Fiber photometry (FP) is a commonly used method to measure the neural activity of freely behaving animals. The analysis of FP data can be complex and is especially difficult for those with little programming experience. Venus Sherathiya and colleagues at Northwestern University Feinberg School of Medicine have developed Guided Photometry Analysis in Python (GuPPy), a Python toolbox that makes FP data analysis intuitive and light on programming.
GuPPy provides a set of graphical user interfaces for loading data, inputting parameters, and producing easily exportable graphs. It is cross platform, and supports data from TDT, Neurophotometrics, and more using ‘.csv’ files as input. GuPPy is well documented, and provides detailed instructional videos on installation, parameter explanations, individual analysis steps, group analysis steps, artifact removal, and more! GuPPy is a great tool to get started with FP analysis that is adaptable and intuitive.