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A cortical–spinal prosthesis for targeted limb movement in paralysed primate avatars

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  • Maryam M. Shanechi

    (School of Electrical and Computer Engineering, Cornell University)

  • Rollin C. Hu

    (MGH-HMS Center for Nervous System Repair, Harvard Medical School)

  • Ziv M. Williams

    (MGH-HMS Center for Nervous System Repair, Harvard Medical School)

Abstract

Motor paralysis is among the most disabling aspects of injury to the central nervous system. Here we develop and test a target-based cortical–spinal neural prosthesis that employs neural activity recorded from premotor neurons to control limb movements in functionally paralysed primate avatars. Given the complexity by which muscle contractions are naturally controlled, we approach the problem of eliciting goal-directed limb movement in paralysed animals by focusing on the intended targets of movement rather than their intermediate trajectories. We then match this information in real-time with spinal cord and muscle stimulation parameters that produce free planar limb movements to those intended target locations. We demonstrate that both the decoded activities of premotor populations and their adaptive responses can be used, after brief training, to effectively direct an avatar’s limb to distinct targets variably displayed on a screen. These findings advance the future possibility of reconstituting targeted limb movement in paralysed subjects.

Suggested Citation

  • Maryam M. Shanechi & Rollin C. Hu & Ziv M. Williams, 2014. "A cortical–spinal prosthesis for targeted limb movement in paralysed primate avatars," Nature Communications, Nature, vol. 5(1), pages 1-9, May.
  • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms4237
    DOI: 10.1038/ncomms4237
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    Cited by:

    1. Han-Lin Hsieh & Maryam M Shanechi, 2018. "Optimizing the learning rate for adaptive estimation of neural encoding models," PLOS Computational Biology, Public Library of Science, vol. 14(5), pages 1-34, May.

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