ERP Signals During Speech Articulation: Does Auditory Feedback Mask Other Ongoing Cognitive-motor Processes?

The study of speech planning/programming may require analysing Event-Related Potentials (ERPs) during articulation. However, ERPs identified during speech production also contain brain signals associated with auditory feedback. Because these processes are both time-locked to the vocal onset, existing algorithms for signal separation have difficulties distinguishing one from the other. Here, we investigated the use of the multi-channel Wiener filter (MWF) to remove the ERP signal related to auditory processing from the ERP signal related to speech production. In a first step, participants were asked to overtly produce mono- or disyllabic pseudowords. In a second step, they had to listen to the recording of their own productions. We used the ERP signal associated with hearing one's own production (referred to as listening ERPs) to estimate and filter out the auditory part of the production ERP. We investigated three versions of the ERPs during speech articulation: (1) the original production ERPs, (2) the ERPs filtered through the MWF, and (3) subtraction ERPs obtained by subtracting the listening ERPs from the original ERPs. Firstly, we conducted a microstate analysis comparing all three versions of the ERPs. Secondly, we conducted separate microstate analyses comparing mono- versus disyllabic conditions on each of the three versions. The results indicate that the subtraction method alters topography consistency and may remove relevant signal from the ERPs. The filtered ERP produced similar results to the original production ERP and thus, it may be unnecessary to remove auditory feedback or other overlapping signal if time-locked to the production onset.

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Publication Details

Journal
Brain Topography
Published
2025-08-14
DOI
https://doi.org/10.1007/s10548-025-01131-0
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00

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article

ERP Signals During Speech Articulation: Does Auditory Feedback Mask Other Ongoing Cognitive-motor Processes?

Marina Laganaro, Ina Kodrasi, Michael De Pretto
Brain Topography
EEG and Brain-Computer Interfaces
article

ERP Signals During Speech Articulation: Does Auditory Feedback Mask Other Ongoing Cognitive-motor Processes?

Marina Laganaro, Ina Kodrasi, Michael De Pretto
article en

Abstract

The study of speech planning/programming may require analysing Event-Related Potentials (ERPs) during articulation. However, ERPs identified during speech production also contain brain signals associated with auditory feedback. Because these processes are both time-locked to the vocal onset, existing algorithms for signal separation have difficulties distinguishing one from the other. Here, we investigated the use of the multi-channel Wiener filter (MWF) to remove the ERP signal related to auditory processing from the ERP signal related to speech production. In a first step, participants were asked to overtly produce mono- or disyllabic pseudowords. In a second step, they had to listen to the recording of their own productions. We used the ERP signal associated with hearing one's own production (referred to as listening ERPs) to estimate and filter out the auditory part of the production ERP. We investigated three versions of the ERPs during speech articulation: (1) the original production ERPs, (2) the ERPs filtered through the MWF, and (3) subtraction ERPs obtained by subtracting the listening ERPs from the original ERPs. Firstly, we conducted a microstate analysis comparing all three versions of the ERPs. Secondly, we conducted separate microstate analyses comparing mono- versus disyllabic conditions on each of the three versions. The results indicate that the subtraction method alters topography consistency and may remove relevant signal from the ERPs. The filtered ERP produced similar results to the original production ERP and thus, it may be unnecessary to remove auditory feedback or other overlapping signal if time-locked to the production onset.

Brain TopographyVol. 38(5)
University of Geneva (CH), Idiap Research Institute (CH)
National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Université de Genève, Centre d'Imagerie BioMédicale
Peace, Justice and strong institutions
Openalex Percentile: Top 80%
EEG and Brain-Computer Interfaces
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