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Saccade Adaptation in Response to Altered Arm Dynamics

Laboratory for Computational Motor Control, Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, Maryland 21205

Submitted 3 June 2003; accepted in final form 12 July 2003

The delays in sensorimotor pathways pose a formidable challenge to the implementation of stable error feedback control, and yet the intact brain has little trouble maintaining limb stability. How is this achieved? One idea is that feedback control depends not only on delayed proprioceptive feedback but also on internal models of limb dynamics. In theory, an internal model allows the brain to predict limb position. Earlier we had found that during reaching, the brain estimates hand position in real-time in a coordinate system that can be used for generating saccades. Here we tested the idea that the estimate of hand position, as expressed through saccades, depends on an internal model that adapts to dynamics of the arm. We focused on the behavior of the eyes as perturbations were applied to the unseen hand. We found that when the hand was perturbed from stable posture with a 100-ms force pulse of random direction and magnitude, a saccade was generated on average at 182 ms postpulse onset to a position that was an unbiased estimate of real-time hand position. To test whether planning of saccades depended on an internal model of arm dynamics, arm dynamics were altered either predictably or unpredictably during the postpulse period. When arm dynamics were predictable, saccade amplitudes changed to reflect the change in the arm's behavior. We suggest that proprioceptive feedback from the arm is integrated into an adaptable internal model that computes an estimate of current hand position in eye-centered coordinates.

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