Rapid adaptation to scaled changes of the mechanical environment.

We investigated adaptation to simple force field scaling to determine whether the same strategy is used as during adaptation to more complex changes in the mechanical environment. Subjects initially trained in a force field, consisting of a rightward lateral force with a parabolic spatial profile (PF). The field strength was then unexpectedly increased or decreased (DeltaPF) for repeated sets of five consecutive trials, with intervening PF trials. Stiff elastic walls, which prevented lateral movement of the arm, randomly replaced 25% of DeltaPF trials. Lateral deviation on DeltaPF trials and lateral force against the elastic walls were used to assess the extent to which feedforward adaptations could be attributed to changes in lateral force or increased stiffness of the arm. When force field strength was increased or decreased hand paths were perturbed to the right or left, respectively. Performance error was significantly reduced between the first and second DeltaPF trial positions of the set, whereas the lateral force impulse exerted against the elastic walls did not change until the third trial position. The lateral force was scaled upward or downward in response to the change in force field strength, suggesting a gradual change in the internal model. The results support a dual strategy of cocontraction (increased stiffness) and internal model modification. The development of an accurate internal model is a slower process than cocontraction and error reduction. This may explain the need to represent motor learning as two parallel processes with varying timescales, as recently proposed by Smith and colleagues.