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SUMMARY:Nonlinear optimization method for the estimation of neural activat
 ion patterns in users of cochlear implants - Tobias Goering\, MRC Cognitio
 n and Brain Sciences Unit
DTSTART:20180130T130000Z
DTEND:20180130T140000Z
UID:TALK100738@talks.cam.ac.uk
CONTACT:Dr Vivien Gruar
DESCRIPTION:"A cochlear implant (CI) is an auditory prosthesis that provid
 es a sensation of hearing to more than half a million deaf or severely hea
 ring-impaired individuals. A CI uses an electrode array placed in the inne
 r ear to electrically stimulate frequency-specific regions of auditory ner
 ve fibres\, as occurs in the normal hearing ear when listening to sound. H
 owever\, sometimes stimulation sites along the array lie in neural “dead
  regions”\, or are stimulating neurons at an adjacent turn of the cochle
 a\, thus leading to distortions to the ideal pattern of excitation. These 
 distortions are often harmful to sound perception and may result in diffic
 ulties for the user to understand speech. \nThe aim of the proposed resear
 ch project is to develop and evaluate an objective method that can be appl
 ied to CI users so as to identify these “distortions” and to guide met
 hods for re-programming the CI so as to minimize their negative effects. T
 he project is currently on-going and builds on data measurements from neur
 al 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 lea
 der and two post-docs. This is an exciting opportunity for an interested s
 tudent to apply their theoretical knowledge to biomedical research and to 
 experience being part of a research group at the MRC CBU. While the propos
 ed task is quite defined for this project\, creative and innovative approa
 ches to improve the estimation performance and robustness of the algorithm
  are welcomed.\nCosentino\, S.\, Gaudrain\, E.\, Deeks\, J. M.\, & Carlyon
 \, R. P. (2016). Multistage nonlinear optimization to recover neural activ
 ation patterns from evoked compound action potentials of cochlear implant 
 users. IEEE Transactions on Biomedical Engineering\, 63(4)\, 833-840.\n"\n
LOCATION:MR3 Centre for Mathematical Sciences
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