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Restoration of grasp following paralysis through brain-controlled stimulation of muscles
Open accessAbstract
Patients with spinal cord injury lack the connections between brain and spinal cord circuits that are essential for voluntary movement. Clinical systems that achieve muscle contraction through functional electrical stimulation (FES) have proven to be effective in allowing patients with tetraplegia to regain control of hand movements and to achieve a greater measure of independence in daily activities. In existing clinical systems, the patient uses residual proximal limb movements to trigger pre-programmed stimulation that causes the paralysed muscles to contract, allowing use of one or two basic grasps. Instead, we have developed an FES system in primates that is controlled by recordings made from microelectrodes permanently implanted in the brain. We simulated some of the effects of the paralysis caused by C5 or C6 spinal cord injury by injecting rhesus monkeys with a local anaesthetic to block the median and ulnar nerves at the elbow. Then, using recordings from approximately 100 neurons in the motor cortex, we predicted the intended activity of several of the paralysed muscles, and used these predictions to control the intensity of stimulation of the same muscles. This process essentially bypassed the spinal cord, restoring to the monkeys voluntary control of their paralysed muscles. This achievement is a major advance towards similar restoration of hand function in human patients through brain-controlled FES. We anticipate that in human patients, this neuroprosthesis would allow much more flexible and dexterous use of the hand than is possible with existing FES systems.
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“CNS-based neuroprostheses, or brain–machine interfaces (BMIs), are systems whereby neural electrical activities are decoded and used to control robotic limbs [76, 89, 105] or to stimulate muscles for restoring limb function [35].”
From Implantable neurotechnologies: a review of integrated circuit neural amplifiers (2016) · cites this paper as [35]
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“Currently, all reported BMI experiments with human patients [26, 35, 57, 58, 150] require the subjects tethered percutaneously to a bench-top computer for neural signal acquisition and decoding.”
From Implantable neurotechnologies: a review of integrated circuit neural amplifiers (2016) · cites this paper as [35]
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Cites
Targeting Recovery: Priorities of the Spinal Cord-Injured Population
Anderson, K. D. (2004) · Journal of Neurotrauma · doi:10.1089/neu.2004.21.1371 · Cited by 2,094
McDonald, J. W., & Sadowsky, C. L. (2002) · The Lancet · doi:10.1016/s0140-6736(02)07603-1 · Cited by 1,858
Learning to control a brain–machine interface for reaching and grasping by primates
Carmena, J. M., Lebedev, M. A., Crist, R. E., O'Doherty, J. E., Santucci, D. M., Dimitrov, D. F., Patil, P. G., Henriquez, C. S., & Nicolelis, M. A. L. (2003) · PLoS Biology · doi:10.1371/journal.pbio.0000042 · Cited by 1,761
Relation of pyramidal tract activity to force exerted during voluntary movement.
Evarts, E. V. (1968) · Journal of Neurophysiology · doi:10.1152/jn.1968.31.1.14 · Cited by 1,258
Direct control of paralysed muscles by cortical neurons
Moritz, C. T., Perlmutter, S. I., & Fetz, E. E. (2008) · Nature · doi:10.1038/nature07418 · Cited by 610
Spasticity after spinal cord injury
Adams, M. M., & Hicks, A. L. (2005) · Spinal Cord · doi:10.1038/sj.sc.3101757 · Cited by 517
Motor and sensory recovery following incomplete tetraplegia
Waters, R. L., Adkins, R. H., Yakura, J. S., & Sie, I. H. (1994) · Archives of Physical Medicine and Rehabilitation · doi:10.1016/0003-9993(94)90034-5 · Cited by 438
Predicting Measures of Motor Performance from Multiple Cortical Spike Trains
Humphrey, D. R., Schmidt, E. M., & Thompson, W. (1970) · Science · doi:10.1126/science.170.3959.758 · Cited by 372
Peckham, P. H., Keith, M. W., Kilgore, K. L., Grill, J. H., Wuolle, K. S., Thrope, G. B., Gorman, P., Hobby, J., Mulcahey, M. J., Carroll, S., et al. (2001) · Archives of Physical Medicine and Rehabilitation · doi:10.1053/apmr.2001.25910 · Cited by 319
Implantable functional neuromuscular stimulation in the tetraplegic hand
Keith, M. W., Peckham, P. H., Thrope, G. B., Stroh, K. C., Smith, B., Buckett, J. R., Kilgore, K. L., & Jatich, J. W. (1989) · The Journal Of Hand Surgery · doi:10.1016/s0363-5023(89)80017-6 · Cited by 212
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Items 201–300 of 480
Hosman, T., Hynes, J. B., Saab, J., Wilcoxen, K. G., Buchbinder, B. R., Schmansky, N. J., Cash, S. S., Eskandar, E. N., Simeral, J. D., Franco, B., et al. (2021) · Scientific Reports · doi:10.1038/s41598-020-77616-8 · Cited by 26
Deep learning for neural decoding in motor cortex
Liu, F., Meamardoost, S., Gunawan, R., Komiyama, T., Mewes, C. K. A., Zhang, Y., Hwang, E. J., & Wang, L. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac8fb5 · Cited by 27
Output Properties of the Cortical Hindlimb Motor Area in Spinal Cord-Injured Rats
Frost, S. B., Dunham, C., Barbay, S., Krizsan‐Agbas, D., Winter, M. K., Guggenmos, D. J., & Nudo, R. J. (2015) · Journal of Neurotrauma · doi:10.1089/neu.2015.3961 · Cited by 24
Tian, H., Liu, J.-Q., Kang, X.-Y., Tang, L.-J., Wang, M.-H., Bo-Wen, J., Yang, B. T., Wang, X. L., Chen, X., & Yang, C.-S. (2016) · Scientific Reports · doi:10.1038/srep26910 · Cited by 24
Sombeck, J. T., & Miller, L. E. (2019) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab5cf3 · Cited by 24
Self-citationDecoding methods for neural prostheses: where have we reached?
