Letter

A brain–spine interface alleviating gait deficits after spinal cord injury in primates

Received:
Accepted:
Published online:

Abstract

Spinal cord injury disrupts the communication between the brain and the spinal circuits that orchestrate movement. To bypass the lesion, brain–computer interfaces1,2,3 have directly linked cortical activity to electrical stimulation of muscles, and have thus restored grasping abilities after hand paralysis1,4. Theoretically, this strategy could also restore control over leg muscle activity for walking5. However, replicating the complex sequence of individual muscle activation patterns underlying natural and adaptive locomotor movements poses formidable conceptual and technological challenges6,7. Recently, it was shown in rats that epidural electrical stimulation of the lumbar spinal cord can reproduce the natural activation of synergistic muscle groups producing locomotion8,9,10. Here we interface leg motor cortex activity with epidural electrical stimulation protocols to establish a brain–spine interface that alleviated gait deficits after a spinal cord injury in non-human primates. Rhesus monkeys (Macaca mulatta) were implanted with an intracortical microelectrode array in the leg area of the motor cortex and with a spinal cord stimulation system composed of a spatially selective epidural implant and a pulse generator with real-time triggering capabilities. We designed and implemented wireless control systems that linked online neural decoding of extension and flexion motor states with stimulation protocols promoting these movements. These systems allowed the monkeys to behave freely without any restrictions or constraining tethered electronics. After validation of the brain–spine interface in intact (uninjured) monkeys, we performed a unilateral corticospinal tract lesion at the thoracic level. As early as six days post-injury and without prior training of the monkeys, the brain–spine interface restored weight-bearing locomotion of the paralysed leg on a treadmill and overground. The implantable components integrated in the brain–spine interface have all been approved for investigational applications in similar human research, suggesting a practical translational pathway for proof-of-concept studies in people with spinal cord injury.

  • Subscribe to Nature for full access:

    $199

    Subscribe

Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.

References

  1. 1.

    , , & Restoration of grasp following paralysis through brain-controlled stimulation of muscles. Nature 485, 368–371 (2012)

  2. 2.

    et al. High-performance neuroprosthetic control by an individual with tetraplegia. Lancet 381, 557–564 (2013)

  3. 3.

    et al. Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature 485, 372–375 (2012)

  4. 4.

    et al. Restoring cortical control of functional movement in a human with quadriplegia. Nature 533, 247–250 (2016)

  5. 5.

    , & Could cortical signals control intraspinal stimulators? A theoretical evaluation. IEEE Trans. Neural Syst. Rehabil. Eng. 14, 198–201 (2006)

  6. 6.

    et al. Functional electrical stimulation and spinal cord injury. Phys. Med. Rehabilitation Clinics North Am. 25, 631–654 (2014)

  7. 7.

    et al. A randomized trial of functional electrical stimulation for walking in incomplete spinal cord injury: effects on walking competency. J. Spinal Cord Med. 37, 511–524 (2014)

  8. 8.

    et al. Closed-loop neuromodulation of spinal sensorimotor circuits controls refined locomotion after complete spinal cord injury. Sci. Transl. Med. 6, 255ra133 (2014)

  9. 9.

    et al. Spatiotemporal neuromodulation therapies engaging muscle synergies improve motor control after spinal cord injury. Nat. Med. 22, 138–145 (2016)

  10. 10.

    et al. Mechanisms underlying the neuromodulation of spinal circuits for correcting gait and balance deficits after spinal cord injury. Neuron 89, 814–828 (2016)

  11. 11.

    Flexion-reflex of the limb, crossed extension-reflex, and reflex stepping and standing. J. Physiol. 40, 28–121 (1910)

  12. 12.

    Decoding the organization of spinal circuits that control locomotion. Nat. Rev. Neurosci. 17, 224–238 (2016)

  13. 13.

    , , & Real-time control of walking using recordings from dorsal root ganglia. J. Neural Eng. 10, 056008 (2013)

  14. 14.

    , , & Altering spinal cord excitability enables voluntary movements after chronic complete paralysis in humans. Brain 137, 1394–1409 (2014)

  15. 15.

    et al. Noninvasive reactivation of motor descending control after paralysis. J. Neurotrauma 32, 1968–1980 (2015)

  16. 16.

    et al. Human spinal locomotor control is based on flexibly organized burst generators. Brain 138, 577–588 (2015)

  17. 17.

    , & Characteristics and mechanisms of locomotion induced by intraspinal microstimulation and dorsal root stimulation in spinal cats. J. Neurophysiol. 97, 1986–2000 (2007)

  18. 18.

    & Combining decoder design and neural adaptation in brain–machine interfaces. Neuron 84, 665–680 (2014)

  19. 19.

