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Epidural electrical stimulation of the cervical dorsal roots restores voluntary upper limb control in paralyzed monkeys

Nature Neuroscience volume 25, pages 924–934 (2022)Cite this article

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Abstract

Regaining arm control is a top priority for people with paralysis. Unfortunately, the complexity of the neural mechanisms underlying arm control has limited the effectiveness of neurotechnology approaches. Here, we exploited the neural function of surviving spinal circuits to restore voluntary arm and hand control in three monkeys with spinal cord injury, using spinal cord stimulation. Our neural interface leverages the functional organization of the dorsal roots to convey artificial excitation via electrical stimulation to relevant spinal segments at appropriate movement phases. Stimulation bursts targeting specific spinal segments produced sustained arm movements, enabling monkeys with arm paralysis to perform an unconstrained reach-and-grasp task. Stimulation specifically improved strength, task performances and movement quality. Electrophysiology suggested that residual descending inputs were necessary to produce coordinated movements. The efficacy and reliability of our approach hold realistic promises of clinical translation.

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Fig. 1: Experimental framework.
Fig. 2: Muscle recruitment of spinal stimulation.
Fig. 3: EES produces functional joint movements in anesthetized animals.
Fig. 4: EES improves task performance.
Fig. 5: EES improves muscle strength and movement quality.
Fig. 6: EES must be synchronized with motor intention.

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Data availability

Due to the sensitive nature of the dataset, which contains graphic information on monkeys, raw data, including videos, will be available upon reasonable request to the corresponding author and after authorization from the Swiss cantonal authorities. A set of preprocessed data will be deposited on the Open-Data Commons for Spinal Cord Injury (https://odc-sci.org). Source data are provided with this paper.

Code availability

Software routines utilized for data analysis will be deposited on GitHub under search keyword NN-A75365C.

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Acknowledgements

We thank J. Maillard and L. Bossy for the care provided to the animals; E. Schmidlin and S. Borgognon for their help with anesthesia and surgery preparations; M. Badi for her help and advice during experiment preparations and experimental procedures; A. Zbinden for her contribution to the health survey of the monkeys; A. Gaillard and A. Francovich for their help with the implementation of the hardware; and students of the University of Fribourg A. Jeanneret, A. Jelusic, L. M. Jacquemet and S. Borra for their help in processing data. We acknowledge the financial support from the Wyss Center grant (no. WCP 008) to M.C., G.C. and T.M.; an industrial grant from GTX Medicals to G.C. and M.C; the Bertarelli Foundation (Catalyst Fund Grant to M.C. and T.M. and funds to S.L.); a Swiss National Science Foundation Ambizione Fellowship (no. 167912 to M.C.) and a Swiss National Science Foundation Doc-Mobility Grant (no. 188027 to B.B.); the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement no. 665667 (G.S.); the Swiss National Foundation grant no. BSCGI0_157800 (S.L.); a Whitaker International Scholars Program fellowship to M.G.P.; and an internal pilot grant of the University of Fribourg to M.C.

Author information

Author notes

  1. These authors contributed equally: Beatrice Barra, Sara Conti.

Authors and Affiliations

  1. Platform of Translational Neuroscience, Department of Neuroscience and Movement Sciences, Faculty of Sciences and Medicine, University of Fribourg, Fribourg, Switzerland

    Beatrice Barra, Sara Conti, Katie Zhuang, Maude Delacombaz, Mélanie Kaeser, Eric M. Rouiller & Marco Capogrosso

  2. Rehab and Neural Engineering Labs, University of Pittsburgh, Pittsburgh, PA, USA

    Beatrice Barra & Marco Capogrosso

  3. Department of Fundamental Neuroscience, Faculty of Medicine, University of Geneva, Geneva, Switzerland

    Matthew G. Perich & Tomislav Milekovic

  4. Bertarelli Foundation Chair in Neuroprosthetic Technology, Laboratory for Soft Bioelectronic Interfaces, Institute of Microengineering, Institute of Bioengineering, Centre for Neuroprosthetics, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland

