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用细胞水平的机制来解释视觉等系统水平的过程。视网膜是弥合这一差距的最佳地点之一，因为我们已经知道了它的细胞类型的基本特性，也因为我们对视网膜复杂的、适应性的视觉处理过程的了解越来越多。该项目的具体目标是：1)直接测量无突细胞（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时是如何变化的。许多技术结合在一起，创造了一个确定视网膜回路如何运作的通用程序。一组细胞外电极被用来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被总结为数学模型，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有一个全面的了解。视网膜功能丧失是许多导致失明的广泛疾病的一个普遍方面，包括视网膜色素变性和黄斑变性。预计了解视网膜回路如何处理视觉场景将有助于视网膜电子假体装置的开发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.