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FicTrac: A visual method for tracking spherical motion and generating fictive animal paths

Moore, Richard JD; Taylor, Gavin LU ; Paulk, Angelique C; Pearson, Thomas; van Swinderen, Bruno and Srinivasan, Mandyam V (2014) In Journal of Neuroscience Methods 225. p.106-119
Abstract
Studying how animals interface with a virtual reality can further our understanding of how attention, learning and memory, sensory processing, and navigation are handled by the brain, at both the neurophysiological and behavioural levels. To this end, we have developed a novel vision-based tracking system, FicTrac (Fictive path Tracking software), for estimating the path an animal makes whilst rotating an air-supported sphere using only input from a standard camera and computer vision techniques. We have found that the accuracy and robustness of FicTrac outperforms a low-cost implementation of a standard optical mouse-based approach for generating fictive paths. FicTrac is simple to implement for a wide variety of experimental... (More)
Studying how animals interface with a virtual reality can further our understanding of how attention, learning and memory, sensory processing, and navigation are handled by the brain, at both the neurophysiological and behavioural levels. To this end, we have developed a novel vision-based tracking system, FicTrac (Fictive path Tracking software), for estimating the path an animal makes whilst rotating an air-supported sphere using only input from a standard camera and computer vision techniques. We have found that the accuracy and robustness of FicTrac outperforms a low-cost implementation of a standard optical mouse-based approach for generating fictive paths. FicTrac is simple to implement for a wide variety of experimental configurations and, importantly, is fast to execute, enabling real-time sensory feedback for behaving animals. We have used FicTrac to record the behaviour of tethered honeybees, Apis mellifera, whilst presenting visual stimuli in both open-loop and closed-loop experimental paradigms. We found that FicTrac could accurately register the fictive paths of bees as they walked towards bright green vertical bars presented on an LED arena. Using FicTrac, we have demonstrated closed-loop visual fixation in both the honeybee and the fruit fly, Drosophila melanogaster, establishing the flexibility of this system. FicTrac provides the experimenter with a simple yet adaptable system that can be combined with electrophysiological recording techniques to study the neural mechanisms of behaviour in a variety of organisms, including walking vertebrates (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of Neuroscience Methods
volume
225
pages
106 - 119
publisher
Elsevier
external identifiers
  • scopus:84894155153
ISSN
1872-678X
DOI
10.1016/j.jneumeth.2014.01.010
language
English
LU publication?
yes
id
c47e5ac8-0ffd-46dc-86e2-956138f33552 (old id 8054637)
date added to LUP
2015-10-22 13:09:51
date last changed
2017-10-22 03:07:36
@article{c47e5ac8-0ffd-46dc-86e2-956138f33552,
  abstract     = {Studying how animals interface with a virtual reality can further our understanding of how attention, learning and memory, sensory processing, and navigation are handled by the brain, at both the neurophysiological and behavioural levels. To this end, we have developed a novel vision-based tracking system, FicTrac (Fictive path Tracking software), for estimating the path an animal makes whilst rotating an air-supported sphere using only input from a standard camera and computer vision techniques. We have found that the accuracy and robustness of FicTrac outperforms a low-cost implementation of a standard optical mouse-based approach for generating fictive paths. FicTrac is simple to implement for a wide variety of experimental configurations and, importantly, is fast to execute, enabling real-time sensory feedback for behaving animals. We have used FicTrac to record the behaviour of tethered honeybees, Apis mellifera, whilst presenting visual stimuli in both open-loop and closed-loop experimental paradigms. We found that FicTrac could accurately register the fictive paths of bees as they walked towards bright green vertical bars presented on an LED arena. Using FicTrac, we have demonstrated closed-loop visual fixation in both the honeybee and the fruit fly, Drosophila melanogaster, establishing the flexibility of this system. FicTrac provides the experimenter with a simple yet adaptable system that can be combined with electrophysiological recording techniques to study the neural mechanisms of behaviour in a variety of organisms, including walking vertebrates},
  author       = {Moore, Richard JD and Taylor, Gavin and Paulk, Angelique C and Pearson, Thomas and van Swinderen, Bruno and Srinivasan, Mandyam V},
  issn         = {1872-678X},
  language     = {eng},
  pages        = {106--119},
  publisher    = {Elsevier},
  series       = {Journal of Neuroscience Methods},
  title        = {FicTrac: A visual method for tracking spherical motion and generating fictive animal paths},
  url          = {http://dx.doi.org/10.1016/j.jneumeth.2014.01.010},
  volume       = {225},
  year         = {2014},
}