    Giuseppe Schiavone, Florian Fallegger & Stephanie Lacour

  5. Center for Neuroprosthetics and Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Katia Galan, Nicholas D. James, Quentin Barraud & Grégoire Courtine

  6. Defitech Center for Interventional Neurotherapies (NeuroRestore), University Hospital Lausanne (CHUV), University of Lausanne (UNIL) and École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Katia Galan, Quentin Barraud, Maude Delacombaz, Tomislav Milekovic, Jocelyne Bloch & Grégoire Courtine

  7. Department of Neurosurgery, CHUV, Lausanne, Switzerland

    Jocelyne Bloch & Grégoire Courtine

  8. Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA

    Marco Capogrosso

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  1. Beatrice Barra
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Contributions

M.C., B.B. and S.C. conceived the study. B.B., M.G.P. and T.M. designed and implemented the hardware and software tools. S.C. designed the behavioral task and training strategy. G.S., F.F. and S.L. designed and manufactured the implantable interface. B.B., S.C., M.G.P. and M.C. conducted the experiments. B.B., S.C., M.G.P. and K.Z. performed the data analysis. S.C., M.D. and M.K. trained the animals. S.C., K.G., N.D.J. and Q.B. processed the histological data. J.B., G.C. and M.C. designed surgical implantation strategies and stimulation strategies. G.C. and J.B. performed surgical implantations and lesions. E.M.R. and M.C. implemented and supervised procedures on monkeys. M.C., B.B., S.C. and M.G.P. wrote the manuscript. All authors edited the manuscript. S.L., T.M., J.B., G.C. and M.C. secured funding for the study. M.C. supervised the study.

Corresponding author

Correspondence to Marco Capogrosso.

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Competing interests

G.C., J.B., S.L., M.C., B.B. and K.Z. hold various patents in relation to the present work. G.C., S.L. and J.B. are founders and shareholders of Onwarrd Medical, a company developing an EES-based therapy to restore movement after spinal cord injury. M.C. is a founder and shareholder of Reach Neuro, Inc., a company developing spinal cord stimulation technologies for stroke. All other authors declare no competing interests.

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Nature Neuroscience thanks Sliman Bensmaia, Andrew Jackson and Arthur Prochazka for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Monkey’s Specific Movement Performances.

(a) Portfolio of signals recorded during intact movement for each animal. These signals have been recorded during the experimental session prior to the lesion. Motor cortex recordings show firing rate profiles for the 64 microelectrodes. Each row shows the firing rate of a specific electrode. Electrodes are displayed from top to bottom by order of first activation in a reference trial. Arbitrary units in motor cortex recording indicate normalized firing rate for each electrode (see Methods). In kinematic and EMG plots, black lines correspond to the mean profile across all trials, shaded area shows the SEM across all trials. Kinematic scales are expressed in mm. For Mk-Yg, arbitrary units on kinematic plots represent displacement units derived by the count of video pixels. EMG scales are expressed in mV. (b) Kinematic strategies implemented by each monkey. Stick diagrams representations of the arm kinematic during reach (blue) and pull (yellow). The black line highlights the elbow trajectory. Pie charts represent the percentage of success and failure in task performance before lesion. (c) Offline decoding performance for Mk-Br and Mk-Yg before lesion. Histograms show timing accuracy of reach (blue) and pull (yellow) event decoding. The height of bars (y coordinate) illustrates the amount of events decoded with a specific timing accuracy (x coordinate). Pie charts (inset) show the percentage of correctly identified (true positive) reaches (blue) and pulls (yellow), across all decoded events. The black portion of the pie chart highlights the percentage of false positive decoded events.

Extended Data Fig. 2 Electrode array personalization.

