FiPhA: an open-source platform for fiber photometry analysis

Area of Science:

• Behavioral Neuroscience
• Neuroimaging Techniques
• Data Analysis Software

Background:

• Fiber photometry (FP) is crucial for monitoring neural activity and neurotransmitter release in awake animals.
• Analyzing FP data is often labor-intensive and time-consuming, hindering research progress.

Purpose of the Study:

• To develop a general-purpose application, Fiber Photometry Analysis (FiPhA), for streamlined FP data analysis.
• To create a versatile pipeline compatible with various FP methods like spectrally resolved, camera-based, and lock-in demodulation.

Main Methods:

• FiPhA was developed using the R Shiny framework, ensuring a user-friendly interface.
• The application incorporates interactive visualization, quality control, and batch processing features.
• It enables event-triggered average processing and filtering of behavioral events.

Main Results:

• FiPhA significantly simplifies and accelerates the analysis of fiber photometry data.
• The app provides interactive visualizations and robust quality control measures.
• Batch processing capabilities enhance efficiency for large datasets.

Conclusions:

• FiPhA offers a valuable, user-friendly solution for analyzing discrete, event-based FP data in behavioral neuroscience.
• It reduces the need for custom analysis pipelines, promoting standardization in FP data investigation.
• This tool empowers researchers to efficiently analyze complex neural activity data.