The Mouse Action Recognition System (MARS) software pipeline for automated analysis of social behaviors in mice

eLife

Jalani Williams¹  Cristina Segalin¹  Pietro Perona¹  Jennifer J Sun¹  Ann Kennedy²  May Hui²  Moriel Zelikowsky²  Tomomi Karigo²  David J Anderson³ 

[1] Department of Computing & Mathematical Sciences, California Institute of Technology, Pasadena, United States;Division of Biology and Biological Engineering 156-29, TianQiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, United States;Division of Biology and Biological Engineering 156-29, TianQiao and Chrissy Chen Institute for Neuroscience, California Institute of Technology, Pasadena, United States;Howard Hughes Medical Institute, California Institute of Technology, Pasadena, United States;

关键词: social behavior;    pose estimation;    machine learning;    computer vision;    microendoscopic imaging;    software;    Mouse;   

DOI  :  10.7554/eLife.63720

来源: eLife Sciences Publications, Ltd

【 摘 要 】

The study of naturalistic social behavior requires quantification of animals’ interactions. This is generally done through manual annotation—a highly time-consuming and tedious process. Recent advances in computer vision enable tracking the pose (posture) of freely behaving animals. However, automatically and accurately classifying complex social behaviors remains technically challenging. We introduce the Mouse Action Recognition System (MARS), an automated pipeline for pose estimation and behavior quantification in pairs of freely interacting mice. We compare MARS’s annotations to human annotations and find that MARS’s pose estimation and behavior classification achieve human-level performance. We also release the pose and annotation datasets used to train MARS to serve as community benchmarks and resources. Finally, we introduce the Behavior Ensemble and Neural Trajectory Observatory (BENTO), a graphical user interface for analysis of multimodal neuroscience datasets. Together, MARS and BENTO provide an end-to-end pipeline for behavior data extraction and analysis in a package that is user-friendly and easily modifiable.

【 授权许可】

CC BY