Moving in time : Bayesian causal inference explains movement coordination to auditory beats

M. T. Elliott, A. M. Wing, A. E. Welchman

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)
177 Downloads (Pure)


Many everyday skilled actions depend on moving in time with signals that are embedded in complex auditory streams (e.g. musical performance, dancing or simply holding a conversation). Such behaviour is apparently effortless; however, it is not known how humans combine auditory signals to support movement production and coordination. Here, we test how participants synchronize their movements when there are potentially conflicting auditory targets to guide their actions. Participants tapped their fingers in time with two simultaneously presented metronomes of equal tempo, but differing in phase and temporal regularity. Synchronization therefore depended on integrating the two timing cues into a single-event estimate or treating the cues as independent and thereby selecting one signal over the other. We show that a Bayesian inference process explains the situations in which participants choose to integrate or separate signals, and predicts motor timing errors. Simulations of this causal inference process demonstrate that this model provides a better description of the data than other plausible models. Our findings suggest that humans exploit a Bayesian inference process to control movement timing in situations where the origin of auditory signals needs to be resolved.
Original languageEnglish
Article number20140751
JournalRoyal Society of London. Proceedings B. Biological Sciences
Issue number1786
Early online date21 May 2014
Publication statusPublished - 7 Jul 2014


  • movement synchronization
  • Bayesian inference
  • sensory integration
  • motor timing


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