Retinal circuits for precise coding

用于精确编码的视网膜电路

• 批准号: 7350117
• 负责人: Robert G Smith
• 金额: $ 38.34万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-09-30 至 2011-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7350117
• 关键词: Amacrine Cells; Benchmarking; Brain; Cells; Clinical; Code; Complex; Computer Simulation; Condition; Coupling; Data Set; Dendrites; Detection; Electrodes; Elements; Environment; Event; Eye; Eye diseases; Frequencies; Gap Junctions; Gray unit of radiation dose; Knowledge; Life; Measures; Methods; Modeling; Morphology; Motion; Neurons; Night Blindness; Noise; Numbers; Pathway interactions; Performance; Potassium Channel; Process; Property; Range; Research Personnel; Retina; Retinal; Retinal Cone; Retinal Dystrophy; Signal Transduction; Standards of Weights and Measures; Stimulus; Sum; Synapses; Testing; Time; Trees; Vesicle; Visual; Visual Pathways; Work; computer program; computerized data processing; detector; ganglion cell; improved; neural circuit; paired stimuli; postsynaptic; presynaptic; receptive field; relating to nervous system; response; retinal rods; theories; transmission process; visual coding; visual performance; voltage; voltage gated channel

We propose to study the precision of coding in the retina where correlated visual signals are processed before being passed to ganglion cells for transmission to the brain. Performance of retinal circuits is limited by noise because the visual signal has a large (10 log unit) dynamic range but is carried by discrete stochastic events such as vesicle release, channel opening, and spikes. Therefore the retina takes advantage of correlated features of the visual environment such as extended objects, velocity, or direction of motion to code these features with specific circuits, improving their signal/noise ratio. But exactly how retinal circuits accomplish this is unknown. One standard theory is that noise from synaptic release and voltage- gated channels is removed by integrating over an extended time. However, the presence of nonlinearities in retinal circuitry suggests that encoding is more complex. For example, the All amacrine cells and bipolar cells contain voltage-gated channels that may amplify and provide adaptation, and they also contain gap junctions that detect correlated signals and remove noise. The dendrites of many ganglion cells are active and may boost postsynaptic potentials nonlinearly to generate a reliable signal. We hypothesize that these neural elements are poised to specifically amplify fast spatially-correlated signals, creating a coincidence detector that imparts salience to visual signals. We propose to test this hypothesis by applying an ideal observer to the responses of real and model neurons. The ideal observer is a computer program that discriminates using the likelihood rule between the responses to a pair of stimuli to measure the precision with which a neuron signals e.g. motion or contrast. This analysis provides the number of gray levels, a fundamental measure of information capacity. We will record from live bipolar, amacrine, and ganglion cells, construct realistic computer models of these neurons and their circuits, and measure the precision of real neurons and model with the ideal observer. Tracking the precision of transient, sustained, and directional selective visual signals from one layer to the next, we will discover where in the visual pathway information is lost and preserved, and gain a better understanding of how information is coded. This work will help to understand how the eye functions, and this knowledge will help clinical researchers determine what has gone wrong in many types of eye disease such as night blindness and other retinal dystrophies.

我们建议研究处理相关视觉信号的视网膜中编码的精度 在传递到神经节细胞之前，将其传播到大脑。视网膜电路的性能有限 通过噪声，因为视觉信号具有较大（10 log单元）的动态范围，但由离散携带 随机事件，例如囊泡释放，通道开口和尖峰。因此，视网膜需要 视觉环境的相关特征的优势，例如扩展对象，速度或方向 用特定电路对这些特征进行编码的运动，从而提高其信号/噪声比。但是确切的视网膜 电路实现这一目标是未知的。一种标准理论是突触释放和电压的噪声 - 通过在延长的时间内集成来删除封闭通道。但是，存在非线性 视网膜电路表明编码更为复杂。例如，所有的无聚细胞和双极细胞 单元包含可能扩大和提供适应的电压门控通道，并且还包含间隙 检测相关信号并消除噪声的连接。许多神经节细胞的树突是活跃的 并可能非线性地增强突触后电位以产生可靠的信号。我们假设这些 神经元素有望特别放大快速的空间相关信号，从而创造出巧合 赋予视觉信号的探测器。我们建议通过应用理想来检验这一假设 观察者对真实和模型神经元的反应。理想的观察者是计算机程序 使用对一对刺激的响应之间的可能性规则进行区分以测量精度 神经元信号，例如运动或对比。该分析提供了灰度的数量， 信息能力的基本衡量。我们将记录来自活躁郁症，悬脂和神经节细胞的记录， 构建这些神经元及其电路的现实计算机模型，并测量真实的精度 具有理想观察者的神经元和模型。跟踪瞬态，持续和定向的精度 从一层到另一层的选择性视觉信号，我们将在视觉途径信息中发现位置 丢失和保存，并更好地了解信息的编码方式。这项工作将有助于 了解眼睛的功能以及这些知识如何帮助临床研究人员确定什么 在许多类型的眼病中出错，例如夜失明和其他视网膜营养不良。