The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
A brain–spine interface alleviating gait deficits after spinal cord injury in primates
Open accessAbstract
Spinal cord injury disrupts the communication between the brain and the spinal circuits that orchestrate movement. To bypass the lesion, brain-computer interfaces have directly linked cortical activity to electrical stimulation of muscles, and have thus restored grasping abilities after hand paralysis. Theoretically, this strategy could also restore control over leg muscle activity for walking. However, replicating the complex sequence of individual muscle activation patterns underlying natural and adaptive locomotor movements poses formidable conceptual and technological challenges. 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 locomotion. 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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“In turn, recruiting these dorsal root entry zones with preprogrammed spatiotemporal sequences replicates the physiological activation of leg motor pools underlying standing and walking4,5,11,13,14.”
From Walking naturally after spinal cord injury using a brain–spine interface (2023) · cites this paper as [13]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Reach and grasp by people with tetraplegia using a neurally controlled robotic arm
Hochberg, L. R., Bacher, D., Jarosiewicz, B., Masse, N. Y., Simeral, J. D., Vogel, J., Haddadin, S., Liu, J., Cash, S. S., van der Smagt, P., et al. (2012) · Nature · doi:10.1038/nature11076 · Cited by 2,719
High-performance neuroprosthetic control by an individual with tetraplegia
Collinger, J. L., Wodlinger, B., Downey, J. E., Wang, W., Tyler-Kabara, E. C., Weber, D. J., McMorland, A. J., Velliste, M., Boninger, M. L., & Schwartz, A. B. (2013) · The Lancet · doi:10.1016/s0140-6736(12)61816-9 · Cited by 1,848
Descending Pathways in Motor Control
Lemon, R. N. (2008) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.31.060407.125547 · Cited by 1,599
Flexion‐reflex of the limb, crossed extension‐reflex, and reflex stepping and standing
Sherrington, C. (1910) · The Journal of Physiology · doi:10.1113/jphysiol.1910.sp001362 · Cited by 1,336
Restoring cortical control of functional movement in a human with quadriplegia
Bouton, C. E., Shaikhouni, A., Annetta, N. V., Bockbrader, M. A., Friedenberg, D. A., Nielson, D. M., Sharma, G., Sederberg, P. B., Glenn, B. C., Mysiw, W. J., et al. (2016) · Nature · doi:10.1038/nature17435 · Cited by 924
Restoring Voluntary Control of Locomotion after Paralyzing Spinal Cord Injury
van den Brand, R., Heutschi, J., Barraud, Q., DiGiovanna, J., Bartholdi, K., Huerlimann, M., Friedli, L., Vollenweider, I., Moraud, E. M., Duis, S., et al. (2012) · Science · doi:10.1126/science.1217416 · Cited by 767
Self-citationAngeli, C. A., Edgerton, V. R., Gerasimenko, Y. P., & Harkema, S. J. (2014) · Brain · doi:10.1093/brain/awu038 · Cited by 750
Decoding the organization of spinal circuits that control locomotion
Kiehn, O. (2016) · Nature Reviews Neuroscience · doi:10.1038/nrn.2016.9 · Cited by 742
Decoding motor imagery from the posterior parietal cortex of a tetraplegic human
Aflalo, T., Kellis, S., Klaes, C., Lee, B., Shi, Y., Pejsa, K., Shanfield, K., Hayes-Jackson, S., Aisen, M., Heck, C., et al. (2015) · Science · doi:10.1126/science.aaa5417 · Cited by 649
