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TACI: An ImageJ Plugin for 3D Calcium Imaging Analysis
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TACI: An ImageJ Plugin for 3D Calcium Imaging Analysis.

Alisa A Omelchenko1, Hua Bai2, Sibtain Hussain2

  • 1School of Neuroscience, Virginia Polytechnic Institute and State University; CMU-Pitt Joint Computational Biology, School of Medicine, University of Pittsburgh.

Journal of Visualized Experiments : Jove
|January 2, 2023
PubMed
Summary

This study introduces TrackMate Analysis of Calcium Imaging (TACI), an open-source ImageJ plugin, to analyze 3D calcium imaging data. TACI effectively corrects for z-axis motion, improving neuron separation and analysis in complex neuroscience research.

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Area of Science:

  • Neuroscience
  • Computational Biology
  • Bioimaging

Background:

  • Calcium imaging is crucial in neuroscience but faces challenges with computational analysis and motion correction.
  • Laboratories often struggle with adopting advanced computational methods due to programming barriers and software costs.
  • Existing methods primarily address lateral (x/y) motion, leaving z-axis movement uncorrected in 3D imaging.

Purpose of the Study:

  • To present a novel workflow for analyzing 3D calcium imaging data with a focus on z-axis motion correction.
  • To introduce the TrackMate Analysis of Calcium Imaging (TACI) plugin as a user-friendly, open-source solution.
  • To enable more accurate neuronal analysis by separating overlapping neurons in 3D space.

Main Methods:

  • Development and application of the TrackMate Analysis of Calcium Imaging (TACI) plugin for ImageJ.
  • Utilizing TACI to identify maximum fluorescence across z-positions for each neuron at each time point.
  • Validating the workflow on 3D calcium imaging data from fly larval thermosensitive neurons experiencing temperature fluctuations.

Main Results:

  • TACI successfully quantifies neuron intensity by integrating information across the z-axis.
  • The plugin effectively separates neurons that overlap in the x/y plane but are distinct in the z-plane.
  • The workflow demonstrated robust performance in correcting for multi-directional movement in 3D calcium imaging datasets.

Conclusions:

  • TACI provides an accessible, open-source tool for researchers to analyze 3D calcium imaging data.
  • This method enhances the accuracy of neuronal activity analysis by accounting for z-axis motion.
  • The TACI plugin facilitates the adoption of advanced computational techniques in neuroscience labs.