Activity-dependent spinal cord neuromodulation rapidly restores trunk and leg motor functions after complete paralysis.

Humans Leg Paralysis / rehabilitation Spinal Cord / physiology Spinal Cord Injuries / rehabilitation Spinal Cord Stimulation Walking / physiology

Journal

Nature medicine

ISSN: 1546-170X

Titre abrégé: Nat Med

Pays: United States

ID NLM: 9502015

Informations de publication

Date de publication:
02 2022

Historique:

received: 25 05 2021

accepted: 16 12 2021

pubmed: 9 2 2022

medline: 20 4 2022

entrez: 8 2 2022

Statut: ppublish

Résumé

Epidural electrical stimulation (EES) targeting the dorsal roots of lumbosacral segments restores walking in people with spinal cord injury (SCI). However, EES is delivered with multielectrode paddle leads that were originally designed to target the dorsal column of the spinal cord. Here, we hypothesized that an arrangement of electrodes targeting the ensemble of dorsal roots involved in leg and trunk movements would result in superior efficacy, restoring more diverse motor activities after the most severe SCI. To test this hypothesis, we established a computational framework that informed the optimal arrangement of electrodes on a new paddle lead and guided its neurosurgical positioning. We also developed software supporting the rapid configuration of activity-specific stimulation programs that reproduced the natural activation of motor neurons underlying each activity. We tested these neurotechnologies in three individuals with complete sensorimotor paralysis as part of an ongoing clinical trial ( www.clinicaltrials.gov identifier NCT02936453). Within a single day, activity-specific stimulation programs enabled these three individuals to stand, walk, cycle, swim and control trunk movements. Neurorehabilitation mediated sufficient improvement to restore these activities in community settings, opening a realistic path to support everyday mobility with EES in people with SCI.

Identifiants

DOI: 10.1038/s41591-021-01663-5 PMID: 35132264

pubmed: 35132264

doi: 10.1038/s41591-021-01663-5

pii: 10.1038/s41591-021-01663-5

doi:

Banques de données

ClinicalTrials.gov

['NCT02936453']

Types de publication

Clinical Trial Journal Article

Langues

eng

Sous-ensembles de citation

Pagination

260-271

Commentaires et corrections

Type : CommentIn

Informations de copyright

Références

Ichiyama, R. M. et al. Step training reinforces specific spinal locomotor circuitry in adult spinal rats. J. Neurosci. 28, 7370–7375 (2008).

pubmed: 18632941 pmcid: 6670403 doi: 10.1523/JNEUROSCI.1881-08.2008

Courtine, G. et al. Transformation of nonfunctional spinal circuits into functional states after the loss of brain input. Nat. Neurosci. 12, 1333–1342 (2009).

pubmed: 19767747 pmcid: 2828944 doi: 10.1038/nn.2401

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

pubmed: 25253676 doi: 10.1126/scitranslmed.3008325

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

pubmed: 26779815 pmcid: 5061079 doi: 10.1038/nm.4025

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

pubmed: 22654062 doi: 10.1126/science.1217416

Asboth, L. et al. Cortico–reticulo–spinal circuit reorganization enables functional recovery after severe spinal cord contusion. Nat. Neurosci. 21, 576–588 (2018).

pubmed: 29556028 doi: 10.1038/s41593-018-0093-5

Gill, M. L. et al. Neuromodulation of lumbosacral spinal networks enables independent stepping after complete paraplegia. Nat. Med. 24, 1677–1682 (2018).

pubmed: 30250140 doi: 10.1038/s41591-018-0175-7

Wagner, F. B. et al. Targeted neurotechnology restores walking in humans with spinal cord injury. Nature 563, 65–71 (2018).

pubmed: 30382197 doi: 10.1038/s41586-018-0649-2

Harkema, S. et al. Effect of epidural stimulation of the lumbosacral spinal cord on voluntary movement, standing, and assisted stepping after motor complete paraplegia: a case study. Lancet 377, 1938–1947 (2011).

