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Tuesday, November 17, 2020

Noninvasive Measures of Distorted Tonotopic Speech Coding Following Noise-Induced Hearing Loss

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Abstract

Animal models of noise-induced hearing loss (NIHL) show a dramatic mismatch between cochlear characteristic frequency (CF, based on place of innervation) and the dominant response frequency in single auditory-nerve-fiber responses to broadband sounds (i.e., distorted tonotopy, DT). This noise trauma effect is associated with decreased frequency-tuning-curve (FTC) tip-to-tail ratio, which results from decreased tip sensitivity and enhanced tail sensitivity. Notably, DT is more severe for noise trauma than for metabolic (e.g., age-related) losses of comparable degree, suggesting that individual differences in DT may contribute to speech intelligibility differences in patients with similar audiograms. Although DT has implications for many neural-coding theories for real-world sounds, it has primarily been explored in single-neuron studies that are not viable with humans. Thus, there are no noninvasive measures to detect DT. Here, frequency following responses (FFRs) to a conversational speech sentence were recorded in anesthetized male chinchillas with either normal hearing or NIHL. Tonotopic sources of FFR envelope and temporal fine structure (TFS) were evaluated in normal-hearing chinchillas. Results suggest that FFR envelope primarily reflects activity from high-frequency neurons, whereas FFR-TFS receives broad tonotopic contributions. Representation of low- and high-frequency speech power in FFRs was also assessed. FFRs in hearing-impaired animals were dominated by low-frequency stimulus power, consistent with oversensitivity of high-frequency neurons to low-frequency power. These results suggest that DT can be diagnosed noninvasively. A normalized DT metric computed from speech FFRs provides a potential diagnostic tool to test for DT in humans. A sensitive noninvasive DT metric could be used to evaluate perceptual consequences of DT and to optimize hearing-aid amplification strategies to improve tonotopic coding for hearing-impaired liste ners.

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