Low-cost solution for rodent home-cage behaviour monitoring.

In the current research on measuring complex behaviours/phenotyping in rodents, most of the experimental design requires the experimenter to remove the animal from its home-cage environment and place it in an unfamiliar apparatus (novel environment). This interaction may influence behaviour, general...

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Main Authors: Surjeet Singh, Edgar Bermudez-Contreras, Mojtaba Nazari, Robert J Sutherland, Majid H Mohajerani
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2019-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0220751
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spelling doaj-fcc7f5240acd44e08a8b3080a79cd65b2021-03-03T20:32:12ZengPublic Library of Science (PLoS)PLoS ONE1932-62032019-01-01148e022075110.1371/journal.pone.0220751Low-cost solution for rodent home-cage behaviour monitoring.Surjeet SinghEdgar Bermudez-ContrerasMojtaba NazariRobert J SutherlandMajid H MohajeraniIn the current research on measuring complex behaviours/phenotyping in rodents, most of the experimental design requires the experimenter to remove the animal from its home-cage environment and place it in an unfamiliar apparatus (novel environment). This interaction may influence behaviour, general well-being, and the metabolism of the animal, affecting the phenotypic outcome even if the data collection method is automated. Most of the commercially available solutions for home-cage monitoring are expensive and usually lack the flexibility to be incorporated with existing home-cages. Here we present a low-cost solution for monitoring home-cage behaviour of rodents that can be easily incorporated to practically any available rodent home-cage. To demonstrate the use of our system, we reliably predict the sleep/wake state of mice in their home-cage using only video. We validate these results using hippocampal local field potential (LFP) and electromyography (EMG) data. Our approach provides a low-cost flexible methodology for high-throughput studies of sleep, circadian rhythm and rodent behaviour with minimal experimenter interference.https://doi.org/10.1371/journal.pone.0220751
collection DOAJ
language English
format Article
sources DOAJ
author Surjeet Singh
Edgar Bermudez-Contreras
Mojtaba Nazari
Robert J Sutherland
Majid H Mohajerani
spellingShingle Surjeet Singh
Edgar Bermudez-Contreras
Mojtaba Nazari
Robert J Sutherland
Majid H Mohajerani
Low-cost solution for rodent home-cage behaviour monitoring.
PLoS ONE
author_facet Surjeet Singh
Edgar Bermudez-Contreras
Mojtaba Nazari
Robert J Sutherland
Majid H Mohajerani
author_sort Surjeet Singh
title Low-cost solution for rodent home-cage behaviour monitoring.
title_short Low-cost solution for rodent home-cage behaviour monitoring.
title_full Low-cost solution for rodent home-cage behaviour monitoring.
title_fullStr Low-cost solution for rodent home-cage behaviour monitoring.
title_full_unstemmed Low-cost solution for rodent home-cage behaviour monitoring.
title_sort low-cost solution for rodent home-cage behaviour monitoring.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2019-01-01
description In the current research on measuring complex behaviours/phenotyping in rodents, most of the experimental design requires the experimenter to remove the animal from its home-cage environment and place it in an unfamiliar apparatus (novel environment). This interaction may influence behaviour, general well-being, and the metabolism of the animal, affecting the phenotypic outcome even if the data collection method is automated. Most of the commercially available solutions for home-cage monitoring are expensive and usually lack the flexibility to be incorporated with existing home-cages. Here we present a low-cost solution for monitoring home-cage behaviour of rodents that can be easily incorporated to practically any available rodent home-cage. To demonstrate the use of our system, we reliably predict the sleep/wake state of mice in their home-cage using only video. We validate these results using hippocampal local field potential (LFP) and electromyography (EMG) data. Our approach provides a low-cost flexible methodology for high-throughput studies of sleep, circadian rhythm and rodent behaviour with minimal experimenter interference.
url https://doi.org/10.1371/journal.pone.0220751
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