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Supervised and Unsupervised Learning Technology in the Study of Rodent Behavior
Quantifying behavior is a challenge for scientists studying neuroscience, ethology, psychology, pathology, etc. Until now, behavior was mostly considered as qualitative descriptions of postures or labor intensive counting of bouts of individual movements. Many prominent behavioral scientists conduct...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5532435/ https://www.ncbi.nlm.nih.gov/pubmed/28804452 http://dx.doi.org/10.3389/fnbeh.2017.00141 |
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author | Gris, Katsiaryna V. Coutu, Jean-Philippe Gris, Denis |
author_facet | Gris, Katsiaryna V. Coutu, Jean-Philippe Gris, Denis |
author_sort | Gris, Katsiaryna V. |
collection | PubMed |
description | Quantifying behavior is a challenge for scientists studying neuroscience, ethology, psychology, pathology, etc. Until now, behavior was mostly considered as qualitative descriptions of postures or labor intensive counting of bouts of individual movements. Many prominent behavioral scientists conducted studies describing postures of mice and rats, depicting step by step eating, grooming, courting, and other behaviors. Automated video assessment technologies permit scientists to quantify daily behavioral patterns/routines, social interactions, and postural changes in an unbiased manner. Here, we extensively reviewed published research on the topic of the structural blocks of behavior and proposed a structure of behavior based on the latest publications. We discuss the importance of defining a clear structure of behavior to allow professionals to write viable algorithms. We presented a discussion of technologies that are used in automated video assessment of behavior in mice and rats. We considered advantages and limitations of supervised and unsupervised learning. We presented the latest scientific discoveries that were made using automated video assessment. In conclusion, we proposed that the automated quantitative approach to evaluating animal behavior is the future of understanding the effect of brain signaling, pathologies, genetic content, and environment on behavior. |
format | Online Article Text |
id | pubmed-5532435 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-55324352017-08-11 Supervised and Unsupervised Learning Technology in the Study of Rodent Behavior Gris, Katsiaryna V. Coutu, Jean-Philippe Gris, Denis Front Behav Neurosci Neuroscience Quantifying behavior is a challenge for scientists studying neuroscience, ethology, psychology, pathology, etc. Until now, behavior was mostly considered as qualitative descriptions of postures or labor intensive counting of bouts of individual movements. Many prominent behavioral scientists conducted studies describing postures of mice and rats, depicting step by step eating, grooming, courting, and other behaviors. Automated video assessment technologies permit scientists to quantify daily behavioral patterns/routines, social interactions, and postural changes in an unbiased manner. Here, we extensively reviewed published research on the topic of the structural blocks of behavior and proposed a structure of behavior based on the latest publications. We discuss the importance of defining a clear structure of behavior to allow professionals to write viable algorithms. We presented a discussion of technologies that are used in automated video assessment of behavior in mice and rats. We considered advantages and limitations of supervised and unsupervised learning. We presented the latest scientific discoveries that were made using automated video assessment. In conclusion, we proposed that the automated quantitative approach to evaluating animal behavior is the future of understanding the effect of brain signaling, pathologies, genetic content, and environment on behavior. Frontiers Media S.A. 2017-07-28 /pmc/articles/PMC5532435/ /pubmed/28804452 http://dx.doi.org/10.3389/fnbeh.2017.00141 Text en Copyright © 2017 Gris, Coutu and Gris. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Gris, Katsiaryna V. Coutu, Jean-Philippe Gris, Denis Supervised and Unsupervised Learning Technology in the Study of Rodent Behavior |
title | Supervised and Unsupervised Learning Technology in the Study of Rodent Behavior |
title_full | Supervised and Unsupervised Learning Technology in the Study of Rodent Behavior |
title_fullStr | Supervised and Unsupervised Learning Technology in the Study of Rodent Behavior |
title_full_unstemmed | Supervised and Unsupervised Learning Technology in the Study of Rodent Behavior |
title_short | Supervised and Unsupervised Learning Technology in the Study of Rodent Behavior |
title_sort | supervised and unsupervised learning technology in the study of rodent behavior |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5532435/ https://www.ncbi.nlm.nih.gov/pubmed/28804452 http://dx.doi.org/10.3389/fnbeh.2017.00141 |
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