Generating New Musical Preferences From Multilevel Mapping of Predictions to Reward
通过创建全新音阶的旋律，研究揭示预测编码如何使新音乐变得令人愉悦，涉及行为实验和脑成像，对理解音乐偏好形成机制有贡献。
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 = 1,185), adult 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 U.S. and Chinese participants. Furthermore, functional MRI 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.