Neuromechanics of movement control
Course duration:10 h
Movement is the dynamic expression of our brain that can effect the environment through coordinated musculoskeletal actions. The neuromechanical system has evolved to diversify the ability to move efficiently, fast, with high accuracy and diversity. While the main elements are well-described, the compounded action of multiple and overlapping mechanisms remains to be poorly understood. The young field of computational neuroscience is built on methodology from computer science and engineering to describe the complexity of experimental datasets. These computational approaches are shared across several modern applied fields of neural engineering, robotics, and active prosthetics.
In this course we will discuss the bottom-up organization of neuromechanical system and build computational models of musculoskeletal elements and neural pathways that control them. In particular, we will build models of muscles and tendons, use mechanical simulation environment to create musculoskeletal models, and add models of sensory feedback from the main proprioceptors. The sensory feedback will be combined with the intrinsic spinal mechanisms and the descending drive. We will use both the inverse and forward dynamic modeling combined with optimization techniques to gain insight in the functional interactions between these components.
Dr. Sergiy Yakovenko
Place of employment: Assistant Professor, Neural Engineering Laboratory, West Virginia University School of Medicine, WV, USA
Spheres of scientific research: coordinated action of neural, muscular, and skeletal systems controlling goal-directed and stereotypic movements.