Graeme Clark Collection

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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]
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    The influence of electrode geometry on the electrically evoked auditory brain stem response
    Shepherd, R. K. ; Hatsushika, S. ; Clark, Graeme M. ( 1988)
    The electrically-evoked auditory brainstem response (EABR) consists of a series of far-field potentials that reflect synchronous neural activity within the auditory brainstem in response to a transient electrical stimulus. The EABR appears relatively simply organized in terms of its amplitude and latency behaviour. The growth in amplitude of wave IV of the EABR, for example, reflects changes in the amplitude of the electrically-evoked VIII nerve compound action potential as a function of stimulus intensity. In addition, single unit population studies have shown a monotonic relationship between the growth in EABR amplitude and the number of nerve fibres being stimulated (Merzenich and White, 1977). The EABR can therefore, provide an insight into the response of the auditory nerve to electrical stimulation. We have used this technique to investigate the efficacy of electrical stimulation of the auditory nerve using a variety of stimulating electrode geometries.