Tracking when the number of individuals in the video frame changes.
<p>(A) Overview of the verification process. The yellow box in the schematic represents the processes using multi-animal tracking tools, while the green box represents the processes using single-animal tracking tools. (B) Schematic diagram of the annotation method. The outlined mouse in the sc...
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| مؤلفون آخرون: | |
| منشور في: |
2025
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| الملخص: | <p>(A) Overview of the verification process. The yellow box in the schematic represents the processes using multi-animal tracking tools, while the green box represents the processes using single-animal tracking tools. (B) Schematic diagram of the annotation method. The outlined mouse in the schematic indicates that the mouse was removed from the arena and is absent in the frame. In the case of 3 mice (left), 6 standard annotations were made for each mouse. In the case of 2 mice (center), keypoints for Mouse 2 and Mouse 3 were annotated on each body part of the same mouse. In the case of one mouse (right), keypoints for all mice were annotated on the body parts of that single mouse. Here, the labels are color-coded by individual. (C) Schematic diagram (top) of an experiment that altered the number of mice in the video frame by introducing or removing mice from the arena, and examples of tracking photos during this procedure (bottom). To verify tracking of other mice with leftover keypoints due to the absence of some mice, distances (d: pixels) between identical keypoints for 3 IDs were calculated for each keypoint. The stray keypoints indicated above the outlined mouse, which represents absence in the frame in the top schematic, were evaluated to determine whether they could predict another mouse in the arena, following the annotation method described in (B). Here, the labels are color-coded by body part. (D) If the distance between identical keypoints was within 10 pixels, the 2 ID keypoints were considered overlapping, and the frequency of such frames was calculated for each keypoint and ID pair combination. The diagram illustrates changes across different experimental conditions, with plots indicating the frequency for each keypoint and bars representing each ID pair. The “+” below the diagram indicates the presence of mice in the arena, while “−” indicates their absence. Statistical analysis was conducted using the Friedman test for comparisons within each condition and the Kruskal–Wallis test for comparisons between conditions, with Bonferroni correction applied to account for the 45 total comparison pairs. Additionally, Cliff’s delta was calculated as an effect size for these pairs (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003002#pbio.3003002.s013" target="_blank">S1</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003002#pbio.3003002.s014" target="_blank">S2</a> Tables). (Ea–c) In Original tracking, markers for Mouse 1 (blue), Mouse 2 (green), and Mouse 3 (red) overlap under various conditions. After removing data from absent mice, a video with no overlaps and accurate tracking by correct IDs is created (delete overlapping keypoints). (Ed) Even in markerless multi-animal pose tracking, markers can overlap. Removing such overlaps allows for creating virtual marker videos with accurate ID identification. In this example, extraneous white data obscuring the correct gray virtual marker are removed. The removal of unnecessary keypoint data is achieved through a Python code that allows specified ranges of tracking data obtained from DeepLabCut to be rewritten as NaN (no data) (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003002#pbio.3003002.s019" target="_blank">S1 Protocol</a> and <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003002#pbio.3003002.s010" target="_blank">S10C Fig</a>). The data underlying these analyses are provided in S1 Data. Additionally, these figures can be reproduced using the MATLAB data and code available in the Zenodo repository (<a href="https://doi.org/10.5281/zenodo.14545410" target="_blank">https://doi.org/10.5281/zenodo.14545410</a>).</p> <p>(TIFF)</p> |
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