A Phenomenological Model Reproducing Temporal Response Characteristics of an Electrically Stimulated Auditory Nerve Fiber

Insights Into Electrophysiological Metrics of Cochlear Health in Cochlear Implant Users Using a Computational Model

PURPOSE

The hearing outcomes of cochlear implant users depend on the functional status of the electrode-neuron interface inside the cochlea. This can be assessed by measuring electrically evoked compound action potentials (eCAPs). Variations in cochlear neural health and survival are reflected in eCAP-based metrics. The difficulty in translating promising results from animal studies into clinical use has raised questions about to what degree eCAP-based metrics are influenced by non-neural factors. Here, we addressed these questions using a computational model.

METHODS

A 2-D computational model was designed to simulate how electrical signals from the stimulating electrode reach the auditory nerve fibers distributed along the cochlea, evoking action potentials that can be recorded as compound responses at the recording electrodes. Effects of physiologically relevant variations in neural survival and in electrode-neuron and stimulating-recording electrode distances on eCAP amplitude growth functions (AGFs) were investigated.

RESULTS

In line with existing literature, the predicted eCAP AGF slopes and the inter-phase gap (IPG) effects depended on the neural survival, but only when the IPG effect was calculated as the difference between the slopes of the two AGFs expressed in linear input-output scale. As expected, shallower eCAP AGF slopes were obtained for increased stimulating-recording electrode distance and larger eCAP thresholds for greater electrode-neuron distance. These non-neural factors had also minor interference on the predicted IPG effect.

CONCLUSIONS

The model predictions demonstrate previously found dependencies of eCAP metrics on neural survival and non-neural aspects. The present findings confirm data from animal studies and provide insights into applying described metrics in clinical practice.

Models of Cochlea Used in Cochlear Implant Research: A Review

As the first clinically translated machine-neural interface, cochlear implants (CI) have demonstrated much success in providing hearing to those with severe to profound hearing loss. Despite their clinical effectiveness, key drawbacks such as hearing damage, partly from insertion forces that arise during implantation, and current spread, which limits focussing ability, prevent wider CI eligibility. In this review, we provide an overview of the anatomical and physical properties of the cochlea as a resource to aid the development of accurate models to improve future CI treatments. We highlight the advancements in the development of various physical, animal, tissue engineering, and computational models of the cochlea and the need for such models, challenges in their use, and a perspective on their future directions.