This is a Fellowship Grant awarded to Dr Charlotte Garcia at the University of Cambridge. It will start in March 2026.
Background
Cochlear implants are medical devices that restore a sense of hearing to people with severe to profound hearing loss. They do this by sending electrical signals directly to the hearing nerve inside the ear. They work very well for some users, allowing them to hear and understand speech. However, others do not get as much benefit from their devices and struggle to follow conversations, especially in noisy environments with background conversations or street noise. There is a lot of variation in the hearing abilities of cochlear implant users, including when perceiving tone of voice or listening to music, as these sounds rely on hearing different frequencies, or pitches, of sound.
The external processor of a cochlear implant separates the sound information it receives into bands based on pitch – each band is called a channel, and they can be manipulated and programmed separately. Numerous researchers have tested personalised approaches for programming cochlear implant software, based on switching off channels if they are identified as being inefficient at communicating with the hearing nerve. The signals from these channels are then redirected into other, more efficient channels. So far, however, these approaches have led to only small improvements in understanding speech.
One reason for this could be that these approaches use only one technique at a time to identify good vs bad channels. Another reason is that they focus on changes in understanding speech, a complex signal that requires a person to be able to detect multiple features of a sound. In this project, Charlotte will focus on a simpler sound signal – pitch – and use multiple methods to identify the best channels for individual cochlear implant users, providing a personalised approach to improving their hearing.
Aims
The aim of the project is to identify ways to improve the ability of cochlear implant users to hear different pitches of sound. To do this, Charlotte will first build a multi-faceted ‘fingerprint’ of the relationship between the cochlear implant and the ear of each individual user. This will involve experiments that will record the response of the brain to sound signals delivered through the implant. Additionally, Charlotte will measure behavioural responses to sounds – she will send signals to different channels and at different speeds within the implant, and ask users to tell her which, of a pair of sounds, is higher in pitch.
When taken together, the brain measurements and the pitch-rating information may help to design automated procedures for choosing the settings of an individual’s cochlear-implant software. It may also identify the best channels for hearing different pitches of sound.
Benefit
Ultimately, this research will shed light on the relationships between different methods for measuring how individuals hear through their cochlear implant. This will help improve how clinicians assess how people using a cochlear implant can hear.
This project will also provide insight into ways of programming cochlear implants to use additional pitch cues that help users perceive details such as tone of voice, better understand tonal languages like Mandarin, and pitches of melodies or chords within music.