Decoding Neural Population Dynamics through Robotic Analog

This paper introduces a robotic system that mimics biological motor systems using artificial muscles, sensors, and reinforcement learning. The model exhibits movement patterns and neural dynamics similar to animals, revealing how neural rotations optimize trajectory adjustments and uncovering counterintuitive energy principles during motor learning.