Retinal circuits for precise coding

用于精确编码的视网膜电路

• 批准号: 7168436
• 负责人: Robert G Smith
• 金额: $ 37.94万
• 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/7168436
• 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

DESCRIPTION (provided by applicant): 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.

描述（由申请人提供）：我们提出研究视网膜中编码的精确性，其中相关的视觉信号在传递到神经节细胞以传输到大脑之前被处理。视网膜电路的性能受到噪声的限制，因为视觉信号具有大的（10个对数单位）动态范围，但由离散的随机事件（如囊泡释放、通道开放和尖峰）携带。因此，视网膜利用视觉环境的相关特征，如扩展的物体，速度或运动方向，用特定的电路编码这些特征，提高它们的信噪比。但视网膜回路究竟是如何实现这一点的还不清楚。一个标准的理论是，通过在延长的时间上积分来去除来自突触释放和电压门控通道的噪声。然而，视网膜回路中存在的非线性表明编码更为复杂。例如，所有无长突细胞和双极细胞都含有电压门控通道，可以放大和提供适应，它们还含有间隙连接，可以检测相关信号并消除噪音。许多神经节细胞的树突是活跃的，并且可以非线性地增强突触后电位以产生可靠的信号。我们假设，这些神经元准备专门放大快速的空间相关信号，创造一个重合检测器，赋予视觉信号的显着性。我们建议测试这一假设，通过应用一个理想的观察者的响应真实的和模型神经元。理想的观测器是一个计算机程序，它使用对一对刺激的响应之间的似然规则进行区分，以测量神经元发出信号（例如运动或对比度）的精度。这种分析提供了灰度级的数量，这是信息容量的基本度量。我们将记录活的双极细胞、无长突细胞和神经节细胞，构建这些神经元及其回路的真实计算机模型，并测量真实的神经元和模型的精度。通过跟踪瞬时、持续和方向选择性视觉信号从一层到下一层的精确度，我们将发现视觉通路中信息的丢失和保存位置，并更好地理解信息是如何编码的。这项工作将有助于了解眼睛的功能，这些知识将有助于临床研究人员确定夜盲症和其他视网膜营养不良等多种眼科疾病的问题。