Prof. Daniel Wolpert
Sobell Dept. of Motor Neuroscience
Institute of Neurology 
Queen Square 
London WC1N 3BG 
United Kingdom 
Direct/Fax: +44 (20) 7681 7166
Email wolpert@hera.ucl.ac.uk
Home-page: http://www.hera.ucl.ac.uk
Institute of Movement Neuroscience : http://www.imn.ucl.ac.uk

Sensory and motor uncertainties form fundamental constraints on human 
sensorimotor control. I will first describe how signal-dependent noise on the 
motor output places constraints on performance. Given these constraints 
features of goal-directed movement arise from a model in which the statistics 
of our actions are optimized. I will then describe how prediction of the 
consequences of our actions can be used to reduce uncertainty and present 
experiments on tickling and force escalation which elucidate the predictive 
mechanisms. Finally, I will show that the CNS reduces the uncertainty in 
estimates about the state of the world by using a Bayesian combination of 
prior knowledge with an estimate of the uncertainty of its own sensors. 
Together these studies provide a probabilistic framework for sensorimotor 
control in which prediction plays a key role.