FiPhA: an open-source platform for fiber photometry analysis

• Published in: Neurophotonics (Print) 2024-01, Vol.11 (1), p.014305-014305
• Main Authors: Bridge, Matthew F., Wilson, Leslie R., Panda, Sambit, Stevanovic, Korey D., Letsinger, Ayland C., McBride, Sandra, Cushman, Jesse D.
• Format: Article
• Language: English
• ISSN: 2329-423X; 2329-4248
• DOI: 10.1117/1.NPh.11.1.014305

Fiber photometry (FP) is a widely used technique in modern behavioral neuroscience, employing genetically encoded fluorescent sensors to monitor neural activity and neurotransmitter release in awake-behaving animals. However, analyzing photometry data can be both laborious and time-consuming. We propose the fiber photometry analysis (FiPhA) app, which is a general-purpose FP analysis application. The goal is to develop a pipeline suitable for a wide range of photometry approaches, including spectrally resolved, camera-based, and lock-in demodulation. FiPhA was developed using the R Shiny framework and offers interactive visualization, quality control, and batch processing functionalities in a user-friendly interface. This application simplifies and streamlines the analysis process, thereby reducing labor and time requirements. It offers interactive visualizations, event-triggered average processing, powerful tools for filtering behavioral events, and quality control features. FiPhA is a valuable tool for behavioral neuroscientists working with discrete, event-based FP data. It addresses the challenges associated with analyzing and investigating such data, offering a robust and user-friendly solution without the complexity of having to hand-design custom analysis pipelines. This application thus helps standardize an approach to FP analysis.