GuPPy, a Python toolbox for the analysis of fiber photometry data

Venus N. Sherathiya, Michael D. Schaid, Jillian L. Seiler, Gabriela C. Lopez, Talia N. Lerner*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


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.

Original languageEnglish (US)
Article number24212
JournalScientific reports
Issue number1
StatePublished - Dec 2021

ASJC Scopus subject areas

  • General


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