Enhanced cochlear implant coding using stochastic beam-forming

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.