ArticleJournal of the Association for Research in Otolaryngology : JARO2023
Spectral Grouping of Electrically Encoded Sound Predicts Speech-in-Noise Performance in Cochlear Implantees.
Article in Journal of the Association for Research in Otolaryngology : JARO, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Cortical oscillations predict auditory grouping in listeners with various hearing configurations.NeuroImage · 2025Article
- Cortical oscillations predict auditory grouping in listeners with and without hearing loss.medRxiv : the preprint server for health sciences · 2025Article
- Temporal-coherence induces binding of responses to sound sequences in ferret auditory cortex.iScience · 2025Article
- Predicting speech-in-noise ability with static and dynamic auditory figure-ground analysis using structural equation modelling.Proceedings. Biological sciences · 2025Article
- Validating the Iowa Test of Consonant Perception in a large cohort of cochlear implant users.JASA express letters · 2025Article
- Temporal-Coherence Induces Binding of Responses to Sound Sequences in Ferret Auditory Cortex.bioRxiv : the preprint server for biology · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
objectivesCochlear 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.
designForty-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.
resultsNo 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.
conclusionMeasures 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.
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