Computational modeling of the human auditory periphery: Auditory-nerve responses, evoked potentials and hearing loss
Models of the human auditory periphery range from very basic functional descriptions of auditory filtering to detailed computational models of cochlear mechanics, inner-hair cell (IHC), auditory-nerve (AN) and brainstem signal processing. It is challenging to include detailed physiological descripti...
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| Published in | Hearing research Vol. 360; pp. 55 - 75 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Netherlands
Elsevier B.V
01.03.2018
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| Online Access | Get full text |
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| Abstract | Models of the human auditory periphery range from very basic functional descriptions of auditory filtering to detailed computational models of cochlear mechanics, inner-hair cell (IHC), auditory-nerve (AN) and brainstem signal processing. It is challenging to include detailed physiological descriptions of cellular components into human auditory models because single-cell data stems from invasive animal recordings while human reference data only exists in the form of population responses (e.g., otoacoustic emissions, auditory evoked potentials). To embed physiological models within a comprehensive human auditory periphery framework, it is important to capitalize on the success of basic functional models of hearing and render their descriptions more biophysical where possible. At the same time, comprehensive models should capture a variety of key auditory features, rather than fitting their parameters to a single reference dataset. In this study, we review and improve existing models of the IHC-AN complex by updating their equations and expressing their fitting parameters into biophysical quantities. The quality of the model framework for human auditory processing is evaluated using recorded auditory brainstem response (ABR) and envelope-following response (EFR) reference data from normal and hearing-impaired listeners. We present a model with 12 fitting parameters from the cochlea to the brainstem that can be rendered hearing impaired to simulate how cochlear gain loss and synaptopathy affect human population responses. The model description forms a compromise between capturing well-described single-unit IHC and AN properties and human population response features.
•An overview of computational models from cochlea to auditory-nerve (AN).•IHC-AN model descriptions are made biophysical to reduce model fitting parameters.•The presented auditory model captures key aspects of human OAE, ABR and EFRs.•Simulated impact of sensorineural hearing loss on human population responses. |
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| AbstractList | Models of the human auditory periphery range from very basic functional descriptions of auditory filtering to detailed computational models of cochlear mechanics, inner-hair cell (IHC), auditory-nerve (AN) and brainstem signal processing. It is challenging to include detailed physiological descriptions of cellular components into human auditory models because single-cell data stems from invasive animal recordings while human reference data only exists in the form of population responses (e.g., otoacoustic emissions, auditory evoked potentials). To embed physiological models within a comprehensive human auditory periphery framework, it is important to capitalize on the success of basic functional models of hearing and render their descriptions more biophysical where possible. At the same time, comprehensive models should capture a variety of key auditory features, rather than fitting their parameters to a single reference dataset. In this study, we review and improve existing models of the IHC-AN complex by updating their equations and expressing their fitting parameters into biophysical quantities. The quality of the model framework for human auditory processing is evaluated using recorded auditory brainstem response (ABR) and envelope-following response (EFR) reference data from normal and hearing-impaired listeners. We present a model with 12 fitting parameters from the cochlea to the brainstem that can be rendered hearing impaired to simulate how cochlear gain loss and synaptopathy affect human population responses. The model description forms a compromise between capturing well-described single-unit IHC and AN properties and human population response features.Models of the human auditory periphery range from very basic functional descriptions of auditory filtering to detailed computational models of cochlear mechanics, inner-hair cell (IHC), auditory-nerve (AN) and brainstem signal processing. It is challenging to include detailed physiological descriptions of cellular components into human auditory models because single-cell data stems from invasive animal recordings while human reference data only exists in the form of population responses (e.g., otoacoustic emissions, auditory evoked potentials). To embed physiological models within a comprehensive human auditory periphery framework, it is important to capitalize on the success of basic functional models of hearing and render their descriptions more biophysical where possible. At the same time, comprehensive models should capture a variety of key auditory features, rather than fitting their parameters to a single