Research Output
The effects of dual-task interference in predicting turn-ends in speech and music
  Determining when a partner’s spoken or musical turn will end requires well-honed predictive abilities. Evidence suggests that our motor systems are activated during perception of both speech and music, and it has been argued that motor simulation is used to predict turn-ends across domains. Here we used a dual-task interference paradigm to investigate whether motor simulation of our partner’s action underlies our ability to make accurate turn-end predictions in speech and in music. Furthermore, we explored how specific this simulation is to the action being predicted. We conducted two experiments, one investigating speech turn-ends, and one investigating music turn-ends. In each, 34 proficient pianists predicted turn-endings while (1) passively listening, (2) producing an effector-specific motor activity (mouth/hand movement), or (3) producing a task- and effector-specific motor activity (mouthing words/fingering a piano melody). In the speech experiment, any movement during speech perception disrupted predictions of spoken turn-ends, whether the movement was task-specific or not. In the music experiment, only task-specific movement (i.e., fingering a piano melody) disrupted predictions of musical turn-ends. These findings support the use of motor simulation to make turn-end predictions in both speech and music but suggest that the specificity of this simulation may differ between domains.

  • Type:

    Article

  • Date:

    01 July 2021

  • Publication Status:

    Published

  • Publisher

    Elsevier BV

  • DOI:

    10.1016/j.brainres.2021.147571

  • Cross Ref:

    10.1016/j.brainres.2021.147571

  • ISSN:

    0006-8993

  • Funders:

    Leverhulme Trust; Medical Research Council

Citation

Fisher, N. K., Hadley, L. V., Corps, R. E., & Pickering, M. J. (2021). The effects of dual-task interference in predicting turn-ends in speech and music. Brain Research, 1768, https://doi.org/10.1016/j.brainres.2021.147571

Authors

Keywords

Prediction, Language, Music, Simulation, Motor interference

Monthly Views:

Available Documents