U n c o r r e c t e d P r o o f Abstract Brain injury often results a partial loss of the neural resources communicating to the periphery that controls movements. Consequently, the prior signals may no longer be appropriate for getting the muscles to do what is neededa new pattern needs to be learned that appropriately uses the residual resources. Such learning may not be too different from the learning of skills in sports, music performance, surgery, teleoperation, piloting, and child

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... nt. Our lab has leveraged what we know about neural adaptation and engineering control theory to develop and test new interactive environments that enhance learning (or relearning). One successful application is the use of robotics and video feedback technology to augment error signals, which tests standing hypotheses about error-mediated neuroplasticity and illustrates an exciting prospect for rehabilitation environments of tomorrow. Keywords Learning • Motor control • Movement • Human • Rehabilitation • Adaptation • Training • Feedforward control As research continues to support prolonged practice of functionally relevant activities for restoration of function, interactions with technology have revealed new prospects in the areas of motor teaching. The compelling question many researchers are currently pursuing is whether such new applications of technology can go further than simply giving a higher intensity or more prolonged care. This chapter will focus on how robotic devices combined with computer displays can augment error in order to speed up, enhance, or trigger motor relearning. Below, we outline the sources of this rationale, as well as present some early examples.