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Horne, C.D.F., Sumner, C.J. 
ORCID: 0000-0002-2573-7418 and Seeber, B.U.,
2016.
A phenomenological model of the electrically stimulated auditory nerve fiber: temporal and biphasic response properties.
Frontiers in Computational Neuroscience, 10: 8.
ISSN 1662-5188
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Abstract
We present a phenomenological model of electrically stimulated auditory nerve fibers (ANFs). The model reproduces the probabilistic and temporal properties of the ANF response to both monophasic and biphasic stimuli, in isolation. The main contribution of the model lies in its ability to reproduce statistics of the ANF response (mean latency, jitter, and firing probability) under both monophasic and cathodic-anodic biphasic stimulation, without changing the model's parameters. The response statistics of the model depend on stimulus level and duration of the stimulating pulse, reproducing trends observed in the ANF. In the case of biphasic stimulation, the model reproduces the effects of pseudomonophasic pulse shapes and also the dependence on the interphase gap (IPG) of the stimulus pulse, an effect that is quantitatively reproduced. The model is fitted to ANF data using a procedure that uniquely determines each model parameter. It is thus possible to rapidly parameterize a large population of neurons to reproduce a given set of response statistic distributions. Our work extends the stochastic leaky integrate and fire (SLIF) neuron, a well-studied phenomenological model of the electrically stimulated neuron. We extend the SLIF neuron so as to produce a realistic latency distribution by delaying the moment of spiking. During this delay, spiking may be abolished by anodic current. By this means, the probability of the model neuron responding to a stimulus is reduced when a trailing phase of opposite polarity is introduced. By introducing a minimum wait period that must elapse before a spike may be emitted, the model is able to reproduce the differences in the threshold level observed in the ANF for monophasic and biphasic stimuli. Thus, the ANF response to a large variety of pulse shapes are reproduced correctly by this model.
| Item Type: | Journal article | ||||
|---|---|---|---|---|---|
| Publication Title: | Frontiers in Computational Neuroscience | ||||
| Creators: | Horne, C.D.F., Sumner, C.J. and Seeber, B.U. | ||||
| Publisher: | Frontiers Research Foundation | ||||
| Date: | 8 February 2016 | ||||
| Volume: | 10 | ||||
| ISSN: | 1662-5188 | ||||
| Identifiers: |
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| Rights: | Copyright © 2016 Horne, Sumner and Seeber. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. | ||||
| Divisions: | Schools > School of Social Sciences | ||||
| Record created by: | Jonathan Gallacher | ||||
| Date Added: | 27 Feb 2019 10:41 | ||||
| Last Modified: | 27 Feb 2019 10:41 | ||||
| URI: | https://irep.ntu.ac.uk/id/eprint/35825 |
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