Fluorescence calcium imaging using a range of microscopy approaches, such as two-photon excitation or head-mounted “miniscopes,” is one of the preferred methods to record neuronal activity and glial signals in various experimental settings, including acute brain slices, brain organoids, and behaving animals. Because changes in the fluorescence intensity of genetically encoded or chemical calcium indicators correlate with action potential firing in neurons, data analysis is based on inferring such spiking from changes in pixel intensity values across time within different regions of interest. However, the algorithms necessary to extract biologically relevant information from these fluorescent signals are complex and require significant expertise in programming to develop robust analysis pipelines. For decades, the only way to perform these analyses was for individual laboratories to write their custom code. These routines were typically not well annotated and lacked intuitive graphical user interfaces (GUIs), which made it difficult for scientists in other laboratories to adopt them. Although the panorama is changing with recent tools like CaImAn, Suite2P, and others, there is still a barrier for many laboratories to adopt these packages, especially for potential users without sophisticated programming skills. As two-photon microscopes are becoming increasingly affordable, the bottleneck is no longer the hardware, but the software used to analyze the calcium data optimally and consistently across different groups. We addressed this unmet need by incorporating recent software solutions, namely NoRMCorre and CaImAn, for motion correction, segmentation, signal extraction, and deconvolution of calcium imaging data into an open-source, easy to use, GUI-based, intuitive and automated data analysis software package, which we named EZcalcium.

使用多种显微镜方法（例如双光子激发或头戴式“微型镜”）进行荧光钙成像是在各种实验环境下记录神经元活动和神经胶质信号的首选方法之一，包括急性脑切片，脑类器官，并表现动物。由于遗传编码或化学钙指示剂的荧光强度变化与神经元中的动作电位触发相关，因此数据分析基于从不同关注区域内整个时间的像素强度值变化推断出这种尖峰。但是，从这些荧光信号中提取生物学相关信息所必需的算法很复杂，并且需要大量的专业知识才能进行编程，以开发出强大的分析流程。几十年来 进行这些分析的唯一方法是让各个实验室编写其自定义代码。这些例程通常没有很好的注释，并且缺少直观的图形用户界面（GUI），这使得其他实验室的科学家很难采用它们。尽管全景图随着最新工具（例如卡门， Suite2P等等，对于许多实验室来说，采用这些软件包仍然存在障碍，特别是对于那些没有复杂编程技能的潜在用户。随着两光子显微镜变得越来越便宜，瓶颈不再是硬件，而是用于在不同组之间最佳且一致地分析钙数据的软件。我们通过结合最新的软件解决方案（即NoRMCorre和CaImAn）来满足这一未满足的需求，该解决方案将运动校正，分割，信号提取和钙成像数据的解卷积处理成开源，易于使用，基于GUI的直观和自动化数据分析软件包，我们命名为易钙。