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Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut

Clemensson, Erik K.H. LU ; Abbaszadeh, Morteza LU ; Fanni, Silvia LU ; Espa, Elena LU and Cenci, M. Angela LU (2020) In Journal of visualized experiments : JoVE
Abstract

Operant conditioning chambers are used to perform a wide range of behavioral tests in the field of neuroscience. The recorded data is typically based on the triggering of lever and nose-poke sensors present inside the chambers. While this provides a detailed view of when and how animals perform certain responses, it cannot be used to evaluate behaviors that do not trigger any sensors. As such, assessing how animals position themselves and move inside the chamber is rarely possible. To obtain this information, researchers generally have to record and analyze videos. Manufacturers of operant conditioning chambers can typically supply their customers with high-quality camera setups. However, these can be very costly and do not necessarily... (More)

Operant conditioning chambers are used to perform a wide range of behavioral tests in the field of neuroscience. The recorded data is typically based on the triggering of lever and nose-poke sensors present inside the chambers. While this provides a detailed view of when and how animals perform certain responses, it cannot be used to evaluate behaviors that do not trigger any sensors. As such, assessing how animals position themselves and move inside the chamber is rarely possible. To obtain this information, researchers generally have to record and analyze videos. Manufacturers of operant conditioning chambers can typically supply their customers with high-quality camera setups. However, these can be very costly and do not necessarily fit chambers from other manufacturers or other behavioral test setups. The current protocol describes how to build an inexpensive and versatile video camera using hobby electronics components. It further describes how to use the image analysis software package DeepLabCut to track the status of a strong light signal, as well as the position of a rat, in videos gathered from an operant conditioning chamber. The former is a great aid when selecting short segments of interest in videos that cover entire test sessions, and the latter enables analysis of parameters that cannot be obtained from the data logs produced by the operant chambers.

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Contribution to journal
publication status
published
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in
Journal of visualized experiments : JoVE
issue
160
publisher
JoVE
external identifiers
  • scopus:85087433733
  • pmid:32597866
ISSN
1940-087X
DOI
10.3791/61409
language
English
LU publication?
yes
id
67d99d69-3508-4e88-9ad3-a6fba60b6d50
date added to LUP
2020-07-16 12:22:59
date last changed
2020-07-22 04:21:58
@article{67d99d69-3508-4e88-9ad3-a6fba60b6d50,
  abstract     = {<p>Operant conditioning chambers are used to perform a wide range of behavioral tests in the field of neuroscience. The recorded data is typically based on the triggering of lever and nose-poke sensors present inside the chambers. While this provides a detailed view of when and how animals perform certain responses, it cannot be used to evaluate behaviors that do not trigger any sensors. As such, assessing how animals position themselves and move inside the chamber is rarely possible. To obtain this information, researchers generally have to record and analyze videos. Manufacturers of operant conditioning chambers can typically supply their customers with high-quality camera setups. However, these can be very costly and do not necessarily fit chambers from other manufacturers or other behavioral test setups. The current protocol describes how to build an inexpensive and versatile video camera using hobby electronics components. It further describes how to use the image analysis software package DeepLabCut to track the status of a strong light signal, as well as the position of a rat, in videos gathered from an operant conditioning chamber. The former is a great aid when selecting short segments of interest in videos that cover entire test sessions, and the latter enables analysis of parameters that cannot be obtained from the data logs produced by the operant chambers.</p>},
  author       = {Clemensson, Erik K.H. and Abbaszadeh, Morteza and Fanni, Silvia and Espa, Elena and Cenci, M. Angela},
  issn         = {1940-087X},
  language     = {eng},
  month        = {06},
  number       = {160},
  publisher    = {JoVE},
  series       = {Journal of visualized experiments : JoVE},
  title        = {Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut},
  url          = {http://dx.doi.org/10.3791/61409},
  doi          = {10.3791/61409},
  year         = {2020},
}