    , & A cortical-spinal prosthesis for targeted limb movement in paralysed primate avatars. Nat. Commun. 5, 3237 (2014)

  20. 20.

    & Closed-loop control of spinal cord stimulation to restore hand function after paralysis. Front. Neurosci. 8, 87 (2014)

  21. 21.

    , , & Spike-timing-dependent plasticity in primate corticospinal connections induced during free behavior. Neuron 80, 1301–1309 (2013)

  22. 22.

    Descending pathways in motor control. Annu. Rev. Neurosci. 31, 195–218 (2008)

  23. 23.

    et al. Pronounced species divergence in corticospinal tract reorganization and functional recovery after lateralized spinal cord injury favors primates. Sci. Transl. Med. 7, 302ra134 (2015)

  24. 24.

    et al. Can experiments in nonhuman primates expedite the translation of treatments for spinal cord injury in humans? Nat. Med. 13, 561–566 (2007)

  25. 25.

    et al. Wireless neurosensor for full-spectrum electrophysiology recordings during free behavior. Neuron 84, 1170–1182 (2014)

  26. 26.

    , , , & Spatiotemporal activation of lumbosacral motoneurons in the locomotor step cycle. J. Neurophysiol. 87, 1542–1553 (2002)

  27. 27.

    , & Epidural electrical stimulation of posterior structures of the human lumbosacral cord: 2. Quantitative analysis by computer modeling. Spinal Cord 38, 473–489 (2000)

  28. 28.

    & Defining ecological strategies in neuroprosthetics. Neuron 86, 29–33 (2015)

  29. 29.

    , , & Motor-cortical activity in tetraplegics. Nature 413, 793 (2001)

  30. 30.

    et al. Restoring voluntary control of locomotion after paralyzing spinal cord injury. Science 336, 1182–1185 (2012)

  31. 31.

    et al. Kinematic and EMG determinants in quadrupedal locomotion of a non-human primate (Rhesus). J. Neurophysiol. 93, 3127–3145 (2005)

  32. 32.

    , , & Control of a brain-computer interface without spike sorting. J. Neural Eng. 6, 055004 (2009)

  33. 33.

    et al. Clinical translation of a high-performance neural prosthesis. Nat. Med. 21, 1142–1145 (2015)

  34. 34.

    et al. Decoding motor imagery from the posterior parietal cortex of a tetraplegic human. Science 348, 906–910 (2015)

  35. 35.

    , , , & Detection of error related neuronal responses recorded by electrocorticography in humans during continuous movements. PLoS One 8, e55235 (2013)

  36. 36.

    Human Anatomy and Physiology 6th edn (Pearson Education, 2003)

  37. 37.

    in Comprehensive Physiology Ch. 3 (John Wiley & Sons, 2011)

Download references

Acknowledgements

G.C. holds the International Foundation for Research in Paraplegia Chair in Spinal Cord Repair. S.M. holds the Bertarelli Foundation Chair in Translational Neuroengineering. We thank X. Rulin and C. Yunlong for providing support, taking care of the monkeys, performing behavioural training, and collecting data; E. Pirondini, N. Pavlova and P. Musienko for help with experiments; J. Courtine, I. Pitteloud, J. Rubattel, L. Dalang and R. Hasler for help with kinematic reconstruction; J. Courtine for the voice-over in video; J. Kreider for help with anatomy; and J. Laurens for discussions and photographs. The illustrations were created by Jemère Ruby. This work was supported by Medtronic, the European Community's Seventh Framework Program (CP-IP 258654, NeuWALK), the International Paraplegic foundation, a Starting Grant from the European Research Council (ERC 261247, Walk Again), the Wyss centre in Geneva, a Marie Curie Fellowship to D.B. (331602, e-WALK), Marie Curie COFUND EPFL fellowships to T.M. and F.W., a Morton Cure Paralysis Fund fellowship to T.M., and the Swiss National Science Foundation including the National Centre of Competence in Research in Robotics, the Sinergia program (CRSII3_160696), the Sino-Swiss Science and Technology Cooperation (IZLCZ3_156331), and the NanoTera.ch programme (SpineRepair).

Author information

Author notes

    • Marco Capogrosso
    • , Tomislav Milekovic
    •  & David Borton

    These authors contributed equally to this work.

