Computer modelling of the cochlear implant-brain interface: factors influencing speech perception

Cochlear implants can recover a basic sense of hearing to the profoundly deaf, but they cannot restore normal hearing. What limits the transmission of sound information through cochlear implants? This project aims to identify the key factors using computer simulations.
Most cochlear implant (CI) users regain at least a basic ability to understand speech. This is remarkable given that CIs provide a much sparser information than the normal cochlea. However, outcomes with CIs vary greatly between individuals and CI users’ ability to understand speech in noisy environments is usually very limited. Despite current progress in CI technology, the source of these limitations is still poorly understood. This project aims to create a better understanding of the factors that might influence CI outcome using computer modelling of auditory nerve responses to CI stimulation, allied with machine learning methods and information theory. We will test how factors known to influence CI performance, such as electrode placement and auditory nerve survival, will affect the dynamic range and frequency resolution of the simulated responses.
Applicants should be highly motivated, highly numerate, with good programming skills, and have a first- or upper second-class degree in a quantitative subject such as engineering, computer science, maths or physics. They should have an interest in auditory neuroscience and willing to work in an interdisciplinary environment. Information on how to apply can be found at: http://www.ihr.mrc.ac.uk/pages/postgraduates/postgraduate_homepage.

With Dr Chris Sumner, Dr Robert Pierzycki, Dr Padraig Kitterick