Classification of mouse RGC subtypes using large-scale multielectrode recording

使用大规模多电极记录对小鼠 RGC 亚型进行分类

• 批准号: 7642260
• 负责人: DAVID A FELDHEIM
• 金额: $ 19.8万
• 依托单位: UNIVERSITY OF CALIFORNIA SANTA CRUZ
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-04-01 至 2011-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7642260
• 关键词: Affect; Biological Models; Blindness; Cells; Classification; Color; Degenerative Disorder; Development; Disease; Electrodes; Electrophysiology (science); Foundations; Future; Genes; Genetic; Glaucoma; Goals; Grant; Human; Image; Individual; Injury; Knowledge; Label; Link; Modeling; Molecular; Monitor; Morphology; Motion; Mus; Neurons; Pattern; Perception; Physiological; Physiology; Play; Positioning Attribute; Principal Investigator; Property; Relative (related person); Retina; Retinal; Retinal Degeneration; Retinal Diseases; Retinal Ganglion Cells; Role; Solid; Structure; Study models; System; Techniques; Technology; Transgenic Mice; Vision; Visual; Visual Fields; Visual system structure; Wild Type Mouse; Work; cell type; density; design; neural circuit; novel; public health relevance; receptive field; research study; response; retinal damage; spatiotemporal; therapy development; visual stimulus

DESCRIPTION (provided by applicant): The goal of this co-principal investigator, interdisciplinary proposal is to develop techniques for the comprehensive functional characterization of retinal ganglion cell (RGC) types in the mouse retina, and to combine this characterization with mouse transgenic technology in order to determine the relationships between the morphology and physiology of RGC types. Our experiments take advantage of novel multi- electrode array (MEA) recording systems built in the Litke lab. These systems contain over 500 electrodes and can simultaneously record the activity from hundreds of neurons in an intact retina; this represents a 10 fold better yield over currently available technology. We find that this increase in yield is critical for unambiguous functional classification and reliable characterization of the many RGC types in the retina. Furthermore, we hypothesize that the detailed information provided by these MEA systems will make it possible to match the physiologically identified neurons to optically imaged RGCs. Such a match will create a link between function and structure in an unprecedented manner. We have two main aims to accomplish our goals. In the first aim we propose to use two types of large- scale MEAs, a 512-electrode array with 605m interelectrode spacing, and a high density 519-electrode array with 305m spacing, to characterize the receptive field and mosaic properties of RGC types of wild type mice. We have chosen to use these arrays to characterize RGC types in mice because the mouse retina has become an important model to study the role various genes/molecules play in the development of retinal circuitry. The mouse also serves as a model for studying the progression of retinal-degenerative diseases such as glaucoma. In the second aim we plan to use the large-scale MEA technology to correlate the morphological RGC types to their functional counterparts. In addition to being classified using physiological criteria, RGCs are classified using morphological criteria. However, only in rare circumstances can cells be classified by both morphological and physiological properties. Experiments proposed in this aim are designed to correlate morphologically labeled cells with their physiological properties. We will do this by matching the morphological images of GFP marked RGCs with their electrophysiological images and receptive fields. (As described in section c, the electrophysiological image is a technique, developed by the Litke lab, for imaging the spatiotemporal pattern of electrical activity generated by individual neurons.). The purpose of this grant is to obtain a comprehensive characterization of retinal ganglion cell (RGC) types in the mouse retina. This knowledge is essential in order to understand how various molecular and environmental perturbations affect the retina's development and function. Vision is a crucial component of human perception and blindness is a devastating affliction. Understanding what the retinal circuits are is the first step toward understanding how they develop and is also essential to better understand the progression of retinal degenerative diseases (Are specific circuits differentially affected in disease?). In the last 10-20 years, modern molecular techniques, in combination with powerful advances in imaging and electrophysiology, have led to an increase in the use of the mouse as a model system for studying retinal circuitry. It is likely that the knowledge obtained from experiments proposed here will be essential to all who use the mouse visual system as a model. PUBLIC HEALTH RELEVANCE: The first aim of this project is to develop techniques for the classification and functional characterization of retinal ganglion cell (RGC) types in the mouse retina. The second aim is to combine this characterization with mouse transgenic technology in order to determine the relationship between the morphology and physiology of RGC types. Upon completion of the proposed aims, we will be in a strong position to use these techniques to determine how various genetic, activity-related, and disease perturbations affect and control the development of neural circuits. This will build a solid foundation for future work aimed at developing therapies for treating retinal damage due to injury or disease.

描述（由申请人提供）：该联合主要研究者、跨学科提案的目标是开发用于小鼠视网膜中视网膜神经节细胞（RGC）类型的全面功能表征的技术，并将该表征与小鼠相结合。联合收割机转基因技术，以确定RGC类型的形态学和生理学之间的关系。我们的实验利用了新型的多电极阵列（MEA）记录系统建立在利特克实验室。这些系统包含500多个电极，可以同时记录完整视网膜中数百个神经元的活动;这比目前可用的技术高出10倍。我们发现，这种产量的增加是至关重要的明确的功能分类和可靠的表征视网膜中的许多RGC类型。此外，我们假设这些MEA系统提供的详细信息将使其能够将生理识别的神经元与光学成像的RGC相匹配。这种匹配将以前所未有的方式在功能和结构之间建立联系。我们有两个主要目标来实现我们的目标。在第一个目标中，我们建议使用两种类型的大规模MEA，一个512电极阵列与605米的电极间距，和一个高密度519电极阵列与305米的间距，以表征感受野和镶嵌性质的RGC类型的野生型小鼠。我们选择使用这些阵列来表征小鼠的RGC类型，因为小鼠视网膜已成为研究各种基因/分子在视网膜回路发育中所起作用的重要模型。该小鼠还可以作为研究青光眼等视网膜退行性疾病进展的模型。在第二个目标中，我们计划使用大规模MEA技术将RGC的形态类型与其功能对应物相关联。除了使用生理学标准分类之外，还使用形态学标准对RGC进行分类。然而，只有在极少数情况下，细胞才能通过形态学和生理学特性进行分类。为此目的提出的实验旨在将形态标记的细胞与其生理特性相关联。我们将通过将GFP标记的RGCs的形态学图像与它们的电生理图像和感受野相匹配来做到这一点。(As如c部分所述，电生理学图像是由Litke实验室开发的一种技术，用于对单个神经元产生的电活动的时空模式进行成像。这项资助的目的是获得小鼠视网膜中视网膜神经节细胞（RGC）类型的全面表征。这些知识对于了解各种分子和环境扰动如何影响视网膜的发育和功能至关重要。视觉是人类感知的重要组成部分，失明是一种毁灭性的痛苦。了解视网膜回路是什么是了解它们如何发展的第一步，也是更好地了解视网膜退行性疾病进展的关键（特定回路在疾病中受到不同影响吗？）。在过去的10-20年里，现代分子技术，结合成像和电生理学的强大进步，导致小鼠作为研究视网膜回路的模型系统的使用增加。很可能，从这里提出的实验中获得的知识将是必不可少的所有谁使用小鼠视觉系统作为一个模型。 公共卫生关系：该项目的第一个目的是开发用于小鼠视网膜中视网膜神经节细胞（RGC）类型的分类和功能表征的技术。第二个目的是将联合收割机这一特征与小鼠转基因技术相结合，以确定RGC类型的形态学和生理学之间的关系。在完成这些目标后，我们将能够利用这些技术来确定各种遗传、活动相关和疾病扰动如何影响和控制神经回路的发育。这将为未来的工作奠定坚实的基础，旨在开发治疗因损伤或疾病引起的视网膜损伤的疗法。