CaImAn : An open source tool for 1 scalable Calcium Imaging data 2 Analysis 3

Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with 13 finer time resolution. The resulting data rates require reproducible analysis pipelines that are 14 reliable, fully automated, and scalable to datasets generated over the course of months. Here we 15 present CAIMAN, an open-source library for calcium imaging data analysis. CAIMAN provides 16 automatic and scalable methods to address problems common to pre-processing, including motion 17 correction, neural activity identification, and registration across different sessions of data collection. 18 It does this while requiring minimal user intervention, with good performance on computers 19 ranging from laptops to high-performance computing clusters. CAIMAN is suitable for two-photon 20 and one-photon imaging, and also enables real-time analysis on streaming data. To benchmark the 21 performance of CAIMAN we collected a corpus of ground truth annotations from multiple labelers 22 on nine mouse two-photon datasets. We demonstrate that CAIMAN achieves near-human 23 performance in detecting locations of active neurons. 24