Towards Decoding Selective Attention Through Cochlear Implant Electrodes as Sensors in Subjects with Contralateral Acoustic Hearing

ObjectivesFocusing attention on one speaker in a situation with multiple background speakers or noise is referred to as auditory selective attention. Decoding selective attention is an interesting line of research with respect to future brain-guided hearing aids or cochlear implants (CIs) that are designed to adaptively adjust sound processing through cortical feedback loops. This study investigates the feasibility of using the electrodes and backward telemetry of a CI to record electroencephalography (EEG). ApproachThe study population included 6 normal-hearing (NH) listeners and 5 CI users with contralateral acoustic hearing. Cortical auditory evoked potentials (CAEP) and selective attention were recorded using a state-of-the-art high-density scalp EEG and, in the case of CI users, also using two CI electrodes as sensors in combination with the backward telemetry system of these devices (iEEG). Main resultsThe peak amplitudes of the CAEPs recorded with iEEG were lower and the latencies were higher than those recorded with scalp EEG. In the selective attention paradigm with multi-channel scalp EEG the mean decoding accuracy across subjects was 92.0 and 92.5% for NH listeners and CI users, respectively. With single-channel scalp EEG the accuracy decreased to 65.6 and to 75.8% for NH listeners and CI users, respectively, and was above chance level in 9 out of 11 subjects. With the single-channel iEEG, the accuracy for CI users decreased to 70% and was above chance level in 3 out of 5 subjects. SignificanceThis study shows that single-channel EEG is suitable for auditory selective attention decoding, even though it reduces the decoding quality compared to a multi-channel approach. CI-based iEEG can be used for the purpose of recording CAEPs and decoding selective attention. However, the study also points out the need for further technical development for the CI backward telemetry regarding long-term recordings and the optimal sensor positions.