Nonlinear Oscillator Model of Complex Rhythm Perception

Human listeners spontaneously coordinate periodic movements with highly syncopated musical rhythms. The perception of periodic pulse or beat in complex rhythms has been modeled with various methods of frequency and periodicity analysis. Here we show that nonlinear oscillators can model important aspects of human rhythmic behavior that are difficult to explain with linear signal processing methods, such as phase alignment to selective onset events and phase multistability for complex rhythms. An oscillator network model developed in this research runs in Synchrony, a music-activated LED controller which synchronizes light patterns to the beat of music in real time.