Krakauer and colleagues bolstered their experimental fi ndings by comparing them with a statistical model of movements of the arm and wrist. The model uses a Bayesian approach, where previous experience and new **data** are combined to form a new parameter estimate. A key aspect of this approach is that greater uncertainty about the parameter leads to faster learning. Crucially, in their model, the investigators assumed that the majority of movements with the arm also include moving the wrist, but not vice versa. This led to a situation where the uncertainty in the parameter estimate-the imposed rotationdepended not only on the current limb context but also on the history of training in previous limb contexts. The model was able to reproduce most of the effects they saw in the experiments, such as the fi nding that learning would transfer from arm to wrist, but not vice versa, and blocking of generalization.