(a) Anatomical landmarks used to tailor the epidural interface to each monkey’s anatomy (Length of dorsal aspect of spinal canal Lcs, length of C5-T1 spinal segment LC5-T1, electrode width Wel, electrode length Lel). Three-dimensional reconstructions of vertebras are obtained by CT-reconstruction (Osirix, Pixmeo, Switzerland). (b) Personalized design of the epidural implant for each animal. All measures are in millimeters. Yellow traces at the bottom of the electrode identify connectors. (c) Position stability of the epidural array over time, illustrated through X-rays imaging taken during 3 consecutive weeks after the implantation, images from Mk-Yg (d) Compression injury at the insertion level of the array (T2-T3 segment) in Mk-Br, discovered post-mortem, stained with NeuN (neuronal cell bodies) and Iba1 (microglia).

Extended Data Fig. 3 Recruitment curves.

Muscle recruitment obtained by stimulating, through different electrode contacts (E1, E2, E3, E5), at 1 Hz at C5, C6/C7, and T1 spinal segments for Mk-Br and Mk-Sa. Mk-Sa only had three muscles implanted: biceps, triceps, and flexor digitorium superficialis.

Extended Data Fig. 4 Graded muscle activation during train pulses.

(a) Energy of EMG signals of triceps (Mk-Br and Mk-Yg), Flexor Digitorium Superficialis (Mk-Yg) and abductor pollicis (Mk-Br) muscles, following pulse-train stimulation at different frequencies (on the x-axis). Black bullets represent mean values. (b) Evolution over time of the peak-to-peak value of stimulation evoked responses during a stimulation burst. Each plot shows the evolution for a specific muscle following pulse-train stimulation at 50 and 100 Hz. Triceps is shown for Mk-Br and Mk-Yg, Flexor Digitorium Superficialis for Mk-Yg and abductor pollicis for Mk-Br. Each data point is represented as a bullet and lines represent mean values over time.

Extended Data Fig. 5 Design of stimulation protocol.

(a) Combined representation of movement smoothness, elbow and finger flexion, and pulling force during anesthetized stimulation. Shades of gray highlight three frequency ranges that produce: (1) smooth trajectory, but little movement and low force (20 Hz), (2) smooth trajectory, extended movement and medium force (40 and 50 Hz), (3) abrupt and very extended movement and low force (80 and 100 Hz). Kinematics and force reported here were measured in different experiments, kinematics was unconstrained, force data were acquired in isometric conditions (see Methods). The range 40-50 Hz was selected as the best optimization of sufficient movement, smoothness and force production. (b) Schematic representation of arm and hand kinematics during stimulation delivered from the selection of three contacts to produce elbow extension (blue), hand and wrist flexion (yellow and black), and elbow flexion (yellow). (c) Example of comparison between EMG activity during intact movement (left) and movement elicited by chaining stimulation from the three selected contacts (right). (d) Scheme illustrating how stimulation is triggered from movement-related intra-cortical signals. On the right, online performances of movement attempt decoder in two animals with SCI. Pie charts represent percentage of predicted (blue) and unpredicted (black) reach events by our decoder.

Extended Data Fig. 6 Kinematic is modulated by stimulation frequency.

(a) Stick diagram schematic of movements elicited by pulse-trains of stimulation in anesthetized conditions. Mk-Br: on the left, arm kinematic obtained by delivering stimulation at different frequencies from contact number 5, on the bottom-left, arm kinematics obtained by repetitive delivery of a burst at 50 Hz; on the bottom right, superimposition of stick diagrams obtained with stimulation at 20 Hz and at higher frequencies (50 or 100 Hz) from different contacts. For Mk-Yg: arm kinematic obtained by delivering stimulation at different frequencies from contact number 2 and superimposition of stick diagrams obtained with stimulation at 20 Hz and at higher frequencies (50 or 100 Hz) from different contacts. (b) On the left, finger flexion produced by stimulation at different frequencies from the grasp contact in Mk-Br. Black bullets represent the mean value across different pulse-trains. On the right, wrist flexion obtained by stimulation at different frequencies from the grasp contact in Mk-Yg.

Extended Data Fig. 7 Performance evolution.

