Several excellent computational frameworks exist that enable high-throughput and consistent tracking of freely moving unmarked animals. Here we introduce and distribute a plug-and play pipeline that enabled users to use these pose-estimation approaches in combination with behavioral annotatation and generatation of supervised machine-learning behavioral predictive classifiers. We have developed this pipeline for the analysis of complex social behaviors, but have included the flexibility for users to generate predictive classifiers across other behavioral modalities with minimal effort and no specialized computuational background.
SimBA does not require computer science and programing experience, and SimBA is optimized for wide-ranging video acquisition parameters and quality. We may be able to provide support and advice for specific use instances, especially if it benefits multiple users and advances the scope of SimBA. Feel free to post issues and bugs here or contact us directly and we'll work on squashing them as they appear. We hope that users will contribute to the community!
- The SimBA pipeline requires no programing knowledge
- Specialized commercial or custom-made equipment is not required
- Extensive annotations are not required
- The pipeline is flexible and can be used to create and validate classifiers for different behaviors and environments
- Currently included behavioral classifiers have been validated in mice and rats
SimBA currently does not support analysis of video recordings of multiple similarly colored animals, and is validated using videos filmed from above at 90° angle using pose-estimation data from 8 body parts per animal. However we and others are developeing multi-animal tracking of similarly colored and sized animals, and multiple recording angles supported! 💪 We also include other body -part tracking schemes within the GUI pipeline (i.e., 1 or 2 mice, 3 to 8 body parts per mouse), but please consider these a work in progress.
Step 1: Pre-process videos
Step 3: Building classfier(s)
Step 4: Analysis/Visualization
- Process video using tools 🔨
- Batch pre-process video 🏭
- Using DeepLabCut through SimBA 📗
- SimBA 📘
- Label behavior 🏷️
Below is a link to download trained models to apply it on your dataset
This project is licensed under the GNU Lesser General Public License v3.0. Note that the software is provided "as is", without warranty of any kind, express or implied. If you use the code or data, please cite us :)
