward sensitivity, but were similar for USA and Chinese participants. Furthermore, fMRI activity in auditory areas reflected prediction errors whereas functional connectivity between auditory and medial prefrontal regions reflected both exposure and prediction errors. Collectively, results support predictive coding as a cognitive mechanism by which new musical sounds become rewarding.