Graeme Clark Collection
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ItemDischarge rate-level functions from dorsal cochlear nucleus single units in response to acoustic and electrical stimulation of the auditory nerve( 1995)Discharge rate-level (I/O) functions possessed by dorsal cochlear nucleus (DCN) units were examined, in response to bipolar electrical stimulation of the cochlea of the barbiturate-anesthetized cat. Spontaneously active units usually possessed nonmonotonic functions with a minimum, and spontaneously inactive units usually possessed monotonic functions or nonmonotonic functions with a maximum (NM+). In response to acoustic high-pass filtered noise, the function relating discharge rate and cut off frequency resembled the same unit's I/O function to electrical stimulation. The I/O functions to acoustic characteristic tones were usually monotonic or NM+. These results suggest that in the DCN, a prerequisite for the generation of acoustic-like responses with an electrical stimulus may be the matching of the cochlear place and spatial extent activated by each stimulus.
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ItemModel of discharge rate from auditory nerve fibers responding to electrical stimulation of the cochlea: identification of cues for current and time-interval coding( 1995)A model of the response of auditory nerve fibers to electrical stimulation of the cochlea is presented. Auditory nerve fiber responses are described in terms of cochlear regions activated by the stimulus: region A, in which the discharge rate equals a value of the pulse rate plus spontaneous activity, and region B, in which the discharge rate is less than pulse rate plus spontaneous activity but greater than spontaneous activity. The cues for intensity and time-interval coding provided by regions A and B are discussed.
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ItemNeural processes in the dorsal cochlear nucleus of the anaesthetised cat investigated from unit responses to electrical stimulation of the auditory nerve( 1994)Extracellular responses of dorsal cochlear nucleus single units were recorded in response to biphasic, bipolar electrical stimulation of spiral ganglion cells and their peripheral processes using a banded electrode array in the scala tympani of the barbiturate anaesthetised cat. The DCN responses to this stimulus were the result of excitatory and suppressive (including inhibitory) processes. The excitatory responses from DCN units were usually within a range of 1.8-2.8 ms and these responses were probably the result of monosynaptic input from the auditory nerve. Latencies > 2.8 ms were most likely due to activation of di- and poly-synaptic pathways from auditory nerve fibres, except that latencies between 3.5-4.75 in hearing animals could have arisen from electrophonic mechanisms. Suppression of spontaneous activity was usually long acting, lasting > 70 ms following each pulse of the pulse train, but short acting suppression with a latency of 3.5-4.75 ms and a duration of < 10 ms was occasionally observed. These suppressive responses probably resulted from synaptic inhibitory input, but neural membrane properties may have contributed. In hearing animals, excitatory latencies within the range 1.8-5.2 ms were similar for units with different response area types or different PSTH patterns in response to acoustic CF tones or noise.
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ItemIntracochlear electrical simulation of normal and deaf cats investigated using brainstem response audiometry( 1983)Brainstem response audiometry for intracochlear electrical stimulation of normal-hearing and deafened cats was investigated. In normal cochleas the brainstem response amplitude grew slowly near threshold as a current-amplitude dependent process, identified as electrophonic in origin. This terminated in a rapidly growing charge-dependent process at approximately 20 dB above threshold, identified as direct electrical stimulation of the auditory nerve. Small levels of white noise (25-35 dB SPL) were sufficient to mask most of the electrophonic response, leaving the direct stimulation process essentially unmodified. In cochleas damaged with d.c. currents and loud sounds, only a rapidly growing charge-dependent process was observed which grew similarly to that in normal-hearing cats but occurred at lower currents. This indicates that possibly the electrical properties of the cochlea were altered in the deafening process, suggesting the inadequacy of normal animals as deaf models for electrical stimulation. Using the technique of derived brainstem responses, it was shown that direct electrical stimulus components were localized to the vicinity of the stimulus electrode with electrophonic components distributed more widely. However, at high currents there was some evidence of the stimulus spreading into the internal auditory meatus.
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ItemThe auditory brainstem response in hearing and deaf cats evoked by intracochlear electrical stimulation(Monash University Press, 1983)This study was performed to investigate in detail the auditory brainstem response (ABR) for intracochlear electrical stimulation. Brainstem response audiometry is a simple, noninvasive procedure with the responses under many stimulus conditions being readily understood in terms of single auditory nerve discharge properties. The amplitude and latency behaviour of the Nl brainstem response correlates well with that recorded directly from the auditory nerve (Huang & Buchwald, 1978). In addition, the brainstem response can be divided into frequency-specific components corresponding to tonotopical locations in the cochlea, as exhibited in the method of derived responses (e.g. Parker &Thornton, 1978). It is therefore well suited to both physiological and clinical investigation of auditory function and therefore should be useful in evaluating auditory function under conditions of electrical stimulation of the cochlea.
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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]
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ItemAdvances in relating cochlear implant physiology and psychophysics [Abstract]( 1999)More than a decade has passed since apparent discrepancies between physiological and psychophysical thresholds in cochlear implant users were first pointed out. This incongruity has been largely ignored in the intervening time. In a recent series of studies we have undertaken to determine if the definition of threshold in physiological studies is the cause of these differences. Analysis of auditory nerve physiology indicates that fluctuations in the membrane potential are a significant source of stochastic activity (noise) in electrical stimulation, such that responses are best described by discharge probability as a function of stimulus intensity, rather than just a simple deterministic (zero-noise) threshold. We hypothesize that quite low discharge probabilities in individual fibers may be sufficient to account for psychophysical thresholds, if responses in a population of fibers are used in this task by higher auditory pathways.
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ItemPrediction of variance in neural response to cochlear implant stimulation and its implications for perception [Abstract]( 1997)Cochlear implant patients' perception of sound is derived via electrical pulses arising from an electrode array. Chosen aspects of the acoustic spectrum are coded via a stimulation pattern designed according to some sound coding algorithm. Thus, a patients' ability to discriminate between sounds, and in turn their understanding, is directly related to their ability to differentiate between the patterns of electrical stimulation which code various sounds.
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ItemA stochastic model of the electrically stimulated nerve designed for the analysis of large-scale population [Abstract]( 1997)Accurate models of Auditory Nerve (AN) response to electrical stimulation may aid in the development of speech processing strategies for cochlear implants. Most models of AN response to electrical stimulation utilize deterministic (non-random) description in spite of strong evidence for stochastic (random) activity in physiological data. Inclusion of stochastic activity in complex models of neural response such as the Hodgkin-Huxley equations has proven to be computationally expensive. They are therefore unsuitable at this time for the calculation of large-scale population responses which could be required for the investigation of sound coding in ensembles of nerve fibers, for the explanation or prediction of psychophysical results, or for the development of speech processing strategies for cochlear implants. It is therefore necessary to develop a simpler model of single-fiber response to electrical stimulation which includes stochastic activity.
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ItemElectrical stimulation of the auditory nerve: prediction psychophysical by a model including stochastic aspects of neural response [Abstracts]( 1997)Accurate models of Auditory Nerve (AN) response to electrical Stimulation may assist with the development of speech processing strategies for cochlear implants. Until recently most models of AN response to electrical stimulation have utilised deterministic (non random) descriptions, in spite of strong evidence for stochastic (random) components of behaviour in the neurophysiological data models of auditory performance using these deterministic descriptions have been unable to predict many important psychophysical phenomena. Can stochastic models improve these predictions.