# A multicellular analysis calcium imaging toolbox for ImageJ

## TL;DR

The paper introduces MCA, an open-source ImageJ plugin for analyzing calcium imaging data, validated across multiple organisms and sensory responses.

## Contribution

MCA is a modular, user-friendly, open-source functional imaging analysis toolbox for ImageJ.

## Key findings

- MCA was validated using zebrafish calcium imaging data.
- MCA supports analysis of multiple sensory responses and model organisms like Drosophila and mouse.
- MCA includes features like motion correction and data annotation.

## Abstract

Functional imaging using genetically encoded indicators has become a foundational tool for cellular dynamics and communication analysis. However, large or complex experiments pose analytical challenges. Many programs address these challenges; however, most require proprietary software, impose restrictions, or require programming knowledge, which limits their utility. To address this, we designed MCA (Multicellular Analysis toolkit) to work with ImageJ, a widely used open-source software. MCA utilizes ImageJ to generate new images based on completed tasks, allowing visualization of the analysis pipeline. MCA also implements a user-friendly graphical user interface (GUI) resembling native ImageJ plugins. We incorporated rigid registration for motion correction, cell prediction algorithms, and data annotation and exporting features. We validated MCA using previously published zebrafish visual response calcium imaging data. To further show MCA’s versatility, we also tested multiple sensory responses, brain regions, and model organisms, including Drosophila and mouse. Altogether, MCA is a user-friendly environment viable for multiple forms of functional imaging analysis.

•We develop MCA, an ImageJ-based plugin for analyzing functional imaging datasets•MCA is validated on zebrafish calcium imaging datasets•MCA is suitable for multiple sensory modalities and model organisms

We develop MCA, an ImageJ-based plugin for analyzing functional imaging datasets

MCA is validated on zebrafish calcium imaging datasets

MCA is suitable for multiple sensory modalities and model organisms

Calcium imaging has become one of the most common methods for investigating neural activity; however, analytical methods are limited to a few software platforms or are custom-made. This limits replicability and imposes restrictions on incorporating additional tools to support analysis. To address these challenges, we developed a modular, graphical-based, open-source toolbox, based in the ImageJ application, for performing functional imaging analysis in diverse models and datasets.

Hageter et al. developed an open-source toolkit (MCA) that works within the widely used imaging software, ImageJ. They provide an overview of the main functions MCA uses to analyze data from imaging datasets. They apply their software to a variety of model organisms and stimulus types to highlight the versatility of their software.