Uncovering the retinal circuits that underlie visual feature detection

揭示视觉特征检测背后的视网膜回路

• 批准号: RGPIN-2017-04472
• 负责人: Krishnaswamy, Arjun
• 金额: $ 2.4万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=711070
• 关键词: Uncovering; retinal; circuits; underlie; visual

Complex patterns of synaptic wiring unite neurons together to form circuits whose computations are critical for a wide range of our sensory, motor and cognitive behaviours. Yet, clear links between such computations and underlying circuit patterns are unclear. The goal of my research is to learn how neural circuitry gives rise to computations such as stimulus detection, information storage, and prediction. To meet this goal, we will map the connections of these retinal circuits to understand how they create the retina's primary computation: to detect salient visual features. Approximately 30 types of retinal circuits analyze the visual scene, each tuned to detect a particular feature such as motion, edges, colour, and so on; each circuit ends with a retinal ganglion cell (RGC), which sends feature signals to the brain for further analysis. The current model is that the RGCs are endowed with their feature preference via the connections they receive from particular types of retinal interneurons, called amacrine and bipolar cells. However, clear maps of such circuitry and its links to feature detection are lacking. To learn more, we will devise methods to rapidly map connections among RGCs, ACs, and BCs using recent advances in genetically encoded calcium indicators (gcamp6f) and optogenetics. Armed with this technique, we will map functional connections from genetically defined interneurons to all RGC types in parallel (Objective #1) and obtain valuable information about the patterns of interneuron connectivity. In parallel, we will measure the visual responses of interneurons to understand how their signals could be used to create RGC feature signals (Objective#2). Interneuron responses to a battery of stimuli that include tests for direction, orientation, and contrast-selectivity will be measured with gcamp6f and related to responses from RGCs evoked by the same stimuli; this will allow us to define transformation from photons to features that occurs in interneuron-RGC circuitry. Finally, we seek causal links between interneuron input and RGC feature preference and will employ genetic methods to ablate or silence particular interneuron types while imaging RGC responses (Objective #3). This research will lead to the training of Highly Qualified Personnel, who will leave my lab armed with a combination of cutting-edge life- and neuroscience research methods. This training is a core objective of this proposal and our plan poises my personnel to become leaders in science and innovation in Canada. The training people receive in my lab will make them highly attractive to employers in research, biotech, foundations and beyond. What we learn together will uncover links between circuit-patterns and circuit function in the retina and offer immense potential to generilize these links to higher centers. The reagents, basic insights and tools from this work offer a way to dissect this issue in the brain

复杂的突触连接模式将神经元连接在一起，形成电路，其计算对我们的感觉、运动和认知行为的广泛范围至关重要。然而，这种计算和潜在电路模式之间的明确联系尚不清楚。我的研究目标是了解神经电路如何产生刺激检测、信息存储和预测等计算。为了实现这一目标，我们将绘制这些视网膜电路的连接图，以了解它们是如何创建视网膜的主要计算的：检测显著的视觉特征。大约有30种类型的视网膜电路分析视觉场景，每种电路都被调整以检测特定的特征，如运动、边缘、颜色等；每个电路以视网膜神经节细胞(RGC)结束，RGC将特征信号发送到大脑进行进一步分析。目前的模型是，视网膜节细胞通过它们从称为无长突细胞和双极细胞的特定类型的视网膜中间神经元获得的连接来赋予它们特征偏好。然而，这种电路及其与特征检测的联系缺乏清晰的地图。为了了解更多，我们将设计方法，利用遗传编码的钙指示剂(Gcamp6f)和光遗传学的最新进展，快速定位RGC、ACS和BCS之间的联系。有了这项技术，我们将并行地映射从遗传定义的中间神经元到所有RGC类型的功能连接(目标1)，并获得关于神经元间连接模式的有价值的信息。同时，我们将测量中间神经元的视觉反应，以了解它们的信号如何被用来创建RGC特征信号(目标2)。神经元间对包括方向、定向和对比度选择性测试在内的一系列刺激的反应将通过gcamp6f进行测量，并与相同刺激引起的RGC的反应相关；这将使我们能够定义在神经元间-RGC电路中发生的从光子到特征的转换。最后，我们寻找神经元间输入和RGC特征偏好之间的因果联系，并将使用遗传方法来消融或沉默特定类型的中间神经元，同时成像RGC反应(目标#3)。这项研究将培养高素质的人员，他们将带着尖端的生命科学和神经科学研究方法的组合离开我的实验室。这项培训是这项提议的核心目标，我们的计划使我的人员能够成为加拿大科学和创新的领导者。人们在我的实验室接受的培训将使他们在研究、生物技术、基金会等领域对雇主具有极大的吸引力。我们共同学习的东西将揭示视网膜中电路模式和电路功能之间的联系，并提供巨大的潜力，将这些联系推广到更高的中心。来自这项工作的试剂、基本见解和工具提供了一种在大脑中剖析这一问题的方法