RETINAL CIRCUITRY FOR PRECISE TEMPORAL CODING

描述(逐字摘自申请者的摘要)：我们建议研究时间 在电路中编码到维持活跃的神经节细胞是至关重要的 与视觉系统的可靠性有关。神经节细胞的表现为 受限于视觉输入中的噪声以及来自 突触前回路，但神经节细胞如何整合噪音信号 传播到大脑的情况尚不清楚。突触的标准理论 整合一直是一棵被动的树状树，与整合和火灾相结合 生成器将信号编码为尖峰速率。两个新的事实暗示着不同的 理论：(1)神经节细胞的树突表达钠通道， 放大突触噪声，是棘波发生器设置的一个组成部分 它的尖峰频率增益，以及(2)尖峰发生器强调高 具有高时间精度的对瞬时刺激的频率和响应， 与具有比速率更高效率的“定时代码”相一致 密码。我们假设这些观察结果是相互关联的，因为 突触输入噪声中存在的高频的增强可能 提高尖峰发生器的时间精度。我们建议对此进行测试 通过将“理想观察者”应用于真实细胞的响应来进行假说 一个模特。理想的观察者是一个计算机程序，它能区分 利用神经系统反应中的所有信息的两种刺激。它计算出 对比的可靠性如何可以使用似然规则来区分，并且是 因此，比较REAL的基本性能是一种合适的方法 细胞、模型和人类行为。使用从神经节细胞记录的数据集 完整的视网膜准备和现有的计算模型，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什么因素限制了它 精确度。我们将比较真实单元和模型的性能，以确定 哪些时间特征被编码得最可靠，我们将确定这些特征如何 通过修改特征(例如，通道动力学、尖峰信号 穗频率与输入曲线的适应性、斜率和阈值) 计算模型。我们将评估电压门控的贡献 树突状PSPs扩增的通道，以及时间和空间 花纹可以提高扣球的精确度。最后，我们将确定 兴奋性和抑制性mPSP，由于它们之间以及它们之间的相关性。 该项目将有助于理解神经回路如何对精确的 人类视觉中的时间代码。

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.