Robert Morse

The application of suprathreshold stochastic resonance to cochlear implant coding

In this paper we explore the possibility of using a recently discovered form of stochastic resonance - termed suprathreshold stochastic resonance - to improve speech comprehension in patients fitted with cochlear implants. A leaky-integrate-and-fire (LIF) neurone is used to model cochlear nerve activity when subject to electrical stimulation. This model, in principle, captures key aspects of temporal coding in analogue cochlear implants. Estimates for the information transmitted by a population of nerve fibres is obtained as a function of internal (neuronal) noise level. We conclude that SSR does indeed provide a possible mechanism by which information transmission along the cochlear nerve can be improved - and thus may well lead to improved speech comprehension.

Neural Population Coding is Optimized by Discrete Tuning Curves

The sigmoidal tuning curve that maximizes the mutual information for a Poisson neuron, or population of Poisson neurons, is obtained. The optimal tuning curve is found to have a discrete structure that results in a quantization of the input signal. The number of quantization levels undergoes a hierarchy of phase transitions as the length of the coding window is varied. We postulate, using the mammalian auditory system as an example, that the presence of a subpopulation structure within a neural population is consistent with an optimal neural code.

Noise-enhanced information transmission in a model of multichannel cochlear implantation

Cochlear implants are used to restore functional hearing to people with profound deafness. Success, as measured by speech intelligibility scores, varies greatly amongst patients; a few receive almost no benefit while some are able to use a telephone under favourable listening conditions. Using a novel nerve model and the principles of suprathreshold stochastic resonance, we demonstrate that the rate of information transfer through a cochlear implant system can be globally maximized by the addition of noise. If this additional information could be used by the brain then it would lead to greater speech intelligibility, which is important given that the intelligibility of all cochlear implant recipients is poorer than that of people with normal hearing, particularly in adverse listening conditions.

Use of suprathreshold stochastic resonance in cochlear implant coding

In this article we discuss the possible use of a novel form of stochastic resonance, termed suprathreshold stochastic resonance (SSR), to improve signal encoding/transmission in cochlear implants. A model, based on the leaky-integrate-and-fire (LIF) neuron, has been developed from physiological data and use to model information flow in a population of cochlear nerve fibers. It is demonstrated that information flow can, in principle, be enhanced by the SSR effect. Furthermore, SSR was found to enhance information transmission for signal parameters that are commonly encountered in cochlear implants. This, therefore, gives hope that SSR may be implemented in cochlear implants to improve speech comprehension.

Cochlear Implant Coding with Stochastic Beamforming and Suprathreshold Stochastic Resonance

Cochlear implants are prosthetic devices used to provide hearing to people who would otherwise be profoundly deaf. The deliberate addition of noise to the electrode signals can in principle increase the amount of information transmitted via an effect termed suprathreshold stochastic resonance (SSR). However, for SSR to occur the noise must be added in such a way so as to achieve, at least partial, independent stochastic activity across the nerve fibre population.

STOCHASTIC BEAMFORMING FOR COCHLEAR IMPLANT CODING

Cochlear implants are prosthetic devices used to provide hearing to people who would otherwise be profoundly deaf. The deliberate addition of noise to the electrode signals could increase the amount of information transmitted, but standard cochlear implants do not replicate the noise characteristic of normal hearing because if noise is added in an uncontrolled manner with a limited number of electrodes then it will almost certainly lead to worse performance. Only if partially independent stochastic activity can be achieved in each nerve fibre can mechanisms like suprathreshold stochastic resonance be effective. We are investigating the use of stochastic beamforming to achieve greater independence. The strategy involves presenting each electrode with a linear combination of independent Gaussian noise sources. Because the cochlea is filled with conductive salt solutions, the noise currents from the electrodes interact and the effective stimulus for each nerve fibre will therefore be a different weighted sum of the noise sources. To some extent therefore, the effective stimulus for a nerve fibre will be independent of the effective stimulus of neighbouring fibres. For a particular patient, the electrode position and the amount of current spread are fixed. The objective is therefore to find the linear combination of noise sources that leads to the greatest independence between nerve discharges. In this theoretical study we show that it is possible to get one independent point of excitation (one null) for each electrode and that stochastic beamforming can greatly decrease the correlation between the noise exciting different regions of the cochlea.

A hierarchy of phase transitions in optimal neuronal coding : from binary to M-ary discrete optimal codes

We have investigated how optimal coding for neural systems changes with the time available for decoding. Optimization was in terms of maximizing information transmission. We have estimated the parameters for Poisson neurons that optimize Shannon transinformation with the assumption of rate coding. We observed a hierarchy of phase transitions from binary coding, for small decoding times, toward discrete (M-ary) coding with two, three and more quantization levels for larger decoding times. We postulate that the presence of subpopulations with specific neural characteristics could be a signiture of an optimal population coding scheme and we use the mammalian auditory system as an example.