van Gendt M J, Briaire J J, Frijns J H M
ENT-Department, Leiden University Medical Centre, PO Box 9600, 2300, RC Leiden, the Netherlands.
ENT-Department, Leiden University Medical Centre, PO Box 9600, 2300, RC Leiden, the Netherlands.
Hear Res. 2019 Jun;377:167-178. doi: 10.1016/j.heares.2019.03.013. Epub 2019 Mar 23.
Electrically evoked compound action potentials (eCAPs) are measurements of the auditory nerve's response to electrical stimulation. ECAP amplitudes during pulse trains can exhibit temporal alternations. The magnitude of this alternation tends to diminish over time during the stimulus. How this pattern relates to the temporal behavior of nerve fibers is not known. We hypothesized that the stochasticity, refractoriness, adaptation of the threshold and spike-times influence pulse-train eCAP responses. Thirty thousand auditory nerve fibers were modeled in a three-dimensional cochlear model incorporating pulse-shape effects, pulse-history effects, and stochasticity in the individual neural responses. ECAPs in response to pulse trains of different rates and amplitudes were modeled for fibers with different stochastic properties (by variation of the relative spread) and different temporal properties (by variation of the refractory periods, adaptation and latency). The model predicts alternation of peak amplitudes similar to available human data. In addition, the peak alternation was affected by changing the refractoriness, adaptation, and relative spread of auditory nerve fibers. As these parameters are related to factors such as the duration of deafness and neural survival, this study suggests that the eCAP pattern in response to pulse trains could be used to assess the underlying temporal and stochastic behavior of the auditory nerve. As these properties affect the nerve's response to pulse trains, they are of uttermost importance to sound perception with cochlear implants.
电诱发复合动作电位（eCAPs）是对听神经对电刺激反应的测量。脉冲序列期间的eCAP振幅可表现出时间上的交替变化。在刺激过程中，这种交替变化的幅度往往会随着时间而减小。这种模式与神经纤维的时间行为之间的关系尚不清楚。我们假设，神经纤维的随机性、不应期、阈值适应性和峰电位时间会影响脉冲序列的eCAP反应。在一个三维耳蜗模型中对30000根听神经纤维进行了建模，该模型纳入了脉冲形状效应、脉冲历史效应以及个体神经反应中的随机性。针对具有不同随机特性（通过相对离散度的变化）和不同时间特性（通过不应期、适应性和潜伏期的变化）的纤维，对不同频率和幅度的脉冲序列所引发的eCAP进行了建模。该模型预测的峰值振幅交替变化与现有的人体数据相似。此外，通过改变听神经纤维的不应期、适应性和相对离散度，峰值交替变化也会受到影响。由于这些参数与耳聋持续时间和神经存活等因素有关，本研究表明，对脉冲序列的eCAP模式可用于评估听神经潜在的时间和随机行为。由于这些特性会影响神经对脉冲序列的反应，它们对于人工耳蜗的声音感知至关重要。
