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GuPPy, a Python toolbox for the analysis of fiber photometry data
Fiber photometry (FP) is an adaptable method for recording in vivo neural activity in freely behaving animals. It has become a popular tool in neuroscience due to its ease of use, low cost, the ability to combine FP with freely moving behavior, among other advantages. However, analysis of FP data ca...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8688475/ https://www.ncbi.nlm.nih.gov/pubmed/34930955 http://dx.doi.org/10.1038/s41598-021-03626-9 |
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author | Sherathiya, Venus N. Schaid, Michael D. Seiler, Jillian L. Lopez, Gabriela C. Lerner, Talia N. |
author_facet | Sherathiya, Venus N. Schaid, Michael D. Seiler, Jillian L. Lopez, Gabriela C. Lerner, Talia N. |
author_sort | Sherathiya, Venus N. |
collection | PubMed |
description | Fiber photometry (FP) is an adaptable method for recording in vivo neural activity in freely behaving animals. It has become a popular tool in neuroscience due to its ease of use, low cost, the ability to combine FP with freely moving behavior, among other advantages. However, analysis of FP data can be challenging for new users, especially those with a limited programming background. Here, we present Guided Photometry Analysis in Python (GuPPy), a free and open-source FP analysis tool. GuPPy is designed to operate across computing platforms and can accept data from a variety of FP data acquisition systems. The program presents users with a set of graphic user interfaces (GUIs) to load data and provide input parameters. Graphs are produced that can be easily exported for integration into scientific figures. As an open-source tool, GuPPy can be modified by users with knowledge of Python to fit their specific needs. |
format | Online Article Text |
id | pubmed-8688475 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-86884752021-12-22 GuPPy, a Python toolbox for the analysis of fiber photometry data Sherathiya, Venus N. Schaid, Michael D. Seiler, Jillian L. Lopez, Gabriela C. Lerner, Talia N. Sci Rep Article Fiber photometry (FP) is an adaptable method for recording in vivo neural activity in freely behaving animals. It has become a popular tool in neuroscience due to its ease of use, low cost, the ability to combine FP with freely moving behavior, among other advantages. However, analysis of FP data can be challenging for new users, especially those with a limited programming background. Here, we present Guided Photometry Analysis in Python (GuPPy), a free and open-source FP analysis tool. GuPPy is designed to operate across computing platforms and can accept data from a variety of FP data acquisition systems. The program presents users with a set of graphic user interfaces (GUIs) to load data and provide input parameters. Graphs are produced that can be easily exported for integration into scientific figures. As an open-source tool, GuPPy can be modified by users with knowledge of Python to fit their specific needs. Nature Publishing Group UK 2021-12-20 /pmc/articles/PMC8688475/ /pubmed/34930955 http://dx.doi.org/10.1038/s41598-021-03626-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Sherathiya, Venus N. Schaid, Michael D. Seiler, Jillian L. Lopez, Gabriela C. Lerner, Talia N. GuPPy, a Python toolbox for the analysis of fiber photometry data |
title | GuPPy, a Python toolbox for the analysis of fiber photometry data |
title_full | GuPPy, a Python toolbox for the analysis of fiber photometry data |
title_fullStr | GuPPy, a Python toolbox for the analysis of fiber photometry data |
title_full_unstemmed | GuPPy, a Python toolbox for the analysis of fiber photometry data |
title_short | GuPPy, a Python toolbox for the analysis of fiber photometry data |
title_sort | guppy, a python toolbox for the analysis of fiber photometry data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8688475/ https://www.ncbi.nlm.nih.gov/pubmed/34930955 http://dx.doi.org/10.1038/s41598-021-03626-9 |
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