Comparative Quantitative Image Acquisition, Analysis and Modeling

摘要：RobustCircuit的目标是了解在较低级别(从分子到细胞)的不精确过程要求下的共同原理，以在较高级别(从细胞到行为)的神经电路组装中产生稳健的结果。实时成像是在分子、亚细胞和细胞动力学水平上获得不精确和健壮过程的定量数据的主要手段。八个项目中的七个利用活体内和体外活体成像来获得关于亚细胞动力学中的不精确度(包括噪声)的统计上强大的数据。基于这样的定量数据，计算建模允许人们对不精确在创建健壮系统中所起的作用做出预测。因此，Z1项目旨在解决由我们的协作项目设计产生的两个核心挑战：挑战1：分子、亚细胞和细胞动力学应该具有相同的数据类型和质量，以便在项目之间进行定量比较。解决方案：目标1旨在为4D实时成像采集和比较跟踪方法的适应和分析提供一种通用和标准化的方法。挑战2：在生物实验中处理不精确的参数而不产生附带影响是具有挑战性的。与生物实验不同的是，计算建模允许特定地调节不精确的参数，并为产生稳健的结果提供可测试的假设。解决方案：目标2旨在提供建模方法，该方法可以改编自先前由RobustCircuit PI测试的已建立的随机建模框架，用于基于随机亚细胞动力学生成健壮的突触形成。

Summary: The goal of RobustCircuit is to understand common principles underlying the requirements of imprecise processes at lower scales (from molecules to cells) to yield robust outcomes at higher scales (from cells to behavior) in neural circuit assembly. Live imaging is the principle means to obtain quantitative data on imprecise and robust processes at the levels of molecular, subcellular and cellular dynamics. Seven of the eight projects utilize intravital and ex vivo live imaging to obtain statistically powerful data on imprecisions, including noise, in subcellular dynamics. Based on such quantitative data, computational modeling allows one to make predictions for the roles imprecisions play in creating robust systems. The Z1 project is therefore designed to tackle two core challenges resulting from our collaborative project design:Challenge 1: Molecular, subcellular and cellular dynamics should be of the same data type and quality to be quantitatively comparable between projects. Solution: Objective 1 is devised to provide a common and standardized approach to 4D live imaging acquisition and comparative tracking method adaptations and analyses.Challenge 2: The manipulation of imprecise parameters without collateral effects is challenging in biological experiments. In contrast to the biological experiment, computational modeling allows to specifically modulate imprecise parameters and provide testable hypotheses for the generation of robust outcomes. Solution: Objective 2 is devised to provide modeling approaches that can be adapted from an established stochastic modeling framework previously tested by RobustCircuit PIs for the generation of robust synapse formation based on stochastic subcellular dynamics.