What to do and how to do it: sequence learning of action effects and transformation rules.

Many goal-oriented actions, for example in tool use, can be characterized by the involvement of two components: The effect that the acting person wants to achieve and the transformation rule that defines the relationship between a bodily movement and the associated action effect. Both in conjunction specify the concrete action that has to be executed. In our experiments, we utilized a sequence learning paradigm to investigate whether these components are represented separately or are bound together to form a more holistic representation of the action.