RT Journal Article
SR Electronic
T1 AlphaTracker: A Multi-Animal Tracking and Behavioral Analysis Tool
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.12.04.405159
DO 10.1101/2020.12.04.405159
A1 Zexin Chen
A1 Ruihan Zhang
A1 Yu Eva Zhang
A1 Haowen Zhou
A1 Hao-Shu Fang
A1 Rachel R. Rock
A1 Aneesh Bal
A1 Nancy Padilla-Coreano
A1 Laurel Keyes
A1 Kay M. Tye
A1 Cewu Lu
YR 2020
UL http://biorxiv.org/content/early/2020/12/06/2020.12.04.405159.abstract
AB The advancement of behavioral analysis in neuroscience has been aided by the development of computational tools1,2. Specifically, computer vision algorithms have emerged as a powerful tool to elevate behavioral research3,4. Yet fully automatic analysis of social behavior remains challenging in two ways. First, existing tools to track and analyze behavior often focus on single animals, not multiple, interacting animals. Second, many available tools are not developed for novice users and require programming experience to run. Here, we unveil a computer vision pipeline called AlphaTracker, which requires minimal hardware requirements and produces reliable tracking of multiple unmarked animals. An easy-to-use user interface further enables manual inspection and curation of results. We demonstrate the practical, real-time advantages of AlphaTracker through the study of multiple, socially-interacting mice.Competing Interest StatementThe authors have declared no competing interest.