FiPhA

FiPhA streamlines fiber photometry data analysis through interactive visualization, quality control, and batch processing for spectrally resolved, camera-based, and lock-in demodulation photometry approaches.

Key Features:

• Interactive Visualization: Provides interactive visualizations for exploring fiber photometry data.
• Event-Triggered Average Processing: Supports event-triggered average processing for analyzing neural responses to discrete behavioral events.
• Behavioral Event Filtering: Includes powerful tools for filtering behavioral events in photometry datasets.
• Quality Control: Incorporates quality control features to ensure data integrity during analysis.
• Batch Processing: Enables batch processing functionalities for handling multiple photometry datasets efficiently.

Scientific Applications:

• Neural Activity Monitoring: Analyzes data from genetically encoded fluorescent sensors used to monitor neural activity in awake-behaving animals.
• Neurotransmitter Release Analysis: Supports analysis of neurotransmitter release dynamics measured through fiber photometry.
• Discrete Event-Based Photometry Analysis: Standardizes analysis approaches for discrete, event-based fiber photometry data in behavioral neuroscience research.

Methodology:

FiPhA was developed using the R Shiny framework.