Entraining IDyOT: Timing in the Information Dynamics of Thinking.
We present a novel hypothetical account of entrainment in music and language, in context of the Information Dynamics of Thinking model, IDyOT. The extended model affords an alternative view of entrainment, and its companion term, pulse, from earlier accounts. The model is based on hierarchical, statistical prediction, modeling expectations of both what an event will be and when it will happen. As such, it constitutes a kind of predictive coding, with a particular novel hypothetical implementation. Here, we focus on the model's mechanism for predicting when a perceptual event will happen, given an existing sequence of past events, which may be musical or linguistic. We propose a range of tests to validate or falsify the model, at various different levels of abstraction, and argue that computational modeling in general, and this model in particular, can offer a means of providing limited but useful evidence for evolutionary hypotheses.
Computational Creativity Lab, Computational Linguistics Lab, Cognitive Science Group, School of Electronic Engineering and Computer Science, Queen Mary University of London London, UK.
Jamie
J
Forth
Computational Creativity Lab, Computational Linguistics Lab, Cognitive Science Group, School of Electronic Engineering and Computer Science, Queen Mary University of London London, UK.
Kat
K
Agres
Computational Creativity Lab, Computational Linguistics Lab, Cognitive Science Group, School of Electronic Engineering and Computer Science, Queen Mary University of London London, UK.
Matthew
M
Purver
Computational Creativity Lab, Computational Linguistics Lab, Cognitive Science Group, School of Electronic Engineering and Computer Science, Queen Mary University of London London, UK.
Geraint A
GA
Wiggins
cognition; cognitive modeling; entrainment; information dynamics; rhythm