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PASTa: An Open-Source Analysis and Signal Processing Toolbox for Fiber Photometry Data
Rachel M Donka1, Maxine K Loh1, Vaibhav R Konanur2
1Department of Psychology, University of Illinois Chicago, Chicago, Illinois.
Current Protocols
|July 3, 2025
Summary
We developed PASTa, a user-friendly MATLAB toolbox for analyzing fiber photometry data. This tool simplifies neural signal processing and transient event detection for researchers.
Area of Science:
- Neuroscience
- Bioengineering
- Computational Biology
Background:
- Fiber photometry is crucial for real-time neural activity recording in behaving subjects.
- Existing analysis tools for fiber photometry data are often inflexible, inconsistent, and difficult for new users.
- Recent sensor advancements create challenges in signal and control stream fluorescence interpretation.
Purpose of the Study:
- To introduce PASTa (Photometry Analysis and Signal Processing Toolbox), an open-source MATLAB-based solution.
- To provide a comprehensive and user-friendly pipeline for fiber photometry data analysis.
- To improve the reliability of neural signal processing and transient event detection.
Main Methods:
- Developed PASTa, an open-source MATLAB toolbox with a full analysis pipeline.
- Implemented customizable parameters for signal processing and transient event detection.
- Annotated code for readability, accessibility, and adaptability for novice users.
Main Results:
- PASta offers a standardized protocol for fiber photometry data processing.
- The toolbox enables reliable detection and characterization of neural transient events.
- PASta accommodates diverse experimental designs and sensor types.
Conclusions:
- PASta provides a customizable and accessible platform for fiber photometry analysis.
- The toolbox addresses limitations of existing methods, enhancing data interpretation.
- Future updates will integrate novel signal processing methods for broader applicability.
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