pubmed: 21601270 pmcid: 3154251 doi: 10.1016/S0140-6736(11)60547-3

Angeli, C. A. et al. Recovery of over-ground walking after chronic motor complete spinal cord injury. N. Engl. J. Med. 379, 1244–1250 (2018).

pubmed: 30247091 doi: 10.1056/NEJMoa1803588

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

pubmed: 25582580 pmcid: 4408427 doi: 10.1093/brain/awu372

Formento, E. et al. Electrical spinal cord stimulation must preserve proprioception to enable locomotion in humans with spinal cord injury. Nat. Neurosci. 21, 1728–1741 (2018).

pubmed: 30382196 pmcid: 6268129 doi: 10.1038/s41593-018-0262-6

Herman, R., He, J., D’Luzansky, S., Willis, W. & Dilli, S. Spinal cord stimulation facilitates functional walking in a chronic, incomplete spinal cord injured. Spinal Cord 40, 65–68 (2002).

pubmed: 11926417 doi: 10.1038/sj.sc.3101263

Barolat, G., Myklebust, J. B. & Wenninger, W. Enhancement of voluntary motor function following spinal cord stimulation: case study. Appl. Neurophysiol. 49, 307–314 (1986).

pubmed: 3499118

Dimitrijevic, M. R., Gerasimenko, Y. & Pinter, M. M. Evidence for a spinal central pattern generator in humans. Ann. N Y Acad. Sci. 860, 360–376 (1998).

pubmed: 9928325 doi: 10.1111/j.1749-6632.1998.tb09062.x

& Darrow, D. et al. Epidural spinal cord stimulation facilitates immediate restoration of dormant motor and autonomic supraspinal pathways after chronic neurologically complete spinal cord injury. J. Neurotrauma 36, 2325–2336 (2019).

pubmed: 30667299 pmcid: 6648195 doi: 10.1089/neu.2018.6006

Gerasimenko, Y. P. et al. Spinal cord reflexes induced by epidural spinal cord stimulation in normal awake rats. J. Neurosci. Methods 157, 253–263 (2006).

pubmed: 16764937 doi: 10.1016/j.jneumeth.2006.05.004

Rattay, F. et al. Mechanisms of electrical stimulation with neural prostheses. Neuromodulation 6, 42–56 (2003).

pubmed: 22150913 doi: 10.1046/j.1525-1403.2003.03006.x

Capogrosso, M. et al. A computational model for epidural electrical stimulation of spinal sensorimotor circuits. J. Neurosci. 33, 19326–19340 (2013).

pubmed: 24305828 pmcid: 6618777 doi: 10.1523/JNEUROSCI.1688-13.2013

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

pubmed: 26853304 doi: 10.1016/j.neuron.2016.01.009

Capogrosso, M. et al. A brain–spine interface alleviating gait deficits after spinal cord injury in primates. Nature 539, 284–288 (2016).

pubmed: 27830790 pmcid: 5108412 doi: 10.1038/nature20118

Minev, I. R. et al. Electronic dura mater for long-term multimodal neural interfaces. Science 347, 159–163 (2015).

pubmed: 25574019 doi: 10.1126/science.1260318

Capogrosso, M. et al. Configuration of electrical spinal cord stimulation through real-time processing of gait kinematics. Nat. Protoc. 13, 2031–2061 (2018).

pubmed: 30190556 doi: 10.1038/s41596-018-0030-9

Yakovenko, S., Mushahwar, V., VanderHorst, V., Holstege, G. & Prochazka, A. Spatiotemporal activation of lumbosacral motoneurons in the locomotor step cycle. J. Neurophysiol. 87, 1542–1553 (2002).

pubmed: 11877525 doi: 10.1152/jn.00479.2001

Cappellini, G., Ivanenko, Y. P., Dominici, N., Poppele, R. E. & Lacquaniti, F. Migration of motor pool activity in the spinal cord reflects body mechanics in human locomotion. J. Neurophysiol. 104, 3064–3073 (2010).

