Circuit Mechanisms of Neural Coding in the Retina

描述（由申请人提供）：该提案将研究脊椎动物视网膜的电路如何将视觉场景转换为视神经中电脉冲的复杂语言。神经科学中最大的差距之一是在细胞水平机制方面解释系统水平的过程，如视觉。视网膜是弥合这一差距的最佳场所之一，因为它的细胞类型的基本特性已经为人所知，并且因为对视网膜执行的复杂的自适应视觉处理的了解越来越多。本项目的具体目标是：1）直接测量无长突细胞（一种不同类型的抑制性中间神经元）与视网膜输出的功能连接，并确定这些回路的整体组织。2)了解无长突细胞如何改变视网膜神经节细胞的视觉反应。3)了解这些功能属性在适应视觉场景的过程中如何变化。许多技术相结合，以创建一个通用程序，用于确定如何视网膜电路的功能。细胞外电极阵列用于同时记录许多神经节细胞的光反应。同时，细胞内记录监测回路中中间神经元的视觉反应。将电流注入这些中间神经元可以直接测量功能连接，揭示中间神经元的输出如何影响操作电路的整体输出。由此产生的大量数据用数学模型进行了总结，这些模型证实了我们对神经回路的理解。这种结合的方法有望对神经回路的功能进行全面的了解。视网膜功能的丧失是导致失明的许多广泛疾病的普遍方面，包括视网膜色素变性和黄斑变性。预计了解视网膜电路如何处理视觉场景将有助于开发视网膜电子假体装置和视网膜疾病进展的早期诊断测试。

DESCRIPTION (provided by applicant): This proposal will study how the circuitry of the vertebrate retina translates the visual scene into a complex language of electrical impulses in the optic nerve. One of the largest gaps in neuroscience is in the explaining of systems-level processes like vision in terms of cellular-level mechanisms. The retina is one of the best places in which to bridge this gap because of the basic properties that are already known of its cell types, and because of growing knowledge about the complex, adaptive visual processing the retina performs. The specific goals of this project are to 1) Directly measure functional connections of amacrine cells, a diverse type of inhibitory interneuron, to the output of the retina, and determine the overall organization of these circuits. 2) Understand how amacrine cells change the visual responses of retinal ganglion cells. 3) Understand how these functional properties change during adaptation to the visual scene. A number of techniques are combined to create a general program for determining how the retinal circuit functions. An array of extracellular electrodes is used to record the light responses of many ganglion cells at once. Simultaneously, intracellular recordings monitor the visual responses of interneurons in the circuit. Injection of current into these interneurons allows direct measurement of functional connections, revealing how the interneuron's output affects the overall output of the operating circuit. The resulting large sets of data are summarized with mathematical models that confirm our understanding of the neural circuitry. This combined approach promises general insight into the function of neural circuits. The loss of retinal function is a prevalent aspect of many widespread diseases that produce blindness, including retinitis pigmentosa and macular degeneration. It is expected that learning how the retinal circuitry processes visual scenes will aid in the development of a retinal electronic prosthetic device and early diagnostic tests for the progression of retinal disorders.