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A system for tracking whisker kinematics and whisker shape in three dimensions.

Rasmus S PetersenAndrea Colins RodriguezMathew H EvansDario CampagnerMichaela S E Loft
Published in: PLoS computational biology (2020)
Quantification of behaviour is essential for biology. Since the whisker system is a popular model, it is important to have methods for measuring whisker movements from behaving animals. Here, we developed a high-speed imaging system that measures whisker movements simultaneously from two vantage points. We developed a whisker tracker algorithm that automatically reconstructs 3D whisker information directly from the 'stereo' video data. The tracker is controlled via a Graphical User Interface that also allows user-friendly curation. The algorithm tracks whiskers, by fitting a 3D Bezier curve to the basal section of each target whisker. By using prior knowledge of natural whisker motion and natural whisker shape to constrain the fits and by minimising the number of fitted parameters, the algorithm is able to track multiple whiskers in parallel with low error rate. We used the output of the tracker to produce a 3D description of each tracked whisker, including its 3D orientation and 3D shape, as well as bending-related mechanical force. In conclusion, we present a non-invasive, automatic system to track whiskers in 3D from high-speed video, creating the opportunity for comprehensive 3D analysis of sensorimotor behaviour and its neural basis.
Keyphrases
  • high speed
  • machine learning
  • deep learning
  • atomic force microscopy
  • high resolution
  • healthcare
  • mass spectrometry
  • health information
  • functional connectivity