Deep learning approaches have provided quantitative measurements of pose estimation and behavior tracking, though the quality and consistency of these results are dependent on the camera system. Commercially available cameras are often used; while these cameras...
Ann Kennedy, @Antihebbiann, from Northwestern University, contributed this post on a series of tools for joint analysis of behavioral and neural recording data: MARS, MARS-Developer, and BENTO. The Mouse Action Recognition System (MARS) is a Python-based end-to-end...
DeepEthogram (DEG) is a recently developed method for temporal action detection in video recordings. It was developed by Jim Bohnslav and colleagues in Chris Harvey’s lab and is described in this preprint. The general idea of DeepEthogram is to extract relevant...
An evolving set of tools from the labs of Joshua Shaevitz and Mala Murthy at Princeton offers an interesting way to do video analysis in behavioral neuroscience applications. MotionMapper was published in 2014. It works on videos (not poses) and uses image analysis...
Rapid data acquisition and analysis of behavioral and neural data allow neuroscientists to use real-time events to control experimental parameters. These kinds of closed-loop experiments are important for understanding the relationships between sensory and motor...
