Motor Learning and Control
Motor Learning and Control is an interdisciplinary field that investigates how the central nervous system produces and acquires skillful, coordinated movements. Drawing heavily from control systems theory, it models the body as a dynamic system where the brain acts as a controller, using sensory feedback and predictive (feedforward) mechanisms to generate precise motor commands for muscles. From a computer science perspective, this field focuses on understanding the underlying computational principles and algorithms the brain employs for tasks such as state estimation, error correction, and optimization, with direct applications in robotics, neuroprosthetics, and the development of artificial intelligence that can physically interact with the world.