pubmed: 20881204 doi: 10.1152/jn.00318.2010

Molnar, G. & Barolat, G. Principles of cord activation during spinal cord stimulation. Neuromodulation 17, 12–21 (2014).

pubmed: 24974772 doi: 10.1111/ner.12171

Minassian, K., Hofstoetter, U., Tansey, K. & Mayr, W. Neuromodulation of lower limb motor control in restorative neurology. Clin. Neurol. Neurosurg. 114, 489–497 (2012).

pubmed: 22464657 pmcid: 3341569 doi: 10.1016/j.clineuro.2012.03.013

Moraud, E. M. et al. Closed-loop control of trunk posture improves locomotion through the regulation of leg proprioceptive feedback after spinal cord injury. Sci. Rep. 8, 76 (2018).

pubmed: 29311614 pmcid: 5758718 doi: 10.1038/s41598-017-18293-y

Gill, M. et al. Epidural electrical stimulation of the lumbosacral spinal cord improves trunk stability during seated reaching in two humans with severe thoracic spinal cord injury. Front. Syst. Neurosci. 14, 79 (2020).

pubmed: 33328910 pmcid: 7710539 doi: 10.3389/fnsys.2020.569337

Greiner, N. et al. Recruitment of upper-limb motoneurons with epidural electrical stimulation of the cervical spinal cord. Nat. Commun. 12, 435 (2021).

pubmed: 33469022 pmcid: 7815834 doi: 10.1038/s41467-020-20703-1

Neufeld, E., Szczerba, D., Chavannes, N. & Kuster, N. A novel medical image data-based multi-physics simulation platform for computational life sciences. Interface Focus 3, 20120058 (2013).

pubmed: 24427518 pmcid: 3638470 doi: 10.1098/rsfs.2012.0058

Kinany, N., Pirondini, E., Micera, S. & Ville, D. V. D. Dynamic functional connectivity of resting-state spinal cord fMRI reveals fine-grained intrinsic architecture. Neuron 108, 424–435 (2020).

doi: 10.1016/j.neuron.2020.07.024 pubmed: 32910894

Landelle, C. et al. Functional brain changes in the elderly for the perception of hand movements: a greater impairment occurs in proprioception than touch. Neuroimage 220, 117056 (2020).

doi: 10.1016/j.neuroimage.2020.117056 pubmed: 32562781

Courtine, G., Nunzio, A. M. D., Schmid, M., Beretta, M. V. & Schieppati, M. Stance- and locomotion-dependent processing of vibration-induced proprioceptive inflow from multiple muscles in humans. J. Neurophysiol. 97, 772–779 (2007).

doi: 10.1152/jn.00764.2006 pubmed: 17065250

Roll, J. P., Vedel, J. P. & Ribot, E. Alteration of proprioceptive messages induced by tendon vibration in man: a microneurographic study. Exp. Brain Res. 76, 213–222 (1989).

doi: 10.1007/BF00253639 pubmed: 2753103

Pierrot-Deseilligny, E. & Burke, D. The Circuitry of the Human Spinal Cord (Cambridge University Press, 2005).

Lempka, S. F. et al. Patient‐specific analysis of neural activation during spinal cord stimulation for pain. Neuromodulation 23, 572–581 (2020).

doi: 10.1111/ner.13037 pubmed: 31464040

Mignardot, J.-B. et al. A multidirectional gravity-assist algorithm that enhances locomotor control in patients with stroke or spinal cord injury. Sci. Transl. Med. 9, eaah3621 (2017).

doi: 10.1126/scitranslmed.aah3621 pubmed: 28724575

Shokur, S., Mazzoni, A., Schiavone, G., Weber, D. J. & Micera, S. A modular strategy for next-generation upper-limb sensory-motor neuroprostheses. Med 2, 912–937 (2021).

doi: 10.1016/j.medj.2021.05.002

Edgerton, V. R. & Harkema, S. Epidural stimulation of the spinal cord in spinal cord injury: current status and future challenges. Expert Rev. Neurother. 11, 1351–1353 (2011).

