Graeme Clark Collection

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Author: O'Leary, Stephen × End date: 2009 × Start date: 2000 × Subject: auditory nerve ×

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    Renewal-process approximation of a stochastic threshold model for electrical neural stimulation
    Bruce, Ian C. ; Irlicht, Laurence S. ; White, Mark W. ; O'Leary, Stephen J. ; Clark, Graeme M. ( 2000)
    In a recent set of modelling studies we have developed a stochastic threshold model of auditory nerveresponse to single biphasic electrical pulses (Bruce et al., 1999c) and moderate rate (less than 800 pulses per second) pulse trains (Bruce et al., 1999a). In this article we derive an analytical approximation for the single-pulse model, which is then extended to describe the pulse-train model in the case of evenly timed, uniform pulses. This renewal process description provides an accurate and computationally efficient model of electrical stimulation of single auditory nerve fibers by a cochlear implant that may be extended to other forms of electrical neural stimulation.
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    Advances in computational modelling of cochlear implant physiology and perception
    Bruce, Ian C. ; White, M. W. ; Irlicht, L. S. ; O'Leary, Stephen J. ; Clark, Graeme M. (IOS Press, 2001)
    Models of cochlear implant physiology and perception have historically utilized deterministic descriptions of auditory-nerve (AN) responses to electrical stimulation, which ignore stochastic activity present in the response. Physiological models of AN responses have been developed that do incorporate stochastic activity [8][13][14][27][38][39], but the consequences of stochastic activity for the perception of cochlear implant stimulation have not been investigated until recently [3]. Such an investigation is prompted by inaccuracies in predicting cochlear implant perception by deterministic models. For example, studies of single-fiber responses, where only an arbitrary deterministic measure of threshold is recorded, do not accurately predict perceptual threshold versus phase duration (strength-duration) curves for sinusoidal stimulation [24] or for pulsatile stimulation [25][26]. Furthermore, strength-duration curves of cochlear implant users are not well predicted by deterministic Hodgkin Huxley type models [25] [30].However, the complexity of previous stochastic physiological models has made the computation of responses for large numbers of fibers both laborious and time-consuming. Furthermore, the parameters of these models are often not easily matched to the fiber characteristics of the auditory nerve in humans or other mammals. This has prompted us to develop a simpler and more computationally efficient model of electrical stimulation of the auditory nerve [1][2][4] which is capable of direct and rapid prediction of perceptual data[3]