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Quantifying Envelope and Fine-Structure Coding in Auditory Nerve Responses to Chimaeric Speech

机译:量化听觉神经对Chimaeric语音响应中的信封和精细结构编码。

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摘要

Any sound can be separated mathematically into a slowly varying envelope and rapidly varying fine-structure component. This property has motivated numerous perceptual studies to understand the relative importance of each component for speech and music perception. Specialized acoustic stimuli, such as auditory chimaeras with the envelope of one sound and fine structure of another have been used to separate the perceptual roles for envelope and fine structure. Cochlear narrowband filtering limits the ability to isolate fine structure from envelope; however, envelope recovery from fine structure has been difficult to evaluate physiologically. To evaluate envelope recovery at the output of the cochlea, neural cross-correlation coefficients were developed that quantify the similarity between two sets of spike-train responses. Shuffled auto- and cross-correlogram analyses were used to compute separate correlations for responses to envelope and fine structure based on both model and recorded spike trains from auditory nerve fibers. Previous correlogram analyses were extended to isolate envelope coding more effectively in auditory nerve fibers with low center frequencies, which are particularly important for speech coding. Recovered speech envelopes were present in both model and recorded responses to one- and 16-band speech fine-structure chimaeras and were significantly greater for the one-band case, consistent with perceptual studies. Model predictions suggest that cochlear recovered envelopes are reduced following sensorineural hearing loss due to broadened tuning associated with outer-hair cell dysfunction. In addition to the within-fiber cross-stimulus cases considered here, these neural cross-correlation coefficients can also be used to evaluate spatiotemporal coding by applying them to cross-fiber within-stimulus conditions. Thus, these neural metrics can be used to quantitatively evaluate a wide range of perceptually significant temporal coding issues relevant to normal and impaired hearing.
机译:任何声音都可以在数学上分为缓慢变化的包络线和快速变化的精细结构分量。这种特性激发了许多感知研究,以理解语音和音乐感知中每个组成部分的相对重要性。特殊的声音刺激,例如具有一种声音的包络和另一种声音的精巧结构的听觉chimaeras,已被用于区分对于包络和精细结构的感知作用。耳蜗窄带滤波限制了将精细结构与包膜隔离的能力;但是,很难从生理学上评价从精细结构恢复的包膜。为了评估耳蜗输出处的包膜恢复,开发了神经互相关系数,用于量化两组峰值响应之间的相似性。混洗后的自相关和交叉相关图分析用于基于模型和听神经纤维记录的尖峰序列,分别计算对包膜和精细结构的响应的相关性。以前的相关图分析已扩展到更有效地隔离中心频率低的听神经纤维中的包络编码,这对语音编码尤为重要。恢复的语音包络同时存在于模型中,并且记录了对单频带和16频带语音精细结构的响应,并且在单频带情况下明显更大,这与感知研究一致。模型预测表明,由于与外毛细胞功能障碍相关的扩大调节,在感觉神经性听力损失后,耳蜗恢复的包膜减少。除了此处考虑的光纤内交叉刺激情况外,这些神经互相关系数还可以通过将它们应用于跨光纤内刺激条件来评估时空编码。因此,这些神经度量可用于定量评估与正常和听力受损有关的各种感知上重要的时间编码问题。

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