pubmed: 21955190 pmcid: 3361963 doi: 10.1586/ern.11.129

Courtine, G. & Sofroniew, M. V. Spinal cord repair: advances in biology and technology. Nat. Med. 25, 898–908 (2019).

pubmed: 31160817 doi: 10.1038/s41591-019-0475-6

Morse, L. R. et al. Meeting proceedings for SCI 2020: launching a decade of disruption in spinal cord injury research. J. Neurotrauma 38, 1251–1266 (2021).

pubmed: 33353467 doi: 10.1089/neu.2020.7174

Schiavone, G. et al. Soft, implantable bioelectronic interfaces for translational research. Adv. Mater. 32, 1906512 (2020).

doi: 10.1002/adma.201906512

Barra, B. et al. Epidural electrical stimulation of the cervical dorsal roots restores voluntary arm control in paralyzed monkeys. Preprint at bioRxiv https://doi.org/10.1101/2020.11.13.379750 (2021).

Bonizzato, M. et al. Brain-controlled modulation of spinal circuits improves recovery from spinal cord injury. Nat. Commun. 9, 3015 (2018).

pubmed: 30068906 pmcid: 6070513 doi: 10.1038/s41467-018-05282-6

Benabid, A. L. et al. An exoskeleton controlled by an epidural wireless brain–machine interface in a tetraplegic patient: a proof-of-concept demonstration. Lancet Neurol. 18, 1112–1122 (2019).

pubmed: 31587955 doi: 10.1016/S1474-4422(19)30321-7

Chen, C.-L. et al. The relationship between sitting stability and functional performance in patients with paraplegia. Arch. Phys. Med. Rehab 84, 1276–1281 (2003).

doi: 10.1016/S0003-9993(03)00200-4

Anderson, K. D. Targeting recovery: priorities of the spinal cord-injured population. J. Neurotrauma 21, 1371–1383 (2004).

pubmed: 15672628 doi: 10.1089/neu.2004.21.1371

Herrity, A. N., Williams, C. S., Angeli, C. A., Harkema, S. J. & Hubscher, C. H. Lumbosacral spinal cord epidural stimulation improves voiding function after human spinal cord injury. Sci. Rep. 8, 8688 (2018).

pubmed: 29875362 pmcid: 5989228 doi: 10.1038/s41598-018-26602-2

Squair, J. W. et al. Neuroprosthetic baroreflex controls haemodynamics after spinal cord injury. Nature 590, 308–314 (2021).

pubmed: 33505019 doi: 10.1038/s41586-020-03180-w

Ditterline, B. E. L. et al. Beneficial cardiac structural and functional adaptations after lumbosacral spinal cord epidural stimulation and task-specific interventions: a pilot study. Front Neurosci. 14, 554018 (2020).

doi: 10.3389/fnins.2020.554018

Soloukey, S. et al. The dorsal root ganglion as a novel neuromodulatory target to evoke strong and reproducible motor responses in chronic motor complete spinal cord injury: a case series of five patients. Neuromodulation 24, 779–793 (2021).

pubmed: 32706445 doi: 10.1111/ner.13235

Kirshblum, S. & Waring, W. Updates of the International Standards for Neurologic Classification of Spinal Cord Injury. Phys. Med. Rehabil. Clin. N. Am. 25, 505–517 (2014).

pubmed: 25064785 doi: 10.1016/j.pmr.2014.04.001

Roll, J. P. & Vedel, J. P. Kinaesthetic role of muscle afferents in man, studied by tendon vibration and microneurography. Exp. Brain Res. 47, 177–190 (1982).

pubmed: 6214420 doi: 10.1007/BF00239377

Landelle, C., Ahmadi, A. E. & Kavounoudias, A. Age-related impairment of hand movement perception based on muscle proprioception and touch. Neuroscience 381, 91–104 (2018).

