Novel tools for cell-specific imaging of functional connectivity and circuit operations

 描述（由申请人提供）：理解脑功能的基础是将特定神经元的时空放电模式与其功能连接性联系起来并确定这些连接的强度和经验依赖性调节的能力。遗传编码的光学指示器彻底改变了这两种努力，使动作电位和突触传递能够被检测到，但这些方法面临两个主要障碍：1）过度密集的表达通常使得不可能追踪特定神经元的形态和因此的连接性，以及2）还没有方法来测量体内突触传递的概率（Pr）和突触的量子尺寸，导致突触强度连接和经验依赖性变化的机制尚未解决。第一个问题是缺乏将活动指示器瞄准特定细胞的能力，这些细胞数量很少，因此可以在密集的环境中确定它们的形态和物理连接，然后允许物理图像与活动和连接相关。为了应对这一挑战，我们提出了一个可推广的战略，创造“打开”的遗传编码的活动指标。这些指标是从一些最好的神经活动和突触传递的现有指标合理修改。重新设计使指示器能够被光激活，以提供细胞形态的高尔基体样视图，并报告动作电位和突触输入。因为指示剂是由光打开的（不像高尔基染色等随机标记方法）， 可以选择特定的目标细胞，并在功能上对密集堆积的细胞成像，这些细胞的过程严重重叠，同时知道哪个过程属于哪个细胞，从而允许简单形式的优雅的连通性映射。第二个问题是缺乏突触特异性量子分析的方法。突触反应的大规模量子分辨率成像将代表实验神经科学工具包的一个强大补充，以帮助解决突触强度的动态变化如何有助于感觉，行动，学习和记忆。尽管在减少的离体制备物（例如脑切片）中关于突触功能的知识丰富，但由于缺乏有效的工具，我们在学习和行为期间对突触功能的体内知识极其有限。一种克服这一技术差距的新方法将弥合清醒行为动物的突触和电路水平分析之间的鸿沟。高信噪比脊柱水平钙成像行为的动物可以解决这个问题。为了应对这一挑战，我们建议开发突触靶向钙指标，使兴奋性突触传递的量子分辨率同时成像在数百至数千个连接。因为这是一种成像方法，它提供了突触特异性信息，而这些信息不能从电生理记录中轻易获得，电生理记录将分布在神经元树突树上的大量输入的测量结果汇总在一起。在行为动物中进行光学量子分析将允许直接评估突触功效的动态波动，这可能是学习的基础。它还将开辟全新的研究途径，探索突触功效的变化如何有助于感觉，行动和高级认知功能的基本方面。Isacoff，Scott和Adesnik之间的合作使这些新工具能够在三种模式生物（斑马鱼，果蝇和小鼠）的脑回路分析和行为中进行体内应用验证。

 DESCRIPTION (provided by applicant): Fundamental to understanding brain function is the ability to relate the spatio-temporal firing patterns of specific neurons to their functional connectivity and determine the strength and experience-dependent regulation of those connections. Genetically-encoded optical indicators have revolutionized both endeavors, enabling action potentials and synaptic transmission to be detected, but these approaches face two major hurdles: 1) overly dense expression often makes it impossible to trace the morphology and hence connectivity of specific neurons, and 2) there has been no method to measure the probability of synaptic transmission (Pr) and quantal size of synapses in vivo, leading synaptic strength connections and the mechanism of experience- dependent change unresolved. The first problem emerges from a lack of ability to target activity indicators to specific cells that are few enough in number so that their morphology and physical connectivity could be determined in a densely packed environment, to then permit the physical picture to be related to activity and connectivity. To meet this challenge, we propose a generalizable strategy for the creation of "turn-on" genetically-encoded activity indicators. These indicators are rationally modified from some of the best existing indicators of neural activity and synaptic transmission. The re-engineering enables the indicators to be activated by light to provide a Golgi-like view of cell morphology and report on action potentials and synaptic input. Because the indicators are turned on by light (unlike in the random labeling methods like the Golgi stain), one can select specific target cells and functionally image densely packed cells whose processes heavily overlap while knowing which process belongs to which cell, thereby permitting a simple form of elegant connectivity mapping. The second problem emerges from the lack of a method for synapse-specific quantal analysis. Large-scale quantal resolution imaging of synaptic responses would represent a powerful addition to the experimental neuroscience toolkit to help address how dynamic changes in synaptic strength contribute to sensation, action, learning and memory. Despite a wealth of knowledge on synaptic function in reduced ex vivo preparations, such as brain slices, due to the lack of effective tools, our knowledge of synaptic function in vivo during learning and behavior is extremely limited. A new approach that overcomes this technical gap would bridge the divide between synaptic and circuit level analyses in awake, behaving animals. High signal-to-noise spine level calcium imaging in behaving animals could address this gap. To meet this challenge we propose to develop synaptically-targeted calcium indicators that enable excitatory synaptic transmission to be imaged with quantal resolution simultaneously at hundreds to thousands of connections. Because this is an imaging method, it provides synapse-specific information that one cannot readily obtain from electrophysiological recordings that lump together measurements from a large number of inputs distributed over a neuron's dendritic tree. Optical quantal analysis in behaving animals would permit direct assessment of the dynamic fluctuations in synaptic efficacy that may underlie learning. It will also open whole new avenues of research that could explore how changes in synaptic efficacy contribute to fundamental aspects of sensation, action, and higher cognitive function. The collaboration between Isacoff, Scott and Adesnik enables these new tools to be validated for in vivo applications in brain circuit analysis and behavior in three model organisms: zebrafish, fruitfly and mouse.