Biophysical and Phenomenological Models of Cochlear Implant Stimulation

Abstract

Numerous studies showed that cochlear implant (CI) users generally prefer individualized stimulation rates in order to maximize their speech understanding. The underlying reasons for the reported variation in speech perception performance as a function of CI stimulation rate is unknown. However, multiple interacting electrophysiological processes influence the auditory nerve (AN) in response to high-rate CI stimulation. Experiments studying electrical pulse train stimulation of cat AN fibers (ANFs) have demonstrated that spike rates slowly decrease over time relative to onset stimulation and is often attributed to spike rate (spike-triggered) adaptation in addition to refractoriness. Interestingly, this decay tends to adapt more rapidly to higher stimulation rates. This suggests that subthreshold adaptation (accommodation) plays a critical role in reducing neural excitability.

Using biophysical computational models of cat ANF including ion channel types such as hyperpolarization-activated cyclic nucleotide-gated (HCN) and low threshold potassium (KLT) channels, we measured the strength of adaptation in response to pulse train stimulation for a range of current amplitudes and pulse rates. We also tested these stimuli using a phenomenological computational ANF model capable of applying any combination of refractoriness, facilitation, accommodation, and/or spike rate adaptation.

The simulation results show that HCN and KLT channels contribute to reducing model ANF excitability on the order of 1 to 100 ms. These channels contribute to both spike rate adaptation and accommodation. Using our phenomenological model ANF we have also shown that accommodation alone can produce a slow decay in ANF spike rates responding to ongoing stimulation.

The CI users that do not benefit from relatively high stimulation rates may be due to ANF accommodation effects. It may be possible to use electrically evoked compound action potentials (ECAP) recordings to identify CI users exhibiting strong effects of accommodation, i.e., the increasing strength of adaptation as a function of increasing stimulation rate.