Spectral Grouping of Electrically Encoded Sound Predicts Speech-in-Noise Performance in Cochlear Implantees

Inyong Choi; Phillip E Gander; Joel I Berger; Jihwan Woo; Matthew H Choy; Jean Hong; Sarah Colby; Bob McMurray; Timothy D Griffiths

doi:10.1007/s10162-023-00918-x

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Spectral Grouping of Electrically Encoded Sound Predicts Speech-in-Noise Performance in Cochlear Implantees

Journal article

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Peer reviewed

Spectral Grouping of Electrically Encoded Sound Predicts Speech-in-Noise Performance in Cochlear Implantees

Inyong Choi, Phillip E Gander, Joel I Berger, Jihwan Woo, Matthew H Choy, Jean Hong, Sarah Colby, Bob McMurray and Timothy D Griffiths

Journal of the Association for Research in Otolaryngology, Vol.24(6), pp.607-617

12/2023

DOI: 10.1007/s10162-023-00918-x

PMCID: PMC10752853

PMID: 38062284

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Abstract

Cochlear implant (CI) users exhibit large variability in understanding speech in noise. Past work in CI users found that spectral and temporal resolution correlates with speech-in-noise ability, but a large portion of variance remains unexplained. Recent work on normal-hearing listeners showed that the ability to group temporally and spectrally coherent tones in a complex auditory scene predicts speech-in-noise ability independently of the audiogram, highlighting a central mechanism for auditory scene analysis that contributes to speech-in-noise. The current study examined whether the auditory grouping ability also contributes to speech-in-noise understanding in CI users. Forty-seven post-lingually deafened CI users were tested with psychophysical measures of spectral and temporal resolution, a stochastic figure-ground task that depends on the detection of a figure by grouping multiple fixed frequency elements against a random background, and a sentence-in-noise measure. Multiple linear regression was used to predict sentence-in-noise performance from the other tasks. No co-linearity was found between any predictor variables. All three predictors (spectral and temporal resolution plus the figure-ground task) exhibited significant contribution in the multiple linear regression model, indicating that the auditory grouping ability in a complex auditory scene explains a further proportion of variance in CI users' speech-in-noise performance that was not explained by spectral and temporal resolution. Measures of cross-frequency grouping reflect an auditory cognitive mechanism that determines speech-in-noise understanding independently of cochlear function. Such measures are easily implemented clinically as predictors of CI success and suggest potential strategies for rehabilitation based on training with non-speech stimuli.

Cochlear Implants

Auditory grouping

Speech-in-noise

Details

Title: Subtitle: Spectral Grouping of Electrically Encoded Sound Predicts Speech-in-Noise Performance in Cochlear Implantees
Creators: Inyong Choi - University of Iowa Hospitals and Clinics
Phillip E Gander - University of Iowa
Joel I Berger - University of Iowa
Jihwan Woo - University of Ulsan
Matthew H Choy - Newcastle University
Jean Hong - University of Iowa
Sarah Colby - University of Iowa
Bob McMurray - University of Iowa
Timothy D Griffiths - Newcastle University
Resource Type: Journal article
Publication Details: Journal of the Association for Research in Otolaryngology, Vol.24(6), pp.607-617
DOI: 10.1007/s10162-023-00918-x
PMID: 38062284
PMCID: PMC10752853
NLM abbreviation: J Assoc Res Otolaryngol
ISSN: 1525-3961
eISSN: 1438-7573
Grant note: DC000242 36 / NIDCD NIH HHS MR/T032553/1 / Medical Research Council
Language: English
Electronic publication date: 12/07/2023
Date published: 12/2023
Academic Unit: Radiology; Communication Sciences and Disorders; Linguistics; Psychological and Brain Sciences; Iowa Neuroscience Institute; Neurosurgery; Otolaryngology; Health, Sport, and Human Physiology
Record Identifier: 9984528099102771

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