Li, Z. (2014) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2014.00129 · Cited by 25
Daly, J., Liu, J., Aghagolzadeh, M., & Oweiss, K. G. (2012) · Journal of Neural Engineering · doi:10.1088/1741-2560/9/6/065004 · Cited by 23
Sachs, N. A., Ruiz-Torres, R., Perreault, E. J., & Miller, L. E. (2015) · Journal of Neural Engineering · doi:10.1088/1741-2560/13/1/016009 · Cited by 26
Self-citationCurrent Challenges to the Clinical Translation of Brain Machine Interface Technology
Lu, C. W., Patil, P. G., & Chestek, C. A. (2012) · International review of neurobiology · doi:10.1016/b978-0-12-404706-8.00008-5 · Cited by 24
Decoding of muscle activity from the sensorimotor cortex in freely behaving monkeys
Umeda, T., Koizumi, M., Katakai, Y., Saito, R., & Seki, K. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.04.045 · Cited by 23
Viral-Mediated Optogenetic Stimulation of Peripheral Motor Nerves in Non-human Primates
Williams, J. J., Watson, A. M., Vazquez, A. L., & Schwartz, A. B. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00759 · Cited by 23
The Neural Representation of Force across Grasp Types in Motor Cortex of Humans with Tetraplegia
Rastogi, A., Willett, F. R., Abreu, J., Crowder, D. C., Murphy, B. A., Memberg, W. D., Vargas-Irwin, C. E., Miller, J. P., Sweet, J. A., Walter, B. L., et al. (2021) · eNeuro · doi:10.1523/eneuro.0231-20.2020 · Cited by 23
Greenwald, E., Masters, M. R., & Thakor, N. V. (2016) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-016-1452-6 · Cited by 23
Tian, Z., Li, J., Liu, L., Wu, H., Xie, M., Hu, D., Hou, W., & Ou‐Yang, W. (2025) · Advanced Functional Materials · doi:10.1002/adfm.202505900 · Cited by 22
Balasubramanian, K., Vaidya, M., Southerland, J., Badreldin, I. S., Eleryan, A., Takahashi, K., Qian, K., Slutzky, M. W., Fagg, A. H., Oweiss, K. G., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-01909-2 · Cited by 23
Bayesian optimization of peripheral intraneural stimulation protocols to evoke distal limb movements
Losanno, E., Badi, M., Wurth, S. M., Borgognon, S., Courtine, G., Capogrosso, M., Rouiller, E. M., & Micera, S. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac3f6c · Cited by 22
Closed-loop optogenetic neuromodulation enables high-fidelity fatigue-resistant muscle control
Herrera-Arcos, G., Song, H., Yeon, S. H., Ghenand, O., Gutierrez-Arango, S., Sinha, S., & Herr, H. (2024) · Science Robotics · doi:10.1126/scirobotics.adi8995 · Cited by 22
State-Based Decoding of Force Signals From Multi-Channel Local Field Potentials
Ahmadi, A., Khorasani, A., Shalchyan, V., & Daliri, M. R. (2020) · IEEE Access · doi:10.1109/access.2020.3019267 · Cited by 22
Estimating muscle activation from EMG using deep learning-based dynamical systems models
Wimalasena, L. N., Braun, J., Keshtkaran, M. R., Hofmann, D., Gallego, J. Á., Alessandro, C., Tresch, M. C., Miller, L. E., & Pandarinath, C. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac6369 · Cited by 22
Self-citationA pilot study of synergy-based FES for upper-extremity poststroke rehabilitation
Niu, C. M., Chou, C.-H., Bao, Y., Wang, T., Gu, L., Zhang, X., Cui, L., Xuan, Z., Zhuang, C., Li, S., et al. (2022) · Neuroscience Letters · doi:10.1016/j.neulet.2022.136621 · Cited by 21
Reliability in the location of hindlimb motor representations in Fischer-344 rats
