Phenomenological modelling of electrically stimulated auditory nerve fibers: A review

ABSTRACT

Auditory nerve fibers (ANFs) play a crucial role in hearing by encoding and transporting the synaptic input from inner hair cells into afferent spiking information for higher stages of the auditory system. If the inner hair cells are degenerated, cochlear implants may restore hearing by directly stimulating the ANFs. The response of an ANF is affected by several characteristics of the electrical stimulus and of the ANF, and neurophysiological measurements are needed to know how the ANF responds to a particular stimulus. However, recording from individual nerve fibers in humans is not feasible and obtaining compound neural or psychophysical responses is often time-consuming. This motivates the design and use of models to estimate the ANF response to the electrical stimulation. Phenomenological models reproduce the ANF response based on a simplified description of ANF functionality and on a limited parameter space by not directly describing detailed biophysical mechanisms. Here, we give an overview of phenomenological models published to date and demonstrate how different modeling approaches can account for the diverse phenomena affecting the ANF response. To highlight the success achieved in designing such models, we also describe a number of applications of phenomenological models to predict percepts of cochlear implant listeners.

KEYWORDS:

• Auditory system
• single neuron computation
• psychophysics
• spiking neurons
• auditory prosthesis
• auditory models

Funding

This work was supported by BMBF 01 GQ 1004B through the Bernstein Center for Computational Neuroscience Munich and by the Natural Sciences and Engineering Research Council of Canada (Discovery Grant 261736).

Notes

¹ Code for Bruce et al. (1999a) model was acquired from http://www.ece.mcmaster.ca/˜ibruce/. Last accessed July 13, 2016.

² Code for Fredelake and Hohmann (2012) model was acquired from https://www.uni-oldenburg.de/mediphysik-akustik/mediphysik/arbeitsgruppen/digitale-hoerhilfen/modellierung-fuer-hoerhilfen/downloads/. Last accessed 13.07.2016.

³ Code for Goldwyn et al. (2012) model was acquired from http://www.cns.nyu.edu/˜goldwyn/. Last accessed July 13, 2016.

⁴ Code for Horne et al. (2016) model can be acquired from http://www.aip.ei.tum.de. Last accessed July 13, 2016.

⁵ Average vector-strength values were computed from the values reported in Figure 8 of Miller et al. (2008) and in Figures 6 and 10 in Parkins (1989).

Additional information

Funding

This work was supported by BMBF 01 GQ 1004B through the Bernstein Center for Computational Neuroscience Munich and by the Natural Sciences and Engineering Research Council of Canada (Discovery Grant 261736).