Minian an open-source miniscope analysis pipeline
- Icahn School of Medicine at Mount Sinai, United States
- University of California, Los Angeles, United States
Abstract
Miniature microscopes have gained considerable traction for in vivo calcium imaging in freely behaving animals. However, extracting calcium signals from raw videos is a computationally complex problem and remains a bottleneck for many researchers utilizing single-photon in vivo calcium imaging. Despite the existence of many powerful analysis packages designed to detect and extract calcium dynamics, most have either key parameters that are hard-coded or insufficient step-by-step guidance and validations to help the users choose the best parameters. This makes it difficult to know whether the output is reliable and meets the assumptions necessary for proper analysis. Moreover, large memory demand is often a constraint for setting up these pipelines since it limits the choice of hardware to specialized computers. Given these difficulties, there is a need for a low memory demand, user-friendly tool offering interactive visualizations of how altering parameters at each step of the analysis affects data output. Our open-source analysis pipeline, Minian (Miniscope Analysis), facilitates the transparency and accessibility of single-photon calcium imaging analysis, permitting users with little computational experience to extract the location of cells and their corresponding calcium traces and deconvolved neural activities. Minian contains interactive visualization tools for every step of the analysis, as well as detailed documentation and tips on parameter exploration. Furthermore, Minian has relatively small memory demands and can be run on a laptop, making it available to labs that do not have access to specialized computational hardware. Minian has been validated to reliably and robustly extract calcium events across different brain regions and from different cell types. In practice, Minian provides an open-source calcium imaging analysis pipeline with user-friendly interactive visualizations to explore parameters and validate results.
Data availability
github repo: https://github.com/denisecailab/minian
Article and author information
Author details
Funding
NIMH (DP2MH122399)
- Denise J Cai
NIMH (R01MH120162)
- Denise J Cai
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Caleb Kemere, Rice University, United States
Ethics
Animal experimentation: All experiments were performed in accordance with relevant guidelines and regulations approved by the Institutional Animal Care and Use Committee of Icahn School of Medicine at Mount Sinai (Reference #: IACUC-2017-0361, Protocol #: 17-1994).
Version history
- Preprint posted: May 4, 2021 (view preprint)
- Received: May 25, 2021
- Accepted: May 31, 2022
- Accepted Manuscript published: June 1, 2022 (version 1)
- Version of Record published: June 17, 2022 (version 2)
Copyright
© 2022, Dong et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Minian an open-source miniscope analysis pipeline
eLife 11:e70661.
https://doi.org/10.7554/eLife.70661
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