Temporal dynamics of sensorimotor integration in speech perception and production: independent component analysis of EEG data.

David Jenson,Ashley W. Harkrider,Andrew L. Bowers,Tim Saltuklaroglu,Megan Cuellar,David Thornton

doi:10.3389/fpsyg.2014.00656

Abstract

Activity in anterior sensorimotor regions is found in speech production and some perception tasks. Yet, how sensorimotor integration supports these functions is unclear due to a lack of data examining the timing of activity from these regions. Beta (~20 Hz) and alpha (~10 Hz) spectral power within the EEG μ rhythm are considered indices of motor and somatosensory activity, respectively. In the current study, perception conditions required discrimination (same/different) of syllables pairs (/ba/ and /da/) in quiet and noisy conditions. Production conditions required covert and overt syllable productions and overt word production. Independent component analysis was performed on EEG data obtained during these conditions to (1) identify clusters of μ components common to all conditions and (2) examine real-time event-related spectral perturbations (ERSP) within alpha and beta bands. 17 and 15 out of 20 participants produced left and right μ-components, respectively, localized to precentral gyri. Discrimination conditions were characterized by significant (pFDR < 0.05) early alpha event-related synchronization (ERS) prior to and during stimulus presentation and later alpha event-related desynchronization (ERD) following stimulus offset. Beta ERD began early and gained strength across time. Differences were found between quiet and noisy discrimination conditions. Both overt syllable and word productions yielded similar alpha/beta ERD that began prior to production and was strongest during muscle activity. Findings during covert production were weaker than during overt production. One explanation for these findings is that μ-beta ERD indexes early predictive coding (e.g., internal modeling) and/or overt and covert attentional/motor processes. μ-alpha ERS may index inhibitory input to the premotor cortex from sensory regions prior to and during discrimination, while μ-alpha ERD may index sensory feedback during speech rehearsal and production.

Highlights

It remains critical to disentangle the neural networks that allow an infinite array of co-articulated vocal tract gestures to be produced by a speaker and effortlessly sensed, recognized, and understood by a listener
DISCRIMINATION ACCURACY In participants that contributed to μ clusters, the average number of useable trials across participants in each condition were: passively listen to white noise (Pasn) = 73.8 (SD = 7.2); Qdis = 74.8 (SD = 4.6); Ndis = 69.0 (SD = 11.4); imagine producing a pair of syllables (Img) = 75.0 (SD = 5.8); SylP = 71.1 (SD = 7.4); WorP = 69.9 (SD = 8.0)
In the Qdis condition, all participants discriminated with 91–100% accuracy

Summary

Introduction

It remains critical to disentangle the neural networks that allow an infinite array of co-articulated vocal tract gestures to be produced by a speaker and effortlessly sensed, recognized, and understood by a listener. Though these two complimentary and highly integrated processes often are examined independently, considerable recent effort has focused upon understanding how classical production mechanisms (e.g., the motor system) are involved in speech perception (D’Ausilio et al, 2012; Mottonen and Watkins, 2012; Murakami et al, 2013) and classical perception regions (i.e., auditory and somatosensory systems) are involved in production (Burnett et al, 1998; Stuart et al, 2002; Purcell and Munhall, 2006).

Methods

Results

Discussion

Conclusion