Restoration of grasp following paralysis through brain-controlled stimulation of muscles
Ethier, C., Oby, E. R., Bauman, M. J., & Miller, L. E. (2012) · Nature · doi:10.1038/nature10987 · Cited by 485
Flagged first, then by citations
Research works printed but not linked: 2
- Marieb, E. N. Human Anatomy and Physiology 6th edn (Pearson Education, 2003)
- Kuypers, H. G. J. M. in Comprehensive Physiology Ch. 3 (John Wiley & Sons, 2011)
Cited by
Sorted by citations
Items 101–200 of 634
Shapkova, E. Y., Pismennaya, E. V., Емельянников, Д. В., & Ivanenko, Y. P. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00416 · Cited by 72
Eisdorfer, J. T., Smit, R. D., Keefe, K. M., Lemay, M. A., Smith, G. M., & Spence, A. J. (2020) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2020.00163 · Cited by 65
Switchless Multiplexing of Graphene Active Sensor Arrays for Brain Mapping
Garcia‐Cortadella, R., Schaefer, N., Cisneros-Fernández, J., Ré, L., Illa, X., Schwesig, G., Moya, A., Santiago, S., Guirado, G., Villa, R., et al. (2020) · Nano Letters · doi:10.1021/acs.nanolett.0c00467 · Cited by 67
Avila-Tomás, J. F., Mayer, M. Á., & Varela, V. J. Q. (2020) · Atención Primaria · doi:10.1016/j.aprim.2020.04.013 · Cited by 95
Lai, B., Zeng, X., Han, W., Che, M., Ding, Y., Li, G., & Zeng, Y. (2021) · Biomaterials · doi:10.1016/j.biomaterials.2021.121211 · Cited by 66
Bonizzato, M., James, N. D., Pidpruzhnykova, G., Pavlova, N., Shkorbatova, P. Y., Baud, L., Martinez‐Gonzalez, C., Squair, J. W., DiGiovanna, J., Barraud, Q., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-22137-9 · Cited by 64
Self-citationBrain-Computer-Spinal Interface Restores Upper Limb Function After Spinal Cord Injury
Samejima, S., Khorasani, A., Ranganathan, V. N., Nakahara, J., Tolley, N. M., Boissenin, A., Shalchyan, V., Daliri, M. R., Smith, J. R., & Moritz, C. T. (2021) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2021.3090269 · Cited by 69
Surgical Neurostimulation for Spinal Cord Injury
Chari, A., Hentall, I. D., Papadopoulos, M. C., & Pereira, E. A. C. (2017) · Brain Sciences · doi:10.3390/brainsci7020018 · Cited by 63
Neurodegenerative disorders management: state-of-art and prospects of nano-biotechnology
Kumar, R., Aadil, K. R., Mondal, K., Mishra, Y. K., Oupický, D., Ramakrishna, S., & Kaushik, A. K. (2021) · Critical Reviews in Biotechnology · doi:10.1080/07388551.2021.1993126 · Cited by 64
Rao, R. P. N. (2019) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2019.03.008 · Cited by 63
Brain–Machine Interface Control Algorithms
Shanechi, M. M. (2016) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2016.2639501 · Cited by 61
Bioelectronic medicine: updates, challenges and paths forward
Pavlov, V. A., & Tracey, K. J. (2019) · Bioelectronic Medicine · doi:10.1186/s42234-019-0018-y · Cited by 63
Mishra, A. M., Pal, A., Gupta, D., & Carmel, J. B. (2017) · The Journal of Physiology · doi:10.1113/jp274663 · Cited by 59
Li, C., Un, K.-F., Mak, P., Chen, Y., Muñoz‐Ferreras, J., Yang, Z., & Gómez‐García, R. (2018) · IEEE Journal on Emerging and Selected Topics in Circuits and Systems · doi:10.1109/jetcas.2018.2822684 · Cited by 62
A review of emerging neuroprotective and neuroregenerative therapies in traumatic spinal cord injury
