A point process framework for modeling electrical stimulation of the auditory nerve
Joshua H. Goldwyn, Jay T. Rubinstein, Eric Shea-Brown

TL;DR
This paper introduces a compact point process model for auditory nerve responses to electrical stimulation, aiding cochlear implant research by accurately capturing neural responses with biophysical relevance.
Contribution
It develops a biophysically inspired point process model that can be parameterized from fundamental response statistics, improving simulation efficiency and insight into neural encoding.
Findings
Model accurately predicts neural responses to electrical stimulation.
Refractory and summation effects are incorporated into the model.
Pulse rate does not influence modulation detection thresholds in simulations.
Abstract
Model-based studies of auditory nerve responses to electrical stimulation can provide insight into the functioning of cochlear implants. Ideally, these studies can identify limitations in sound processing strategies and lead to improved methods for providing sound information to cochlear implant users. To accomplish this, models must accurately describe auditory nerve spiking while avoiding excessive complexity that would preclude large-scale simulations of populations of auditory nerve fibers and obscure insight into the mechanisms that influence neural encoding of sound information. In this spirit, we develop a point process model of the auditory nerve that provides a compact and accurate description of neural responses to electric stimulation. Inspired by the framework of generalized linear models, the proposed model consists of a cascade of linear and nonlinear stages. We show how…
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