AUTHOR=Tran Lina M. , Mocle Andrew J. , Ramsaran Adam I. , Jacob Alexander D. , Frankland Paul W. , Josselyn Sheena A. TITLE=Automated Curation of CNMF-E-Extracted ROI Spatial Footprints and Calcium Traces Using Open-Source AutoML Tools JOURNAL=Frontiers in Neural Circuits VOLUME=14 YEAR=2020 URL=https://www.frontiersin.org/journals/neural-circuits/articles/10.3389/fncir.2020.00042 DOI=10.3389/fncir.2020.00042 ISSN=1662-5110 ABSTRACT=

In vivo 1-photon (1p) calcium imaging is an increasingly prevalent method in behavioral neuroscience. Numerous analysis pipelines have been developed to improve the reliability and scalability of pre-processing and ROI extraction for these large calcium imaging datasets. Despite these advancements in pre-processing methods, manual curation of the extracted spatial footprints and calcium traces of neurons remains important for quality control. Here, we propose an additional semi-automated curation step for sorting spatial footprints and calcium traces from putative neurons extracted using the popular constrained non-negative matrixfactorization for microendoscopic data (CNMF-E) algorithm. We used the automated machine learning (AutoML) tools TPOT and AutoSklearn to generate classifiers to curate the extracted ROIs trained on a subset of human-labeled data. AutoSklearn produced the best performing classifier, achieving an F1 score >92% on the ground truth test dataset. This automated approach is a useful strategy for filtering ROIs with relatively few labeled data points and can be easily added to pre-existing pipelines currently using CNMF-E for ROI extraction.