Spatial patterns as a model to understand musical pleasure
A large body of research from different disciplines (philosophy, musicology, neuroscience) suggests that much of music’s power comes from its ability to generate expectations, particularly when those expectations are violated. Under this context, a very appealing hypothesis is that music-induced pleasure results from an intrinsic reward for learning, representing an epistemic pursuit akin to curiosity. Consistent with this idea, several studies have shown that an intermediate amount of music predictability – which optimizes learning – maximizes musical pleasure. Entirely predictable music is unpleasant because it prevents learning as it provides no new information, but music that is too random is also unpleasant because it hinders learning as it is hard to interpret. However, previous studies are purely correlational. In this study, we aim to provide causal evidence by directly manipulating temporal expectations and their predictability. To do so, we use an additional layer of complexity in music, that is: spatial patterns. The addition of this new level of complexity allows us to manipulate temporal expectations in real music, without affecting the music itself. Our findings indicate that musical pleasure is increased when temporally structured spatial patterns are embodied in real music as compared to non-structured patterns. These findings provide further evidence of the role of temporal expectations in musical pleasure and highlight that spatial patterns may represent a good model to better understand predictive processes in music.
The seminar will be hybrid. I share the connection link below: