TASK- AND FEEDBACK-DEPENDENT SENSORY INTEGRATION DURING REACH PLANNING

Samuel J. Sober and Philip N. Sabes

Dept. of Physiology, University of California, San Francisco, San Francisco, CA,  94143, U.S.A.

       When planning goal-directed reaches, subjects must estimate the position of the arm by integrating visual and proprioceptive signals from the sensory periphery.  These integrated position estimates are required at two stages of motor planning: first to determine the desired movement vector, and second to transform the movement vector into a joint-based motor command.  We quantified the contributions of each sensory modality to the position estimate formed at each planning stage.

     Subjects made reaches in a virtual reality environment in which vision and proprioception were dissociated by shifting the location of visual feedback.  The relative weighting of vision and proprioception at each stage was then determined using computational models of feedforward motor control.  We found that the position estimate used for movement vector planning relies mostly on visual input, whereas the estimate used to compute the joint-based motor command relies more on proprioceptive signals.  This suggests that the brain selects different combinations of sensory input based on the computation in which the resulting estimate will be used, perhaps because vector planning and inverse model computation are performed in different coordinate frames.

    This hypothesis was tested in two additional experiments in which we varied either the demands of the task or the information content of the visual feedback.  By comparing the weighting of vision and proprioception in these contrasting tasks, we show that sensory integration at both stages of reach planning is flexible.  Furthermore, our results suggest that the CNS chooses integration strategies that minimize the reliance on sensory signals that must be transformed between coordinate systems, perhaps to avoid position estimation errors due to coordinate transformations (see "Testing Prediction #1" on poster) and the ambiguity of degraded visual feedback (see "Testing Prediction #2").