Monopolar Detection Thresholds Predict Spatial Selectivity of Neural Excitation in Cochlear Implants: Implications
1Department of Communication Sciences and Disorders, East Carolina University, Greenville, NC, United States of America.
Plos One
|November 1, 2016
Summary
Monopolar detection thresholds in cochlear implant (CI) users can estimate neural excitation spread. Optimizing CI speech recognition involved deactivating high-threshold sites, improving performance in quiet and noise.
Area of Science:
- Audiology
- Neuroscience
- Biomedical Engineering
Background:
- Cochlear implants (CIs) aim to restore hearing by electrically stimulating the auditory nerve.
- Understanding neural excitation patterns is crucial for optimizing CI performance.
- Monopolar psychophysical detection thresholds offer a potential non-invasive measure.
Purpose of the Study:
- To assess monopolar detection thresholds for estimating neural excitation spatial selectivity in CI users.
- To investigate the impact of removing stimulation sites based on these thresholds on speech recognition.
Main Methods:
- Detection thresholds were measured using monopolar stimulation with varying pulse train rates and durations.
- Spatial selectivity was assessed via a forward-masking paradigm.
- Speech recognition was evaluated with experimental maps deactivating high-threshold and random sites.
Main Results:
- Low-rate monopolar thresholds showed the strongest correlation with neural excitation spread, unlike high-rate stimuli.
- Deactivating high-threshold sites significantly improved speech recognition in quiet and noise compared to clinical maps.
- Random site deactivation did not significantly alter speech recognition performance.
Conclusions:
- Monopolar low-rate detection thresholds reflect spatial neural excitation patterns in CI users.
- Targeted deactivation of high-threshold sites can enhance speech recognition outcomes.
- This threshold measure provides a viable method for optimizing CI speech processor programming.
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