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

 描述(申请人提供)：了解大脑功能的基础是将特定神经元的时空放电模式与它们的功能连接联系起来，并确定这些连接的强度和依赖于经验的调节。基因编码的光学指示物使这两项努力都发生了革命性的变化，使动作电位和突触传递得以检测，但这些方法面临两大障碍：1)过度密集的表达往往使追踪特定神经元的形态和连接变得不可能，2)还没有方法测量体内突触传递的概率(Pr)和突触的量子大小，导致突触强度联系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定向到数量足够少的特定细胞的能力，以便能够在密集的环境中确定其形态和物理连通性，然后允许物理图像与活动和连通性相关。为了应对这一挑战，我们提出了一种可推广的策略，用于创建“开启”的遗传编码活动指标。这些指标是在现有的一些最好的神经活动和突触传递指标的基础上进行合理修改的。这种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。因为指示器是通过光打开的(不同于像高尔基染色那样的随机标记方法)， 人们可以选择特定的目标细胞，并在功能上成像其进程严重重叠的密集排列的细胞，同时知道哪个进程属于哪个细胞，从而允许简单形式的优雅的连通性映射。第二个问题出现在缺乏突触特有的量化分析方法上。对突触反应的大规模量子分辨率成像将是对实验神经科学工具包的有力补充，以帮助解决突触强度的动态变化如何影响感觉、动作、学习和记忆。尽管在简化的体外准备中，如脑片，关于突触功能的知识非常丰富，但由于缺乏有效的工具，我们对体内突触功能在学习和行为方面的知识极其有限。一种克服这一技术差距的新方法将在清醒的行为动物的突触和电路水平分析之间架起一座桥梁。在行为正常的动物身上进行高信噪比的脊柱钙质成像可以弥补这一差距。为了应对这一挑战，我们建议开发突触靶向钙指示剂，使兴奋性突触传递能够在数百到数千个连接上同时以量子分辨率成像。因为这是一种成像方法，它提供了突触特有的信息，人们不能轻易从电生理记录中获得这些信息，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聚集在一起。对行为动物的光学量子分析将允许直接评估可能构成学习基础的突触效率的动态波动。它还将开辟全新的研究途径，探索突触效能的变化如何有助于感觉、行动和更高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、果蝇和小鼠的大脑电路分析和行为的活体应用中得到验证。

 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.