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PhAT: A flexible open-source GUI-driven toolkit for photometry analysis.
Murphy, Kathleen Z; Haile, Eyobel; McTigue, Anna; Pierce, Anne F; Donaldson, Zoe R.
Afiliação
  • Murphy KZ; Department of Psychology & Neuroscience, 345 UCB, University of Colorado Boulder, Boulder, CO 80304.
  • Haile E; Department of Computer Science, 430 UCB, University of Colorado Boulder, Boulder, CO 80304.
  • McTigue A; Department of Molecular, Cellular, and Developmental Biology, UCB 347, University of Colorado Boulder, Boulder, CO 80304.
  • Pierce AF; Department of Psychology & Neuroscience, 345 UCB, University of Colorado Boulder, Boulder, CO 80304.
  • Donaldson ZR; Department of Psychology & Neuroscience, 345 UCB, University of Colorado Boulder, Boulder, CO 80304.
bioRxiv ; 2023 Mar 14.
Article em En | MEDLINE | ID: mdl-36993180
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. While multiple data acquisition systems for photometry now exist, robust analytical pipelines for the resulting data remain limited. Here we present the Ph otometry A nalysis T oolkit (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 data can 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 protocol will lower the barrier to entry for new photometry users and improve the quality of collected data, increasing transparency and reproducibility in photometry analyses. Basic Protocol 1 Software Environment InstallationBasic Protocol 2 GUI-driven Fiber Photometry AnalysisBasic Protocol 3 Adding Modules.

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article