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ezTrack: An open-source video analysis pipeline for the investigation of animal behavior
Tracking animal behavior by video is one of the most common tasks in the life sciences. Although commercial software exists for executing this task, they often present enormous cost to the researcher and can entail purchasing hardware that is expensive and lacks adaptability. Additionally, the under...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6934800/ https://www.ncbi.nlm.nih.gov/pubmed/31882950 http://dx.doi.org/10.1038/s41598-019-56408-9 |
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author | Pennington, Zachary T. Dong, Zhe Feng, Yu Vetere, Lauren M. Page-Harley, Lucia Shuman, Tristan Cai, Denise J. |
author_facet | Pennington, Zachary T. Dong, Zhe Feng, Yu Vetere, Lauren M. Page-Harley, Lucia Shuman, Tristan Cai, Denise J. |
author_sort | Pennington, Zachary T. |
collection | PubMed |
description | Tracking animal behavior by video is one of the most common tasks in the life sciences. Although commercial software exists for executing this task, they often present enormous cost to the researcher and can entail purchasing hardware that is expensive and lacks adaptability. Additionally, the underlying code is often proprietary. Alternatively, available open-source options frequently require model training and can be challenging for those inexperienced with programming. Here we present an open-source and platform independent set of behavior analysis pipelines using interactive Python that researchers with no prior programming experience can use. Two modules are described. One module can be used for the positional analysis of an individual animal, amenable to a wide range of behavioral tasks. A second module is described for the analysis of freezing behavior. For both modules, a range of interactive plots and visualizations are available to confirm that chosen parameters produce the anticipated results. Moreover, batch processing tools for the fast analysis of multiple videos is provided, and frame-by-frame output makes alignment with biological recording data simple. Lastly, options for cropping video frames to mitigate the influence of fiberoptic/electrophysiology cables, analyzing specified portions of time, and defining regions of interest, are readily implemented. |
format | Online Article Text |
id | pubmed-6934800 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-69348002019-12-31 ezTrack: An open-source video analysis pipeline for the investigation of animal behavior Pennington, Zachary T. Dong, Zhe Feng, Yu Vetere, Lauren M. Page-Harley, Lucia Shuman, Tristan Cai, Denise J. Sci Rep Article Tracking animal behavior by video is one of the most common tasks in the life sciences. Although commercial software exists for executing this task, they often present enormous cost to the researcher and can entail purchasing hardware that is expensive and lacks adaptability. Additionally, the underlying code is often proprietary. Alternatively, available open-source options frequently require model training and can be challenging for those inexperienced with programming. Here we present an open-source and platform independent set of behavior analysis pipelines using interactive Python that researchers with no prior programming experience can use. Two modules are described. One module can be used for the positional analysis of an individual animal, amenable to a wide range of behavioral tasks. A second module is described for the analysis of freezing behavior. For both modules, a range of interactive plots and visualizations are available to confirm that chosen parameters produce the anticipated results. Moreover, batch processing tools for the fast analysis of multiple videos is provided, and frame-by-frame output makes alignment with biological recording data simple. Lastly, options for cropping video frames to mitigate the influence of fiberoptic/electrophysiology cables, analyzing specified portions of time, and defining regions of interest, are readily implemented. Nature Publishing Group UK 2019-12-27 /pmc/articles/PMC6934800/ /pubmed/31882950 http://dx.doi.org/10.1038/s41598-019-56408-9 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Pennington, Zachary T. Dong, Zhe Feng, Yu Vetere, Lauren M. Page-Harley, Lucia Shuman, Tristan Cai, Denise J. ezTrack: An open-source video analysis pipeline for the investigation of animal behavior |
title | ezTrack: An open-source video analysis pipeline for the investigation of animal behavior |
title_full | ezTrack: An open-source video analysis pipeline for the investigation of animal behavior |
title_fullStr | ezTrack: An open-source video analysis pipeline for the investigation of animal behavior |
title_full_unstemmed | ezTrack: An open-source video analysis pipeline for the investigation of animal behavior |
title_short | ezTrack: An open-source video analysis pipeline for the investigation of animal behavior |
title_sort | eztrack: an open-source video analysis pipeline for the investigation of animal behavior |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6934800/ https://www.ncbi.nlm.nih.gov/pubmed/31882950 http://dx.doi.org/10.1038/s41598-019-56408-9 |
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