Inferring the dynamic range of electrode current by using an information theoretic model of cochlear implant stimulation

Abstract

Information theory has been used in estimating the performance of cochlear implants, which restore partial hearing to people by replacing the function of missing inner hair cells with an electrode array. Previous work has already developed a channel model of the electrode-neural interface in which the channel input is defined as the choice of electrodes and the channel output is defined as the normalized location of all active auditory nerve fibers. This model enables prediction of the optimal number of electrodes for cochlear implants by calculating the mutual information between channel input and channel output. In this paper, we calculate the mutual information with a varied model parameter, in particular, the electrode current. First, we investigate to what extent the different electrode current levels impact on the performance of the modeling framework. Then we estimate the dynamic range of electrode current based on the mutual information calculation. The results in this paper may provide a theoretical guide for optimizing stimulation strategies for future users of cochlear implants.