FPA

FPA: Fiber Photometry Analyzer is an advanced, no-code online software tool developed by Metofico for the analysis and visualization of fiber photometry data. Designed for neuroscience researchers, FPA addresses the challenge of processing the large, complex datasets generated by fiber photometry experiments — without requiring any programming or data science expertise. Whether working individually or in groups, researchers can move from raw data to meaningful insights quickly and reliably.

Fiber photometry is a technique used to monitor population-level calcium dynamics in awake, behaving animals by delivering excitation light via implanted fiber-optic cannulas and collecting fluorescence signals that reflect neuronal activity. FPA is purpose-built to handle the scale and complexity of these datasets, offering a comprehensive suite of preprocessing, analysis, and visualization capabilities through an accessible, fully no-code interface.

Input and Preprocessing

• Batch data import supporting several file formats, including Excel — the most common output format from fiber photometry hardware systems.
• Support for up to 4 light channels per animal, accommodating complex multi-channel experimental setups.
• Artefact removal tools to effortlessly eliminate large artefacts from raw data.
• Smoothing capabilities using digital filters to enhance data clarity prior to analysis.

Study System Management

• Event Manager for conveniently segmenting data with multiple events, with the ability to define events as single time points or as time-bounded intervals for precise experimental analysis.
• Animal Manager enabling researchers to easily organize subjects into groups and subgroups, and to perform both individual and group-level analyses.

Analysis and Visualization

• Multiple normalization methods to accommodate a variety of experimental designs, including ΔF/F, isosbestic fitting, and z-score normalization.
• A range of analysis tools for data exploration, including pre-post baseline comparisons, z-score analysis, and peak detection.
• Built-in plotting features for rapid data exploration, including line plots, bar plots, and heat maps.

Key Benefits

• Efficiency: FPA enables fast processing of vast datasets without writing a single line of code, directly accelerating scientific output.
• Reliability: High-quality data processing and analysis is ensured through the use of the latest published algorithms.
• Repeatability: FPA guarantees precise, repeatable analysis — the same data and parameters will always produce the same results, regardless of the user's skill level.

Why FPA Over Alternatives

• Hardware-bundled analysis software often lacks the usability and features needed to effectively process fiber photometry datasets, based on Metofico's own experience and that of collaborators.
• Open-source tools, while technically free, carry significant hidden costs in implementation time, customization effort, and often suffer from poor interface design and missing critical features.
• FPA provides a robust, fully supported no-code solution accompanied by expert guidance, free demos, and trials.

Module Integration and Compatibility

• FPA is designed to work alongside other Metofico tools — for example, behavioral timestamps generated by TOMB-AI can be used directly within FPA, enabling seamless cross-module workflows.
• The software was initially designed for compatibility with Doric hardware systems but can be adapted to work with other hardware systems by modifying the data extraction and organization process.
• Metofico continuously updates FPA based on customer feedback and market demand to keep the platform aligned with advancements in the field.

FPA is an online software platform offered by Metofico with free demos and trials available. Researchers interested in exploring how FPA can support their specific experimental workflows can contact Metofico directly at [email protected]. The platform has been used in peer-reviewed research published in leading journals including the Journal of Neuroscience, Current Biology, and Cell Metabolism.