Hejrati, N., & Fehlings, M. G. (2021) · Current Opinion in Pharmacology · doi:10.1016/j.coph.2021.08.009 · Cited by 61
Cutrone, A., & Micera, S. (2019) · Advanced Healthcare Materials · doi:10.1002/adhm.201801345 · Cited by 58
Self-citationA shape-memory and spiral light-emitting device for precise multisite stimulation of nerve bundles
Zheng, H., Zhang, Z., Jiang, S., Yan, B., Shi, X., Xie, Y., Huang, X., Yu, Z., Liu, H., Weng, S., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-10418-3 · Cited by 58
Electrical Stimulation as a Tool to Promote Plasticity of the Injured Spinal Cord
Jack, A. S., Hurd, C., Martin, J. H., & Fouad, K. (2020) · Journal of Neurotrauma · doi:10.1089/neu.2020.7033 · Cited by 58
Zhou, K., Wei, W., Yang, D., Zhang, H., Yang, W., Zhang, Y., Nie, Y., Hao, M., Wang, P., Ruan, H., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-44898-9 · Cited by 58
Seáñez, I., & Capogrosso, M. (2021) · Bioelectronic Medicine · doi:10.1186/s42234-021-00077-5 · Cited by 58
Self-citationTargeting Sensory and Motor Integration for Recovery of Movement After CNS Injury
Asan, A. S., McIntosh, J. R., & Carmel, J. B. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.791824 · Cited by 71
Hypothalamic deep brain stimulation augments walking after spinal cord injury
Cho, N., Squair, J. W., Aureli, V., James, N. D., Bole-Feysot, L., Dewany, I., Hankov, N., Baud, L., Leonhartsberger, A., Sveistyte, K., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-03306-x · Cited by 62
Self-citationBonizzato, M., & Martinez, M. (2021) · Science Translational Medicine · doi:10.1126/scitranslmed.abb4422 · Cited by 57
Artificial Intelligence for Metaverse: A Framework
Guo, Y., Yu, T., Wu, J., Wang, Y., Wan, S., Zheng, J., Fang, L., & Dai, Q. (2022) · CAAI Artificial Intelligence Research · doi:10.26599/air.2022.9150004 · Cited by 66
Recent advances in the application of MXenes for neural tissue engineering and regeneration
Liao, M., Cui, Q., Hu, Y., Xing, J., Wu, D., Zheng, S., Zhao, Y., Yu, Y., Sun, J., & Chai, R. (2023) · Neural Regeneration Research · doi:10.4103/1673-5374.379037 · Cited by 58
Therapeutic Stimulation for Restoration of Function After Spinal Cord Injury
Ievins, A., & Moritz, C. T. (2017) · Physiology · doi:10.1152/physiol.00010.2017 · Cited by 58
Online EEG artifact removal for BCI applications by adaptive spatial filtering
Guarnieri, R., Marino, M., Barban, F., Ganzetti, M., & Mantini, D. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aacfdf · Cited by 53
Optimized Real-Time Biomimetic Neural Network on FPGA for Bio-hybridization
Khoyratee, F., Grassia, F., Saïghi, S., & Levi, T. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00377 · Cited by 53
Insausti-Delgado, A., López-Larraz, E., Omedes, J., & Ramos-Murguialday, A. (2020) · bioRxiv · doi:10.3389/fnins.2020.593360 · Cited by 52
A Review of Functional Restoration From Spinal Cord Stimulation in Patients With Spinal Cord Injury
Lin, A., Shaaya, E. A., Calvert, J. S., Parker, S. R., Borton, D. A., & Fridley, J. (2022) · Neurospine · doi:10.14245/ns.2244652.326 · Cited by 52
Self-citationWater-soluble conjugated polymers for bioelectronic systems
Wang, Z., Lin, H., Zhang, M., Yu, W. B., Zhu, C., Wang, P., Huang, Y., Lv, F., Bai, H., & Wang, S. (2023) · Materials Horizons · doi:10.1039/d2mh01520j · Cited by 52
Human Locomotion in Hypogravity: From Basic Research to Clinical Applications
