Assessing the relationship between neural health measures and speech performance with simultaneous electric stimulation in cochlear implant listeners.

Julie G Arenberg,Waldo Nogueira,Andreas Büchner,Qian-Jie Fu,Florian Langner

doi:10.1371/journal.pone.0261295

Julie G Arenberg, Waldo Nogueira + Show 3 more

Open Access

https://doi.org/10.1371/journal.pone.0261295

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Abstract

ObjectivesThe relationship between electrode-nerve interface (ENI) estimates and inter-subject differences in speech performance with sequential and simultaneous channel stimulation in adult cochlear implant listeners were explored. We investigated the hypothesis that individuals with good ENIs would perform better with simultaneous compared to sequential channel stimulation speech processing strategies than those estimated to have poor ENIs.MethodsFourteen postlingually deaf implanted cochlear implant users participated in the study. Speech understanding was assessed with a sentence test at signal-to-noise ratios that resulted in 50% performance for each user with the baseline strategy F120 Sequential. Two simultaneous stimulation strategies with either two (Paired) or three sets of virtual channels (Triplet) were tested at the same signal-to-noise ratio. ENI measures were estimated through: (I) voltage spread with electrical field imaging, (II) behavioral detection thresholds with focused stimulation, and (III) slope (IPG slope effect) and 50%-point differences (dB offset effect) of amplitude growth functions from electrically evoked compound action potentials with two interphase gaps.ResultsA significant effect of strategy on speech understanding performance was found, with Triplets showing a trend towards worse speech understanding performance than sequential stimulation. Focused thresholds correlated positively with the difference required to reach most comfortable level (MCL) between Sequential and Triplet strategies, an indirect measure of channel interaction. A significant offset effect (difference in dB between 50%-point for higher eCAP growth function slopes with two IPGs) was observed. No significant correlation was observed between the slopes for the two IPGs tested. None of the measures used in this study correlated with the differences in speech understanding scores between strategies.ConclusionsThe ENI measure based on behavioral focused thresholds could explain some of the difference in MCLs, but none of the ENI measures could explain the decrease in speech understanding with increasing pairs of simultaneously stimulated electrodes in processing strategies.

Highlights

Cochlear implants (CI) are the most successful sensory implant of our time and provide some restoration of hearing to those with severe to profound hearing loss [1]
The electrode-neural interface (ENI) measure based on behavioral focused thresholds could explain some of the difference in most comfortable level (MCL), but none of the ENI measures could explain the decrease in speech understanding with increasing pairs of simultaneously stimulated electrodes in processing strategies
The following methods have been used to estimate ENI: detection thresholds with focused electrical fields [12,13,14], CT imaging data [12, 15, 16], psycho-physical tuning curves [15], intracochlear resistance estimated with electrical field imaging [14], polarity sensitivity [17,18,19] and electrically evoked compound action potential inter-phase gap (IPG) difference measurements [20, 21]

Summary

Introduction

Cochlear implants (CI) are the most successful sensory implant of our time and provide some restoration of hearing to those with severe to profound hearing loss [1]. Performance is highly variable among CI users and depends most prominently on the age at onset of severe to profound hearing loss [2, 3], duration of deafness [4,5,6] and experience with the CI [7, 8] These demographics, the etiology and the physical attributes of the electrode array, which taken together, describe the electrode-neural interface (ENI). It is desirable to find the most efficient way of stimulating the auditory nerve, which is why this study focuses on various measures to estimate the quality of the ENI We correlate those measures with speech perception performance data from stimulation strategies that vary in the amount of interaction among CI channels

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