File:An-open-source-toolbox-for-automated-phenotyping-of-mice-in-behavioral-tasks-Movie2.ogv
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DescriptionAn-open-source-toolbox-for-automated-phenotyping-of-mice-in-behavioral-tasks-Movie2.ogv |
English: Performance in Y-maze. Overview of YMaze scoring module, also applicable for other maze-like configurations, including T-maze, zero-maze, open field, place preference, etc. Separate GUIs and modules for each are provided in the toolbox. Users define regions of interest, such as arms of a maze or subdivisions of an arena and the algorithm computes the amount of time spent in each ROI and the number of transitions between the ROIs. A simple visual output in a bar-code like format is generated for each experiment, which can be useful to detect patterns of exploration. Common measures of performance specific to different maze-like configurations, such as latency to first exit and risk assessment in elevated zero-maze or path length and number of errors for Barnes maze are computed. |
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Source | Video S2 from Patel T, Gullotti D, Hernandez P, O'Brien W, Capehart B, Morrison B, Bass C, Eberwine J, Abel T, Meaney D (2014). "An open-source toolbox for automated phenotyping of mice in behavioral tasks". Frontiers in Behavioral Neuroscience. DOI:10.3389/fnbeh.2014.00349. PMID 25339878. PMC: 4189437. | ||
Author | Patel T, Gullotti D, Hernandez P, O'Brien W, Capehart B, Morrison B, Bass C, Eberwine J, Abel T, Meaney D | ||
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This file is licensed under the Creative Commons Attribution 4.0 International license.
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current | 13:52, 24 October 2014 | 52 s, 1,280 × 720 (2.01 MB) | Open Access Media Importer Bot (talk | contribs) | Automatically uploaded media file from Open Access source. Please report problems or suggestions here. |
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Author | Patel T, Gullotti D, Hernandez P, O'Brien W, Capehart B, Morrison B, Bass C, Eberwine J, Abel T, Meaney D |
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Usage terms | http://creativecommons.org/licenses/by/4.0/ |
Image title | Performance in Y-maze. Overview of YMaze scoring module, also applicable for other maze-like configurations, including T-maze, zero-maze, open field, place preference, etc. Separate GUIs and modules for each are provided in the toolbox. Users define regions of interest, such as arms of a maze or subdivisions of an arena and the algorithm computes the amount of time spent in each ROI and the number of transitions between the ROIs. A simple visual output in a bar-code like format is generated for each experiment, which can be useful to detect patterns of exploration. Common measures of performance specific to different maze-like configurations, such as latency to first exit and risk assessment in elevated zero-maze or path length and number of errors for Barnes maze are computed. |
Software used | Xiph.Org libtheora 1.1 20090822 (Thusnelda) |
Date and time of digitizing | 2014-10-08 |