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Visual Field Analysis: A reliable method to score left and right eye use using automated tracking

Brain and behavioural asymmetries have been documented in various taxa. Many of these asymmetries involve preferential left and right eye use. However, measuring eye use through manual frame-by-frame analyses from video recordings is laborious and may lead to biases. Recent progress in technology ha...

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Autores principales: Josserand, Mathilde, Rosa-Salva, Orsola, Versace, Elisabetta, Lemaire, Bastien S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9374601/
https://www.ncbi.nlm.nih.gov/pubmed/34625917
http://dx.doi.org/10.3758/s13428-021-01702-6
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author Josserand, Mathilde
Rosa-Salva, Orsola
Versace, Elisabetta
Lemaire, Bastien S.
author_facet Josserand, Mathilde
Rosa-Salva, Orsola
Versace, Elisabetta
Lemaire, Bastien S.
author_sort Josserand, Mathilde
collection PubMed
description Brain and behavioural asymmetries have been documented in various taxa. Many of these asymmetries involve preferential left and right eye use. However, measuring eye use through manual frame-by-frame analyses from video recordings is laborious and may lead to biases. Recent progress in technology has allowed the development of accurate tracking techniques for measuring animal behaviour. Amongst these techniques, DeepLabCut, a Python-based tracking toolbox using transfer learning with deep neural networks, offers the possibility to track different body parts with unprecedented accuracy. Exploiting the potentialities of DeepLabCut, we developed Visual Field Analysis, an additional open-source application for extracting eye use data. To our knowledge, this is the first application that can automatically quantify left–right preferences in eye use. Here we test the performance of our application in measuring preferential eye use in young domestic chicks. The comparison with manual scoring methods revealed a near perfect correlation in the measures of eye use obtained by Visual Field Analysis. With our application, eye use can be analysed reliably, objectively and at a fine scale in different experimental paradigms.
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spelling pubmed-93746012022-08-14 Visual Field Analysis: A reliable method to score left and right eye use using automated tracking Josserand, Mathilde Rosa-Salva, Orsola Versace, Elisabetta Lemaire, Bastien S. Behav Res Methods Article Brain and behavioural asymmetries have been documented in various taxa. Many of these asymmetries involve preferential left and right eye use. However, measuring eye use through manual frame-by-frame analyses from video recordings is laborious and may lead to biases. Recent progress in technology has allowed the development of accurate tracking techniques for measuring animal behaviour. Amongst these techniques, DeepLabCut, a Python-based tracking toolbox using transfer learning with deep neural networks, offers the possibility to track different body parts with unprecedented accuracy. Exploiting the potentialities of DeepLabCut, we developed Visual Field Analysis, an additional open-source application for extracting eye use data. To our knowledge, this is the first application that can automatically quantify left–right preferences in eye use. Here we test the performance of our application in measuring preferential eye use in young domestic chicks. The comparison with manual scoring methods revealed a near perfect correlation in the measures of eye use obtained by Visual Field Analysis. With our application, eye use can be analysed reliably, objectively and at a fine scale in different experimental paradigms. Springer US 2021-10-08 2022 /pmc/articles/PMC9374601/ /pubmed/34625917 http://dx.doi.org/10.3758/s13428-021-01702-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Josserand, Mathilde
Rosa-Salva, Orsola
Versace, Elisabetta
Lemaire, Bastien S.
Visual Field Analysis: A reliable method to score left and right eye use using automated tracking
title Visual Field Analysis: A reliable method to score left and right eye use using automated tracking
title_full Visual Field Analysis: A reliable method to score left and right eye use using automated tracking
title_fullStr Visual Field Analysis: A reliable method to score left and right eye use using automated tracking
title_full_unstemmed Visual Field Analysis: A reliable method to score left and right eye use using automated tracking
title_short Visual Field Analysis: A reliable method to score left and right eye use using automated tracking
title_sort visual field analysis: a reliable method to score left and right eye use using automated tracking
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9374601/
https://www.ncbi.nlm.nih.gov/pubmed/34625917
http://dx.doi.org/10.3758/s13428-021-01702-6
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