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Auditory Nerve Spike Generator Modeled as a Variable Attenuator Based on a Saddle Node on Invariant Circle Bifurcation

机译:听觉神经穗发生器建模为可变衰减器基于一个鞍点上不变圈分岔

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摘要

Mammalian inner hair cells transduce the sound waves amplified by the cochlear amplifier (CA) into a graded neurotransmitter release that activates channels on auditory nerve fibers (ANF). These synaptic channels then charge its dendritic spike generator. While the outer hair cells of the CA employ positive feedback, poising on Andronov-Hopf type instabilities which make them extremely sensitive to faint sounds and make CA output strongly nonlinear, the ANF appears to be based on different principles and a different type of dynamical instability. Its spike generator “digitizes” CA output into trains of action potentials and behaves as a linear filter, rate-coding sound intensity across a wide dynamic range. Here we model the spike generator as a 3 dimensional version of a saddle node on invariant circle (SNIC) bifurcation. The generic 2d SNIC increases its spike rate as the square root of the input current above its spiking threshold. We add negative feedback in the form of a low voltage-threshold potassium conductance that slows down the generator’s rate of increase of its spike rate. A Poisson random source simulates an inner hair cell, outputting a series of noisy periodic current pulses to the model ANF whose spikes phase lock to these pulses and have a linear frequency to current relation with a wide dynamic range. Also, the spike generator compartment has a cholinergic feedback connection from the olive and experiments show that such feedback is able to alter the amount of H conductance inside the generator compartment. We show that an olive able to decrease H would be able to shift the spike generator’s dynamic range to higher sound intensities. In a quiet environment by increasing H the olive would be able to make spike trains similar to those caused by synaptic input.
机译:哺乳动物内部的毛细胞将由耳蜗放大器(CA)放大的声波转换成递阶的神经递质释放,从而激活听觉神经纤维(ANF)上的通道。这些突触通道然后为其树突状刺突发生器充电。虽然CA的外部毛细胞具有正反馈,但仍处于Andronov-Hopf型不稳定性的状态,这使其对微弱的声音极为敏感,并使CA输出强烈非线性,而ANF似乎基于不同的原理和不同类型的动态不稳定性。它的尖峰发生器将CA输出“数字化”为一系列动作电位,并充当线性滤波器,对宽动态范围内的声音强度进行速率编码。在这里,我们将尖峰生成器建模为不变圆(SNIC)分叉上的鞍形节点的3维版本。当输入电流的平方根高于其峰值阈值时,通用2d SNIC会提高其尖峰频率。我们以低电压阈值钾电导的形式添加负反馈,从而减慢了发电机峰值频率的增加速度。泊松随机源模拟一个内部毛细胞,向ANF模型输出一系列有噪声的周期性电流脉冲,其尖峰相位锁定于这些脉冲,并具有宽的动态范围,与电流呈线性关系。同样,尖峰发生器隔室具有来自橄榄的胆碱能反馈连接,实验表明,这种反馈能够改变发生器隔室内的H电导量。我们证明了,能够降低H的橄榄能够将尖峰发生器的动态范围转移到更高的声音强度。在安静的环境中,通过增加H值,橄榄将能够制作类似于突触输入所引起的峰值序列。

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    Mark Ospeck;

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  • 年(卷),期 -1(7),9
  • 年度 -1
  • 页码 e45326
  • 总页数 7
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