Lectures on Motor Control: courses by Prof. Reza Shadmehr

580.691/491 Learning Theory
This course introduces the probabilistic foundations of learning theory. We will discuss topics in regression, estimation, optimal control, system identification, Bayesian learning, and classification. Our aim is to first derive some of the important mathematical results in learning theory, and then apply the framework to problems in biology, particularly animal learning and control of action. However, this is not a machine learning course. Rather, our aim is to use these mathematical results to better understand learning and control processes in the central nervous system. This course is taught in the Spring semester.

440.600 Core Course on Neuroscience
This course introduces the human central nervous system to first year medical students and graduate students at Johns Hopkins. The four lectures introduce the spinal motor structures, descending tracts, posterior parietal cortex, and the motor system of the frontal lobe. This course is taught in the spring semester.

580.423/623 Systems Bioengineering: The nervous systems
This is one of the core courses in undergraduate education at Hopkins BME. The purpose of this course is to introduce the central nervous system from an engineering perspective. This course is taught in the spring semester.

580.431/631 Computational Motor Control
This course uses topics from robotics, control theory, and neuroscience to understand in some depth the primate motor system. Our approach is to use mathematics to explore functions of muscles, spinal reflex systems, posterior parietal cortex, frontal motor areas, cerebellum, and basal ganglia. Our focus is on how these various parts of the motor system contribute to the control and learning of reaching movements. The last time this course was offered was in spring 2003.

Text book: Shadmehr R, Wise SP (2005) Computational Neurobiology of Reaching and Pointing: A Foundation for Motor Learning, MIT Press, Cambridge MA.
Web resources.