Recent perceptual studies suggest that listeners with sensorineural hearing loss (SNHL) have a reduced ability to use temporal fine-structure cues, whereas the effects of SNHL on temporal envelope cues are generally thought to be minimal. Several perceptual studies suggest that envelope coding may actually be enhanced following SNHL and that this effect may actually degrade listening in modulated maskers (e.g., competing talkers). The present study examined physiological effects of SNHL on envelope coding in auditory nerve (AN) fibers in relation to fine-structure coding. Responses were compared between anesthetized chinchillas with normal hearing and those with a mild-moderate noise-induced hearing loss. Temporal envelope coding of narrowband-modulated stimuli (sinusoidally amplitude-modulated tones and single-formant stimuli) was quantified with several neural metrics. The relative strength of envelope and fine-structure coding was compared using shuffled correlogram analyses. On average, the strength of envelope coding was enhanced in noise-exposed AN fibers. A high degree of enhanced envelope coding was observed in AN fibers with high thresholds and very steep rate-level functions, which were likely associated with severe outer and inner hair cell damage. Degradation in fine-structure coding was observed in that the transition between AN fibers coding primarily fine structure or envelope occurred at lower characteristic frequencies following SNHL. This relative fine-structure degradation occurred despite no degradation in the fundamental ability of AN fibers to encode fine structure and did not depend on reduced frequency selectivity. Overall, these data suggest the need to consider the relative effects of SNHL on envelope and fine-structure coding in evaluating perceptual deficits in temporal processing of complex stimuli.
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http://dx.doi.org/10.1007/s10162-010-0223-6 | DOI Listing |
Biophys J
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Department of Biology, New York University, New York, New York, 10003, USA. Electronic address:
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Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, 20742
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January 2025
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