Predictability and the pleasure of music

Mas-Herrero et al. do an interesting study on how predictive processes shape individual musical preferences .

Significance

Using a novel decision-making task, we show that musical pleasure relies on a delicate balance between predictability and uncertainty, consistent with learning theories. In simple terms, music that is not overly expected nor too chaotic is most enjoyable—but the ideal mix of predictability depends on how much the melody keeps you guessing. Very predictable tunes can be delightful with small twists, while a melody full of surprises may need bigger unexpected moments to hit the sweet spot. Computational models incorporating this balance accurately predicted the types of music people like and the pleasure they derive from real compositions. These results reveal fundamental mechanisms driving musical pleasure and offer valuable insights for the music industry and music-based therapies.

Abstract

Current models suggest that musical pleasure is tied to the intrinsic reward of learning, as it relies on predictive processes that challenge our minds. According to predictive coding, optimal learning, which maximizes epistemic value, depends on balancing predictability and uncertainty, implying that musical pleasure should also reflect this equilibrium. We tested this idea in two independent large samples using a novel decision-making paradigm, where participants indicated preferences for melodies varying in surprise and entropy. Consistent with prior research, we found an inverted U-shaped relationship between predictability and preference. Moreover, our results revealed an interaction between predictability and entropy, with smaller surprises preferred in low-entropy melodies and larger surprises favored in high-entropy music, consistent with predictive coding principles. Computational models incorporating this interaction predicted individuals’ genre preferences and pleasure responses to real compositions, highlighting its applicability to real-world music experiences. These findings advance our understanding of the cognitive mechanisms driving music preferences and the role of predictive processes in affective responses.