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Closed-loop neuromodulation of spinal sensorimotor circuits controls refined locomotion after complete spinal cord injury


E. Martin Moraud, Nikolaus Wenger, Stanisa Raspopovic, Marco Bonizzato, J. DiGiovanna, Pavel Musienko, M. Morari, S. Micera, Gregoire Courtine

Science Translational Medicine, vol. 6, no. 255, Eduardo Martin Moraud and Nikolaus Wenger contributed equally to this work

Neuromodulation of spinal sensorimotor circuits improves motor control in animal models and humans with spinal cord injury. With common neuromodulation devices, electrical stimulation parameters are tuned manually and remain constant during movement. We developed a mechanistic framework to optimize neuromodulation in real time to achieve high-fidelity control of leg kinematics during locomotion in rats. We first uncovered relationships between neuromodulation parameters and recruitment of distinct sensorimotor circuits, resulting in predictive adjustments of leg kinematics. Second, we established a technological platform with embedded control policies that integrated robust movement feedback and feed-forward control loops in real time. These developments allowed us to conceive a neuroprosthetic system that controlled a broad range of foot trajectories during continuous locomotion in paralyzed rats. Animals with complete spinal cord injury performed more than 1000 successive steps without failure, and were able to climb staircases of various heights and lengths with precision and fluidity. Beyond therapeutic potential, these findings provide a conceptual and technical framework to personalize neuromodulation treatments for other neurological disorders.


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% Autogenerated BibTeX entry
@Article { MorEtal:2014:IFA_5059,
    author={E. Martin Moraud and Nikolaus Wenger and Stanisa Raspopovic and Marco Bonizzato and J. DiGiovanna and Pavel Musienko and M. Morari and S. Micera and Gregoire Courtine},
    title={{Closed-loop neuromodulation of spinal sensorimotor circuits
	  controls refined locomotion after complete spinal cord
    journal={Science Translational Medicine},
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