The effect of variable force field strength on motor adaptation and subsequent generalization

An exploratory study to test the performance of the ARMANDA robot in a motor learning study

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Abstract

Humans continuously adapt to new sensorimotor environments, wherein we create motor commands to execute movements properly, such as picking up the telephone or riding a bike. Generalization of motor commands means that a learned movement, such as grasping a bottle, transfers to similar but new environments, such as grasping a carton of milk. However, it remains unclear to what extent we are able to learn an uncertain variable environment and to what extent these learned movements transfer to a new environment. We compared generalization to a new environment after learning a fixed (F) or trial-by-trial variable (V) velocity-dependent clockwise force field. Selecting the damping coefficients from a predefined distribution on a trial-by-trial basis introduced the variability for the variable group during the training trials, while the fixed group had a fixed damping coefficient during training. After training, both groups made reaching movements in a new force field that was fixed over all trials. Due to the uncertainty in the force field strengths, we hypothesized that the variable group would have more difficulties with adapting compared to the fixed group. However, because the variable group would experience more different force fields during the training, we hypothesized that they would perform better in the new environment. Based on the force field compensation factors, the adaptation to the training fields was: 79.8% (F) and 79.7% (V), p = 0.982. The generalization learning was similar for both groups: 78.8% (F) and 78.9%, p = 0.986. Interestingly, the trajectory measurements showed that the variable group was less accurate than the fixed group in the training fields, but more accurate in the generalization field. Therefore, our results show that variable force field perturbations can be learned and generalized in a similar manner as fixed perturbations and that the variable group, despite a more inaccurate performance in the training block, reached more accurately than the fixed group in the new environment.