Topic: marker-less pose estimation

The development of algorithms for high-accuracy animal tracking is fundamental to unravel the neural basis of behavior. The recent growth of Deeplabcut, an open source toolbox for marker-less pose estimation based on transfer learning with deep neural networks, promises to greatly enhance our ability to track animal pose with high-accuracy and high-efficiency, because it can match human labelling accuracy with minimal training data. Here, we implement Deeplabcut routines and develop a pipeline to accurately track the pose of mice undergoing defensive behaviors. Defensive behaviors are elicited