Dynamic modulation of shared sensory and motor cortical rhythms mediates speech and non-speech discrimination performance.

Andrew L Bowers,Mary A Toner,Tim Saltuklaroglu,Matt Wilson,Ashley Harkrider

doi:10.3389/fpsyg.2014.00366

Abstract

Oscillatory models of speech processing have proposed that rhythmic cortical oscillations in sensory and motor regions modulate speech sound processing from the bottom-up via phase reset at low frequencies (3–10 Hz) and from the top-down via the disinhibition of alpha/beta rhythms (8–30 Hz). To investigate how the proposed rhythms mediate perceptual performance, electroencephalographic (EEG) was recorded while participants passively listened to or actively identified speech and tone-sweeps in a two-force choice in noise discrimination task presented at high and low signal-to-noise ratios. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB. Left and right hemisphere sensorimotor and posterior temporal lobe clusters were identified. Alpha and beta suppression was associated with active tasks only in sensorimotor and temporal clusters. In posterior temporal clusters, increases in phase reset at low frequencies were driven by the quality of bottom-up acoustic information for speech and non-speech stimuli, whereas phase reset in sensorimotor clusters was associated with top-down active task demands. A comparison of correct discrimination trials to those identified at chance showed an earlier performance related effect for the left sensorimotor cluster relative to the left-temporal lobe cluster during the syllable discrimination task only. The right sensorimotor cluster was associated with performance related differences for tone–sweep stimuli only. Findings are consistent with internal model accounts suggesting that early efferent sensorimotor models transmitted along alpha and beta channels reflect a release from inhibition related to active attention to auditory discrimination. Results are discussed in the broader context of dynamic, oscillatory models of cognition proposing that top-down internally generated states interact with bottom-up sensory processing to enhance task performance.

Highlights

A growing number of neurophysiological models have proposed that processes critical to receptive speech processing involve rhythmic cortical oscillations tuned to temporal regularities of speech (Arnal and Giraud, 2012; Giraud and Poeppel, 2012; Peelle and Davis, 2012; Ghitza, 2013)
To address how proposed sensory and sensorimotor rhythms function in the performance of a speech and non-speech discrimination task, the aims of the current analysis are: (1) to investigate whether alpha-like posterior temporal lobe clusters are associated spectral suppression along shared at beta and alpha frequencies surrounding and during stimulus events; and (2) to investigate how cortical rhythms shared between sensorimotor and temporal lobe clusters vary depending on task and the quality of bottom-up acoustic input
The second aim of the analysis was to investigate how oscillatory rhythms shared between sensorimotor and temporal lobe clusters vary depending on task and the quality of bottom-up acoustic input

Summary

Introduction

A growing number of neurophysiological models have proposed that processes critical to receptive speech processing involve rhythmic cortical oscillations tuned to temporal regularities of speech (Arnal and Giraud, 2012; Giraud and Poeppel, 2012; Peelle and Davis, 2012; Ghitza, 2013). A fundamental link between the speech production mechanism giving rise to the acoustic signal and rhythmic sampling of the same signal in sensorimotor networks would be advantageous for a neural system tasked with resolving highly variable acoustic cues (Callan et al, 2010). It is as yet unknown how rhythmic processes in motor and sensory regions are integrated on a millisecond time scale and it remains unclear under what conditions sensorimotor integration is adapted to improve perceptual outcomes (Gallese et al, 2011). Over the course of development the motor and premotor www.frontiersin.org

Methods

Results

Conclusion