FiPhA: an Open-source Platform for Fiber Photometry Analysis

Overview

Journal Neurophotonics

Date 2024 Feb 26

PMID 38406178

Authors

Matthew F Bridge

Leslie R Wilson

Sambit Panda

Korey D Stevanovic

Ayland C Letsinger

Sandra McBride

Jesse D Cushman

Affiliations

Soon will be listed here.

Abstract

Significance: Fiber photometry (FP) is a widely used technique in modern behavioral neuroscience, employing genetically encoded fluorescent sensors to monitor neural activity and neurotransmitter release in awake-behaving animals. However, analyzing photometry data can be both laborious and time-consuming.

Aim: We propose the fiber photometry analysis (FiPhA) app, which is a general-purpose FP analysis application. The goal is to develop a pipeline suitable for a wide range of photometry approaches, including spectrally resolved, camera-based, and lock-in demodulation.

Approach: FiPhA was developed using the R Shiny framework and offers interactive visualization, quality control, and batch processing functionalities in a user-friendly interface.

Results: This application simplifies and streamlines the analysis process, thereby reducing labor and time requirements. It offers interactive visualizations, event-triggered average processing, powerful tools for filtering behavioral events, and quality control features.

Conclusions: FiPhA is a valuable tool for behavioral neuroscientists working with discrete, event-based FP data. It addresses the challenges associated with analyzing and investigating such data, offering a robust and user-friendly solution without the complexity of having to hand-design custom analysis pipelines. This application thus helps standardize an approach to FP analysis.

Citing Articles

Special Section Guest Editorial: Open-source neurophotonic tools for neuroscience.

Kodandaramaiah S, Aharoni D, Gibson E Neurophotonics. 2024; 11(3):034301.

PMID: 39350913 PMC: 11441622. DOI: 10.1117/1.NPh.11.3.034301.

Fiber photometry in neuroscience research: principles, applications, and future directions.

Kielbinski M, Bernacka J Pharmacol Rep. 2024; 76(6):1242-1255.

PMID: 39235662 PMC: 11582208. DOI: 10.1007/s43440-024-00646-w.

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