Nonlinear optimization method for the estimation of neural activation patterns in users of cochlear implants

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• Tobias Goering, MRC Cognition and Brain Sciences Unit
• Tuesday 30 January 2018, 13:00-14:00
• MR3 Centre for Mathematical Sciences.

If you have a question about this talk, please contact Dr Vivien Gruar.

“A cochlear implant (CI) is an auditory prosthesis that provides a sensation of hearing to more than half a million deaf or severely hearing-impaired individuals. A CI uses an electrode array placed in the inner ear to electrically stimulate frequency-specific regions of auditory nerve fibres, as occurs in the normal hearing ear when listening to sound. However, sometimes stimulation sites along the array lie in neural “dead regions”, or are stimulating neurons at an adjacent turn of the cochlea, thus leading to distortions to the ideal pattern of excitation. These distortions are often harmful to sound perception and may result in difficulties for the user to understand speech. The aim of the proposed research project is to develop and evaluate an objective method that can be applied to CI users so as to identify these “distortions” and to guide methods for re-programming the CI so as to minimize their negative effects. The project is currently on-going and builds on data measurements from neural action potentials in CI users that will be used during the development. The student will be given the specific task to propose and evaluate a new method for non-linear optimization within the current software framework. The student will build on and compare to a previously published method by our lab (Cosentino et al., 2016) and will be supervised by the group leader and two post-docs. This is an exciting opportunity for an interested student to apply their theoretical knowledge to biomedical research and to experience being part of a research group at the MRC CBU . While the proposed task is quite defined for this project, creative and innovative approaches to improve the estimation performance and robustness of the algorithm are welcomed. Cosentino, S., Gaudrain, E., Deeks, J. M., & Carlyon, R. P. (2016). Multistage nonlinear optimization to recover neural activation patterns from evoked compound action potentials of cochlear implant users. IEEE Transactions on Biomedical Engineering, 63(4), 833-840. “

This talk is part of the Cambridge Mathematics Placements Seminars series.

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