Lacquaniti, F., Ivanenko, Y. P., Labini, F. S., Scaleia, V. L., Scaleia, B. L., Willems, P. A., & Zago, M. (2017) · Frontiers in Physiology · doi:10.3389/fphys.2017.00893 · Cited by 50
Invasive Brain Computer Interface for Motor Restoration in Spinal Cord Injury: A Systematic Review
Levett, J. J., Elkaim, L. M., Niazi, F., Weber, M. H., Iorio‐Morin, C., Bonizzato, M., & Weil, A. G. (2023) · Neuromodulation Technology at the Neural Interface · doi:10.1016/j.neurom.2023.10.006 · Cited by 56
Rehabilitative Training in Animal Models of Spinal Cord Injury
Espin, A. T., Beaudry, E., Fenrich, K. K., & Fouad, K. (2018) · Journal of Neurotrauma · doi:10.1089/neu.2018.5906 · Cited by 48
Lee, S., & Lee, C. (2018) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2018.05.004 · Cited by 48
Won, C., Jeong, U., Lee, S., Lee, M., Kwon, C., Cho, S., Yoon, K., Lee, S.-M., Chun, D. W., Cho, I., et al. (2022) · Advanced Functional Materials · doi:10.1002/adfm.202205145 · Cited by 48
Capogrosso, M., Gandar, J., Greiner, N., Moraud, E. M., Wenger, N., Shkorbatova, P. Y., Евгеньевич, М. П., Minev, I. R., Lacour, S. P., & Courtine, G. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aaa87a · Cited by 48
Self-citationRejc, E., & Angeli, C. (2019) · Physical Medicine and Rehabilitation Clinics of North America · doi:10.1016/j.pmr.2018.12.009 · Cited by 45
Spinal Cord Stimulation for Freezing of Gait: From Bench to Bedside
Fonoff, E. T., de Lima‐Pardini, A. C., Coelho, D. B., de Mônaco, B. A., Machado, B. S., Souza, C. P., Ghilardi, M. G. D. S., & Hamani, C. (2019) · Frontiers in Neurology · doi:10.3389/fneur.2019.00905 · Cited by 47
Developing Collaborative Platforms to Advance Neurotechnology and Its Translation
Borton, D. A., Dawes, H. E., Worrell, G. A., Starr, P. A., & Denison, T. (2020) · Neuron · doi:10.1016/j.neuron.2020.10.001 · Cited by 54
Self-citationKo, W. K. D., & Bézard, E. (2017) · Experimental Neurology · doi:10.1016/j.expneurol.2017.07.020 · Cited by 48
Self-citationWoodington, B. J., Jiang, L., Carnicer‐Lombarte, A., Güemes, A., Naegele, T. E., Hilton, S., Hadwe, S. E., Trivedi, R. A., Malliaras, G. G., & Barone, D. G. (2024) · Science Advances · doi:10.1126/sciadv.adl1230 · Cited by 49
Li, G., Che, M., Zeng, X., Qiu, X., Feng, B., Lai, B., Shen, H., Ling, E., & Zeng, Y. (2018) · Journal of Biomedical Materials Research Part A · doi:10.1002/jbm.a.36414 · Cited by 46
Motor cortical dynamics are shaped by multiple distinct subspaces during naturalistic behaviorPreprint
Perich, M. G., Conti, S., Badi, M., Bogaard, A. R., Barra, B., Rajan, K., Bloch, J., Courtine, G., Micera, S., Capogrosso, M., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.07.30.228767 · Cited by 58
Self-citationMariello, M., & Proctor, C. M. (2024) · Advanced Materials Technologies · doi:10.1002/admt.202400797 · Cited by 50
Yao, G., Gan, X., & Lin, Y. (2024) · 中国科学通报:英文版 · doi:10.1016/j.scib.2024.05.012 · Cited by 44
Hu, X.-C., Hu, X., Yang, Y.-N., Kang, X.-W., Wang, Y., Ma, B., & Xing, S. (2020) · Neural Regeneration Research · doi:10.4103/1673-5374.293130 · Cited by 44
Leaving flatland: Advances in 3D behavioral measurement
Marshall, J. D., Li, T., Wu, J. H., & Dunn, T. (2022) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2022.02.002 · Cited by 43
Is Graphene Shortening the Path toward Spinal Cord Regeneration?