(a) Evolution (in weeks) of rates at which Mk-Br performed reach movements after SCI (black), compared to the performances before injury (gray). (b) Evolution (in weeks) of rates at which Mk-Br performed grasp movements after SCI (black), compared to the performances before injury (gray). (c) Evolution (in weeks) of rates at which Mk-Br performed pull movements after SCI (black), compared to the performances before injury (gray). (d) Evolution (in days) of pull force after SCI without stimulation for Mk-Br. Values are plotted as the mean ± STD (from left to right, n = 28, 29, 22, 26, 51 independent samples). Statistical analysis was carried out with two-sided Wilcoxon Ranksum test and Tuckey-Cramer correction. (e) Evolution (in weeks) of rates at which Mk-Yg performed reach movements after SCI (black), compared to the performances before injury (gray). (f) Evolution (in weeks) of rates at which Mk-Yg performed grasp movements after SCI (black), compared to the performances before injury (gray). (g) Evolution (in weeks) of rates at which Mk-Yg performed pull movements after SCI (black), compared to the performances before injury (gray). (h) Evolution (in days) of pull force after SCI without stimulation for Mk-Yg. Values are plotted as the mean ± STD. (from left to right, n = 35, 23, 14, 20, independent samples). Statistical analysis was carried out with two-sided Wilcoxon Ranksum test and Tuckey-Cramer correction.

Source data

Extended Data Fig. 8 Effect of stimulation duration and timing.

(a) Bar plots report the rate of successful movements after SCI, without stimulation (black), with continuous stimulation (gray) and with phase-dependent stimulation (blue or yellow) for Mk-Br and Mk-Yg. Data are presented as mean ± STD and normalized on the mean value in stimulation condition. Significance evaluated by estimating two side residuals via Bootstrap. (b) Left: wrist frontal displacement in trials in which pull stimulation was erroneously triggered during reach (gray and yellow), compared to trials in which pull stimulation was not delivered (black, solid line represents the mean and shaded area represents the SEM). Yellow bullets highlight the instant at which stimulation was delivered: yellow lines highlight the trajectories during and after stimulation. Middle: barplot of the length of the reach movement when pull stimulation was erroneously delivered (n = 4) and when pull stimulation was not delivered (n = 9). Data are presented as mean ± STD. Statistics performed with two-sided Wilcoxon Ranksum test. Right: stick diagram of arm kinematics during reach without (black) and with (yellow) erroneous pull stimulation.

Source data

Supplementary information

Supplementary Information

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Supplementary Video 1

Single-joint movements elicited by pulse-trains of EES at different segmental locations. Shoulder abduction: stimulation at C5; elbow extension: stimulation at C7; finger flexion: stimulation at T1; reach, grasp and pull sequence: cascade stimulation at C7, T1 and C5.

Supplementary Video 2

Effects of EES on reach movement performance on Mk-Sa. Top left, lateral vision of the animal performing the task; bottom left, delivered stimulation pulses; top right, electromyographic activity from deltoid, biceps and triceps muscles; bottom right, neural activity from M1 and PMd cortex.

Supplementary Video 3

Effects of brain-controlled EES on reach and pull movement performance on Mk-Br. Top left, lateral vision of the animal performing the task; middle left, delivered stimulation pulses; bottom left, pulling force applied on the robot end effector; top right, neural activity from S1, M1 and PMd cortex; bottom right, electromyographic activity from deltoid, flexor carpi radialis and abductor pollicis.

Supplementary Video 4

Effects of EES on pull movement performance on Mk-Yg. Top left, lateral vision of the animal performing the task; middle left, delivered stimulation pulses; bottom left, pulling force applied on the robot end effector; top right, neural activity from S1, M1 and PMd cortex; bottom right, electromyographic activity from biceps, triceps, extensor digitorium communis and flexor digitorium superficialis.

Supplementary Video 5

Effects of an EES burst optimized to recover pull, delivered during a reach movement on Mk-Yg. Lateral view of the animal performing the task.

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Barra, B., Conti, S., Perich, M.G. et al. Epidural electrical stimulation of the cervical dorsal roots restores voluntary upper limb control in paralyzed monkeys. Nat Neurosci 25, 924–934 (2022). https://doi.org/10.1038/s41593-022-01106-5

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