Effortful Listening Produces Both Enhancement and Suppression of Alpha in the EEG

ABSTRACT

Introduction

Adverse listening conditions can drive increased mental effort during listening. Neuroelectromagnetic alpha oscillations (8–13 Hz) may index this listening effort, but inconsistencies regarding the direction of the relationship are abundant. We performed source analyses on high-density EEG data collected during a speech-on-speech listening task to address the possibility that opposing alpha power relationships among alpha-producing brain sources drive this inconsistency.

Methods

Listeners (N = 20) heard two simultaneously presented sentences of the form: Ready <call sign> go to <color> <number> now. They either reported the color/number pair of a “Baron” call sign sentence (active: high effort), or ignored the stimuli (passive: low effort). Independent component analysis (ICA) was used to segregate temporally distinct sources in the EEG.

Results

Analysis of independent components (ICs) revealed simultaneous alpha enhancements (e.g., for somatomotor mu ICs) and suppressions (e.g., for left temporal ICs) for different brain sources. The active condition exhibited stronger enhancement for left somatomotor mu rhythm ICs, but stronger suppression for central occipital ICs.

Discussion

This study shows both alpha enhancement and suppression to be associated with increases in listening effort. Literature inconsistencies could partially relate to some source activities overwhelming others in scalp recordings.

KEYWORDS:

• Listening effort
• Event-related desynchronization (ERD)
• Event-related synchronization (ERS)
• speech-in-noise
• tau rhythm

Disclosure statement

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

Notes

1. No coupler was used in this approximation. However, we were mainly concerned with safety for the subjects, and having sounds presented at what could be considered a normal listening level. Actual fit of earphones into the ear can vary among subjects, and we expected exact levels to vary as well. Note however, that this should not be concerning given our within-subjects design and the fact that this fitting should vary randomly.

2. We used a nonparametric test because of the non-normally distributed nature of the proportion correct data.

Additional information

Funding

Research reported in this publication was supported by the Cognitive and Neurobiological Approaches to Plasticity (CNAP) Center of Biomedical Research Excellence (COBRE) of the National Institutes of Health under grant number P20GM113109. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health