Literature DB >> 31285299

Divergent Auditory Nerve Encoding Deficits Between Two Common Etiologies of Sensorineural Hearing Loss.

Kenneth S Henry1,2, Mark Sayles2,3, Ann E Hickox2, Michael G Heinz4,3.   

Abstract

Speech intelligibility can vary dramatically between individuals with similar clinically defined severity of hearing loss based on the audiogram. These perceptual differences, despite equal audiometric-threshold elevation, are often assumed to reflect central-processing variations. Here, we compared peripheral-processing in auditory nerve (AN) fibers of male chinchillas between two prevalent hearing loss etiologies: metabolic hearing loss (MHL) and noise-induced hearing loss (NIHL). MHL results from age-related reduction of the endocochlear potential due to atrophy of the stria vascularis. MHL in the present study was induced using furosemide, which provides a validated model of age-related MHL in young animals by reversibly inhibiting the endocochlear potential. Effects of MHL on peripheral processing were assessed using Wiener-kernel (system identification) analyses of single AN fiber responses to broadband noise, for direct comparison to previously published AN responses from animals with NIHL. Wiener-kernel analyses show that even mild NIHL causes grossly abnormal coding of low-frequency stimulus components. In contrast, for MHL the same abnormal coding was only observed with moderate to severe loss. For equal sensitivity loss, coding impairment was substantially less severe with MHL than with NIHL, probably due to greater preservation of the tip-to-tail ratio of cochlear frequency tuning with MHL compared with NIHL rather than different intrinsic AN properties. Differences in peripheral neural coding between these two pathologies-the more severe of which, NIHL, is preventable-likely contribute to individual speech perception differences. Our results underscore the need to minimize noise overexposure and for strategies to personalize diagnosis and treatment for individuals with sensorineural hearing loss.SIGNIFICANCE STATEMENT Differences in speech perception ability between individuals with similar clinically defined severity of hearing loss are often assumed to reflect central neural-processing differences. Here, we demonstrate for the first time that peripheral neural processing of complex sounds differs dramatically between the two most common etiologies of hearing loss. Greater processing impairment with noise-induced compared with an age-related (metabolic) hearing loss etiology may explain heightened speech perception difficulties in people overexposed to loud environments. These results highlight the need for public policies to prevent noise-induced hearing loss, an entirely avoidable hearing loss etiology, and for personalized strategies to diagnose and treat sensorineural hearing loss.
Copyright © 2019 the authors.

Entities:  

Keywords:  Wiener–kernel analysis; auditory nerve; envelope; metabolic hearing loss; noise-induced hearing loss; temporal fine structure

Mesh:

Substances:

Year:  2019        PMID: 31285299      PMCID: PMC6733559          DOI: 10.1523/JNEUROSCI.0038-19.2019

Source DB:  PubMed          Journal:  J Neurosci        ISSN: 0270-6474            Impact factor:   6.167


  33 in total

1.  Inter-relationship between different psychoacoustic measures assumed to be related to the cochlear active mechanism.

Authors:  B C Moore; D A Vickers; C J Plack; A J Oxenham
Journal:  J Acoust Soc Am       Date:  1999-11       Impact factor: 1.840

2.  Evaluating auditory performance limits: i. one-parameter discrimination using a computational model for the auditory nerve.

Authors:  M G Heinz; H S Colburn; L H Carney
Journal:  Neural Comput       Date:  2001-10       Impact factor: 2.026

3.  Effects of furosemide applied chronically to the round window: a model of metabolic presbyacusis.

Authors:  Richard A Schmiedt; Hainan Lang; Hiro-oki Okamura; Bradley A Schulte
Journal:  J Neurosci       Date:  2002-11-01       Impact factor: 6.167

4.  Tuning and timing in the gerbil ear: Wiener-kernel analysis.

Authors:  Edwin R Lewis; Kenneth R Henry; Walter M Yamada
Journal:  Hear Res       Date:  2002-12       Impact factor: 3.208

5.  Two-tone suppression in the basilar membrane of the cochlea: mechanical basis of auditory-nerve rate suppression.

Authors:  M A Ruggero; L Robles; N C Rich
Journal:  J Neurophysiol       Date:  1992-10       Impact factor: 2.714