Girão, A. F., Serrano, M. C., Completo, A., & Marques, P. A. A. P. (2022) · ACS Nano · doi:10.1021/acsnano.2c04756 · Cited by 44
Digital implementation of Hodgkin–Huxley neuron model for neurological diseases studies
Levi, T., Khoyratee, F., Saïghi, S., & Ikeuchi, Y. (2017) · Artificial Life and Robotics · doi:10.1007/s10015-017-0397-7 · Cited by 44
Samejima, S., Henderson, R. P., Pradarelli, J. J., Mondello, S. E., & Moritz, C. T. (2022) · Experimental Neurology · doi:10.1016/j.expneurol.2022.114178 · Cited by 42
Leveraging neural dynamics to extend functional lifetime of brain-machine interfaces
Kao, J. C., Ryu, S. I., & Shenoy, K. V. (2017) · Scientific Reports · doi:10.1038/s41598-017-06029-x · Cited by 42
Injecting Instructions into Premotor Cortex
Mazurek, K. A., & Schieber, M. H. (2017) · Neuron · doi:10.1016/j.neuron.2017.11.006 · Cited by 42
Moraud, E. M., Zitzewitz, J. V., Miehlbradt, J., Wurth, S. M., Formento, E., DiGiovanna, J., Capogrosso, M., Courtine, G., & Micera, S. (2018) · Scientific Reports · doi:10.1038/s41598-017-18293-y · Cited by 39
Self-citationNeurophysiology and neural engineering: a review
Procházka, A. (2017) · Journal of Neurophysiology · doi:10.1152/jn.00149.2017 · Cited by 39
Progress in Brain‐Compatible Interfaces with Soft Nanomaterials
Jeong, Y., Lee, H. E., Shin, A., Kim, D., Lee, K. J., & Kim, D. (2020) · Advanced Materials · doi:10.1002/adma.201907522 · Cited by 40
Controlled Information Transfer Through An In Vivo Nervous System
Abbasi, N. A., Lafci, D., & Akan, Ö. B. (2018) · Scientific Reports · doi:10.1038/s41598-018-20725-2 · Cited by 39
Current progress of rehabilitative strategies in stem cell therapy for spinal cord injury: a review
Tashiro, S., Tsuji, O., Shinozaki, M., Shibata, T., Yoshida, T., Tomioka, Y., Unai, K., Kondo, T., Itakura, G., Kobayashi, Y., et al. (2021) · npj Regenerative Medicine · doi:10.1038/s41536-021-00191-7 · Cited by 40
Sculpting neurotransmission during synaptic development by 2D nanostructured interfaces
Pampaloni, N. P., Scaini, D., Perissinotto, F., Bosi, S., Prato, M., & Ballerini, L. (2017) · Nanomedicine Nanotechnology Biology and Medicine · doi:10.1016/j.nano.2017.01.020 · Cited by 38
Krucoff, M. O., Miller, J. P., Saxena, T. K., Bellamkonda, R., Rahimpour, S., Harward, S. C., Lad, S. P., & Turner, D. A. (2018) · Neurosurgery · doi:10.1093/neuros/nyy128 · Cited by 38
Advances in Material‐Assisted Electromagnetic Neural Stimulation
Sun, Y., Zhifeng, X., Chen, B., Zhao, Y., & Dai, J. (2024) · Advanced Materials · doi:10.1002/adma.202400346 · Cited by 38
Neurocognitive Benefits of Physiotherapy for Spinal Cord Injury
Scandola, M., Dodoni, L., Lazzeri, G., Arcangeli, C. A., Avesani, R., Moro, V., & Ionta, S. (2018) · Journal of Neurotrauma · doi:10.1089/neu.2018.6123 · Cited by 37
Zhu, B., Li, Y., Huang, F., Chen, Z., Xie, J., Ding, C., & Li, J. (2019) · Biomaterials Science · doi:10.1039/c9bm01203f · Cited by 37
From the field to the lab and back: neuroethology of primate social behavior
Testard, C., Tremblay, S., & Platt, M. L. (2021) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2021.01.005 · Cited by 40
Johnson, L. D. V., Pickard, M. R., & Johnson, W. E. B. (2021) · Biology · doi:10.3390/biology10030230 · Cited by 37
First-in-human study of epidural spinal cord stimulation in individuals with spinal muscular atrophy
