Zebrafish automatic monitoring system for conditioning and behavioral analysis
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRN |
Texto Completo: | https://repositorio.ufrn.br/handle/123456789/32343 |
Resumo: | Studies using zebrafish (Danio rerio) in neuro-behavioural research are growing. Measuring fish behavior by computational methods is one of the most efficient ways to avoid human bias in experimental analyses, extending them to various approaches. Sometimes, thorough analyses are difficult to do, as fish can behave unpredictably during an experimental strategy. However, the analyses can be implemented in an automated way, using an online strategy and video processing for a complete assessment of the zebrafish behavior, based on the detection and tracking of fish during an activity. Here, a fully automatic conditioning and detailed analysis of zebrafish behavior is presented. Microcontrolled components were used to control the delivery of visual and sound stimuli, in addition to the concise amounts of food after conditioned stimuli for adult zebrafish groups in a conventional tank. The images were captured and processed for automatic detection of the fish, and the training of the fish was done in two evaluation strategies: simple and complex. In simple conditioning, the zebrafish showed significant responses from the second attempt, learning that the conditioned stimulus was a predictor of food presentation in a specific space of the tank, where the food was dumped. When the fish were subjected to two stimuli for decision-making in the food reward, the zebrafish obtained better responses to red light stimuli in relation to vibration. The behavior change was clear in stimulated fish in relation to the control group, thus, the distances traveled and the speed were greater, while the polarization was lower in stimulated fish. This automated system allows for the conditioning and assessment of zebrafish behavior online, with greater stability in experiments, and in the analysis of the behavior of individual fish or fish schools, including learning and memory studies |
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Barreiros, Marta de OliveiraBarbosa, Felipe GomesDantas, Diego de OliveiraSantos, Daniel de Matos Luna dosRibeiro, Sidarta Tollendal GomesSantos, Giselle Cutrim de OliveiraBarros, Allan Kardec2021-04-30T13:20:40Z2021-04-30T13:20:40Z2021-04-29BARREIROS, Marta de Oliveira; BARBOSA, Felipe Gomes; DANTAS, Diego de Oliveira; SANTOS, Daniel de Matos Luna dos; RIBEIRO, Sidarta; SANTOS, Giselle Cutrim de Oliveira; BARROS, Allan Kardec. Zebrafish automatic monitoring system for conditioning and behavioral analysis. Scientific Reports, [S.L.], v. 11, p. 9330, abr. 2021. Doi: http://dx.doi.org/10.1038/s41598-021-87502-6. Disponível em: https://www.nature.com/articles/s41598-021-87502-6. Acesso em: 30 abr. 2021.https://repositorio.ufrn.br/handle/123456789/3234310.1038/s41598-021-87502-6Springer Science and Business Media LLCAttribution 3.0 Brazilhttp://creativecommons.org/licenses/by/3.0/br/info:eu-repo/semantics/openAccessZebrafish - Automatic monitoring systemYOLOv2 networkBehavior, animalZebrafish automatic monitoring system for conditioning and behavioral analysisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleStudies using zebrafish (Danio rerio) in neuro-behavioural research are growing. Measuring fish behavior by computational methods is one of the most efficient ways to avoid human bias in experimental analyses, extending them to various approaches. Sometimes, thorough analyses are difficult to do, as fish can behave unpredictably during an experimental strategy. However, the analyses can be implemented in an automated way, using an online strategy and video processing for a complete assessment of the zebrafish behavior, based on the detection and tracking of fish during an activity. Here, a fully automatic conditioning and detailed analysis of zebrafish behavior is presented. Microcontrolled components were used to control the delivery of visual and sound stimuli, in addition to the concise amounts of food after conditioned stimuli for adult zebrafish groups in a conventional tank. The images were captured and processed for