Rhythm processing: entraining to a beat or learning a pattern?

In musical rhythm, predicting the timing of sounds is essential to many musical behaviors, such as dancing together. Humans can form such temporal predictions based on different types of structure in music, including a regular beat, or a repeating rhythmic pattern. In this project, we aim to disentangle beat-based and pattern-based expectations, using computational models of rhythm cognition. Also, we want to see whether individuals differ in their propensity to follow a beat or a pattern.

We will invite a large group of participants to the lab to complete three different rhythm tasks, including a rating task, and a tapping task. We will, in collaboration with the Amsterdam Conservatory, aim to include many musical experts, with different types of expertise (e.g., percussionists, singers, pianists, etc.).

Students have some flexibility in the questions they would like to ask within the bigger experiment, and could for example look at expertise and other individual factors that may influence musical behavior. The specific data analysis methods of course depend on the question the students would like to answer. For research master students, using computational models to explain rhythmic behavior will be part of their work, and therefore, interest in and experience with programming and modelling is useful.

Key reference:

Bouwer F.L., Nityananda V., Rouse A.A., & ten Cate C. (2021). Rhythmic abilities in humans and non-human animals: a review and recommendations from a methodological perspective. Phil. Trans. R. Soc. B 376: 20200335. https://doi.org/10.1098/rstb.2020.0335