Graeme Clark Collection
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ItemRenewal-process approximation of a stochastic threshold model for electrical neural stimulation( 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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ItemInner ear implants(Dekker, 2004)The cochlear implant is an electronic device that brings useful hearing to severely to profoundly deaf people through multiple-channel electrical stimulation of the auditory nerves in the inner ear. This is required if their inner ears are so badly damaged by injury and disease, or so inadequately developed, that they cannot provide sufficient hearing for communication, even when the sound is amplified with a hearing aid. By stimulating the nerve directly with patterns of electrical pulses, the implant bypasses the normal function of the sense organ of hearing in the inner ear to partially reproduce the coding of sound. It consists of a wearable speech processor that picks up sound with a microphone, analyzes the signal, and then sends it by radio waves to the implanted receiver stimulator, which decodes the message and stimulates the electrode wires inserted into the inner ear.
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ItemTemporal processing from the auditory nerve to the medial nucleus of the trapezoid body in the rat(ELSEVIER SCIENCE BV, 2001-09)This investigation examines temporal processing through successive sites in the rat auditory pathway: auditory nerve (AN), anteroventral cochlear nucleus (AVCN) and the medial nucleus of the trapezoid body (MNTB). The degree of phase-locking, measured as vector strength, varied with intensity relative to the cell's threshold, and saturated at a value that depended upon stimulus frequency. A typical pattern showed decline in the saturated vector strength from approximately 0.8 at 400 Hz to about 0.3 at 2000 Hz, with similar profiles in units with a range of characteristic frequencies (480-32,000 Hz). A new expression for temporal dispersion indicates that this variation corresponds to a limiting degree of temporal imprecision, which is relatively consistent between different cells. From AN to AVCN, an increase in vector strength was seen for frequencies below 1000 Hz. At higher frequencies, a decrease in vector strength was observed. From AVCN to MNTB a tendency for temporal coding to be improved below 800 Hz and degraded further above 1500 Hz was seen. This change in temporal processing ability could be attributed to units classified as primary-like with notch (PL(N)). PL(N) MNTB units showed a similar vector strength distribution to PL(N) AVCN units. Our results suggest that AVCN PL(N) units, representing globular bushy cells, are specialised for enhancing the temporal code at low frequencies and relaying this information to principal cells of the MNTB.
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ItemChronic monopolar high rate simulation of the auditory nerve: physiological and histopathological effects(Kugler Publications, 2001)There is clinical interest in the development of high rate speech processing strategies, since there are indications that these might enhance speech perception due to an improved representation of the rapid variations in amplitude of speech. Significant improvement in speech perception using high rate stimulation has been demonstrated in cochlear implant recipients. However, it is important that the long-term safety of high rate stimulation is clearly established prior to its general clinical application. This is especially important, since acute animal studies have shown that high rate stimulation can induce a reduction in the excitability of the auditory nerve. This was also associated with an increase in both threshold and latency of the electrically evoked auditory brainstem response (EABR). However, while a chronic stimulation study indicated that monopolar electrical stimulation of the auditory nerve at rates of 1000 pulses per second (pps)/channel (three channels) had no adverse effects on the spiral ganglion cell density (SGCO),5 there is limited data concerning higher rates. In the present study, we evaluated the electrophysiological and histopathological effects of chronic monopolar electrical stimulation of the auditory nerve using considerably higher stimulus rates than have been used in previous studies.
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ItemAdvances in computational modelling of cochlear implant physiology and perception(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]