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Open-source software for automated rodent behavioral analysis
Rodent behavioral analysis is a major specialization in experimental psychology and behavioral neuroscience. Rodents display a wide range of species-specific behaviors, not only in their natural habitats but also under behavioral testing in controlled laboratory conditions. Detecting and categorizin...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10149747/ https://www.ncbi.nlm.nih.gov/pubmed/37139530 http://dx.doi.org/10.3389/fnins.2023.1149027 |
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author | Isik, Sena Unal, Gunes |
author_facet | Isik, Sena Unal, Gunes |
author_sort | Isik, Sena |
collection | PubMed |
description | Rodent behavioral analysis is a major specialization in experimental psychology and behavioral neuroscience. Rodents display a wide range of species-specific behaviors, not only in their natural habitats but also under behavioral testing in controlled laboratory conditions. Detecting and categorizing these different kinds of behavior in a consistent way is a challenging task. Observing and analyzing rodent behaviors manually limits the reproducibility and replicability of the analyses due to potentially low inter-rater reliability. The advancement and accessibility of object tracking and pose estimation technologies led to several open-source artificial intelligence (AI) tools that utilize various algorithms for rodent behavioral analysis. These software provide high consistency compared to manual methods, and offer more flexibility than commercial systems by allowing custom-purpose modifications for specific research needs. Open-source software reviewed in this paper offer automated or semi-automated methods for detecting and categorizing rodent behaviors by using hand-coded heuristics, machine learning, or neural networks. The underlying algorithms show key differences in their internal dynamics, interfaces, user-friendliness, and the variety of their outputs. This work reviews the algorithms, capability, functionality, features and software properties of open-source behavioral analysis tools, and discusses how this emergent technology facilitates behavioral quantification in rodent research. |
format | Online Article Text |
id | pubmed-10149747 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101497472023-05-02 Open-source software for automated rodent behavioral analysis Isik, Sena Unal, Gunes Front Neurosci Neuroscience Rodent behavioral analysis is a major specialization in experimental psychology and behavioral neuroscience. Rodents display a wide range of species-specific behaviors, not only in their natural habitats but also under behavioral testing in controlled laboratory conditions. Detecting and categorizing these different kinds of behavior in a consistent way is a challenging task. Observing and analyzing rodent behaviors manually limits the reproducibility and replicability of the analyses due to potentially low inter-rater reliability. The advancement and accessibility of object tracking and pose estimation technologies led to several open-source artificial intelligence (AI) tools that utilize various algorithms for rodent behavioral analysis. These software provide high consistency compared to manual methods, and offer more flexibility than commercial systems by allowing custom-purpose modifications for specific research needs. Open-source software reviewed in this paper offer automated or semi-automated methods for detecting and categorizing rodent behaviors by using hand-coded heuristics, machine learning, or neural networks. The underlying algorithms show key differences in their internal dynamics, interfaces, user-friendliness, and the variety of their outputs. This work reviews the algorithms, capability, functionality, features and software properties of open-source behavioral analysis tools, and discusses how this emergent technology facilitates behavioral quantification in rodent research. Frontiers Media S.A. 2023-04-17 /pmc/articles/PMC10149747/ /pubmed/37139530 http://dx.doi.org/10.3389/fnins.2023.1149027 Text en Copyright © 2023 Isik and Unal. https://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) and the copyright owner(s) 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 Isik, Sena Unal, Gunes Open-source software for automated rodent behavioral analysis |
title | Open-source software for automated rodent behavioral analysis |
title_full | Open-source software for automated rodent behavioral analysis |
title_fullStr | Open-source software for automated rodent behavioral analysis |
title_full_unstemmed | Open-source software for automated rodent behavioral analysis |
title_short | Open-source software for automated rodent behavioral analysis |
title_sort | open-source software for automated rodent behavioral analysis |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10149747/ https://www.ncbi.nlm.nih.gov/pubmed/37139530 http://dx.doi.org/10.3389/fnins.2023.1149027 |
work_keys_str_mv | AT isiksena opensourcesoftwareforautomatedrodentbehavioralanalysis AT unalgunes opensourcesoftwareforautomatedrodentbehavioralanalysis |