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There is still no robotic device that can match the ease and grace with which the brain produces skilled movements. The complexities of our muscular-skeletal system, the compliance and variability in our muscles and the unpredictable ever-changing environment make the control of movements one of the hardest computational problems that the brain faces. What are the principles that underlie production of coordinated movements? How are skilled movements learned? Which brain areas are involved? How does the brain compensate after damage to these areas?
In the motor control group, we are using robotic devices to investigate human motor behavior. By simulating novel objects or dynamic environments we can study how the brain recalibrates well-learned motor skills or acquires new ones. We develop computational models to understand the underlying control and learning processes. These insights are used to design fMRI studies to investigate how these processes map onto the brain. In the process, we have developed a number of novel techniques of how to study motor control in the MRI environment, and how to analyze MRI data of the human cerebellum. Finally, we study patients with stroke or neurological disease to further determine how the brain manages to control the body. After all – that is what the brain “does”.
News:
Principles
of motor learning |
Wolpert D.M., Diedrichsen J., Flanagan J.R., (2011) Principles of sensorimotor learning. Nat Rev Neurosci. |
Reasearch Assistant
PhD student position |
We have an opening for a Research Assistant (50%) open in our laboratory, with the opportunity to pursue a part-time PhD at the Institute of cognitive Neuroscience. The position is for 4 years in the first instance. Closing date for applications is the 12th of January, 2012. More information. |
Funding |
Work in the laboratory is supported by Grants of the Biotechnology and Biological Sciences Research Council (BBSRC), the Marie-Curie Program, the Wellcome Trust, and the James S. McDonnell foundation. |