Center for Computational Mathematics, Flatiron Institute, New York, NY 10010, United States.
Curr Opin Neurobiol. 2019 Apr;55:15-21. doi: 10.1016/j.conb.2018.11.004. Epub 2019 Feb 15.
Calcium imaging is a popular tool among neuroscientists because of its capability to monitor in vivo large neural populations across weeks with single neuron and single spike resolution. Before any downstream analysis, the data needs to be pre-processed to extract the location and activity of the neurons and processes in the observed field of view. The ever increasing size of calcium imaging datasets necessitates scalable analysis pipelines that are reproducible and fully automated. This review focuses on recent methods for addressing the pre-processing problems that arise in calcium imaging data analysis, and available software tools for high throughput analysis pipelines.
钙成像技术是神经科学家常用的工具，因为它能够以单细胞和单脉冲分辨率在数周内监测活体中的大量神经元群体。在进行任何下游分析之前，数据需要经过预处理，以提取观察视野中神经元和过程的位置和活动。钙成像数据集的规模不断增大，需要可扩展的分析管道，这些管道应该是可重现且完全自动化的。本文综述了当前用于解决钙成像数据分析中出现的预处理问题的方法，以及用于高通量分析管道的可用软件工具。
