Abstract

Epidural electrical stimulation (EES) of the spinal cord restores locomotion in animal models of spinal cord injury but is less effective in humans. Here we hypothesized that this interspecies discrepancy is due to interference between EES and proprioceptive information in humans. Computational simulations and preclinical and clinical experiments reveal that EES blocks a significant amount of proprioceptive input in humans, but not in rats. This transient deafferentation prevents modulation of reciprocal inhibitory networks involved in locomotion and reduces or abolishes the conscious perception of leg position. Consequently, continuous EES can only facilitate locomotion within a narrow range of stimulation parameters and is unable to provide meaningful locomotor improvements in humans without rehabilitation. Simulations showed that burst stimulation and spatiotemporal stimulation profiles mitigate the cancellation of proprioceptive information, enabling robust control over motor neuron activity. This demonstrates the importance of stimulation protocols that preserve proprioceptive information to facilitate walking with EES.

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Acknowledgements

We thank K. Bartholdi, A. Bichat, and L. Baud for their help with the rat experiments, and we thank all the individuals involved in the STIMO clinical study. This research was supported by the HBP Neurorobotics Platform, funded from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 720270 (Human Brain Project SGA1). Financial support was provided by the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreements No. 720270 (Human Brain Project SGA1) and No. 785907 (Human Brain Project SGA2); RESTORE: Eurostars E10889, Wings for Life, GTXmedical, Consolidator Grant from the European Research Council (ERC-2015-CoG HOW2WALKAGAIN 682999), Wyss Center for Neuroengineering, National Center of Competence in Research (NCCR) Robotics of the Swiss National Science Foundation, the Commission of Technology and Innovation (CTI) Innosuisse (CTI) OptiStim 25761.1, International Foundation for Research in Paraplegia (IRP), the Michel-Adrien Voirol Foundation, the Firmenich Foundation, the Pictet Group Charitable Foundation, the Panacée Foundation, and the Marie-Curie EPFL fellowship program.

Author information

Author notes

  1. These authors jointly supervised this work: Silvestro Micera, Marco Capogrosso, Gregoire Courine.

Affiliations

  1. Bertarelli Foundation Chair in Translational NeuroEngineering, Institute of Bioengineering, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland

    • Emanuele Formento
    •  & Silvestro Micera
  2. Center for Neuroprosthetics and Brain Mind Institute, School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland

    • Emanuele Formento
    • , Karen Minassian
    • , Fabien Wagner
    • , Jean Baptiste Mignardot
    • , Camille G. Le Goff-Mignardot
    • , Andreas Rowald
    •  & Gregoire Courtine
  3. Department of Medicine, Faculty of Sciences, University of Fribourg, Fribourg, Switzerland

    • Andreas Rowald
    •  & Marco Capogrosso
  4. Department of Neurosurgery, University Hospital of Lausanne (CHUV), Lausanne, Switzerland

    • Jocelyne Bloch
    •  & Gregoire Courtine
  5. Neural Engineering Area, Institute of Biorobotics, Scuola Superiore Sant’Anna, Pisa, Italy

    • Silvestro Micera

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Contributions

E.F., M.C., K.M., S.M., and G.C. conceived the study. E.F. and M.C. designed the computational model and E.F. performed the simulations. J.B. performed the surgery in humans. E.F., K.M., F.W., J.B.M., and C.G.LG. performed the experiments. A.R. and E.F. built the robotic platform to control rat ankle kinematics. E.F. performed the data analyses and prepared the figures. G.C. wrote the manuscript with E.F., M.C., and K.M., and all the authors contributed to its editing. G.C., S.M., M.C., and J.B. supervised the work.

Competing interests

G.C, J.B., and S.M. are founders and shareholders of GTXmedical SA, a company developing neuroprosthetic systems in direct relationship with the present work. E.F., M.C., G.C., and S.M. hold several patents related to electrical spinal cord stimulation.

Corresponding author

Correspondence to Gregoire Courtine.

Integrated supplementary information

  1. Supplementary Figure 1 Impact of continuous EES on the threshold to detection of passive movement test performance.

    Scatter plots reporting the detection angle and and plots reporting the error rate (percentage correct trials ± 95% CI) on the TTDPM test performance without EES and when delivering continuous EES at 0.8 and 1.5 times motor response threshold amplitudes and a range of EES frequencies. Different EES frequencies were tested on subject #1 (10 Hz, 50 Hz, 100 Hz) and subject #3 (30 Hz, 50 Hz). At 1.5 motor response threshold amplitude, EES frequencies below 50 Hz induced spasms in the muscles and were thus not tested. Grey dots report the detection angle for successful trials, while pink dots and red crosses indicate false positive and failure to detect movement within the allowed range of motion, respectively (n = 65 for subject #1 and n = 66 for subject #3). *, P < 0.05, Clopper-Pearson non-overlapping intervals, two-sided.

