Fontenot Tatyana E, Giardina Christopher K, Fitzpatrick Douglas C
Otolaryngology-Head and Neck Surgery, University of North Carolina, Chapel Hill, NC, United States.
School of Medicine, University of North Carolina, Chapel Hill, NC, United States.
Front Neurosci. 2017 Oct 23;11:592. doi: 10.3389/fnins.2017.00592. eCollection 2017.
Electrocochleography (ECochG) is a potential clinically valuable technique for predicting speech perception outcomes in cochlear implant (CI) recipients, among other uses. Current analysis is limited by an inability to quantify hair cell and neural contributions which are mixed in the ongoing part of the response to low frequency tones. Here, we used a model based on source properties to account for recorded waveform shapes and to separate the combined signal into its components. The model for the cochlear microphonic (CM) was a sinusoid with parameters for independent saturation of the peaks and the troughs of the responses. The model for the auditory nerve neurophonic (ANN) was the convolution of a unit potential and population cycle histogram with a parameter for spread of excitation. Phases of the ANN and CM were additional parameters. The average cycle from the ongoing response was the input, and adaptive fitting identified CM and ANN parameters that best reproduced the waveform shape. Test datasets were responses recorded from the round windows of CI recipients, from the round window of gerbils before and after application of neurotoxins, and with simulated signals where each parameter could be manipulated in isolation. Waveforms recorded from 284 CI recipients had a variety of morphologies that the model fit with an average of 0.97 ± 0.058 (standard deviation). With simulated signals, small systematic differences between outputs and inputs were seen with some variable combinations, but in general there were limited interactions among the parameters. In gerbils, the CM reported was relatively unaffected by the neurotoxins. In contrast, the ANN was strongly reduced and the reduction was limited to frequencies of 1,000 Hz and lower, consistent with the range of strong neural phase-locking. Across human CI subjects, the ANN contribution was variable, ranging from nearly none to larger than the CM. Development of this model could provide a means to isolate hair cell and neural activity that are mixed in the ongoing response to low-frequency tones. This tool can help characterize the residual physiology across CI subjects, and can be useful in other clinical settings where a description of the cochlear physiology is desirable.
耳蜗电图(ECochG)在预测人工耳蜗(CI)植入者的言语感知结果等方面具有潜在的临床应用价值。目前的分析受到限制,因为无法量化毛细胞和神经的贡献,而这些贡献在对低频音调的持续反应中是混合在一起的。在此,我们使用了一个基于源特性的模型来解释记录到的波形形状,并将组合信号分离为其各个组成部分。耳蜗微音电位(CM)的模型是一个正弦波,其参数用于独立饱和反应的峰值和谷值。听神经神经音(ANN)的模型是单位电位与群体周期直方图的卷积,并带有一个用于兴奋扩散的参数。ANN和CM的相位是额外的参数。将持续反应的平均周期作为输入,通过自适应拟合确定能最佳重现波形形状的CM和ANN参数。测试数据集包括来自CI植入者圆窗记录的反应、应用神经毒素前后沙鼠圆窗的记录反应,以及每个参数可单独操控的模拟信号。从284名CI植入者记录的波形具有多种形态,该模型的拟合平均得分为0.97±0.058(标准差)。对于模拟信号,在某些变量组合下,输出和输入之间存在小范围的系统差异,但总体而言参数之间的相互作用有限。在沙鼠中,所记录的CM相对不受神经毒素影响。相比之下,ANN大幅降低,且降低仅限于1000赫兹及以下频率,这与强烈的神经锁相范围一致。在人类CI受试者中,ANN的贡献各不相同,从几乎没有到大于CM。该模型的开发可以提供一种方法来分离在对低频音调的持续反应中混合的毛细胞和神经活动。这个工具可以帮助描述CI受试者的残余生理特征,并且在其他需要描述耳蜗生理特征的临床环境中可能会有用。