Abstract

A computational model of cat auditory nerve fiber (ANF) responses to electrical stimulation is presented. The model assumes that (1) there exist at least two sites of spike generation along the ANF and (2) both an anodic (positive) and a cathodic (negative) charge in isolation can evoke a spike. A single ANF is modeled as a network of two exponential integrate-and-fire point-neuron models, referred to as peripheral and central axons of the ANF. The peripheral axon is excited by the cathodic charge, inhibited by the anodic charge, and exhibits longer spike latencies than the central axon; the central axon is excited by the anodic charge, inhibited by the cathodic charge, and exhibits shorter spike latencies than the peripheral axon. The model also includes subthreshold and suprathreshold adaptive feedback loops which continuously modify the membrane potential and can account for effects of facilitation, accommodation, refractoriness, and spike-rate adaptation in ANF. Although the model is parameterized using data for either single or paired pulse stimulation with monophasic rectangular pulses, it correctly predicts effects of various stimulus pulse shapes, stimulation pulse rates, and level on the neural response statistics. The model may serve as a framework to explore the effects of different stimulus parameters on psychophysical performance measured in cochlear implant listeners.

Highlights

  • Patients with severe hearing loss or deafness are commonly prescribed with cochlear implants (CIs)

  • The effects of current level on the firing efficiency (FE), the spike latency, and the jitter for anodic and cathodic pulses of 39-μs duration are shown in Figure 3a–c, respectively

  • The results demonstrate that the charge integration properties of the neural membrane derived from responses to monophasic pulses can characterize the responsiveness of the neuron to electrical stimulation sufficiently well to account for the stimulation with biphasic pulses and pulses of alternative shapes

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Summary

Introduction

Patients with severe hearing loss or deafness are commonly prescribed with cochlear implants (CIs). CI signal processing strategies aim to mimic the cochlear processing of the acoustic inputs and to provide the CI listeners the Bessential^ cues for successful communication. They extract the slowly-varying envelopes of the acoustic signals and stimulate the ANFs with a train of biphasic pulses modulated with the processed envelope (Wilson et al 1991). Despite significant efforts in the development of signal processing strategies for better and efficient processing of the acoustical cues, the improvements in the performance of the CI listeners have been minimal and have been related mainly to the more advanced cue extraction strategies

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