用神经图相似度衡量听力损失与耳蜗神经退化，可精准预测语音识别表现。
Using Neurogram Similarity Index Measure (NSIM) to Model Hearing Loss and Cochlear Neural Degeneration
- 通过神经图相似度指数（NSIM）比较听觉神经纤维反应，量化听力损伤。
- NSIM能准确映射听力障碍者对音素识别的表现，相关性良好。
- 该方法可作为耳蜗突触病变的无创生物标志物，适合临床研究使用。
在嘈杂环境中听不清是听力障碍者及听力正常者常见的困扰，这可能源于耳蜗神经退化（CND），后者也导致助听器效果差异显著。本文利用听觉外周的计算模型模拟多种听力任务，提出一种基于神经图相似度指数（NSIM）的客观方法，通过比较听觉神经纤维响应来量化听力损失与CND。研究1表明，NSIM可较准确地映射听力损失个体在音素识别任务中的表现；研究2显示，NSIM对由CND引起的听力缺陷具有高敏感性，有望成为听觉突触病变的非侵入性生物标志物。
原文摘要 · Abstract (English)
Trouble hearing in noisy situations remains a common complaint for both individuals with hearing loss and individuals with normal hearing. This is hypothesized to arise due to condition called: cochlear neural degeneration (CND) which can also result in significant variabilities in hearing aids outcomes. This paper uses computational models of auditory periphery to simulate various hearing tasks. We present an objective method to quantify hearing loss and CND by comparing auditory nerve fiber responses using a Neurogram Similarity Index Measure (NSIM). Specifically study 1, shows that NSIM can be used to map performance of individuals with hearing loss on phoneme recognition task with reasonable accuracy. In the study 2, we show that NSIM is a sensitive measure that can also be used to capture the deficits resulting from CND and can be a candidate for noninvasive biomarker of auditory synaptopathy.
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