The use of electrophysiological testing procedures to determine auditory nerve fibre damage

Abstract

Damage to a cochlear implant (CI) user’s auditory nerve fibres (ANFs) is one of the factors that may contribute to poor performance with the implant, likely because neural propagation of the electrical signal from the cochlear implant to the brain is impaired. Various mechanisms have been identified in literature that can cause damage to the auditory nerve. These mechanisms include neural degeneration, demyelination and nerve fibre loss. There is no standardised testing procedure to identify the location or types of cochlear nerve damage in cochlear implant users. Research has been conducted to investigate if the results of electrophysiological measurements could be used to identity auditory nerve fibre damage. The aim of this study is to develop a procedure to identify potential neural damage using electrophysiological measurements. Two different clinical electrophysiological tests were identified for use in this procedure, namely electrically evoked compound action potential (eCAPs) and electrically evoked auditory brainstem responses (eABRs). First, indicators of distinct neural damage mechanisms reported in the literature for both electrophysiological tests were consolidated. The neural model used in this study was then verified against the expected eCAP responses from literature. A population of auditory neural fibres was integrated with a three-dimensional volume conduction model to allow investigation of eCAP responses to the application of different damage mechanisms. ECAP and eABR measures were recorded for a specific CI recipient. These electrophysiological data were used to determine a neural damage profile. The identified damage was applied to a userspecific model of the CI recipients cochlea and implant electrode, and the effects on the predicted eCAP responses were analysed. The procedure developed in this study to identify potential neural damage proved promising, suggesting that neural damage could be identified using electrophysiological measures.