Department of Biology, University of Maryland, College Park, Maryland 20742, USA.
J Neurophysiol. 2012 Nov;108(10):2794-809. doi: 10.1152/jn.00092.2012. Epub 2012 Aug 22.
The intrinsic properties of tonically firing neurons in the cochlear nucleus contribute to representing average sound intensity by favoring synaptic integration across auditory nerve inputs, reducing phase locking to fine temporal acoustic structure and enhancing envelope locking. To determine whether tonically firing neurons of the avian cochlear nucleus angularis (NA) resemble ideal integrators, we investigated their firing responses to noisy current injections during whole cell patch-clamp recordings in brain slices. One subclass of neurons (36% of tonically firing neurons, mainly subtype tonic III) showed no significant changes in firing rate with noise fluctuations, acting like pure integrators. In contrast, many tonically firing neurons (>60%, mainly subtype tonic I or II) showed a robust sensitivity to noisy current fluctuations, increasing their firing rates with increased fluctuation amplitudes. For noise-sensitive tonic neurons, the firing rate vs. average current curves with noise had larger maximal firing rates, lower gains, and wider dynamic ranges compared with FI curves for current steps without noise. All NA neurons showed fluctuation-driven patterning of spikes with a high degree of temporal reliability and millisecond spike time precision. Single-spiking neurons in NA also responded to noisy currents with higher firing rates and reliable spike trains, although less precisely than nucleus magnocellularis neurons. Thus some NA neurons function as integrators by encoding average input levels over wide dynamic ranges regardless of current fluctuations, others detect the degree of coherence in the inputs, and most encode the temporal patterns contained in their inputs with a high degree of precision.
耳蜗核中持续放电神经元的固有特性通过有利于听神经输入的突触整合、降低对精细时间声学结构的相位锁定以及增强包络锁定来表示平均声音强度。为了确定鸟类耳蜗核角状核(NA)的持续放电神经元是否类似于理想的积分器,我们在脑片全细胞膜片钳记录中研究了它们对噪声电流注入的放电反应。一类神经元(36%的持续放电神经元,主要是亚类 tonic III)的放电率随噪声波动没有明显变化,表现得像纯积分器。相比之下,许多持续放电神经元(>60%,主要是亚类 tonic I 或 II)对噪声电流波动表现出很强的敏感性,随着波动幅度的增加,它们的放电率增加。对于对噪声敏感的持续放电神经元,与没有噪声的电流阶跃的 FI 曲线相比,噪声下的放电率与平均电流曲线具有更大的最大放电率、更低的增益和更宽的动态范围。所有 NA 神经元都表现出具有高度时间可靠性和毫秒级时间精度的波动驱动的尖峰模式。NA 中的单峰神经元也对噪声电流以更高的放电率和可靠的尖峰序列作出反应,尽管不如大细胞核神经元精确。因此,一些 NA 神经元通过在宽动态范围内编码平均输入水平来作为积分器,而不考虑电流波动,其他神经元检测输入的相干程度,并且大多数以高精度编码其输入中包含的时间模式。