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

Author:

Berger Joel I.1,Gander Phillip E.1,Kim Subong2,Schwalje Adam T.3,Woo Jihwan4,Na Young-min4,Holmes Ann5,Hong Jean M.3,Dunn Camille C.3,Hansen Marlan R.3,Gantz Bruce J.3,McMurray Bob367,Griffiths Timothy D.8,Choi Inyong37

Affiliation:

1. Department of Neurosurgery, University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA

2. Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, Indiana, USA

3. Department of Otolaryngology – Head and Neck Surgery, University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA

4. Department of Biomedical Engineering, University of Ulsan, Ulsan, South Korea

5. Department of Psychological and Brain Sciences, University of Louisville, Louisville, Kentucky, USA

6. Department of Psychological and Brain Sciences, University of Iowa, Iowa City, Iowa, USA

7. Department of Communication Sciences and Disorders, University of Iowa, Iowa City, Iowa, USA

8. Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom.

Abstract

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.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Speech and Hearing,Otorhinolaryngology

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