pubmed: 29684506 doi: 10.1016/j.neuroscience.2018.04.015

Kavounoudias, A. et al. Proprio-tactile integration for kinesthetic perception: an fMRI study. Neuropsychologia 46, 567–575 (2008).

pubmed: 18023825 doi: 10.1016/j.neuropsychologia.2007.10.002

Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W. & Smith, S. M. FSL. Neuroimage 62, 782–790 (2012).

pubmed: 21979382 doi: 10.1016/j.neuroimage.2011.09.015

Leener, B. D. et al. SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data. Neuroimage 145, 24–43 (2017).

pubmed: 27720818 doi: 10.1016/j.neuroimage.2016.10.009

Jenkinson, M., Bannister, P., Brady, M. & Smith, S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage 17, 825–841 (2002).

pubmed: 12377157

Gros, C. et al. Automatic spinal cord localization, robust to MRI contrasts using global curve optimization. Med. Image Anal. 44, 215–227 (2018).

pubmed: 29288983 doi: 10.1016/j.media.2017.12.001

Cohen-Adad, J. et al. Venous effect in spinal cord fMRI: insights from intrinsic optical imaging and laser speckle. Neuroimage 47, S186 (2009).

doi: 10.1016/S1053-8119(09)72063-4

Power, J. D. et al. Methods to detect, characterize, and remove motion artifact in resting state fMRI. Neuroimage 84, 320–341 (2014).

pubmed: 23994314 doi: 10.1016/j.neuroimage.2013.08.048

Gros, C. et al. Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks. Neuroimage 184, 901–915 (2019).

pubmed: 30300751 doi: 10.1016/j.neuroimage.2018.09.081

Eippert, F., Kong, Y., Jenkinson, M., Tracey, I. & Brooks, J. C. W. Denoising spinal cord fMRI data: approaches to acquisition and analysis. Neuroimage 154, 255–266 (2017).

pubmed: 27693613 doi: 10.1016/j.neuroimage.2016.09.065

Brooks, J. C. W. et al. Physiological noise modelling for spinal functional magnetic resonance imaging studies. Neuroimage 39, 680–692 (2008).

pubmed: 17950627 doi: 10.1016/j.neuroimage.2007.09.018

Kong, Y., Jenkinson, M., Andersson, J., Tracey, I. & Brooks, J. C. W. Assessment of physiological noise modelling methods for functional imaging of the spinal cord. Neuroimage 60, 1538–1549 (2012).

pubmed: 22178812 doi: 10.1016/j.neuroimage.2011.11.077

Behzadi, Y., Restom, K., Liau, J. & Liu, T. T. A component-based noise correction method (CompCor) for BOLD and perfusion-based fMRI. Neuroimage 37, 90–101 (2007).

doi: 10.1016/j.neuroimage.2007.04.042 pubmed: 17560126

Kasper, L. et al. The PhysIO Toolbox for modeling physiological noise in fMRI data. J. Neurosci. Meth 276, 56–72 (2017).

doi: 10.1016/j.jneumeth.2016.10.019

Woolrich, M. W., Ripley, B. D., Brady, M. & Smith, S. M. Temporal autocorrelation in univariate linear modeling of FMRI data. Neuroimage 14, 1370–1386 (2001).

pubmed: 11707093 doi: 10.1006/nimg.2001.0931

Woolrich, M. W., Behrens, T. E. J. & Smith, S. M. Constrained linear basis sets for HRF modelling using variational Bayes. Neuroimage 21, 1748–1761 (2004).

pubmed: 15050595 doi: 10.1016/j.neuroimage.2003.12.024

Gomez‐Perez, S. L. et al. Measuring abdominal circumference and skeletal muscle from a single cross‐sectional computed tomography image. Jpen-parenter. Enter. 40, 308–318 (2016).

doi: 10.1177/0148607115604149

Schirmer, C. M. et al. Heuristic map of myotomal innervation in humans using direct intraoperative nerve root stimulation. J. Neurosurg. Spine 15, 64–70 (2011).

doi: 10.3171/2011.2.SPINE1068 pubmed: 21476796