reference dataset. In this study, we review and improve existing models of the IHC-AN complex by updating their equations and expressing their fitting parameters into biophysical quantities. The quality of the model framework for human auditory processing is evaluated using recorded auditory brainstem response (ABR) and envelope-following response (EFR) reference data from normal and hearing-impaired listeners. We present a model with 12 fitting parameters from the cochlea to the brainstem that can be rendered hearing impaired to simulate how cochlear gain loss and synaptopathy affect human population responses. The model description forms a compromise between capturing well-described single-unit IHC and AN properties and human population response features. Models of the human auditory periphery range from very basic functional descriptions of auditory filtering to detailed computational models of cochlear mechanics, inner-hair cell (IHC), auditory-nerve (AN) and brainstem signal processing. It is challenging to include detailed physiological descriptions of cellular components into human auditory models because single-cell data stems from invasive animal recordings while human reference data only exists in the form of population responses (e.g., otoacoustic emissions, auditory evoked potentials). To embed physiological models within a comprehensive human auditory periphery framework, it is important to capitalize on the success of basic functional models of hearing and render their descriptions more biophysical where possible. At the same time, comprehensive models should capture a variety of key auditory features, rather than fitting their parameters to a single reference dataset. In this study, we review and improve existing models of the IHC-AN complex by updating their equations and expressing their fitting parameters into biophysical quantities. The quality of the model framework for human auditory processing is evaluated using recorded auditory brainstem response (ABR) and envelope-following response (EFR) reference data from normal and hearing-impaired listeners. We present a model with 12 fitting parameters from the cochlea to the brainstem that can be rendered hearing impaired to simulate how cochlear gain loss and synaptopathy affect human population responses. The model description forms a compromise between capturing well-described single-unit IHC and AN properties and human population response features. •An overview of computational models from cochlea to auditory-nerve (AN).•IHC-AN model descriptions are made biophysical to reduce model fitting parameters.•The presented auditory model captures key aspects of human OAE, ABR and EFRs.•Simulated impact of sensorineural hearing loss on human population responses. Models of the human auditory periphery range from very basic functional descriptions of auditory filtering to detailed computational models of cochlear mechanics, inner-hair cell (IHC), auditory-nerve (AN) and brainstem signal processing. It is challenging to include detailed physiological descriptions of cellular components into human auditory models because single-cell data stems from invasive animal recordings while human reference data only exists in the form of population responses (e.g., otoacoustic emissions, auditory evoked potentials). To embed physiological models within a comprehensive human auditory periphery framework, it is important to capitalize on the success of basic functional models of hearing and render their descriptions more biophysical where possible. At the same time, comprehensive models should capture a variety of key auditory features, rather than fitting their parameters to a single reference dataset. In this study, we review and improve existing models of the IHC-AN complex by updating their equations and expressing their fitting parameters into biophysical quantities. The quality of the model framework for human auditory processing is evaluated using recorded auditory brainstem response (ABR) and envelope-following response (EFR) reference data from normal and hearing-impaired listeners. We present a model with 12 fitting parameters from the cochlea to the brainstem that can be rendered hearing impaired to simulate how cochlear gain loss and synaptopathy affect human population responses. The model description forms a compromise between capturing well-described single-unit IHC and AN properties and human population response features. |
| Author | Verhulst, Sarah Altoè, Alessandro Vasilkov, Viacheslav |
| Author_xml | – sequence: 1 givenname: Sarah surname: Verhulst fullname: Verhulst, Sarah email: s.verhulst@ugent.be organization: WAVES, Dept. of Information Technology, Ghent University, Technologiepark 15, 9052 Zwijnaarde, Belgium – sequence: 2 givenname: Alessandro orcidid: 0000-0003-3004-6918 surname: Altoè fullname: Altoè, Alessandro email: Alessandro.altoe@aalto.fi organization: Department of Signal Processing and Acoustics, School of Electrical Engineering, Aalto University, P.O. Box 13000, FI-00076 Aalto, Finland – sequence: 3 givenname: Viacheslav surname: Vasilkov fullname: Vasilkov, Viacheslav email: Viacheslav.vasilkov@uni-oldenburg.de organization: Medizinische Physik, Oldenburg University, Carl-von-Ossietzky strasse 9-11, 26120 Oldenburg, Germany |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29472062$$D View this record in MEDLINE/PubMed |
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