| dc.description.abstract | Temporal expectations allow us to anticipate upcoming events and enhance the speed and accuracy of perceptual decisions. Within rhythm perception and cognition, there are two theoretical frameworks of temporal expectations that we take into account in our study. Neural resonance theory hypothesizes that people perceive a beat and rhythm due to resonance of neural oscillations to rhythmic stimuli and a connection between the motor and sensory system. This network tries to find periodicity in the input and we call these beat-based expectations. Predictive processing theory on the other hand argues that the brain uses statistical learning to acquire cognitive models of statistical regularities and then applies these models to make probabilistic predictions on the rhythmic input. This system thus searches for patterns and we call these pattern-based expectations. This study looks into the effect of beat-based expectations, pattern-based expectations and musical expertise on performance of an implicit, explicit and motor task. All tasks were performed on a set of 56 rhythms that were divided into four categories: periodic predictable, periodic unpredictable, aperiodic predictable and aperiodic unpredictable. We found that pattern-based expectations improved performance in all tasks, while beat-based expectations by themselves only increased performance in target detection in the implicit task. We also found interactions between beat-based and pattern-based expectations, in which the effect of periodicity was dependent on the predictability condition. Musical expertise as a main effect was significant for the hit rate in the implicit task and all measures of the motor task. In addition to this, we found interactions between musical expertise and both beat-based expectations and pattern-based expectations, in which the performance of participants with more musical expertise increased most for periodic and unpredictable rhythms. Overall, we cannot make definitive conclusions about the differences between beat-based and pattern-based expectations, as the computing of these expectations cannot be directly compared. Still, this study opens new avenues for research into the interplay between beat-based expectations, pattern-based expectations and musical expertise. | |
