ArticleCurrent protocols2023
PhAT: A Flexible Open-Source GUI-Driven Toolkit for Photometry Analysis.
Article in Current protocols, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
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- PASTa: An Open-Source Analysis and Signal Processing Toolbox for Fiber Photometry Data.Current protocols · 2025Article
- Optimized workflow for behavior-coupled fiber photometry experiment: improved data navigation and accessibility.Frontiers in neuroscience · 2025Article
- Fiber photometry in neuroscience research: principles, applications, and future directions.Pharmacological reports : PR · 2024Review
- Review
- Nucleus accumbens dopamine release reflects the selective nature of pair bonds.Current biology : CB · 2024Article
- FiPhA: an open-source platform for fiber photometry analysis.Neurophotonics · 2024Article
- How can I measure brain acetylcholine levels in vivo? Advantages and caveats of commonly used approaches.Journal of neurochemistry · 2023Review
Corrections and comments
- Update of
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Photometry approaches detect sensor-mediated changes in fluorescence as a proxy for rapid molecular changes within the brain. As a flexible technique with a relatively low cost to implement, photometry is rapidly being incorporated into neuroscience laboratories. Yet, although multiple data acquisition systems for photometry now exist, robust analytical pipelines for the resulting data remain limited. Here we present the Photometry Analysis Toolkit (PhAT)-a free open-source analysis pipeline that provides options for signal normalization, incorporation of multiple data streams to align photometry data with behavior and other events, calculation of event-related changes in fluorescence, and comparison of similarity across fluorescent traces. A graphical user interface (GUI) enables use of this software without prior coding knowledge. In addition to providing foundational analytical tools, PhAT is designed to readily incorporate community-driven development of new modules for more bespoke analyses, and enables data to be easily exported to enable subsequent statistical testing and/or code-based analyses. In addition, we provide recommendations regarding technical aspects of photometry experiments, including sensor selection and validation, reference signal considerations, and best practices for experimental design and data collection. We hope that the distribution of this software and protocols will lower the barrier to entry for new photometry users and improve the quality of collected data, increasing transparency and reproducibility in photometry analyses. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Software and environment installation Alternate Protocol 1: Software and environment update Basic Protocol 2: GUI-driven fiber photometry analysis Support Protocol 1: Examining signal quality Support Protocol 2: Interacting with graphs Basic Protocol 3: Adding modules to PhAT Alternate Protocol 2: Creating functions for use in Jupyter Notebook.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.