Characteristics of the Adaptation Recovery Function of the Auditory Nerve and Its Association With Advanced Age in Postlingually Deafened Adult Cochlear Implant Users

Contributions of Auditory Nerve Density and Synchrony to Speech Understanding in Older Cochlear Implant Users

PURPOSE

The majority of adult cochlear implant (CI) recipients are over the age of 65, and previous research in non-implanted older adults shows that auditory nerve (AN) pathophysiology contributes to senescent declines in speech understanding. However, age-related changes to AN structure and function have not yet been explored as a contributory factor to poorer speech understanding outcomes in older CI users. Here, we explore how estimates of AN disengagement (i.e., AN density) and dyssynchrony in CI users contribute to poorer speech recognition performance observed in older CI users.

METHODS

We examined electrically evoked compound action potentials (ECAPs) in 47 adult (Male = 25) CI recipients. We measured the interphase gap (IPG) effect for the amplitude-growth function (AGF) slope and the N1-P2 interpeak latency as independent metrics of AN density and dyssynchrony, respectively.

RESULTS

Estimates of AN density and dyssynchrony worsen with increasing age in older CI listeners. These measures were not significantly correlated with one another, but were independently related to speech recognition in noise performance. Lower ECAP IPG effect values (lower density of AN fibers) are observed in older CI users. Longer N1-P2 interpeak latency values (poorer neural synchrony) are also observed in older CI users. When controlling for listener age, poorer AN dyssynchrony contributes to declines in speech-recognition-in-noise performance in CI users.

CONCLUSION

These results suggest that AN dyssynchrony rather than density is the primary contributing factor to age-related declines in speech understanding in CI users. These results have important implications for better understanding neural contributions to speech understanding in adult CI users.

How differ eCAP types in cochlear implants users with and without inner ear malformations: amplitude growth function, spread of excitation, refractory recovery function

OBJECTIVES

Inner ear malformations (IEMs) may result in differences in outcomes of cochlear implant user. These differences could be observed in both behavioral and objective tests. eCAP is the most common used objective test in cochlear implants and have different presence rate in cochlear implant users with and without IEMs. This study aims to evaluate eCAP results from CI user with and without IEMs through different recoding methods; amplitude growth function, spreads of excitation and refractory recovery.

METHODS

There were 42 CI users (20 IEM&22 normal) above five-years old and with at least one year experience. Three different eCAP measurement was conducted at several intracochlear electrodes. Presence rate, threshold levels and amplitude were compared between groups.

RESULTS

For Amplitude growth function measurement, when the percentage of detected eCAP thresholds was analyzed between groups, there was a significant difference only for basal electrode and no significant difference for apical and middle electrodes. Similarly, the presence rate of RecF-eCAP for both groups were in a downward trend from apical to basal. However, there was no significant difference in AGF-eCAP and RecF-eCAP amplitudes between groups for the cochlea's apical, middle and basal region. Although the presence rate of SOE-eCAP was lower for IEM group, there was no significant difference in ECAP amplitudes for all maskers.

CONCLUSIONS

It could be inferred that even though the observable eCAP rate differed between these two groups when the observable eCAP was recorded, the IEM group produced eCAP with similar amplitudes to normal cochlea group.

The Relationship Between Cochlear Implant Speech Perception Outcomes and Electrophysiological Measures of the Electrically Evoked Compound Action Potential

OBJECTIVE

This study assessed the relationship between electrophysiological measures of the electrically evoked compound action potential (eCAP) and speech perception scores measured in quiet and in noise in postlingually deafened adult cochlear implant (CI) users. It tested the hypothesis that how well the auditory nerve (AN) responds to electrical stimulation is important for speech perception with a CI in challenging listening conditions.

DESIGN

Study participants included 24 postlingually deafened adult CI users. All participants used Cochlear Nucleus CIs in their test ears. In each participant, eCAPs were measured at multiple electrode locations in response to single-pulse, paired-pulse, and pulse-train stimuli. Independent variables included six metrics calculated from the eCAP recordings: the electrode-neuron interface (ENI) index, the neural adaptation (NA) ratio, NA speed, the adaptation recovery (AR) ratio, AR speed, and the amplitude modulation (AM) ratio. The ENI index quantified the effectiveness of the CI electrodes in stimulating the targeted AN fibers. The NA ratio indicated the amount of NA at the AN caused by a train of constant-amplitude pulses. NA speed was defined as the speed/rate of NA. The AR ratio estimated the amount of recovery from NA at a fixed time point after the cessation of pulse-train stimulation. AR speed referred to the speed of recovery from NA caused by previous pulse-train stimulation. The AM ratio provided a measure of AN sensitivity to AM cues. Participants' speech perception scores were measured using Consonant-Nucleus-Consonant (CNC) word lists and AzBio sentences presented in quiet, as well as in noise at signal-to-noise ratios (SNRs) of +10 and +5 dB. Predictive models were created for each speech measure to identify eCAP metrics with meaningful predictive power.

RESULTS

The ENI index and AR speed individually explained at least 10% of the variance in most of the speech perception scores measured in this study, while the NA ratio, NA speed, the AR ratio, and the AM ratio did not. The ENI index was identified as the only eCAP metric that had unique predictive power for each of the speech test results. The amount of variance in speech perception scores (both CNC words and AzBio sentences) explained by the eCAP metrics increased with increased difficulty under the listening condition. Over half of the variance in speech perception scores measured in +5 dB SNR noise (both CNC words and AzBio sentences) was explained by a model with only three eCAP metrics: the ENI index, NA speed, and AR speed.

CONCLUSIONS

Of the six electrophysiological measures assessed in this study, the ENI index is the most informative predictor for speech perception performance in CI users. In agreement with the tested hypothesis, the response characteristics of the AN to electrical stimulation are more important for speech perception with a CI in noise than they are in quiet.

Comparison of response properties of the electrically stimulated auditory nerve reported in human listeners and in animal models

Cochlear implants (CIs) provide acoustic information to implanted patients by electrically stimulating nearby auditory nerve fibers (ANFs) which then transmit the information to higher-level neural structures for further processing and interpretation. Computational models that simulate ANF responses to CI stimuli enable the exploration of the mechanisms underlying CI performance beyond the capacity of in vivo experimentation alone. However, all ANF models developed to date utilize to some extent anatomical/morphometric data, biophysical properties and/or physiological data measured in non-human animal models. This review compares response properties of the electrically stimulated auditory nerve (AN) in human listeners and different mammalian models. Properties of AN responses to single pulse stimulation, paired-pulse stimulation, and pulse-train stimulation are presented. While some AN response properties are similar between human listeners and animal models (e.g., increased AN sensitivity to single pulse stimuli with long interphase gaps), there are some significant differences. For example, the AN of most animal models is typically more sensitive to cathodic stimulation while the AN of human listeners is generally more sensitive to anodic stimulation. Additionally, there are substantial differences in the speed of recovery from neural adaptation between animal models and human listeners. Therefore, results from animal models cannot be simply translated to human listeners. Recognizing the differences in responses of the AN to electrical stimulation between humans and other mammals is an important step for creating ANF models that are more applicable to various human CI patient populations.