Toggle Main Menu Toggle Search

Open Access padlockePrints

Neural Correlates of Individual Differences in Speech-in-Noise Performance in a Large Cohort of Cochlear Implant Users

Lookup NU author(s): Professor Tim GriffithsORCiD

Downloads


Licence

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).


Abstract

Copyright © 2023 The Authors. Ear & Hearing is published on behalf of the American Auditory Society, by Wolters Kluwer Health, Inc. OBJECTIVES: Understanding speech-in-noise (SiN) is a complex task that recruits multiple cortical subsystems. Individuals vary in their ability to understand SiN. This cannot be explained by simple peripheral hearing profiles, but recent work by our group ( Kim et al. 2021 , Neuroimage ) highlighted central neural factors underlying the variance in SiN ability in normal hearing (NH) subjects. The present study examined neural predictors of SiN ability in a large cohort of cochlear-implant (CI) users. DESIGN: We recorded electroencephalography in 114 postlingually deafened CI users while they completed the California consonant test: a word-in-noise task. In many subjects, data were also collected on two other commonly used clinical measures of speech perception: a word-in-quiet task (consonant-nucleus-consonant) word and a sentence-in-noise task (AzBio sentences). Neural activity was assessed at a vertex electrode (Cz), which could help maximize eventual generalizability to clinical situations. The N1-P2 complex of event-related potentials (ERPs) at this location were included in multiple linear regression analyses, along with several other demographic and hearing factors as predictors of SiN performance. RESULTS: In general, there was a good agreement between the scores on the three speech perception tasks. ERP amplitudes did not predict AzBio performance, which was predicted by the duration of device use, low-frequency hearing thresholds, and age. However, ERP amplitudes were strong predictors for performance for both word recognition tasks: the California consonant test (which was conducted simultaneously with electroencephalography recording) and the consonant-nucleus-consonant (conducted offline). These correlations held even after accounting for known predictors of performance including residual low-frequency hearing thresholds. In CI-users, better performance was predicted by an increased cortical response to the target word, in contrast to previous reports in normal-hearing subjects in whom speech perception ability was accounted for by the ability to suppress noise. CONCLUSIONS: These data indicate a neurophysiological correlate of SiN performance, thereby revealing a richer profile of an individual's hearing performance than shown by psychoacoustic measures alone. These results also highlight important differences between sentence and word recognition measures of performance and suggest that individual differences in these measures may be underwritten by different mechanisms. Finally, the contrast with prior reports of NH listeners in the same task suggests CI-users performance may be explained by a different weighting of neural processes than NH listeners.


Publication metadata

Author(s): Berger JI, Gander PE, Kim S, Schwalje AT, Woo J, Na Y-M, Holmes A, Hong JM, Dunn CC, Hansen MR, Gantz BJ, McMurray B, Griffiths TD, Choi I

Publication type: Article

Publication status: Published

Journal: Ear and Hearing

Year: 2023

Volume: 44

Issue: 5

Pages: 1107-1120

Print publication date: 01/09/2023

Online publication date: 05/05/2023

Acceptance date: 11/01/2023

Date deposited: 31/08/2023

ISSN (print): 0196-0202

ISSN (electronic): 1538-4667

Publisher: Lippincott Williams & Wilkins

URL: https://doi.org/10.1097/AUD.0000000000001357

DOI: 10.1097/AUD.0000000000001357

PubMed id: 37144890


Altmetrics

Altmetrics provided by Altmetric


Funding

Funder referenceFunder name
DC000242 31
DC000040-24
DC008089
Department of Defense Hearing Restoration and Rehabilitation Program
MRC
MR-T032553-1
NIDCD P50
NIH T32
W81XWH1910637

Share