Modeling sensorimotor circuits with task-driven and reinforcement learning

Biological adaptive motor control relies on the integration of proprioception and hierarchical control. To illustrate our research on those topics, I will firstly, present a task-driven modeling approach to quantitatively test hypotheses about the functional role of proprioceptive neurons in the brain stem and cortex. Secondly, I will discuss DMAP, a biologically-inspired, attention-based policy network architecture that can learn to walk with changing bodies (Chiappa et al., NeurIPS 2022).