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The effects of dual-task interference in predicting turn-ends in speech and music

Fisher, Nina K.; Hadley, Lauren V.; Corps, Ruth E.; Pickering, Martin J.


Lauren V. Hadley

Ruth E. Corps

Martin J. Pickering


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.

Journal Article Type Article
Acceptance Date Jun 23, 2021
Online Publication Date Jul 1, 2021
Publication Date 2021-10
Deposit Date Jul 16, 2021
Publicly Available Date Jul 2, 2022
Journal Brain Research
Print ISSN 0006-8993
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 1768
Article Number 147571
Keywords Prediction, Language, Music, Simulation, Motor interference
Public URL


The Effects Of Dual-task Interference In Predicting Turn-ends In Speech And Music (accepted version) (433 Kb)


Copyright Statement
Accepted version licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.

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