CTN Seminar Jonathan Cannon, McMaster

Jonathan Cannon, head of the Trimba Lab at McMaster University will give a  CTN Seminar on Dynamic inference in rhythm perception, production, and synchronization in E5 2004 Sept 26 at 15:30.

Abstract:
Moving in time with rhythmic music is nearly universal across human cultures, and group rhythmic coordination produces remarkable group cohesion effects, in part by dissolving subjective boundaries between self and other. How can we make sense of this unique sensorimotor behavior in the context of the wide human repertoire of perceptual and motor processes? In this talk, I propose that the theory of Bayesian predictive processing provides not only a conceptual framework but also a clear, intuitive mathematical modeling language for rhythm perception, rhythm production, and sensorimotor synchronization through self/other integration.

Following the predictive processing account of perceptual inference, I propose a computational model in which we perform approximate Bayesian inference to estimate the momentary phase and tempo of ongoing underlying metrical cycles using learned metrical models. Then, drawing on the theory of  “active inference” which extends predictive processing to the realm of action, I propose a closely related computational model of rhythm production as a closed loop: timely feedback from our actions informs a dynamic model of our moving body, and that model guides the timing of subsequent action. Bringing these two computational models together, I propose a new formal account of sensorimotor synchronization: by modeling a heard rhythm and our own motor feedback as though they arise from the same underlying metrical cycle (i.e., modeling “self” and “other” as a single unified process), active inference naturally brings our actions into synch with what we hear. I explore evidence for this model, its new predictions, and experiments that might test those predictions.