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Related Experiment Video

Updated: Aug 5, 2025

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

Published on: January 18, 2017

PhAT: A flexible open-source GUI-driven toolkit for photometry analysis.

Kathleen Z Murphy¹, Eyobel Haile², Anna McTigue³

¹Department of Psychology & Neuroscience, 345 UCB, University of Colorado Boulder, Boulder, CO 80304.

Biorxiv : the Preprint Server for Biology

|March 30, 2023

Summary

This summary is machine-generated.

This study introduces the Photometry Analysis Toolkit (PhAT), a free, open-source software designed to streamline the analysis of fiber photometry data. PhAT offers essential tools for signal processing and visualization, enhancing reproducibility in neuroscience research.

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Area of Science:

Neuroscience
Biotechnology

Background:

Fiber photometry is a valuable technique for monitoring neural activity via fluorescence changes.
Existing analytical tools for photometry data are limited, hindering widespread adoption and reproducibility.

Approach:

Developed the Photometry Analysis Toolkit (PhAT), a free, open-source software pipeline with a graphical user interface (GUI).
PhAT includes modules for signal normalization, event-related analysis, and cross-trace similarity comparison.
The toolkit facilitates integration with behavioral data and supports community-driven module development.

Key Points:

PhAT provides essential analytical functions for fiber photometry data, including normalization and event-based analysis.
A user-friendly GUI allows operation without coding expertise, lowering the barrier to entry.
The software promotes transparency and reproducibility in neuroscience research by standardizing data analysis.

Conclusions:

PhAT aims to improve the quality and accessibility of fiber photometry data analysis in neuroscience.
The toolkit supports best practices for experimental design and data collection, fostering more robust research outcomes.