Time-course of phonetic (motor speech) encoding in utterance production

ABSTRACT

Speaking involves the preparation of the linguistic content of an utterance and of the motor programs leading to articulation. The temporal dynamics of linguistic versus motor-speech (phonetic) encoding is highly debated: phonetic encoding has been associated either to the last quarter of an utterance preparation time (∼150ms before articulation), or to virtually the entire planning time, simultaneously with linguistic encoding. We (i) review the evidence on the time-course of motor-speech encoding based on EEG/MEG event-related (ERP) studies and (ii) strive to replicate the early effects of phonological-phonetic factors in referential word production by reanalysing a large EEG/ERP dataset. The review indicates that motor-speech encoding is engaged during at least the last 300ms preceding articulation (about half of a word planning lag). By contrast, the very early involvement of phonological-phonetic factors could be replicated only partially and is not as robust as in the second half of the utterance planning time-window.

KEYWORDS:

• Phonetic encoding
• motor speech planning
• dynamics
• ERP
• time-course

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The analysed time-windows (TW) in previous studies were: 74–145 ms, 186–287 ms, and 316–369 ms in Fairs et al. (2021) and 100–160 ms, 160–240 ms, 260–340 ms in Strijkers et al. (2017). The peak and TW of concurrent lexical-semantic and phonological-phonetic activation also differ across studies: 150 ms in Miozzo et al. (2015), 160–240 ms in Strijkers et al. (2017), 186–287 ms in Fairs et al. (2021).

2 An analysis run on the mean GFP of each time-period/map on the entire set of 120 items with all the continuous psycholinguistic factors (Image Complexity, Name Agreement, Lexical Frequency, Length in syllables, Word Age of Acquisition, First Phoneme Sonority) yielded an effect of frequency on Period-Map III (t(104)  = −3.32, Estimate = −.003, SE = −.0009, p = .001), of Complexity on Map IV (t(115) = 3.32, p = .001 and of Age of Acquisition on Map V (t(115) = −4.58, p < .001).

Additional information

Funding

This work was supported by Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung: [Grant number CRSII5_202228].