Abstract

The past decade has seen a wealth of research dedicated to determining which and how morphological changes in the auditory periphery contribute to people experiencing hearing difficulties in noise despite having clinically normal audiometric thresholds in quiet. Evidence from animal studies suggests that cochlear synaptopathy in the inner ear might lead to auditory nerve deafferentation, resulting in impoverished signal transmission to the brain. Here, we quantify the likely perceptual consequences of auditory deafferentation in humans via a physiologically inspired encoding-decoding model. The encoding stage simulates the processing of an acoustic input stimulus (e.g., speech) at the auditory periphery, while the decoding stage is trained to optimally regenerate the input stimulus from the simulated auditory nerve firing data. This allowed us to quantify the effect of different degrees of auditory deafferentation by measuring the extent to which the decoded signal supported the identification of speech in quiet and in noise. In a series of experiments, speech perception thresholds in quiet and in noise increased (worsened) significantly as a function of the degree of auditory deafferentation for modeled deafferentation greater than 90%. Importantly, this effect was significantly stronger in a noisy than in a quiet background. The encoding-decoding model thus captured the hallmark symptom of degraded speech perception in noise together with normal speech perception in quiet. As such, the model might function as a quantitative guide to evaluating the degree of auditory deafferentation in human listeners.

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