Leclère Thibaud, Johannesen Peter T, Wijetillake Aswin, Segovia-Martínez Manuel, Lopez-Poveda Enrique A
Instituto de Neurociencias de Castilla y León, Universidad de Salamanca, Salamanca 37007, Spain; Instituto de Investigación Biomédica de Salamanca, Universidad de Salamanca, Salamanca 37007, Spain.
Oticon Medical, Smørum DK-2765, Denmark.
Hear Res. 2023 May;432:108744. doi: 10.1016/j.heares.2023.108744. Epub 2023 Mar 25.
Computational models are useful tools to investigate scientific questions that would be complicated to address using an experimental approach. In the context of cochlear-implants (CIs), being able to simulate the neural activity evoked by these devices could help in understanding their limitations to provide natural hearing. Here, we present a computational modelling framework to quantify the transmission of information from sound to spikes in the auditory nerve of a CI user. The framework includes a model to simulate the electrical current waveform sensed by each auditory nerve fiber (electrode-neuron interface), followed by a model to simulate the timing at which a nerve fiber spikes in response to a current waveform (auditory nerve fiber model). Information theory is then applied to determine the amount of information transmitted from a suitable reference signal (e.g., the acoustic stimulus) to a simulated population of auditory nerve fibers. As a use case example, the framework is applied to simulate published data on modulation detection by CI users obtained using direct stimulation via a single electrode. Current spread as well as the number of fibers were varied independently to illustrate the framework capabilities. Simulations reasonably matched experimental data and suggested that the encoded modulation information is proportional to the total neural response. They also suggested that amplitude modulation is well encoded in the auditory nerve for modulation rates up to 1000 Hz and that the variability in modulation sensitivity across CI users is partly because different CI users use different references for detecting modulation.
计算模型是研究科学问题的有用工具，这些问题若采用实验方法解决会很复杂。在人工耳蜗（CI）的背景下，能够模拟这些设备诱发的神经活动有助于理解其在提供自然听力方面的局限性。在此，我们提出一个计算建模框架，用于量化人工耳蜗使用者听神经中从声音到动作电位的信息传递。该框架包括一个模拟每个听神经纤维感知的电流波形的模型（电极 - 神经元接口），接着是一个模拟神经纤维对电流波形产生动作电位的时间的模型（听神经纤维模型）。然后应用信息论来确定从合适的参考信号（例如，声刺激）传递到模拟的听神经纤维群体的信息量。作为一个应用案例示例，该框架被用于模拟通过单电极直接刺激获得的人工耳蜗使用者调制检测的已发表数据。电流扩散以及纤维数量被独立改变以说明该框架的能力。模拟结果与实验数据合理匹配，并表明编码的调制信息与总的神经反应成正比。它们还表明，对于高达1000赫兹的调制率，幅度调制在听神经中得到了很好的编码，并且人工耳蜗使用者之间调制灵敏度的差异部分是因为不同的人工耳蜗使用者在检测调制时使用了不同的参考。
