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Neural mechanisms underlying auditory feedback processing during speech production

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Franken,  Matthias K.
Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen;
Neurobiology of Language Department, MPI for Psycholinguistics, Max Planck Society;
International Max Planck Research School for Language Sciences, MPI for Psycholinguistics, Max Planck Society;

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McQueen,  James M.
Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen;
Research Associates, MPI for Psycholinguistics, Max Planck Society;

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Hagoort,  Peter
Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen;
Neurobiology of Language Department, MPI for Psycholinguistics, Max Planck Society;

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Schoffelen,  Jan-Mathijs
Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen;
Neurobiology of Language Department, MPI for Psycholinguistics, Max Planck Society;

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Citation

Franken, M. K., Eisner, F., Acheson, D. J., McQueen, J. M., Hagoort, P., & Schoffelen, J.-M. (2016). Neural mechanisms underlying auditory feedback processing during speech production. Talk presented at the Donders Discussions 2016. Nijmegen, The Netherlands. 2016-11-23 - 2016-11-24.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002B-ABEE-9
Abstract
Speech production is one of the most complex motor skills, and involves close interaction between perceptual and motor systems. One way to investigate this interaction is to provide speakers with manipulated auditory feedback during speech production. Using this paradigm, investigators have started to identify a neural network that underlies auditory feedback processing and monitoring during speech production. However, to date, still little is known about the neural mechanisms that underlie feedback processing. The present study set out to shed more light on the neural correlates of processing auditory feedback. Participants (N = 39) were seated in an MEG scanner and were asked to vocalize the vowel /e/continuously throughout each trial (of 4 s) while trying to match a pre-specified pitch target of 4, 8 or 11 semitones above the participants’ baseline pitch level. They received auditory feedback through ear plugs. In half of the trials, the pitch in the auditory feedback was unexpectedly manipulated (raised by 25 cents) for 500 ms, starting between 500ms and 1500ms after speech onset. In the other trials, feedback was normal throughout the trial. In a second block of trials, participants listened passively to recordings of the auditory feedback they received during vocalization in the first block. Even though none of the participants reported being aware of any feedback perturbations, behavioral responses showed that participants on average compensated for the feedback perturbation by decreasing the pitch in their vocalizations, starting at about 100ms after perturbation onset until about 100 ms after perturbation offset. MEG data was analyzed, time-locked to the onset of the feedback perturbation in the perturbation trials, and to matched time-points in the control trials. A cluster-based permutation test showed that the event-related field responses differed between the perturbation and the control condition. This difference was mainly driven by an ERF response peaking at about 100ms after perturbation onset and a larger response after perturbation offset. Both these were localized to sensorimotor cortices, with the effect being larger in the right hemisphere. These results are in line with previous reports of right-lateralized pitch processing. In the passive listening condition, we found no differences between the perturbation and the control trials. This suggests that the ERF responses were not merely driven by the pitch change in the auditory input and hence instead reflect speech production processes. We suggest the observed ERF responses in sensorimotor cortex are an index of the mismatch between the self-generated forward model prediction of auditory input and the incoming auditory signal.