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        Proprioception in motor learning: : lessons from a deafferented subject

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        Author
        Yousif, N
        Cole, J
        Rothwell, J
        Diedrichsen, J
        Attention
        2299/19315
        Abstract
        Proprioceptive information arises from a variety of channels, including muscle, tendon, and skin afferents. It tells us where our static limbs are in space and how they are moving. It remains unclear however, how these proprioceptive modes contribute to motor learning. Here, we studied a subject (IW) who has lost large myelinated fibres below the neck and found that he was strongly impaired in sensing the static position of his upper limbs, when passively moved to an unseen location. When making reaching movements however, his ability to discriminate in which direction the trajectory had been diverted was unimpaired. This dissociation allowed us to test the involvement of static and dynamic proprioception in motor learning. We found that IW showed a preserved ability to adapt to force fields when visual feedback was present. He was even sensitive to the exact form of the force perturbation, responding appropriately to a velocity- or position-dependent force after a single perturbation. The ability to adapt to force fields was also preserved when visual feedback about the lateral perturbation of the hand was withdrawn. In this experiment, however, he did not exhibit a form of use-dependent learning, which was evident in the control participants as a drift of the intended direction of the reaching movement in the perturbed direction. This suggests that this form of learning may depend on static position sense at the end of the movement. Our results indicate that dynamic and static proprioception play dissociable roles in motor learning.
        Publication date
        2015-08-01
        Published in
        Experimental Brain Research
        Published version
        https://doi.org/10.1007/s00221-015-4315-8
        License
        http://creativecommons.org/licenses/by/4.0/
        Other links
        http://hdl.handle.net/2299/19315
        Relations
        School of Physics, Engineering & Computer Science
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