Modelling electrical stimulation of the human cochlear nerve

With more than 500.000 implanted devices, Cochlear implants (CIs) are the most successful neuroprostheses. They are able to restore auditory perception in subjects who suffer from severe to profound hearing impairment by activating surviving fibers of the auditory nerve with electric current pulses. While CI users usually regain the ability to understand spoken language, there remains a wide variation in speech recognition performance. At least part of this variation can be attributed to limitations in the electrode-nerve interface. This interface is still poorly understood and as there are fundamental differences between animal models and humans (e.g. opposite polarity sensitivity). Therefore, computational models of the human cochlea are indispensable to gain more insight into the mechanisms how CIs excite auditory nerve fibres, to identify limitations and find strategies to improve the overall performance of CIs. The aim of this project is to establish for the first time a collection of 25 precisely segmented cochleae from deceased humans based on high-resolution micro-CT scans with reconstructed auditory nerve fibers. As not only the number of surviving SGNs but also their distribution along the cochlea plays an important role, we will also evaluate inner and outer hair cell loss, afferent synapses and cochlear nerve status in a correlative TEM / immunohistochemical study. These results will be related to the clinical audiograms of the donators, where available. In a next step, we will generate three-dimensional finite element models of our collection of cochleae with virtually placed CI electrode arrays that predict the electrical potential along the auditory nerve fibres. With this data we aim to understand the specific details of the generation of electrically evoked nerve-action potentials in humans, investigate the impact of variations between cochlea anatomies on the electrical excitation of the auditory nerve and the effects of typical degeneration patterns of the nerve. For this interdisciplinary project it is critical that two groups with different background (Innsbruck: anatomy and segmentation/ Munich: 3d finite element modelling) cooperate closely. The long- term goal of this study is to derive user specific models, which capture the species-specific peculiarities in the electrical excitation of the human auditory nerve and the factors behind intra- patient variations. The detailed knowledge of the mechanisms behind the variability of CI user performance can lead to the advancement of overall CI technology by providing guidelines for the development of next-generation CIs and further refinement of implantation procedures, which, in the end, will improve the quality of life of CI users. The techniques developed in this project together with the rich experience available in CI research will be of high relevance for the development and refinement of other types of neural prostheses.

With more than 500.000 implanted devices, Cochlear implants (CIs) are the most successful neuroprostheses. They are able to restore auditory perception in subjects who suffer from severe to profound hearing impairment by activating surviving fibers of the auditory nerve with electric current pulses. While CI users usually regain the ability to understand spoken language, there remains a wide variation in speech recognition performance. At least part of this variation can be attributed to limitations in the electrode-nerve interface. This interface is still poorly understood and as there are fundamental differences between animal models and humans (e.g. opposite polarity sensitivity). Therefore, computational models of the human cochlea are indispensable to gain more insight into the mechanisms how CIs excite auditory nerve fibers, to identify limitations and find strategies to improve the overall performance of CIs. Based on high-resolution micro-computer tomography scan of 12 precisely segmented cochleae from humans s with reconstructed auditory nerve fibers. We acquired histological data of the changes to type I SGNs from adolescence to high age and correlate the degeneration state of the SGNs with their audiogram, and then implement a physiologically realistic model of auditory nerve fibers. Three-dimensional finite element models of our collection of cochleae with virtually placed CI electrode arrays were created to predict the electrical potential along the auditory nerve fibres. For this interdisciplinary project it is critical that two groups with different background (Innsbruck: anatomy and segmentation/ Munich: finite element modelling) cooperate closely. Our data shall help to derive user specific models for the electrical excitation of the human auditory nerve by providing guidelines for the development of next-generation CIs that will be of high relevance for the development and refinement of other types of neural prostheses.