Characterization of cochlear compressive nonlinearities with forward-masked compound action potentials
Authors/Creators
- 1. Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, Indiana 47907, USA
- 2. Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana 47907, USA
- 3. Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, Indiana 47907, USA; Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana 47907, USA
Contributors
Editor (5):
Project manager:
- 1. Lyon Neuroscience Research Center, CNRS UMR5292, Inserm U1028, Université Claude Bernard Lyon 1, Université Jean Monnet Saint-Étienne, Lyon, France
- 2. ENTPE, Laboratoire Génie Civil et Bâtiment, Vaulx-en-Velin, France
- 3. Starkey France, Créteil, France
Description
Cochlear compressive nonlinearities introduce level-dependent effects in sound processing by the inner ear, which are perceptually relevant for normal hearing and altered with sensorineural hearing loss. Electrocochleography may provide a means to assess nonlinearities of the human cochlea with moderate invasiveness. We recently developed a model for forward-masked Compound Action Potential (CAP), which was successful on predicting CAP waveforms recorded at the round window of chinchillas associated with notched-noise maskers of different notch widths and attenuations. The method relied primarily on the estimation of masking as a function of intensity at the cochlear-filter output. Based on these functions, cochlear 'excitation patterns' were defined and convolved by a unitary response to predict the waveforms of forward-masked CAPs. However, if we remove the low frequency suppressor of the notched-noise maskers (i.e., using derivatives of high-pass noise maskers), differential suppression effects become too important and the linear model acting as a cochlear filter bank becomes insufficient. In this preprint, we illustrate these shortcomings and we show that the inclusion of compression in our model can mitigate these issues.
Notes
Files
ISH2022_Deloche_etal.pdf
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