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Published on: May 10, 2019
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UTILIZING INFORMATION THEORETIC APPROACH TO STUDY COCHLEAR NEURAL DEGENERATION
Ahsan J Cheema1,2, Sunil Puria1,2
1Harvard University, Speech and Hearing Bioscience and Technology Program, Boston MA, USA.
Arxiv
|November 24, 2025
Summary
Hidden hearing loss (cochlear neural degeneration) impairs speech understanding without changing hearing test results. Rapid speech is best for detecting this condition, unlike reverberation.
Area of Science:
- Auditory Neuroscience
- Speech Processing
- Information Theory
Background:
- Hidden hearing loss, or cochlear neural degeneration (CND), affects suprathreshold auditory coding but not clinical hearing thresholds.
- CND diagnosis is challenging due to its subtle effects on auditory processing.
Purpose of the Study:
- To develop an information-theoretic framework to identify speech stimuli that best reveal CND.
- To quantify mutual information (MI) loss between auditory system components under varying CND conditions.
Main Methods:
- Utilized a phenomenological auditory model to simulate neural responses to speech stimuli.
- Varied CND levels by simulating different spontaneous-rate fiber survival rates.
- Analyzed MI between inner hair cell (IHC) potentials and auditory nerve fiber (ANF) responses, and acoustic input and ANF responses.
Main Results:
- Demonstrated progressive MI loss with increasing CND.
- Identified time-compressed speech as the most sensitive stimulus for revealing MI loss.
- Reverberation showed less impact on MI loss compared to temporal compression.
Conclusions:
- Rapid, temporally dense speech stimuli are optimal for detecting CND.
- Findings can inform the development of objective clinical diagnostic tools for hidden hearing loss.
- Highlights limitations of reverberation as a probe for CND.
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