Professor Daniel Wolpert
University position
Professor
Professor Daniel Wolpert is pleased to consider applications from prospective PhD students.
Departments
Home page
http://www.wolpertlab.com (personal home page)
Research Themes
Interests
The group uses engineering approaches to understand how the human brain controls movement. The work includes both computational modelling and experimental approaches using robotic and virtual reality interfaces. Research areas include motor planning and optimal control,
probabilistic (Bayesian) models, motor predictive and modular approaches to motor learning.
Research Focus
Keywordsmotor control human computational methods neural circuit |
Clinical conditionsNo direct clinical relevance |
Equipment
Behavioural analysis
Computational modelling
Collaborators
No collaborators listed
Key publications
Körding KP, Wolpert DM (2004), “The loss function of sensorimotor learning” Proceedings of the National Academy of Sciences 101:9839-42 Details
Körding KP, Wolpert DM (2004), “Bayesian integration in sensorimotor learning” Nature 427:244-247 Details
Shergill SS, Bays PM, Frith CD, Wolpert DM (2003), “Two eyes for an eye: The neuroscience of force escalation” Science 301:187