Investigation of intracochlear electrical fields with spread of excitation and voltage matrix in cochlear implant users and their link to speech perception
Year: 2025
Type: article
Abstract: BACKGROUND: Objective measures and their relation to listening performance are of interest in the study of cochlear implants (CIs). Both spread of excitation (SoE) and the voltage matrix (VM) are objective descriptors of electric field spread. VM is easier to measure and therefore preferable to SoE. The aim of the study was comparing both measurements postoperatively and investigating their relation to listening performance. METHODS: Postoperative SoE and VM data for 10 out of 17 CI-users were normalized to their maximum amplitude before comparison. A previously published SoE-width-based analysis method (Rader et al., 2023) was adapted and applied to the VM data. The ECAP separation index (from Hughes, 2008), comparing SoE data of two neighboring electrodes, was also adapted to the VM data of 17 CI-users and correlated with speech perception. RESULTS: Recorded SoE and VM data correlated strongly in most CI-users. The normalized SoE and VM data showed good alignment. Some deviations were observable: an average RMS-difference of 0.159 normalized amplitude was found between SoE and VM data. Asymmetric width measures extracted from exponential fitting differed significantly between SoE and VM data. No correlation between width measures and speech perception could be found. The VM separation index correlated with speech perception. CONCLUSIONS: SoE and VM are closely related measurements, however they are not identical. The neural information in SoE can't be ignored and VM can't replace SoE. The VM separation index appeared to be a promising approach for predicting listening performance. Nevertheless, further research is required to corroborate this finding.
Source: Hearing Research
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $4,130
OpenAlex ID: W4412044463
