People with more severe hearing loss can be helped to hear again using a cochlear implant - a surgically implanted device that electrically stimulates the cochlear nerve (the nerve of hearing). Part of the device is a set of electrodes within the cochlea (the inner ear). Good speech perception with cochlear implants depends on appropriate adjustment of device parameters, the fitting , by an audiologist. With adults, the initial fitting is usually based on perceptual measurements that require verbal feedback from the patient. When verbal feedback is not possible, the parameters are typically set relative to the minimum level required to get a measurable electrical compound action potential (ECAP) - the summed electrical response from all the nerve fibres that can be recorded by modern cochlear implants. Standard ECAP methods, however, do not lead to a good estimate of perceptual threshold because the rate of stimulation used is much lower than that used for everyday listening; fitting based on ECAPs is therefore suboptimal. Based on our previous animal studies, we are proposing a new method to measure the ECAP threshold in humans. This method involves measuring the variability of an ECAP rather than its average size and will be both more accurate and faster. We will test the approach with cochlear implants patients from Selly Oak Hospital (Birmingham) and the House Ear Institute (Los Angeles); all tests will be in collaboration with Advanced Bionics SARL who will provide the hardware required to test patients.We will combine this method with a computer model to predict the number of cochlear nerve fibres in different regions of the patient's cochlea and determine how the current from each electrode spreads throughout the cochlea. Patient-specific models are required to account for the substantial intersubject variability arising, for example, from underlying pathology, the degree of nerve survival, and electrode placement during surgery. The model will be used to guide fitting and decide, for example, which electrodes should be active. This combination of physiological and computational techniques will overcome the limitation of using ECAPs alone to determine channel interaction (how the nerve activity generated by different electrodes overlap): With the standard use of ECAPs to gauge channel interaction, the effect of fibre distribution and current spread cannot be separated. Such a distinction is clinically important because electrodes need not be made inactive for low nerve survival alone.During the project, these patient-specific models will be extended to predict the pattern of nerve activity in response to more general stimuli. The initial model will be modified so that nerve fibres are simulated by a nerve model we have previously developed. The patient-specific parameters from the model will be selected to match ECAP data, which will require the development of novel physiological methods to improve the reliability of the data. In the later stages of the project, the model will be used to relate perceptual measures to the predicted nerve activity and therefore enable a greater understanding of neural mechanisms underlying the sensory perception of electrical and acoustic stimulation. This will lead to better cochlear implant design. Contemporary fitting by an audiologist is expensive and insufficient to enable a systematic investigation of cochlear implant parameters. In future programmes of work, extended patient-specific models will be used to quickly highlight potentially useful parameter values for standard strategies, e.g. the optimum stimulation rate, and to guide the development of novel strategies. All the above ECAP methods and models will be validated with patients with whom verbal feedback is possible. The enhanced fitting procedures derived in this project are expected to increase speech intelligibility and lead to a better quality-of-life for cochlear implant users.

Cochlear implants (CIs) are used to restore the hearing of profoundly deaf people by electrical stimulation of the cochlear nerve (the nerve of hearing). Notionally, a CI uses electrical stimulation to evoke neural activity (i.e. firing of the cochlear nerve fibres) that mimics the neural activity that would have occurred in normal hearing. However, one aspect of normal neural activity that is not mimicked by conventional CI stimulation is the gross random 'firing' of cochlear nerve fibres - this activity occurs even in the absence of an input stimulus. In the normal ear, this gross random activity is caused by sources of internal noise in the hair cells that transduce sound signals into electrical signals. The noise has several sources such as: Brownian motion of the stereocilia (hairs) of a hair cell, and the random release of the chemicals that transmit the signal from a hair cell to cochlear nerve fibres. These noise sources are absent in the deafened ear because profound deafness is associated with complete loss of the hair cells. There is now considerable evidence, however, that these noise sources are an essential part of normal neural coding and we have therefore previously proposed that they should be re-introduced back into the deafened ear by incorporating noise sources into CIs.But traditionally noise is regarded as a nuisance, and for good reason; if the noise is added in an uncontrolled manner it will almost certainly lead to worse speech comprehension for cochlear implantees. To be useful the noise waveform that excites a particular cochlear nerve fibre must be dissimilar to those that stimulate neighbouring fibres - this will ensure that the firing of adjacent fibres will be independent. Simply applying a noisy current to each surgically implanted electrode is unlikely to produce the desired independence; this is because the cochlea is filled with conductive salt solutions that causes the currents from the electrodes to spread throughout the cochlea; the noise currents therefore interact and result in an effective stimulus that is strongly correlated over a wide spatial range. To circumvent this problem we have developed a technique that reduces the effect of the current spread. The noise currents for each electrode are derived from a sum of independent noise sources, each scaled by a weighting term; these weights can be chosen to produce a spatial random field with a specified de-correlation length (the distance over which the stimulus becomes uncorrelated). In this manner quasi-independent firing can be achieved across a population of cochlear nerve fibres. We refer to this technique as stochastic beamforming because it relies on the incoherent summation of the noise sources to produces 'beams' of zero correlation - this concept is similar to beamforming in antenna arrays. A preliminary computational study has shown that this approach appears feasible and extremely robust.We propose to extend our preliminary study and use more complete models of the electrically stimulated ear. Critically, we will test the approach with users of the Clarion cochlear implant (Advanced Bionics Ltd). We will measure the extent to which our strategy enables independent noise stimulation and we will measure the improvement to the speech comprehension of implantees. These tests will be done at St Thomas' Hospital (London) and in collaboration with Dr Monita Chatterjee (University of Maryland) and Advanced Bionics. The importance of this study cannot be overstated. In our previous and current EPSRC-funded modelling work, we have clearly demonstrated the potential for using noise to improve speech comprehension. The method, however, will only work in practice if we can get greater independence between the nerve impulses for the population of cochlear nerve fibres. This work is the essential step that will enable us to realise the benefits that stochastic coding strategies promise.