  2. Supplementary Figure 2 Effect of EES on the natural modulation of proprioceptive circuits during passive movements: extended data.

    a, Configuration of the experimental setup for subject #1 and #3, as described in Fig. 3a. b, Plots showing EES pulses, EMG activity of the vastus medialis, and changes in knee joint angle during passive oscillations of the knee when EES is delivered at 60 Hz in subject #2 — similar results were achieved in subject #1 and #3. Conventions as in Fig. 3b.

  3. Supplementary Figure 3 Impact of EES amplitude on muscle activity and leg kinematics during locomotion on a treadmill: Subject #1.

    a, AIS leg motor score. b, Configuration of electrodes targeting the left and right posterior roots projecting to the L1 and L4 segments. Continuous EES was delivered through these electrodes to facilitate locomotion. c, EMG activity of flexor (semitendinosus/tibialis anterior) and extensor (rectus femoris/soleus) muscles spanning the right knee and ankle joints, together with the changes in the knee ankle and foot height trajectories over four gait cycles without EES and with EES delivered at 0.9, 1.2 and 1.5 motor response threshold amplitude — similar results were obtained for 30 gait cycles (analyzed in d). EES frequency was set to 40Hz. d, Violin plots reporting the root mean square activity of the recorded muscles, the range of motion of the knee and ankle angles, and the step height for different gait cycles (n = 53 gait cycles). Small grey dots represent the different data points, while the large white dots represent the median of the different distributions. Box and whiskers report the interquartile range and the adjacent values, respectively. *, P < 0.05, ***, P < 0.001, Wilcoxon rank-sum two-sided test with Bonferroni correction for multiple comparisons.

  4. Supplementary Figure 4 Impact of EES frequency and amplitude on muscle activity and leg kinematics during locomotion on a treadmill: Subject #2.

    The results displayed in Fig. 6 and Supplementary Figure 3 for subject #1 are reported for subject #2 using the same conventions. Recordings in panels a and c were repeated for 29 and 20 gait cycles and analyzed in panels b and c, respectively. The statistics in panel d were computed over n = 37 gait cycles. *, P < 0.05, ***, P < 0.001, Wilcoxon rank-sum two-sided test with Bonferroni correction for multiple comparisons.

  5. Supplementary Figure 5 Impact of EES frequency and amplitude on muscle activity and leg kinematics during locomotion on a treadmill: Subject #3.

    The results displayed in Fig. 6 and Supplementary Figure 3 for subject #1 are reported for subject #3 using the same conventions. Recordings in panels a and c were repeated for 51 and 25 gait cycles and were analyzed in panels b and c, respectively. The statistics in panel b and d were computed over n = 77 and n = 51 gait cycles, respectively. *, P < 0.05, ***, P < 0.001, Wilcoxon rank-sum two-sided test with Bonferroni correction for multiple comparisons.

  6. Supplementary Figure 6 High-frequency, low-amplitude EES protocols preserve proprioceptive information and promote motor patterns formation.

    Impact of continuous high-frequency low-amplitude EES protocols (600 Hz, 20% recruited afferents) on the modulation of the muscle spindle feedback circuits, following the same conventions as in Fig. 5. For comparison, the impact of continuous EES on the group-Ia afferent firings is also reported.

  7. Supplementary Figure 7 Integrate-and-fire motor neuron model.

    Schematic of the integrate and fire model and of the different synapses contacting this cell. b, Simulated inhibitory and excitatory post synaptic potentials (IPSPs/EPSPs) induced by the activation of a single Ia-inhibitory interneuron or a single group-Ia afferent fiber, respectively. c, Excitation threshold of our multicompartmental alpha motoneuron model. d, Number and amplitude of experimental and modeled EPSP/IPSPs induced from the synaptic contacts originating from group-Ia afferents (s1), group-II excitatory interneurons (s2), and Ia-inhibitory interneurons (s3).

  8. Supplementary Figure 8 Adaptation of the rat neural network to humans.

    a, Model layout of the hybrid rat-human computational model used to tune the human neural network weights. W1, w2, w3 and w4 represent the weights of the neural network connections that have been modified to adapt the rat neural network to the human one. b, Systematic search results. W1 and w3 were ranged together between 1 and 2 times the weight used in the rat network, while w2 and w4 were ranged between 1 and 4 times. Bar plots report the percentage of simulations that fulfilled the defined fitness criteria. Selected weights that have been used for further simulations are highlighted with an arrow. c, Effect of EES on the natural activity of Ia-inhibitory interneurons and on the production of motor patterns during locomotion, in the hybrid rat-human model for the selected set of synaptic weights. Panels on the left report the average firing rate profiles of the Ia-inhibitory interneuron populations associated to either the flexor or the extensor network, as well as their modulation depth (mean ± SEM, n = 11 gait cycles). Similarly, right-most panels represent the average firing rate profiles of motoneurons and their mean firing rate activity during the phase in which they are active (mean ± SEM, n = 11 gait cycles). Effects of different EES frequencies and amplitudes are reported on the top and bottom panels, respectively.

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https://doi.org/10.1038/s41593-018-0262-6