automatic detection of the fish, and the training of the fish was done in two evaluation strategies: simple and complex. In simple conditioning, the zebrafish showed significant responses from the second attempt, learning that the conditioned stimulus was a predictor of food presentation in a specific space of the tank, where the food was dumped. When the fish were subjected to two stimuli for decision-making in the food reward, the zebrafish obtained better responses to red light stimuli in relation to vibration. The behavior change was clear in stimulated fish in relation to the control group, thus, the distances traveled and the speed were greater, while the polarization was lower in stimulated fish. This automated system allows for the conditioning and assessment of zebrafish behavior online, with greater stability in experiments, and in the analysis of the behavior of individual fish or fish schools, including learning and memory studiesengreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRNCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8914https://repositorio.ufrn.br/bitstream/123456789/32343/2/license_rdf4d2950bda3d176f570a9f8b328dfbbefMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81484https://repositorio.ufrn.br/bitstream/123456789/32343/3/license.txte9597aa2854d128fd968be5edc8a28d9MD53ORIGINALZebrafshAutomaticMonitoring_Ribeiro_2021.pdfZebrafshAutomaticMonitoring_Ribeiro_2021.pdfZebrafishAutomaticMonitoring_Ribeiro_2021application/pdf7594467https://repositorio.ufrn.br/bitstream/123456789/32343/1/ZebrafshAutomaticMonitoring_Ribeiro_2021.pdf779941b55e614161c0f0027cf7a52807MD51TEXTZebrafshAutomaticMonitoring_Ribeiro_2021.pdf.txtZebrafshAutomaticMonitoring_Ribeiro_2021.pdf.txtExtracted texttext/plain65304https://repositorio.ufrn.br/bitstream/123456789/32343/4/ZebrafshAutomaticMonitoring_Ribeiro_2021.pdf.txt0f44a9067ba741126d927a166a39b56dMD54THUMBNAILZebrafshAutomaticMonitoring_Ribeiro_2021.pdf.jpgZebrafshAutomaticMonitoring_Ribeiro_2021.pdf.jpgGenerated Thumbnailimage/jpeg1836https://repositorio.ufrn.br/bitstream/123456789/32343/5/ZebrafshAutomaticMonitoring_Ribeiro_2021.pdf.jpg2c5a6044d5bb8726c1d4905a294e1b76MD55123456789/323432021-05-02 08:35:49.767oai:https://repositorio.ufrn.br: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Repositório de PublicaçõesPUBhttp://repositorio.ufrn.br/oai/opendoar:2021-05-02T11:35:49Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false |
dc.title.pt_BR.fl_str_mv |
Zebrafish automatic monitoring system for conditioning and behavioral analysis |
title |
Zebrafish automatic monitoring system for conditioning and behavioral analysis |
spellingShingle |
Zebrafish automatic monitoring system for conditioning and behavioral analysis Barreiros, Marta de Oliveira Zebrafish - Automatic monitoring system YOLOv2 network Behavior, animal |
title_short |
Zebrafish automatic monitoring system for conditioning and behavioral analysis |
title_full |
Zebrafish automatic monitoring system for conditioning and behavioral analysis |
title_fullStr |
Zebrafish automatic monitoring system for conditioning and behavioral analysis |
title_full_unstemmed |
Zebrafish automatic monitoring system for conditioning and behavioral analysis |
title_sort |
Zebrafish automatic monitoring system for conditioning and behavioral analysis |
author |
Barreiros, Marta de Oliveira |
author_facet |
Barreiros, Marta de Oliveira Barbosa, Felipe Gomes Dantas, Diego de Oliveira Santos, Daniel de Matos Luna dos Ribeiro, Sidarta Tollendal Gomes Santos, Giselle Cutrim de Oliveira Barros, Allan Kardec |
author_role |
author |
author2 |
Barbosa, Felipe Gomes Dantas, Diego de Oliveira Santos, Daniel de Matos Luna dos Ribeiro, Sidarta Tollendal Gomes Santos, Giselle Cutrim de Oliveira Barros, Allan Kardec |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Barreiros, Marta de Oliveira Barbosa, Felipe Gomes Dantas, Diego de Oliveira Santos, Daniel de Matos Luna dos Ribeiro, Sidarta Tollendal Gomes Santos, Giselle Cutrim de Oliveira Barros, Allan Kardec |
dc.subject.por.fl_str_mv |
Zebrafish - Automatic monitoring system YOLOv2 network Behavior, animal |
topic |
Zebrafish - Automatic monitoring system YOLOv2 network Behavior, animal |
