Our Research Updates in Archways give a snapshot of the Rice ARCHES Initiative researchers' current work, research progress, and future directions. Art & Science at the MOH Conference This month Dr....
Our “Project CHROMA Personnel” series in Archways highlights the key researchers behind the Rice ARCHES Initiative. Russell Ku This month Dr. Melia Bonomo from the Department of Bioengineering interviews...
Our “Project CHROMA Personnel” series in Archways highlights the key researchers behind the Rice ARCHES Initiative. Vincent Lai This month Vincent Lai, who previously worked with Project CHROMA as the...
Our Mini Review series in Archways does a brief dive into research topics at the intersection of the arts and health. Research on Music Therapy This month, Amara Anyanwu, a Research Assistant in the BMED Lab...
Our Research Updates in Archways give a snapshot of the Rice ARCHES Initiative’s current work, research progress, and future directions LiveWire This month Dr. Anthony Brandt, a Co-Investigator in the Rice...
This month, Dr. Melia Bonomo, a postdoctoral fellow working on Project CHROMA, tells us about the emerging research on music listening in cochlear implant users.
In the United States, 38 million adults and 5 in every 1000 children experience hearing loss. Children who suffer from hearing loss are at risk of developing a communication disorder, while adults face a greater risk of developing dementia. Fortunately, cochlear implants are devices that can be surgically inserted into the cochlea to restore the sensation of hearing for individuals who are deaf or severely hard-of-hearing. While cochlear implants are currently one of the most successful neuroengineering technologies, several difficulties still remain. A notable one is music perception and, more importantly, music appreciation. Improving music listening is an important area of study, not only for facilitating enjoyment, but also because it opens up the door for music-based interventions, like Project Chroma, for cochlear implant users.
I recently attended the American Cochlear Implant Alliance 2022 Meeting in Washington, DC. The theme of this international conference was emerging issues in cochlear implantation, and some of the key topics explored were: individual differences in performance with cochlear implants, expansion of cochlear implantation eligibility and accessibility, clinical trials and translational research, and rehabilitation and education. Notably, there were a couple of talks on music listening for cochlear implant users.
In one presentation, Dr. Luis Lassaletta at La Paz University Hospital in Madrid spoke about his research team’s efforts to evaluate objective music listening in children (6-11 years old), adolescents (11-16 years old), and adults (17 years or older) with cochlear implants. The team made use of Meludia, an online music training platform, as their evaluation tool to test the three groups. Five tasks were used melody discrimination, instrument density, rhythmic beats, spatialization of whether a note is higher or lower than other, and consonant vs. dissonant note combinations. Their preliminary work showed that the rhythm and spatialization tasks had the highest completion rates amongst all groups, but that adolescents showed both the highest completion rates and scoring overall.
In another presentation, Alberte Seeberg at the Center for Music in the Brain at Aarhus University in Denmark presented work on music discrimination in recently implanted cochlear implant users. The team tested pitch, timbre, rhythm, and intensity discrimination in a group of nine cochlear implant users within the first six weeks of implantation and then three months later. Both behavioral and EEG measurements were collected. Preliminary results showed a significant improvement in neural response at the second time point for pitch and timbre discrimination, evidencing neuroplasticity.
In the Raphael Lab in Rice’s Department of Bioengineering, in collaboration with Dr. Santiago Segarra in the Department of Electrical and Computer Engineering, we’re developing a deep learning model to predict optimal device settings for music processing in cochlear implants. This model takes into account both the complexity of auditory biophysics in the inner ear and a patient’s individual hearing health. More on this to come in a later post, but the end goal is to create individualized solutions to improve music listening, and therefore also music enjoyment, for cochlear implant users.