Input level dependence of distortion products generated by saturating feedback in a cochlear model

Yasuki Murakami, Shunsuke Ishimitsu

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


In this paper, we demonstrate how feedback from a saturation function can explain the generation mechanisms of cochlear distortion products (DPs) using a transmission line model of the cochlea, two simple nonlinear phenomenological models, and a power-law nonlinear model. The first model includes feedback via a saturating element that models outer hair cell motility toggled by mechanoelectric transduction. The second models focus on the saturation process in the cochlea, and result in either feedforward or feedback. The third model can fit compressive growth in the cochlear input-output function. The models show compressive growth in input-output properties for a single tone and generate DPs at moderate input levels for two tones. The results of the transmission line model show a good fit to the experimental results. DP levels are concentrated when the levels of the two tones are equal in the simple feedforward model and are widely distributed in the simple feedback model. The simple feedback model shows similar results to the transmission line model, with the exception of the dependence on the frequency rate. The results of the power-law nonlinear model with an appropriate power are comparable to the results of the simple feedback model. These results suggest that the saturating feedback process generates appropriate power-law nonlinearity and can account for the input level dependence of DP generation in the cochlea.

Original languageEnglish
Pages (from-to)1-9
Number of pages9
JournalAcoustical Science and Technology
Issue number1
Publication statusPublished - Feb 1 2016
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Acoustics and Ultrasonics


Dive into the research topics of 'Input level dependence of distortion products generated by saturating feedback in a cochlear model'. Together they form a unique fingerprint.

Cite this