A Computational Modeling Framework for Auditory Nerve Stimulation with a Cochlear Implant and the Novel Auditory Nerve Implant

This work presents a computational model based on a 3D model of a human cochlea and an auditory nerve model. The model was used to compare neural activation from a conventional cochlear implant (CI) with that from a novel auditory prosthesis for direct stimulation of the auditory nerve, the auditory nerve implant (ANI). The ANI that is currently under development targets the auditory nerve between the cochlea and the brainstem with a 3x5 array with penetrating electrodes. The computational framework offers the possibility to investigate ANI stimulation prior to the first implantations in human subjects. In this context, it is important to estimate the amount of current to elicit threshold and comfort levels with ANI, as the ANI electrodes will likely have higher impedances than the CI electrodes. A 3D finite element method (3D-FEM) model of the cochlea and the auditory nerve including auditory nerve fiber (ANF) pathways was created based on histological data. The 3D-FEM model contains a CI array inserted into the scala tympani and an ANI placed in the auditory nerve. The 3D-FEM model was used to simulate the voltage distribution along the ANFs when stimulating with the CI or the ANI. A phenomenological stochastic neuron model was applied to simulate excitation of the ANFs, resulting in excitation profiles that show the activation of the ANFs over their tonotopic frequency. The computational model predicted that the ANI requires significant less current than the CI to elicit thresholds. This result is consistent with previous studies. The results of this project will be used to understand the basic mechanisms of auditory nerve activation with the CI and for the future development of fitting and speech coding strategies for the ANI clinical trial.

This work was supported by the NINDS BRAIN initiative grant number UG3NS107688 and NSF UtB DGE 1734815.

Publication History

Article published online:
12 May 2023