RETINAL CIRCUITRY FOR PRECISE TEMPORAL CODING

描述（来自申请人摘要的逐字）：我们建议研究时间 神经节细胞的回路中的编码， 视觉系统的可靠性。神经节细胞的表现是 受视觉输入中的噪声以及来自 突触前电路，但神经节细胞如何整合噪声信号， 向大脑的传播是未知的。突触的标准理论 集成一直是一个被动的树突状树耦合到集成和发射 发生器将信号编码为尖峰速率。两个新的事实意味着不同的 理论：（1）神经节细胞的树突表达钠通道， 放大突触噪声，并且是尖峰发生器设置的组成部分 它的尖峰频率增益，和（2）尖峰发生器强调高 频率和响应瞬态刺激具有高的时间精度， 与具有比速率更高的效率的“定时码”一致 代码.我们假设这些观察是相互关联的，因为 在突触输入的噪声中存在的高频的增强可以 提高了尖峰发生器的时间精度。我们打算测试一下 通过将“理想观察者”应用于真实的细胞的响应， 模特理想的观察者是一个计算机程序， 两个刺激使用神经系统反应中的所有信息。它计算 如何可靠地对比可以区分使用似然规则， 因此，一个适当的方法来比较基本性能的真实的 细胞、模型和人类行为。从神经节细胞记录的数据集， 完整的视网膜制备和现有的计算模型，其包括 随机电压门控通道和突触释放，我们建议确定 神经节细胞如何编码突触输入以及哪些因素限制了它的 精度我们将比较真实的细胞和模型的性能，以确定 什么样的时间特征是最可靠的编码，我们将确定这些 通过修改特征来编码特征（例如，通道动力学，尖峰 尖峰频率对输入曲线的自适应、斜率和阈值） 计算模型我们将评估电压门控的贡献， 树突状PSP扩增的通道，以及空间和时间 图案增强了尖峰精度。最后，我们将确定 兴奋性和抑制性mPSP，由于它们之间的相关性。 该项目将有助于了解神经回路如何有助于精确的 人类视觉中的时间编码。

DESCRIPTION (Verbatim from applicant's abstract): We propose to study temporal coding in the circuit to the brisk-sustained ganglion cell that is a crucial link in the visual system's reliability. Performance of the ganglion cell is limited by noise in the visual input and from several sources in the presynaptic circuit, but how the ganglion cell integrates a noisy signal for transmission to the brain is unknown. The standard theory for synaptic integration has been a passive dendritic tree coupled to an integrate-and-fire generator to code the signal as a spike rate. Two new facts imply a different theory: (1) dendrites of the ganglion cell express sodium channels, which amplify synaptic noise and are an integral part of the spike generator setting its spike frequency gain, and (2) the spike generator emphasizes high frequencies and responds to transient stimuli with high temporal precision, consistent with a "timing code" which has a greater efficiency than a rate code. We hypothesize that these observations are interrelated because enhancement of the high frequencies present in the noise of synaptic input may improve the spike generator's temporal precision. We propose to test this hypothesis by applying an "ideal observer" to the responses of a real cell and a model. The ideal observer is a computer program that discriminates between two stimuli using all information in a neural system's response. It calculates how reliably contrasts can be discriminated using a likelihood rule, and is therefore an appropriate method to compare fundamental performance of real cell, model, and human behavior. With data sets recorded from ganglion cells in an intact retina preparation and an existing computational model that includes stochastic voltage-gated channels and synaptic release, we propose to determine how the ganglion cell codes synaptic inputs and what factors limit its precision. We will compare the performance of real cell and model to determine what temporal features are coded most reliably, and we will determine how these features are coded by modifying features (e.g., channel kinetics, spike adaptation, slope and threshold of spike frequency vs. input curve) of the computational model. We will evaluate the contribution of voltage-gated channels to amplification of dendritic PSPs, and what spatial and temporal patterns enhance spike precision. Finally, we will determine the function of excitatory and inhibitory mPSPs, due to correlations among and between them. The project will help understand how neural circuits contribute to a precise temporal code in human vision.