Prat-Ortega, G., Ensel, S., Donadio, S., Borda, L., Boos, A., Yadav, P., Verma, N., Ho, J. C., Carranza, E., Frazier-Kim, S., et al. (2025) · Nature Medicine · doi:10.1038/s41591-024-03484-8 · Cited by 43
Self-citationDewolf, A. H., Ivanenko, Y. P., Zelik, K. E., Lacquaniti, F., & Willems, P. A. (2019) · Journal of Neurophysiology · doi:10.1152/jn.00167.2019 · Cited by 36
Now is the Critical Time for Engineered Neuroplasticity
Moritz, C. T. (2018) · Neurotherapeutics · doi:10.1007/s13311-018-0637-0 · Cited by 37
The future of upper extremity rehabilitation robotics: research and practice
Vu, P. P., Chestek, C. A., Nason, S. R., Kung, T. A., Kemp, S. W. P., & Cederna, P. S. (2020) · Muscle & Nerve · doi:10.1002/mus.26860 · Cited by 33
A computational outlook on neurostimulation
Capogrosso, M., & Lempka, S. F. (2020) · Bioelectronic Medicine · doi:10.1186/s42234-020-00047-3 · Cited by 32
Self-citationA modular strategy for next-generation upper-limb sensory-motor neuroprostheses
Shokur, S., Mazzoni, A., Schiavone, G., Weber, D. J., & Micera, S. (2021) · Med · doi:10.1016/j.medj.2021.05.002 · Cited by 35
Self-citationEditorial: Closed-Loop Systems for Next-Generation Neuroprostheses
Levi, T., Bonifazi, P., Massobrio, P., & Chiappalone, M. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00026 · Cited by 33
Chambel, S. S., & Cruz, C. D. (2023) · Neural Regeneration Research · doi:10.4103/1673-5374.373674 · Cited by 36
A stealthy neural recorder for the study of behaviour in primates
Oh, S., Jekal, J., Won, J., Lim, K. S., Jeon, C., Park, J., Yeo, H.-G., Kim, Y. G., Lee, Y. H., Ha, L. J., et al. (2024) · Nature Biomedical Engineering · doi:10.1038/s41551-024-01280-w · Cited by 35
Benatti, S., Rovere, G., Bosser, J., Montagna, F., Farella, E., Glaser, H., Schönle, P., Burger, T., Fateh, S., Huang, Q., et al. (2017) · International Workshop on Advances in Sensors and Interfaces (IWASI) · doi:10.1109/iwasi.2017.7974234 · Cited by 32
Intraoperative monitoring of neuromuscular function with soft, skin-mounted wireless devices
Liu, Y., Tian, L., Raj, M. S., Cotton, M., Ma, Y., Ma, S., McGrane, B. L., Pendharkar, A. V., Dahaleh, N., Olson, L., et al. (2018) · npj Digital Medicine · doi:10.1038/s41746-018-0023-7 · Cited by 32
Harland, B. C., Aqrawe, Z., Vomero, M., Boehler, C., Cheah, E., Raos, B. J., Asplund, M., O’Carroll, S. J., & Svirskis, D. M. (2022) · Advanced Science · doi:10.1002/advs.202105913 · Cited by 30
Wang, L., Zhao, H., Han, M. H., Yang, H., Lei, M., Wang, W., Li, K., Li, Y., Sang, Y., Xin, T., et al. (2024) · Advanced Science · doi:10.1002/advs.202307527 · Cited by 31
Neurorestorative interventions involving bioelectronic implants after spinal cord injury
Cho, N., Squair, J. W., Bloch, J., & Courtine, G. (2019) · Bioelectronic Medicine · doi:10.1186/s42234-019-0027-x · Cited by 32
Self-citationA Biohybrid Setup for Coupling Biological and Neuromorphic Neural Networks
Keren, H., Partzsch, J., Marom, S., & Mayr, C. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00432 · Cited by 30
A 300 Mbps 37 pJ/bit UWB-Based Transcutaneous Optical Biotelemetry Link
Marcellis, A. D., Stanchieri, G. D. P., Faccio, M., Palange, E., & Constandinou, T. G. (2020) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2020.2972733 · Cited by 30