description |
Studies using zebrafish (Danio rerio) in neuro-behavioural research are growing. Measuring fish behavior by computational methods is one of the most efficient ways to avoid human bias in experimental analyses, extending them to various approaches. Sometimes, thorough analyses are difficult to do, as fish can behave unpredictably during an experimental strategy. However, the analyses can be implemented in an automated way, using an online strategy and video processing for a complete assessment of the zebrafish behavior, based on the detection and tracking of fish during an activity. Here, a fully automatic conditioning and detailed analysis of zebrafish behavior is presented. Microcontrolled components were used to control the delivery of visual and sound stimuli, in addition to the concise amounts of food after conditioned stimuli for adult zebrafish groups in a conventional tank. The images were captured and processed for automatic detection of the fish, and the training of the fish was done in two evaluation strategies: simple and complex. In simple conditioning, the zebrafish showed significant responses from the second attempt, learning that the conditioned stimulus was a predictor of food presentation in a specific space of the tank, where the food was dumped. When the fish were subjected to two stimuli for decision-making in the food reward, the zebrafish obtained better responses to red light stimuli in relation to vibration. The behavior change was clear in stimulated fish in relation to the control group, thus, the distances traveled and the speed were greater, while the polarization was lower in stimulated fish. This automated system allows for the conditioning and assessment of zebrafish behavior online, with greater stability in experiments, and in the analysis of the behavior of individual fish or fish schools, including learning and memory studies |
publishDate |
2021 |
dc.date.accessioned.fl_str_mv |
2021-04-30T13:20:40Z |
dc.date.available.fl_str_mv |
2021-04-30T13:20:40Z |
dc.date.issued.fl_str_mv |
2021-04-29 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
BARREIROS, Marta de Oliveira; BARBOSA, Felipe Gomes; DANTAS, Diego de Oliveira; SANTOS, Daniel de Matos Luna dos; RIBEIRO, Sidarta; SANTOS, Giselle Cutrim de Oliveira; BARROS, Allan Kardec. Zebrafish automatic monitoring system for conditioning and behavioral analysis. Scientific Reports, [S.L.], v. 11, p. 9330, abr. 2021. Doi: http://dx.doi.org/10.1038/s41598-021-87502-6. Disponível em: https://www.nature.com/articles/s41598-021-87502-6. Acesso em: 30 abr. 2021. |
dc.identifier.uri.fl_str_mv |
https://repositorio.ufrn.br/handle/123456789/32343 |
dc.identifier.doi.none.fl_str_mv |
10.1038/s41598-021-87502-6 |
identifier_str_mv |
BARREIROS, Marta de Oliveira; BARBOSA, Felipe Gomes; DANTAS, Diego de Oliveira; SANTOS, Daniel de Matos Luna dos; RIBEIRO, Sidarta; SANTOS, Giselle Cutrim de Oliveira; BARROS, Allan Kardec. Zebrafish automatic monitoring system for conditioning and behavioral analysis. Scientific Reports, [S.L.], v. 11, p. 9330, abr. 2021. Doi: http://dx.doi.org/10.1038/s41598-021-87502-6. Disponível em: https://www.nature.com/articles/s41598-021-87502-6. Acesso em: 30 abr. 2021. 10.1038/s41598-021-87502-6 |
url |
https://repositorio.ufrn.br/handle/123456789/32343 |
dc.language.iso.fl_str_mv |
eng |
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eng |
dc.rights.driver.fl_str_mv |
Attribution 3.0 Brazil http://creativecommons.org/licenses/by/3.0/br/ info:eu-repo/semantics/openAccess |
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Attribution 3.0 Brazil http://creativecommons.org/licenses/by/3.0/br/ |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Springer Science and Business Media LLC |
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Springer Science and Business Media LLC |
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Universidade Federal do Rio Grande do Norte (UFRN) |
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UFRN |
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UFRN |
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Repositório Institucional da UFRN |
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