TY - JOUR
T1 - A system for tracking whisker kinematics and whisker shape in three dimensions
AU - Petersen, Rasmus S.
AU - Rodriguez, Andrea Colins
AU - Evans, Mathew H.
AU - Campagner, Dario
AU - Loft, Michaela S.E.
N1 - Publisher Copyright:
Copyright: © 2020 Petersen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2020
Y1 - 2020
N2 - Quantification of behaviour is essential for biology. Since the whisker system is a popular model system, 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.
AB - Quantification of behaviour is essential for biology. Since the whisker system is a popular model system, 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.
UR - https://www.scopus.com/pages/publications/85078871661
U2 - 10.1371/journal.pcbi.1007402
DO - 10.1371/journal.pcbi.1007402
M3 - Article
C2 - 31978043
AN - SCOPUS:85078871661
SN - 1553-734X
VL - 16
JO - PLoS Computational Biology
JF - PLoS Computational Biology
IS - 1
M1 - e1007402
ER -