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 track specific...
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...
Giovanni Barbera and colleagues have created a versatile, 3D-printed, motorized commutator for neural recordings of small animals in vivo. Commutators are important components for managing the twisting of cables during in vivo neural recordings such as...
Several popular methods for pose estimation have emerged in recent years. DeepLabCut and LEAP are popular tools for tracking actions of individual animals. The projects are well documented and numerous tutorials exist that make it easy for new users to learn and use...
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