6.  New variation on the derivation of spectro-temporal receptive fields for primary auditory afferent axons.

Authors:  Edwin R Lewis; Pim van Dijk
Journal:  Hear Res       Date:  2004-03       Impact factor: 3.208

7.  Responses to amplitude-modulated tones in the auditory nerve of the cat.

Authors:  P X Joris; T C Yin
Journal:  J Acoust Soc Am       Date:  1992-01       Impact factor: 1.840

8.  Wiener-kernel analysis of responses to noise of chinchilla auditory-nerve fibers.

Authors:  Alberto Recio-Spinoso; Andrei N Temchin; Pim van Dijk; Yun-Hui Fan; Mario A Ruggero
Journal:  J Neurophysiol       Date:  2005-01-19       Impact factor: 2.714

9.  Effects of organic acids on the edema of the stria vascularis induced by furosemide.

Authors:  L P Rybak; C Whitworth; A Weberg; V Scott
Journal:  Hear Res       Date:  1992-04       Impact factor: 3.208

10.  Speech perception problems of the hearing impaired reflect inability to use temporal fine structure.

Authors:  Christian Lorenzi; Gaëtan Gilbert; Héloïse Carn; Stéphane Garnier; Brian C J Moore
Journal:  Proc Natl Acad Sci U S A       Date:  2006-11-20       Impact factor: 11.205

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  10 in total

1.  Distorted Tonotopy Severely Degrades Neural Representations of Connected Speech in Noise following Acoustic Trauma.

Authors:  Satyabrata Parida; Michael G Heinz
Journal:  J Neurosci       Date:  2022-01-04       Impact factor: 6.709

2.  Temporal Coding of Single Auditory Nerve Fibers Is Not Degraded in Aging Gerbils.

Authors:  Amarins N Heeringa; Lichun Zhang; Go Ashida; Rainer Beutelmann; Friederike Steenken; Christine Köppl
Journal:  J Neurosci       Date:  2019-11-12       Impact factor: 6.167

3.  Noninvasive Measures of Distorted Tonotopic Speech Coding Following Noise-Induced Hearing Loss.

Authors:  Satyabrata Parida; Michael G Heinz
Journal:  J Assoc Res Otolaryngol       Date:  2020-11-13

4.  Metabolic and Sensory Components of Age-Related Hearing Loss.

Authors:  Kenneth I Vaden; Mark A Eckert; Lois J Matthews; Richard A Schmiedt; Judy R Dubno
Journal:  J Assoc Res Otolaryngol       Date:  2022-01-21

5.  Robust Data-Driven Auditory Profiling Towards Precision Audiology.

Authors:  Raul Sanchez-Lopez; Michal Fereczkowski; Tobias Neher; Sébastien Santurette; Torsten Dau
Journal:  Trends Hear       Date:  2020 Jan-Dec       Impact factor: 3.293

6.  Towards Auditory Profile-Based Hearing-Aid Fitting: Fitting Rationale and Pilot Evaluation.

Authors:  Raul Sanchez-Lopez; Michal Fereczkowski; Sébastien Santurette; Torsten Dau; Tobias Neher
Journal:  Audiol Res       Date:  2021-01-16

7.  The chinchilla animal model for hearing science and noise-induced hearing loss.

Authors:  Monica Trevino; Edward Lobarinas; Amanda C Maulden; Michael G Heinz
Journal:  J Acoust Soc Am       Date:  2019-11       Impact factor: 1.840

8.  Bottom-up and top-down neural signatures of disordered multi-talker speech perception in adults with normal hearing.

Authors:  Aravindakshan Parthasarathy; Kenneth E Hancock; Kara Bennett; Victor DeGruttola; Daniel B Polley
Journal:  Elife       Date:  2020-01-21       Impact factor: 8.140

9.  The role of cochlear place coding in the perception of frequency modulation.

Authors:  Kelly L Whiteford; Heather A Kreft; Andrew J Oxenham
Journal:  Elife       Date:  2020-09-30       Impact factor: 8.140

10.  Spectrally specific temporal analyses of spike-train responses to complex sounds: A unifying framework.

Authors:  Satyabrata Parida; Hari Bharadwaj; Michael G Heinz
Journal:  PLoS Comput Biol       Date:  2021-02-22       Impact factor: 4.475

  10 in total

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