scholarly journals Pitch discrimination in the cat through electrical stimulation of the terminal auditory nerve fibers

1976 ◽  
Vol 4 (1) ◽  
pp. 23-27 ◽  
Author(s):  
Aileen J. Williams ◽  
Graeme M. Clark ◽  
Gordon V. Stanley
Keyword(s):  
Electrical Stimulation ◽  
Auditory Nerve ◽  
Nerve Fibers ◽  
Pitch Discrimination ◽  
Auditory Nerve Fibers ◽  
Stimulation Of

scholarly journals A point process framework for modeling electrical stimulation of the auditory nerve

2012 ◽  
Vol 108 (5) ◽  
pp. 1430-1452 ◽  
Author(s):  
Joshua H. Goldwyn ◽  
Jay T. Rubinstein ◽  
Eric Shea-Brown
Keyword(s):  
Electrical Stimulation ◽  
Point Process ◽  
Pulse Rate ◽  
Auditory Nerve ◽  
Electric Stimulation ◽  
Nerve Fibers ◽  
Ideal Observer ◽  
Physiological Data ◽  
Auditory Nerve Fibers ◽  
Insight Into

Model-based studies of responses of auditory nerve fibers 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 spiking activity 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 individual auditory nerve fibers 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 each of these stages can be associated with biophysical mechanisms and related to models of neuronal dynamics. Moreover, we derive a semianalytical procedure that uniquely determines each parameter in the model on the basis of fundamental statistics from recordings of single fiber responses to electric stimulation, including threshold, relative spread, jitter, and chronaxie. The model also accounts for refractory and summation effects that influence the responses of auditory nerve fibers to high pulse rate stimulation. Throughout, we compare model predictions to published physiological data of response to high and low pulse rate stimulation. We find that the model, although constructed to fit data from single and paired pulse experiments, can accurately predict responses to unmodulated and modulated pulse train stimuli. We close by performing an ideal observer analysis of simulated spike trains in response to sinusoidally amplitude modulated stimuli and find that carrier pulse rate does not affect modulation detection thresholds.

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