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使用听觉神经生物物理模型模拟电调制检测阈值。

Simulating electrical modulation detection thresholds using a biophysical model of the auditory nerve.

作者信息

O'Brien Gabrielle E, Imennov Nikita S, Rubinstein Jay T

机构信息

Department of Otolaryngology, V. M. Bloedel Hearing Research Center, University of Washington, Box 3657923, CHDD building, CD 176, Seattle, Washington 98196, USA.

出版信息

J Acoust Soc Am. 2016 May;139(5):2448. doi: 10.1121/1.4947430.

Abstract

Modulation detection thresholds (MDTs) assess listeners' sensitivity to changes in the temporal envelope of a signal and have been shown to strongly correlate with speech perception in cochlear implant users. MDTs are simulated with a stochastic model of a population of auditory nerve fibers that has been verified to accurately simulate a number of physiologically important temporal response properties. The procedure to estimate detection thresholds has previously been applied to stimulus discrimination tasks. The population model simulates the MDT-stimulus intensity relationship measured in cochlear implant users. The model also recreates the shape of the modulation transfer function and the relationship between MDTs and carrier rate. Discrimination based on fluctuations in synchronous firing activity predicts better performance at low carrier rates, but quantitative measures of modulation coding predict better neural representation of high carrier rate stimuli. Manipulating the number of fibers and a temporal integration parameter, the width of a sliding temporal integration window, varies properties of the MDTs, such as cutoff frequency and peak threshold. These results demonstrate the importance of using a multi-diameter fiber population in modeling the MDTs and demonstrate a wider applicability of this model to simulating behavioral performance in cochlear implant listeners.

摘要

调制检测阈值(MDTs)用于评估听众对信号时间包络变化的敏感度,并且已证明其与人工耳蜗使用者的言语感知密切相关。MDTs是通过一群听觉神经纤维的随机模型进行模拟的,该模型已被验证能够准确模拟许多重要的生理时间响应特性。估计检测阈值的程序先前已应用于刺激辨别任务。群体模型模拟了在人工耳蜗使用者中测量到的MDT与刺激强度的关系。该模型还重现了调制传递函数的形状以及MDTs与载波频率之间的关系。基于同步放电活动波动的辨别预测在低载波频率下具有更好的性能,但调制编码的定量测量预测高载波频率刺激具有更好的神经表征。通过操纵纤维数量和一个时间积分参数(滑动时间积分窗口的宽度),可以改变MDTs的特性,如截止频率和峰值阈值。这些结果证明了在模拟MDTs时使用多直径纤维群体的重要性,并证明了该模型在模拟人工耳蜗听众行为表现方面具有更广泛的适用性。

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