Spatial Representation of Predictive Motor Learning

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Abstract
A key feature of skilled motor behavior is the ability of the CNS to predict the consequences of its actions. Such prediction occurs when one hand pulls on an object held in the other hand; the restraining hand generates an anticipatory increase in grip force, thereby preventing the object from slipping. When manipulating a novel object, the CNS adapts its predictive response to ensure that predictions are accurately tuned to the dynamics of the object. Here we examine whether learning to predict the consequences of an action on a novel object is restricted to the actions performed during manipulation or generalizes to novel actions. A bimanual task in which subjects held an object in each hand and the relationship between actions on one object and the motion of the other could be computer controlled from trial-to-trial was used. In four conditions we varied the spatial relationship between the direction of force subjects applied to the left-hand object and the consequent direction of motion of an object held in their right hand, which subjects were required to restrain. The results show that predictive learning was local to the direction of forces experienced during learning and that the magnitude of predictive responses was greatly reduced for novel directions of action of the left hand. The pattern of generalization shows that the representation of predictive learning is spatially local and can be approximated as having a spatially narrow Gaussian basis function.