Tonotopic Optimization for Temporal Processing in the Cochlear Nucleus
Tonotopic Optimization for Temporal Processing in the Cochlear Nucleus
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DOI：
10.1523/jneurosci.4449-15.2016
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发表时间：
2016-08-10
影响因子：
5.3
通讯作者：
Burger, R. Michael
中科院分区：
文献类型：
--
作者：
Oline, Stefan N.;Ashida, Go;Burger, R. Michael
在听觉系统中，声音在平行的频率调谐电路中处理，从耳蜗开始。听觉神经纤维反映了这种音调，并通过将放电“锁定”到特定的刺激相位来编码声刺激的时间特性。然而，锁相的生理约束取决于刺激频率。有趣的是，耳蜗核中的低特征频率（LCF）神经元相对于其听觉神经输入提高了锁相精度。这被认为是通过突触整合产生的，但突触后膜对不同水平的突触会聚的选择性知之甚少。鸡耳蜗核，大细胞核（NM），表现出tonotopic分布的输入和膜特性。LCF神经元接收许多小的输入并且具有低的输入阈值，而高特征频率（HCF）神经元接收很少的大突触并且需要较大的电流来发放尖峰。因此，NM提供了一个机会，研究小的膜变化如何与突触输入的系统地形梯度相互作用。我们研究了膜输入选择性，并观察到HCF神经元比LCF神经元优先选择更快的输入，并且这种偏好可以容忍膜电压的变化。然后，我们使用计算模型来探测哪些属性对锁相至关重要。该模型预测，突触和membraneproperties的相位锁定的最佳安排是特定的刺激频率和tonotopic分布的输入数量和膜兴奋性NM密切跟踪刺激定义的最佳。这些研究结果，然后证实了生理与动力钳模拟输入NM神经元。
In the auditory system, sounds are processed in parallel frequency-tuned circuits, beginning in the cochlea. Auditory nerve fibers reflect this tonotopy and encode temporal properties of acoustic stimuli by "locking" discharges to a particular stimulus phase. However, physiological constraints on phase-locking depend on stimulus frequency. Interestingly, low characteristic frequency (LCF) neurons in the cochlear nucleus improve phase-locking precision relative to their auditory nerve inputs. This is proposed to arise through synaptic integration, but the postsynaptic membrane's selectivity for varying levels of synaptic convergence is poorly understood. The chick cochlear nucleus, nucleus magnocellularis (NM), exhibits tonotopic distribution of both input and membrane properties. LCF neurons receive many small inputs and have low input thresholds, whereas high characteristic frequency (HCF) neurons receive few, large synapses and require larger currents to spike. NM therefore presents an opportunity to study how small membrane variations interact with a systematic topographic gradient of synaptic inputs. We investigated membrane input selectivity and observed that HCF neurons preferentially select faster input than their LCF counterparts, and that this preference is tolerant of changes to membrane voltage. We then used computational models to probe which properties are crucial to phase-locking. The model predicted that the optimal arrangement of synaptic andmembraneproperties for phase-locking is specific to stimulus frequency and that the tonotopic distribution of input number and membrane excitability in NM closely tracks a stimulus-defined optimum. These findings were then confirmed physiologically with dynamic-clamp simulations of inputs to NM neurons.