Arm position estimates derived from motor biases

Proprioception, including position sense, is critically important for normal sensorimotor and perceptual functioning but remains poorly understood. In the laboratory and clinic, arm position sense is typically assessed using perceptual tasks, e.g., via arm position matching or reporting the arm’s current position against a previously sensed one. Although such assessments provide important information about position sensing, they are incomplete in that they do not directly address the role of position sense in motor planning and control. Here, we used a combination of human psychophysical experiments, forward dynamic simulations, and mathematical optimization to reverse engineer arm positions (‘REAP’) used during motor planning. Subjects performed arm movements in a virtual environment under conditions where visual arm position cues were either aligned with corresponding somatosensory cues or were shifted prior to reach onset in one of four directions. Under shifted conditions, subjects exhibited characteristic ‘motor biases’, i.e., systematic deviations from ideal trajectories to the visually-cued targets. The arm positions used to plan movements under shifted conditions were obtained by minimizing differences between the experimentally induced motor biases and simulated motor biases. These REAP estimates largely conformed to predictions derived from previous perceptual experiments in that they were strongly influenced by the visual cues, and in a manner that was axially dependent. The results suggest that assessments of position sense derived from motor biases can be used to augment perceptual assessments or be used in lieu of them when perceptual reporting isn’t possible. In addition, the observed similarities between position estimates and weights derived from motor and perceptual tasks suggest that the brain’s perceptual and action systems use similar mechanisms to deduce arm position from somatosensory and visual cues.