DYNAMIC PATTERN ANALYSIS OF RETINAL FUNCTION

描述(改编自申请人的摘要)：建议工作的目标 是通过仔细分析视网膜的动态过程来理解视网膜的过程 (空间-时间)在每个视网膜水平产生的活动模式。这个 时空模式将以两种互补的方式生成：(1) 将通过一种新的方法测量和构建图案 大范围刺激和抑制的生理记录 每种视网膜水平的每种细胞类型，并将结果扩展到人群 该细胞类型，以及(2)图案将作为紧急的 结合空间、时间构建的视网膜模型的性质 来自单细胞研究的药理和形态特性。 测量的图案和建模的图案将进行比较，以评估量化的 模型中体现了视网膜的假说。建模基础设施、 细胞神经网络(CNN)现在是公认的大规模并行 模拟阵列处理器设计的体系结构与 脊椎动物视网膜。这些研究将展示简单和复杂的刺激如何 以体力、电活动(兴奋性和 抑制膜电流和电压)跨越数千个阵列 每层视网膜上的元素。对这些数据的分析将产生对 调节视觉功能并提供一些 关于通过每个视网膜的神经元相互作用采取的策略的线索 水平。

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.