Characterizing adaptive behavior of the wrist during lateral force perturbations

Combining functional magnetic resonance imaging (fMRI) with models of neuromotor adaptation is useful for identifying the function of different neuromotor control centers in the brain. Current models of neuromotor adaptation to force perturbations have been studied primarily in whole-arm reaching tasks that are ill-suited for MRI. We have previously developed the MR-SoftWrist, an fMRI-compatible wrist robot, to study motor control during wrist adaptation. Because the wrist joint has intrinsic dynamics dominated by stiffness, it is unclear if these models will apply to the wrist. Here, we characterize adaptation of the wrist to lateral forces to determine if established adaptation models are valid for wrist pointing. We recruited thirteen subjects to perform our task using the MR-SoftWrist. Our task included a clockwise (CW) - counterclockwise (CCW) - error clamp schedule and an alternating CW-CCW force field schedule. To determine applicability of previous models, we fit three candidate models - a single-state, two-state, and context dependent multi-state model - to behavioral data. Our results indicate that features of sensorimotor adaptation reported in the literature are present in the wrist, including spontaneous recovery, and anterograde and retrograde interference between the learning of two oppositely directed force fields. A two-state model best fit our behavioral data. Under this model, adaptation was dominated by a fast learning state with minor engagement of a slow learning state. Finally, all adaptation models tested showed a consistent over-estimation of performance error, suggesting that the control of the wrist relies not only on internal models but likely other mechanisms, like impedance control, to reject perturbations.