Affiliations

  1. Center for Neuroprosthetics and Brain Mind Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland

    • Marco Capogrosso
    • , Tomislav Milekovic
    • , David Borton
    • , Fabien Wagner
    • , Jean-Baptiste Mignardot
    • , Jerome Gandar
    • , Quentin Barraud
    • , Elodie Rey
    • , Simone Duis
    •  & Grégoire Courtine
  2. Center for Neuroprosthetics and Institute of Bioengineering, School of Bioengineering, EPFL, Lausanne, Switzerland

    • Marco Capogrosso
    • , Eduardo Martin Moraud
    •  & Silvestro Micera
  3. School of Engineering, Brown University, Providence, Rhode Island, USA

    • David Borton
    •  & David Xing
  4. Medtronic, Minneapolis, Minnesota, USA

    • Nicolas Buse
    •  & Tim Denison
  5. Motac Neuroscience Ltd, Manchester, UK

    • Yang Jianzhong
    • , Wai Kin D. Ko
    • , Qin Li
    •  & Erwan Bezard
  6. Institute of Lab Animal Sciences, China Academy of Medical Sciences, Beijing, China

    • Qin Li
    •  & Erwan Bezard
  7. Mainz Institute for Microtechnology, Fraunhofer Institute for Chemical Technology (ICT-IMM), Mainz, Germany

    • Peter Detemple
  8. The BioRobotics Institute, Scuola Superiore Sant’Anna, Pisa, Italy

    • Silvestro Micera
  9. Institut des Maladies Neurodégénératives, University of Bordeaux, UMR 5293, Bordeaux, France

    • Erwan Bezard
  10. CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France

    • Erwan Bezard
  11. Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland

    • Jocelyne Bloch
    •  & Grégoire Courtine

Authors

  1. Search for Marco Capogrosso in:

  2. Search for Tomislav Milekovic in:

  3. Search for David Borton in:

  4. Search for Fabien Wagner in:

  5. Search for Eduardo Martin Moraud in:

  6. Search for Jean-Baptiste Mignardot in:

  7. Search for Nicolas Buse in:

  8. Search for Jerome Gandar in:

  9. Search for Quentin Barraud in:

  10. Search for David Xing in:

  11. Search for Elodie Rey in:

  12. Search for Simone Duis in:

  13. Search for Yang Jianzhong in:

  14. Search for Wai Kin D. Ko in:

  15. Search for Qin Li in:

  16. Search for Peter Detemple in:

  17. Search for Tim Denison in:

  18. Search for Silvestro Micera in:

  19. Search for Erwan Bezard in:

  20. Search for Jocelyne Bloch in:

  21. Search for Grégoire Courtine in:

Contributions

M.C., T.M. and D.B. contributed equally to this work. F.W. and E.M.M. contributed equally to this work. S.M., E.B. and J.B. contributed equally to this work. M.C. developed the spinal cord stimulation protocols and the routines for the identification of flexion and extension hotspots. T.M. developed the brain decoder and the decoder calibration routines. D.B. developed the experimental platform. M.C., T.M., F.W. and E.M.M. performed all the behavioural experiments (with help from D.B., J.G., Y.J. and G.C.). M.C., T.M. and F.W. analysed the data (with input from E.M.M., J.-B.M. and D.X.). M.C., T.M., F.W., E.M.M. and J.G. developed the real-time software application. N.B. and T.D. developed the Neural Research Programmer (with input from M.C., D.B., T.M., F.W. and J.G.). Q.B. and E.R. processed the anatomical data. Y.J. trained all the monkeys. W.K.D.K., Q.L. and E.B. managed the experimental protocols and procedures. P.D. developed and produced the spinal implants (from designs by M.C., D.B., J.B. and G.C.). J.B., D.B., Q.L. and G.C. performed the surgeries. G.C., S.M., E.B., J.B. and P.D. secured funding for the study. G.C. conceived and supervised the study. G.C. wrote the paper with M.C., T.M. and F.W., and all the authors contributed to its editing.

Competing interests

G.C., D.B., M.C., S.M., E.M.M. and J.B. hold various patents related to the present work. T.D. and N.B. are Medtronic employees and contributed to the technical accuracy of the work but did not influence the results or the content of the manuscript. E.B. reports receipt of personal fees from Motac Neuroscience Ltd UK and is a shareholder of Motac Holding UK and Plenitudes SARL France. G.C., S.M. and J.B. are founders and shareholders of G-Therapeutics BV.

Corresponding author

Correspondence to Grégoire Courtine.

Reviewer Information

Nature thanks A. Jackson, A. Prochazka, S. Scott and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Text and Data and Supplementary Tables 1-3.

Videos

  1. 1.

    Technical design and therapeutic effects of the brain–spinal interface

    This video explains the design of the spinal cord stimulation system and brain decoding algorithms. The ability of the brain–spinal interface to modulate extension and flexion movements of the leg during continuous locomotion is then illustrated in intact monkeys. Finally, the video shows the recovery of functional leg movements during locomotion on a treadmill and overground in two monkeys with a spinal cord injury.

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.