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Open-source, Python-based, hardware and software for controlling behavioural neuroscience experiments
Laboratory behavioural tasks are an essential research tool. As questions asked of behaviour and brain activity become more sophisticated, the ability to specify and run richly structured tasks becomes more important. An increasing focus on reproducibility also necessitates accurate communication of...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769647/ https://www.ncbi.nlm.nih.gov/pubmed/35043782 http://dx.doi.org/10.7554/eLife.67846 |
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author | Akam, Thomas Lustig, Andy Rowland, James M Kapanaiah, Sampath KT Esteve-Agraz, Joan Panniello, Mariangela Márquez, Cristina Kohl, Michael M Kätzel, Dennis Costa, Rui M Walton, Mark E |
author_facet | Akam, Thomas Lustig, Andy Rowland, James M Kapanaiah, Sampath KT Esteve-Agraz, Joan Panniello, Mariangela Márquez, Cristina Kohl, Michael M Kätzel, Dennis Costa, Rui M Walton, Mark E |
author_sort | Akam, Thomas |
collection | PubMed |
description | Laboratory behavioural tasks are an essential research tool. As questions asked of behaviour and brain activity become more sophisticated, the ability to specify and run richly structured tasks becomes more important. An increasing focus on reproducibility also necessitates accurate communication of task logic to other researchers. To these ends, we developed pyControl, a system of open-source hardware and software for controlling behavioural experiments comprising a simple yet flexible Python-based syntax for specifying tasks as extended state machines, hardware modules for building behavioural setups, and a graphical user interface designed for efficiently running high-throughput experiments on many setups in parallel, all with extensive online documentation. These tools make it quicker, easier, and cheaper to implement rich behavioural tasks at scale. As important, pyControl facilitates communication and reproducibility of behavioural experiments through a highly readable task definition syntax and self-documenting features. Here, we outline the system’s design and rationale, present validation experiments characterising system performance, and demonstrate example applications in freely moving and head-fixed mouse behaviour. |
format | Online Article Text |
id | pubmed-8769647 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-87696472022-01-21 Open-source, Python-based, hardware and software for controlling behavioural neuroscience experiments Akam, Thomas Lustig, Andy Rowland, James M Kapanaiah, Sampath KT Esteve-Agraz, Joan Panniello, Mariangela Márquez, Cristina Kohl, Michael M Kätzel, Dennis Costa, Rui M Walton, Mark E eLife Neuroscience Laboratory behavioural tasks are an essential research tool. As questions asked of behaviour and brain activity become more sophisticated, the ability to specify and run richly structured tasks becomes more important. An increasing focus on reproducibility also necessitates accurate communication of task logic to other researchers. To these ends, we developed pyControl, a system of open-source hardware and software for controlling behavioural experiments comprising a simple yet flexible Python-based syntax for specifying tasks as extended state machines, hardware modules for building behavioural setups, and a graphical user interface designed for efficiently running high-throughput experiments on many setups in parallel, all with extensive online documentation. These tools make it quicker, easier, and cheaper to implement rich behavioural tasks at scale. As important, pyControl facilitates communication and reproducibility of behavioural experiments through a highly readable task definition syntax and self-documenting features. Here, we outline the system’s design and rationale, present validation experiments characterising system performance, and demonstrate example applications in freely moving and head-fixed mouse behaviour. eLife Sciences Publications, Ltd 2022-01-19 /pmc/articles/PMC8769647/ /pubmed/35043782 http://dx.doi.org/10.7554/eLife.67846 Text en © 2022, Akam et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Neuroscience Akam, Thomas Lustig, Andy Rowland, James M Kapanaiah, Sampath KT Esteve-Agraz, Joan Panniello, Mariangela Márquez, Cristina Kohl, Michael M Kätzel, Dennis Costa, Rui M Walton, Mark E Open-source, Python-based, hardware and software for controlling behavioural neuroscience experiments |
title | Open-source, Python-based, hardware and software for controlling behavioural neuroscience experiments |
title_full | Open-source, Python-based, hardware and software for controlling behavioural neuroscience experiments |
title_fullStr | Open-source, Python-based, hardware and software for controlling behavioural neuroscience experiments |
title_full_unstemmed | Open-source, Python-based, hardware and software for controlling behavioural neuroscience experiments |
title_short | Open-source, Python-based, hardware and software for controlling behavioural neuroscience experiments |
title_sort | open-source, python-based, hardware and software for controlling behavioural neuroscience experiments |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769647/ https://www.ncbi.nlm.nih.gov/pubmed/35043782 http://dx.doi.org/10.7554/eLife.67846 |
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