DYNAMIC PATTERN ANALYSIS OF RETINAL FUNCTION

视网膜功能的动态模式分析

• 批准号: 6178352
• 负责人: FRANK S WERBLIN
• 金额: $ 23.85万
• 依托单位: UNIVERSITY OF CALIFORNIA BERKELEY
• 依托单位国家: 美国
• 财政年份: 1980
• 资助国家: 美国
• 起止时间: 1980-05-01 至 2004-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6178352
• 关键词: Urodela; alternatives to animals in research; cell type; disease /disorder model; electrophysiology; neural information processing; neural transmission; neuroanatomy; retina; retinal bipolar neuron; single cell analysis; visual feedback

DESCRIPTION (Adapted from applicant's abstract): The goal of the proposed work is to understand retinal processing through a careful analysis of the dynamic (space-time) patterns of activity that are generated at each retinal level. The spatiotemporal patterns will be generated in two complementary ways: (1) patterns will be measured and constructed through a novel method of physiological recording of excitation and inhibition over a large region for every cell type at each retinal level and extending the result to a population of that cell type, and (2) the patterns will be generated as the emergent properties of retinal models constructed by incorporating the space, time pharmacological and morphological properties derived from single cell studies. The measured and modeled patterns will be compared to evaluate the quantitative hypothesis of retinal embodied in the model. The modeling infrastructure, the Cellular Neural Network, (CNN) is now well-established massively parallel analog array processor designed with an architecture quite similar to the vertebrate retina. These studies will show how both simple and complex stimuli are represented in terms of physical, electrical activity (excitatory and inhibitory membrane currents and voltages) across arrays of thousands of elements at each retinal level. Analyses of these data will yield insights into the underlying neural mechanisms that mediate visual function and provide some clues about the strategies undertaken via neuronal interactions at each retinal level.

描述（改编自申请人的摘要）：拟议工作的目标 是通过仔细分析动态来理解视网膜处理 （时空）在每个视网膜水平上生成的活动模式。这 时空模式将以两种互补的方式产生：（1） 模式将通过一种新颖的方法来测量和构造 对大区域的激发和抑制的生理记录 每个视网膜级别的每种细胞类型，并将结果扩展到人群 该单元格类型，（2）将生成图案作为紧急的 通过合并空间，时间构建的视网膜模型的特性 来自单细胞研究得出的药理和形态学特性。 将比较测量和建模的模式以评估定量 模型中体现的视网膜的假设。建模基础架构， 细胞神经网络（CNN）现在已经建立了良好的平行 模拟阵列处理器设计的结构与 脊椎动物视网膜。这些研究将显示简单和复杂的刺激如何 用物理，电活动（兴奋性和 抑制膜电流和电压） 每个视网膜上的元素。这些数据的分析将产生洞察力 介导视觉功能并提供一些的基本神经机制 关于通过神经元相互作用在每个视网膜上采取的策略的线索 等级。