High Fidelity Bioelectric Modelling of the Implanted Cochlea

Cochlear implants are medical devices that can restore sound perception in individuals with sensorineural hearing loss (SHL). Since their inception, improvements in performance have largely been driven by advances in signal processing, but progress has plateaued for almost a decade. This suggests that there is a bottleneck at the electrode-tissue interface, which is responsible for enacting the biophysical changes that govern neuronal recruitment. Understanding this interface is difficult because the cochlea is small, intricate, and difficult to access. As such, researchers have turned to modelling techniques to provide new insights. The state-of-the-art involves calculating the electric field using a volume conduction model of the implanted cochlea and coupling it with a neural excitation model to predict the response. However, many models are unable to predict patient outcomes consistently. This thesis aims to improve the reliability of these models by creating high fidelity reconstructions of the inner ear and critically assessing the validity of the underlying and hitherto untested assumptions. Regarding boundary conditions, the evidence suggests that the unmodelled monopolar return path should be accounted for, perhaps by applying a voltage offset at a boundary surface. Regarding vasculature, the models show that large modiolar vessels like the vein of the scala tympani have a strong local effect near the stimulating electrode. Finally, it appears that the oft-cited quasi-static assumption is not valid due to the high permittivity of neural tissue. It is hoped that the study improves the trustworthiness of all bioelectric models of the cochlea, either by validating the claims of existing models, or by prompting improvements in future work. Developing our understanding of the underlying physics will pave the way for advancing future electrode array designs as well as patient-specific simulations, ultimately improving the quality of life for those with SHL