Tau seeds from patients induce progressive supranuclear palsy pathology and symptoms in primates
Darricau, M., Katsinelos, T., Raschellà, F., Milekovic, T., Crochemore, L., Li, Q., Courtine, G., McEwan, W. A., Dehay, B., Bézard, E., et al. (2022) · Brain · doi:10.1093/brain/awac428 · Cited by 32
Self-citationLiang, L., Damiani, A., Brocco, M. D., Rogers, E. R., Jantz, M., Fisher, L. E., Gaunt, R. A., Capogrosso, M., Lempka, S. F., & Pirondini, E. (2022) · The Journal of Physiology · doi:10.1113/jp282884 · Cited by 30
Self-citationNicolelis, M. A. L., Alho, E. J. L., Donati, A. R. C., Yamauti, S. Y., Aratanha, M. A., Bao, G., Campos, D. S. F., Almeida, S. B., Fischer, D., & Shokur, S. (2022) · Scientific Reports · doi:10.1038/s41598-022-24864-5 · Cited by 31
Dalrymple, A. N., Everaert, D. G., Hu, D. S., & Mushahwar, V. K. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aad872 · Cited by 28
Gogeascoechea, A., Kuck, A., van Asseldonk, E. H. F., Negro, F., Buitenweg, J. R., Yavuz, U. Ş., & Sartori, M. (2020) · Frontiers in Neurology · doi:10.3389/fneur.2020.00493 · Cited by 29
Zhang, H., Liu, Y., Zhou, K., Wei, W., & Liu, Y. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.749465 · Cited by 32
Electroactive Scaffolds to Improve Neural Stem Cell Therapy for Spinal Cord Injury
Mutepfa, A. R., Hardy, J. G., & Adams, C. F. (2022) · Frontiers in Medical Technology · doi:10.3389/fmedt.2022.693438 · Cited by 29
Chandrasekaran, S., Bhagat, N. A., Ramdeo, R., Ebrahimi, S., Sharma, P., Griffin, D. G., Stein, A., Harkema, S. J., & Bouton, C. E. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1210328 · Cited by 31
Differential changes in the spinal segmental locomotor output in Hereditary Spastic Paraplegia
Martino, G., Ivanenko, Y. P., Serrao, M., Ranavolo, A., Draicchio, F., Rinaldi, M., Casali, C., & Lacquaniti, F. (2017) · Clinical Neurophysiology · doi:10.1016/j.clinph.2017.11.028 · Cited by 28
Mymou: A low-cost, wireless touchscreen system for automated training of nonhuman primates
Butler, J. L., & Kennerley, S. W. (2018) · Behavior Research Methods · doi:10.3758/s13428-018-1109-5 · Cited by 28
Gill, M. L., Linde, M. B., Hale, R. F., Lopez, C., Fautsch, K. J., Calvert, J. S., Veith, D. D., Beck, L. A., Garlanger, K. L., Sayenko, D. G., et al. (2021) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2020.590231 · Cited by 29
Liu, X., Chen, P., Ding, X., Liu, A., Li, P., Sun, C., & Guan, H. (2022) · Annals of Translational Medicine · doi:10.21037/atm-22-2858 · Cited by 33
Akan, O. B., Ramezani, H., Civas, M., Cetinkaya, O., Bilgin, B. A., & Abbasi, N. A. (2021) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2021.3056455 · Cited by 28
Kuliasha, C. A., & Judy, J. W. (2021) · Advanced Materials Technologies · doi:10.1002/admt.202100149 · Cited by 27
Lu, B., Jia, S., Wang, Z., Wu, W., Yan, L. W., Zhu, L., & Hao, D. (2022) · Nano Energy · doi:10.1016/j.nanoen.2022.108133 · Cited by 27
Li, Z., Wang, X., Zhao, Z., & Liu, Y. (2024) · Chemical Engineering Journal · doi:10.1016/j.cej.2024.152238 · Cited by 26
Distributed stimulation increases force elicited with functional electrical stimulation
Buckmire, A. J., Lockwood, D. R., Doane, C. J., & Fuglevand, A. J. (2017) · Journal of Neural Engineering · doi:10.1088/1741-2552/aa9820 · Cited by 26
Recent advances in recording and modulation technologies for next-generation neural interfaces.
