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.
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.
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