ENT-Department, Leiden University Medical Centre, PO Box 9600, Leiden 2300 RC, The Netherlands.
ENT-Department, Leiden University Medical Centre, PO Box 9600, Leiden 2300 RC, The Netherlands.
Hear Res. 2020 Dec;398:108090. doi: 10.1016/j.heares.2020.108090. Epub 2020 Oct 2.
Despite the introduction of many new sound-coding strategies speech perception outcomes in cochlear implant listeners have leveled off. Computer models may help speed up the evaluation of new sound-coding strategies, but most existing models of auditory nerve responses to electrical stimulation include limited temporal detail, as the effects of longer stimulation, such as adaptation, are not well-studied. Measured neural responses to stimulation with both short (400 ms) and long (10 min) duration high-rate (5kpps) pulse trains were compared in terms of spike rate and vector strength (VS) with model outcomes obtained with different forms of adaptation. A previously published model combining biophysical and phenomenological approaches was adjusted with adaptation modeled as a single decaying exponent, multiple exponents and a power law. For long duration data, power law adaptation by far outperforms the single exponent model, especially when it is optimized per fiber. For short duration data, all tested models performed comparably well, with slightly better performance of the single exponent model for VS and of the power law model for the spike rates. The power law parameter sets obtained when fitted to the long duration data also yielded adequate predictions for short duration stimulation, and vice versa. The power law function can be approximated with multiple exponents, which is physiologically more viable. The number of required exponents depends on the duration of simulation; the 400 ms data was well-replicated by two exponents (23 and 212 ms), whereas the 10-minute data required at least seven exponents (ranging from 4 ms to 600 s). Adaptation of the auditory nerve to high-rate electrical stimulation can best be described by a power-law or a sum of exponents. This gives an adequate fit for both short and long duration stimuli, such as CI speech segments.
尽管引入了许多新的声音编码策略，但人工耳蜗植入者的语音感知效果已经趋于平稳。计算机模型可能有助于加快对新声音编码策略的评估，但大多数现有的听觉神经对电刺激反应模型都包含有限的时间细节，因为较长刺激（如适应）的影响尚未得到很好的研究。比较了在不同适应形式下，用短（400ms）和长（10 分钟）持续时间、高率（5kpps）脉冲串对刺激的测量神经反应，比较了尖峰率和向量强度（VS）的模型结果。以前发表的模型结合了生物物理和现象学方法，通过将适应建模为单个衰减指数、多个指数和幂律来进行调整。对于长持续时间数据，幂律适应远远优于单个指数模型，尤其是在按纤维进行优化时。对于短持续时间数据，所有测试的模型性能都相当，对于 VS，单个指数模型的性能稍好，对于尖峰率，幂律模型的性能稍好。拟合长持续时间数据时获得的幂律参数集也能很好地预测短持续时间刺激，反之亦然。幂律函数可以用多个指数来近似，这在生理上更可行。所需的指数数取决于模拟的持续时间；400ms 数据可以用两个指数（23ms 和 212ms）很好地复制，而 10 分钟的数据至少需要七个指数（从 4ms 到 600s）。听觉神经对高率电刺激的适应可以用幂律或指数和来最好地描述。这为短时间和长时间刺激（如 CI 语音片段）提供了足够的拟合。
