Topic: peripheral motor variability

In recent years, advances in the fields of computational ethology and neuroscience have enabled detailed modeling of animal behavior and its neural underpinnings. However, these advances have yet to produce normative models of neuromotor control that generate the full diversity of animal behavior. Using recently developed methods in 3D pose estimation and deep reinforcement learning, we trained a latent variable model to control a virtual rodent body to imitate the natural behaviors of real rats in a physics simulator. Once trained, the model faithfully replicated diverse rat behaviors and gen