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Unifying information theory and machine learning in a model of electrode discrimination in cochlear implants
- Source :
- PLoS ONE, Vol 16, Iss 9, p e0257568 (2021), PLoS ONE
- Publication Year :
- 2021
- Publisher :
- Public Library of Science (PLoS), 2021.
-
Abstract
- Refereed/Peer-reviewed 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. In this paper, an information theoretic method and machine learning technique are unified in a model to investigate the extent to which key factors limit cochlear implant electrode discrimination. The framework uses a neural network classifier to predict which electrode is stimulated for a given simulated activation pattern of the auditory nerve, and mutual information is then estimated between the actual stimulated electrode and predicted ones. We also investigate how and to what extent the choices of parameters affect the performance of the model. The advantages of this framework include i) electrode discrimination ability is quantified using information theory, ii) it provides a flexible framework that may be used to investigate the key factors that limit the performance of cochlear implant users, and iii) it provides insights for future modeling studies of other types of neural prostheses.
- Subjects :
- Medical Implants
Computer science
Physiology
medicine.medical_treatment
Action Potentials
computer.software_genre
Information theory
Nervous System
Activation pattern
Machine Learning
Nerve Fibers
Animal Cells
Cochlear implant
Medicine and Health Sciences
Electrochemistry
Limit (mathematics)
electrode discrimination
Neurons
Multidisciplinary
Neural Prosthesis
Nerves
Mutual information
Cochlear Implantation
Cochlea
Electrophysiology
Chemistry
Physical Sciences
Inner Ear
Engineering and Technology
Medicine
Cellular Types
Anatomy
Research Article
Biotechnology
Computer and Information Sciences
Speech perception
Neural Networks
Science
Neurophysiology
Surgical and Invasive Medical Procedures
Bioengineering
Machine learning
Membrane Potential
Auditory Nerves
Pitch Discrimination
cochlear implants
medicine
otorhinolaryngologic diseases
Humans
Electrodes
hearing loss
Functional Electrical Stimulation
business.industry
Electrode Potentials
Biology and Life Sciences
Cell Biology
Models, Theoretical
Individual level
Cochlear Implants
Ears
Cellular Neuroscience
Medical Devices and Equipment
Artificial intelligence
business
computer
Head
Neuroscience
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 16
- Issue :
- 9
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....66d19b325d1015aa19162957a23317aa