Hong, J.-W., Yoon, C., Jo, K., Won, J. H., & Park, S. (2021) · iScience · doi:10.1016/j.isci.2021.103550 · Cited by 25
Multimodal Technologies for Closed‐Loop Neural Modulation and Sensing
Li, L., Zhang, B., Zhao, W., Sheng, D., Yin, L., Sheng, X., & Yao, D. (2024) · Advanced Healthcare Materials · doi:10.1002/adhm.202303289 · Cited by 25
Metadata
- Authors
- Capogrosso, M., Milekovic, T., Borton, D., Wagner, F., Moraud, E. M., Mignardot, J.-B., Buse, N., Gandar, J., Barraud, Q., Xing, D., Rey, E., Duis, S., Jianzhong, Y., Ko, W. K. D., Li, Q., Detemple, P., Denison, T., Micera, S., Bezard, E., Bloch, J., & Courtine, G.
- Affiliations
- École Polytechnique Fédérale de Lausanne (CH)
- Brown University (US)
- Motac Neuroscience (United Kingdom) (GB)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Fraunhofer Institute for Microengineering and Microsystems (DE)
- Scuola Superiore Sant'Anna (IT)
- Centre Hospitalier Universitaire Vaudois (CH)
- Corresponding author
- Courtine, Grégoire
- ORCID
- Venue
- Nature
- Published
- 2016-11
- Volume
- 539
- Issue
- 7628
- Pages
- 284-288
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC5108412
- OpenAlex
- W2549361605
- Cited by
- 635
- References
- 35
- Citations by year
- 2026: 44 · 2025: 54 · 2024: 52 · 2023: 63 · 2022: 71 · 2021: 75 · 2020: 62 · 2019: 61 · 2018: 78 · 2017: 65 · 2016: 8
- FWCI
- 64.23
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- SERVAL (Université de Lausanne) (acceptedVersion, other-oa)
- IRIS (submittedVersion)
- HAL (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- Fraunhofer-Publica (Fraunhofer-Gesellschaft) (submittedVersion)
- CINECA IRIS Institutional Research Information System (Sant'Anna School of Advanced Studies) (submittedVersion)
- Funders
- National Science Foundation
- European Commission (331602, 258654)
- École Polytechnique Fédérale de Lausanne
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- FP7 Ideas: European Research Council (261247)
- Topics
- Health Sciences › Medicine › Clinical Neurology › Spinal Cord Injury Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- spinal cord injury, epidural stimulation, motor cortex, gait recovery, rhesus monkeys, corticospinal tract lesions, leg paralysis, locomotor recovery, intracortical microelectrode arrays, spinal cord stimulation, non-invasive brain-computer interface
- MeSH terms
- Animals, Disease Models, Animal, Electric Stimulation, Electric Stimulation Therapy, Gait, Leg, Locomotion, Lumbosacral Region, Macaca mulatta, Male, Microelectrodes, Motor Cortex, Paralysis, Spinal Cord, Spinal Cord Injuries, Reproducibility of Results, Gait Disorders, Neurologic, Neural Prostheses, Wireless Technology, Brain-Computer Interfaces
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review