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An open-source high-speed infrared videography database to study the principles of active sensing in freely navigating rodents
BACKGROUND: Active sensing is crucial for navigation. It is characterized by self-generated motor action controlling the accessibility and processing of sensory information. In rodents, active sensing is commonly studied in the whisker system. As rats and mice modulate their whisking contextually, t...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6283211/ https://www.ncbi.nlm.nih.gov/pubmed/30418576 http://dx.doi.org/10.1093/gigascience/giy134 |
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author | Azarfar, Alireza Zhang, Yiping Alishbayli, Artoghrul Miceli, Stéphanie Kepser, Lara van der Wielen, Daan van de Moosdijk, Mike Homberg, Judith Schubert, Dirk Proville, Rémi Celikel, Tansu |
author_facet | Azarfar, Alireza Zhang, Yiping Alishbayli, Artoghrul Miceli, Stéphanie Kepser, Lara van der Wielen, Daan van de Moosdijk, Mike Homberg, Judith Schubert, Dirk Proville, Rémi Celikel, Tansu |
author_sort | Azarfar, Alireza |
collection | PubMed |
description | BACKGROUND: Active sensing is crucial for navigation. It is characterized by self-generated motor action controlling the accessibility and processing of sensory information. In rodents, active sensing is commonly studied in the whisker system. As rats and mice modulate their whisking contextually, they employ frequency and amplitude modulation. Understanding the development, mechanisms, and plasticity of adaptive motor control will require precise behavioral measurements of whisker position. FINDINGS: Advances in high-speed videography and analytical methods now permit collection and systematic analysis of large datasets. Here, we provide 6,642 videos as freely moving juvenile (third to fourth postnatal week) and adult rodents explore a stationary object on the gap-crossing task. The dataset includes sensory exploration with single- or multi-whiskers in wild-type animals, serotonin transporter knockout rats, rats received pharmacological intervention targeting serotonergic signaling. The dataset includes varying background illumination conditions and signal-to-noise ratios (SNRs), ranging from homogenous/high contrast to non-homogenous/low contrast. A subset of videos has been whisker and nose tracked and are provided as reference for image processing algorithms. CONCLUSIONS: The recorded behavioral data can be directly used to study development of sensorimotor computation, top-down mechanisms that control sensory navigation and whisker position, and cross-species comparison of active sensing. It could also help to address contextual modulation of active sensing during touch-induced whisking in head-fixed vs freely behaving animals. Finally, it provides the necessary data for machine learning approaches for automated analysis of sensory and motion parameters across a wide variety of signal-to-noise ratios with accompanying human observer-determined ground-truth. |
format | Online Article Text |
id | pubmed-6283211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-62832112018-12-11 An open-source high-speed infrared videography database to study the principles of active sensing in freely navigating rodents Azarfar, Alireza Zhang, Yiping Alishbayli, Artoghrul Miceli, Stéphanie Kepser, Lara van der Wielen, Daan van de Moosdijk, Mike Homberg, Judith Schubert, Dirk Proville, Rémi Celikel, Tansu Gigascience Data Note BACKGROUND: Active sensing is crucial for navigation. It is characterized by self-generated motor action controlling the accessibility and processing of sensory information. In rodents, active sensing is commonly studied in the whisker system. As rats and mice modulate their whisking contextually, they employ frequency and amplitude modulation. Understanding the development, mechanisms, and plasticity of adaptive motor control will require precise behavioral measurements of whisker position. FINDINGS: Advances in high-speed videography and analytical methods now permit collection and systematic analysis of large datasets. Here, we provide 6,642 videos as freely moving juvenile (third to fourth postnatal week) and adult rodents explore a stationary object on the gap-crossing task. The dataset includes sensory exploration with single- or multi-whiskers in wild-type animals, serotonin transporter knockout rats, rats received pharmacological intervention targeting serotonergic signaling. The dataset includes varying background illumination conditions and signal-to-noise ratios (SNRs), ranging from homogenous/high contrast to non-homogenous/low contrast. A subset of videos has been whisker and nose tracked and are provided as reference for image processing algorithms. CONCLUSIONS: The recorded behavioral data can be directly used to study development of sensorimotor computation, top-down mechanisms that control sensory navigation and whisker position, and cross-species comparison of active sensing. It could also help to address contextual modulation of active sensing during touch-induced whisking in head-fixed vs freely behaving animals. Finally, it provides the necessary data for machine learning approaches for automated analysis of sensory and motion parameters across a wide variety of signal-to-noise ratios with accompanying human observer-determined ground-truth. Oxford University Press 2018-11-10 /pmc/articles/PMC6283211/ /pubmed/30418576 http://dx.doi.org/10.1093/gigascience/giy134 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Data Note Azarfar, Alireza Zhang, Yiping Alishbayli, Artoghrul Miceli, Stéphanie Kepser, Lara van der Wielen, Daan van de Moosdijk, Mike Homberg, Judith Schubert, Dirk Proville, Rémi Celikel, Tansu An open-source high-speed infrared videography database to study the principles of active sensing in freely navigating rodents |
title | An open-source high-speed infrared videography database to study the principles of active sensing in freely navigating rodents |
title_full | An open-source high-speed infrared videography database to study the principles of active sensing in freely navigating rodents |
title_fullStr | An open-source high-speed infrared videography database to study the principles of active sensing in freely navigating rodents |
title_full_unstemmed | An open-source high-speed infrared videography database to study the principles of active sensing in freely navigating rodents |
title_short | An open-source high-speed infrared videography database to study the principles of active sensing in freely navigating rodents |
title_sort | open-source high-speed infrared videography database to study the principles of active sensing in freely navigating rodents |
topic | Data Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6283211/ https://www.ncbi.nlm.nih.gov/pubmed/30418576 http://dx.doi.org/10.1093/gigascience/giy134 |
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