Expert musicians are able to accurately and consistently time their actions during a musical performance. We investigated how musical expertise influences the ability to reproduce auditory intervals and how this generalises to vision in a ‘ready-set-go’ paradigm. Subjects reproduced time intervals drawn from distributions varying in total length (176, 352 or 704 ms) or in the number of discrete intervals within the total length (3, 5, 11 or 21 discrete intervals). Overall musicians performed more veridically than non-musicians, and all subjects reproduced auditory-defined intervals more accurately than visually-defined intervals. However non-musicians, particularly with visual intervals, consistently exhibited a substantial and systematic regression towards the mean of the interval. When subjects judged intervals from distributions of longer total length they tended to exhibit more regression towards the mean, while the ability to discriminate between discrete intervals within the distribution had little influence on subject error. These results are consistent with a Bayesian model which minimizes reproduction errors by incorporating a central tendency prior weighted by the subject’s own temporal precision relative to the current intervals distribution (Cicchini et al., 2012; Jazayeri and Shadlen, 2010). Finally a strong correlation was observed between all durations of formal musical training and total reproduction errors in both modalities (accounting for 30% of the variance). Taken together these results demonstrate that formal musical training improves temporal reproduction, and that this improvement transfers from audition to vision. They further demonstrate the flexibility of sensorimotor mechanisms in adapting to different task conditions to minimise temporal estimation errors.
Statistical cures and other fallacies
