Abstract
Automated detection of complex animal behavior remains a challenge in neuroscience. Developments in computer-vision have greatly advanced automated behavior detection and allow high-throughput pre-clinical studies. An integrated hardware and software solution is necessary to facilitate the adoption of these advances in the field of behavioral neurogenetics, particularly for non-computational labs. We have published a series of papers using an open field arena to annotate complex behaviors such as grooming, posture, and gait as well as higher level constructs such as frailty. Here, we present an integrated rodent phenotyping platform, JAX Animal Behavior System (JABS) to the community for data acquisition, machine learning based behavior annotation and classification, classifier sharing, and genetic analysis. JABS Data acquisition module enables uniform data collection with its combination of 3D hardware designs and software for real-time monitoring and video data collection. JABS-Active Learning Module allows behavior annotation, classifier training, and validation. We also present a novel graph-based framework (ethograph) that enables efficient boutwise comparison of classifiers. JABS-Database Module allows users to share behavior classifiers and finally the JABS-Analysis Module infers a deposited classifier on a library of 600 open field videos consisting of 60 mouse strains, returns frame level and bout level classifier statistics.In summary, this open-source tool is an ecosystem that allows the neuroscience community to build shared resources for behavior analysis.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
We have added figures for JABS active learning system. The concept of ethograph is introduced. Classifier comparison and strain survey data is added.
