Function and circuitry of adaptive inhibition in the retina

视网膜适应性抑制的功能和电路

• 批准号: 10328505
• 负责人: STEPHEN A BACCUS
• 金额: $ 38.04万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-06-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10328505
• 关键词: Address; Amacrine Cells; Archives; Cells; Complex; Computer Models; Data; Disease; Electrophysiology (science); Face; Feedback; Future; Goals; Injections; Interneurons; Lateral; Machine Learning; Measures; Methods; Modeling; Molecular; Motion; Mus; Nervous system structure; Neural Network Simulation; Neurons; Optic Nerve; Optical Methods; Output; Pathway interactions; Periodicity; Population; Process; Property; Research; Retina; Retinal Degeneration; Retinal Diseases; Retinal Ganglion Cells; Salamander; Sensory; Signal Transduction; Spottings; Stereotyping; Stimulus; Structure; Synapses; System; Techniques; Testing; Theoretical Studies; Time; Vision; Visual; Visual system structure; biological systems; cell type; clinically relevant; computerized tools; computing resources; connectome; convolutional neural network; design; experimental study; extracellular; ganglion cell; inhibitory neuron; interest; neural circuit; novel strategies; photoreceptor degeneration; predicting response; receptive field; relating to nervous system; response; retinal prosthesis; sight restoration; therapy design; tool; visual processing; visual stimulus

Studies of the visual system face a number of challenges, two of which are the intricacy of the cell types and synaptic connections that comprise the nervous system, and the complexity of the computational processes that underlie vision. Although the retina is one of the most characterized and well understood neural circuits of the visual system, it nonetheless has a great diversity of cell types, connections and computations. The normal function of the retina is to convey information about natural visual scenes, which have complex spatial and temporal structure. The processing of natural scenes has the greatest relevance towards a fundamental understanding retinal function, and the greatest clinical relevance. Yet most studies of retinal visual processing and circuitry focus on responses to simple artificial stimuli rarely encountered normally, such as flashing spots, drifting stripes and flickering checkerboards. With respect to retinal cell types greatest diversity lies in a class of inhibitory interneurons known as amacrine cells. These cells make extensive lateral and feedback connections, and although they form stereotyped connections between each other, excitatory bipolar cells, and ganglion cells that transit signals in the optic nerve, the functional effects of nearly all of these cell types are poorly understood. This proposal aims towards a direct characterization of the functional effects of amacrine cells under ethologically relevant stimuli, including natural scenes. We combine approaches of perturbation and recording using electrical and optical methods as well as computational modeling to characterize the specific contributions of amacrine cells to stimuli that include the representation of moving objects. We take advantage of recently developed computational approaches that can simultaneously capture the retinal response to a broad range of stimuli including natural scenes, capture a wide range of phenomena previously characterized only with artificial stimuli, and that have internal units highly correlated with retinal interneurons. Our goals are to 1) Create a quantitative understanding of the functional contributions of a class of sustained amacrine cells in the salamander retina for specific stimuli including those that represent moving objects and natural scenes, and test hypotheses related to dynamic effects on visual sensitivity and sensory features generated by those amacrine cells 2) Use molecularly defined amacrine cells in the mouse to quantitatively characterize the functional contribution of specific amacrine cell types to specific stimuli including artificial moving objects and natural scenes. These studies create a new way to generate and test hypotheses related to the quantitative effect of any interneuron on retinal output under any visual stimulus. Understanding how retinal circuitry creates visual processing under natural scenes is critical to our understanding of retinal mechanisms and diseases involving the degeneration of the retinal circuitry. In addition, the computational descriptions of retinal responses will be directly useful in the design of electronic retinal prosthesis systems.

视觉系统的研究面临着许多挑战，其中两个挑战是细胞类型的复杂性 和构成神经系统的突触连接，以及计算的复杂性 视觉基础的过程。尽管视网膜是视觉系统中最具特征和最容易理解的神经回路之一，但它仍然具有多种多样的细胞类型、连接和计算。视网膜的正常功能是传递有关自然视觉场景的信息，这些场景具有复杂的时空结构。自然场景的处理对于基本了解视网膜功能具有最大的相关性，并且具有最大的临床相关性。然而，大多数关于视网膜视觉处理和电路的研究都集中在对通常很少遇到的简单人工刺激的反应上，例如闪烁的斑点、漂移的条纹和闪烁的棋盘。就视网膜细胞类型而言，最大的多样性在于一类被称为无长突细胞的抑制性中间神经元。这些细胞形成广泛的横向和反馈连接，尽管它们在彼此、兴奋性双极细胞和在视神经中传递信号的神经节细胞之间形成刻板的连接，但几乎所有这些细胞类型的功能效应仍知之甚少。该提案旨在直接表征无长突细胞在行为学相关刺激（包括自然场景）下的功能效应。我们结合使用电学和光学方法以及计算模型的扰动和记录方法来表征无长突细胞对刺激（包括移动物体的表示）的具体贡献。我们利用最近开发的计算方法 可以同时捕获视网膜对包括自然场景在内的各种刺激的反应，捕获以前仅用人工刺激表征的各种现象，并且具有与视网膜中间神经元高度相关的内部单元。我们的目标是 1) 定量了解蝾螈视网膜中一类持续无长突细胞对特定刺激（包括代表移动物体和自然场景的刺激）的功能贡献，并测试与视觉敏感度和感官动态影响相关的假设这些无长突细胞产生的特征 2) 使用小鼠中分子定义的无长突细胞来定量表征特定无长突细胞类型对特定刺激（包括人工移动物体和自然场景）的功能贡献。这些研究创造了一种新的方法来生成和测试与任何视觉刺激下任何中间神经元对视网膜输出的定量影响相关的假设。了解视网膜回路如何在自然场景下产生视觉处理对于我们理解视网膜机制和涉及视网膜回路退化的疾病至关重要。此外，视网膜反应的计算描述将直接用于电子视网膜假体系统的设计。