In music, the rhythmic structure allows us to predict the timing of events, which optimized processing, and makes it possible for us to move in synchrony to the music. Several types of structure exist in rhythm, and how we base predictions on these different types of structure (like the rhythmic pattern, groups, and the beat) is unclear. In this project, we will use modelling and behavioural responses to understand how humans process different types of rhythms. Specifically, we will examine whether oscillator models and probabilistic models explain different aspects of rhythmic behaviour: entrainment to a beat, and predictions based on the rhythmic pattern respectively.

Depending on the student’s interest and experience, they can take part in different subprojects associated with the overarching questions. Some of this will be more model-oriented (for example: comparing how different oscillator models react to various rhythms) and some more lab-oriented (for example: collecting and analysing behavioural responses from people listening to various rhythms).

The students will be involved in modelling, collecting and analysing the data, and should be willing/able to do some programming (Python/R/Matlab).