Entropy | Best ECR Presentation Award for CNS*2022 Workshop on Methods of Information Theory in Computational Neuroscience—Winner Announced

We are pleased to announce the Best ECR (Early Career Researcher) Presentation Award, sponsored by Entropy (ISSN: 1099-4300) for CNS*2022 Workshop on Methods of Information Theory in Computational Neuroscience, which was granted to Dr. Demi Gao at the University of Melbourne. Congratulations!

“Towards Personalised Cochlear Implants: Quantifying Hearing Performance Using Information Theory”

Abstract:
Despite the development and success of cochlear implants over several decades, wide inter-subject variability in speech perception is reported. This suggests that cochlear implant user-dependent factors limit speech perception at the individual level. Clinical studies have demonstrated the importance of the number, placement, and insertion depths of electrodes on speech recognition abilities. However, these do not account for all inter-subject variability and to what extent these factors affect speech recognition abilities has not been studied. We unified information theoretic method and machine learning technique to quantitatively study the extent to which key factors limit the hearing performance with cochlear implants. The approach provides insights into personalised strategies for improving speech recognition outcomes.