Personalised stimulation strategies for cochlear implants using EEG source analysis

Cochlear implants (CIs) are successful in restoring hearing in people with severe hearing loss and the benefit CI recipients gain from their device are often life-changing. However, in adverse listening environments speech perception with a CI is highly challenging and there is a high variability in performance across CI users. Currently, there is limited knowledge on how the individual’s auditory pathway processes the electrical CI stimulation. More importantly, it is unclear which neural processes contribute to the large inter-subject variability in performance. Insight in these neural processes, both at cortical and subcortical level of each individual CI recipient could, however, be used to develop personalized stimulation algorithms to improve performance. This PhD project first aims to develop EEG source analysis methods that can overcome the stimulation artifacts caused by the CI who have thus far prevented application of source analysis in CI users. Second, this newly developed method will be used to investigate the neural processing of electric hearing and the factors that contribute to (behavioural) performance on a subject-specific level. Finally, this knowledge will be used to develop neuro-inspired personalized CI stimulation strategies.