GuPPy

GuPPy analyzes fiber photometry (FP) recordings to quantify neural activity and relate FP signals to behavior in neuroscience studies of freely moving animals.

Key Features:

• Fiber photometry data analysis: Implements analysis routines specifically for fiber photometry (FP) recordings to extract neural activity signals.
• Python implementation: Built on a Python-based computational framework for data processing and analysis.
• Parameterized analysis: Supports adjustment of analysis parameters for dataset-specific preprocessing and signal extraction.
• Data visualization: Generates publication-quality graphs that can be exported to various image formats.
• Real-time visualization: Provides real-time visualization of analysis results during processing.

Scientific Applications:

• In vivo neural activity measurement: Analysis of FP recordings to measure neural activity in vivo.
• Behavioral correlation: Correlating FP signals with behavior in studies of freely moving animals.

Methodology:

Implemented in Python; accepts FP data input, allows adjustment of analysis parameters, and provides real-time visualization of results.