Frost, S. B., Iliakova, M., Dunham, C., Barbay, S., Arnold, P. M., & Nudo, R. J. (2013) · Journal of Neurosurgery Spine · doi:10.3171/2013.4.spine12961 · Cited by 21
Zschorlich, V. R., & Köhling, R. (2013) · PLoS ONE · doi:10.1371/journal.pone.0083845 · Cited by 21
Neural interfaces take another step forward
Jackson, A. (2016) · Nature · doi:10.1038/539177a · Cited by 21
A 3D map of the hindlimb motor representation in the lumbar spinal cord in Sprague Dawley rats
Borrell, J. A., Frost, S. B., Peterson, J. C., & Nudo, R. J. (2016) · Journal of Neural Engineering · doi:10.1088/1741-2552/14/1/016007 · Cited by 21
Young, D. R., Willett, F. R., Memberg, W. D., Murphy, B., Rezaii, P. G., Walter, B. L., Sweet, J., Miller, J. P., Shenoy, K. V., Hochberg, L. R., et al. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aaf606 · Cited by 22
Design and testing of a 96-channel neural interface module for the Networked Neuroprosthesis system
Bullard, A. J., Nason, S. R., Irwin, Z. T., Nu, C. S., Smith, B., Campean, A., Peckham, P. H., Kilgore, K. L., Willsey, M. S., Patil, P. G., et al. (2019) · Bioelectronic Medicine · doi:10.1186/s42234-019-0019-x · Cited by 21
Decoding neural activity to predict rat locomotion using intracortical and epidural arrays
Barroso, F. O., Yoder, B., Tentler, D. P., Wallner, J. J., Kinkhabwala, A. A., Jantz, M., Flint, R. D., Tostado-Marcos, P., Pei, E., Satish, A. D. R., et al. (2019) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab0698 · Cited by 21
Self-citationFlexible multi-channel microelectrode with fluidic paths for intramuscular stimulation and recording
Tian, H., Liu, J., Kang, X., He, Q., Yang, B. T., Chen, X., & Yang, C. (2015) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2015.02.035 · Cited by 20
Prins, N. W., Sanchez, J. C., & Prasad, A. (2014) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00111 · Cited by 20
Clinical neuroscience and neurotechnology: An amazing symbiosis
Cometa, A., Falasconi, A., Biasizzo, M., Carpaneto, J., Horn, A., Mazzoni, A., & Micera, S. (2022) · iScience · doi:10.1016/j.isci.2022.105124 · Cited by 21
Kang, X., Liu, J., Tian, H., Yang, B. T., NuLi, Y., & Yang, C. (2014) · Journal of Micromechanics and Microengineering · doi:10.1088/0960-1317/24/2/025015 · Cited by 19
Bhattachargee, C. K., Sikder, N., Hasan, M. T., & Nahid, A.-A. (2019) · International Conference on Computer, Communication, Chemical, Materials and Electronic Engineering (IC4ME2) · doi:10.1109/ic4me247184.2019.9036671 · Cited by 19
Zhang, X., Mo, X., Li, C., Li, F., Jin, J., Xie, P., Yao, G., Lin, Y., Yao, D., & Xu, P. (2023) · Advanced Intelligent Systems · doi:10.1002/aisy.202200313 · Cited by 19
Wang, J., Wang, H., & Lee, C. (2019) · Advanced Biosystems · doi:10.1002/adbi.201800281 · Cited by 18
Closed-Loop Systems and In Vitro Neuronal Cultures: Overview and Applications
Bisio, M., Pimashkin, A. S., Buccelli, S., Tessadori, J., Semprini, M., Levi, T., Colombi, I., Gladkov, A., Mukhina, I. V., Averna, A., et al. (2019) · Advances in neurobiology · doi:10.1007/978-3-030-11135-9_15 · Cited by 19
Debnath, S., Prins, N. W., Pohlmeyer, E. A., Mylavarapu, R. V., Geng, S., Sanchez, J. C., & Prasad, A. (2018) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/aada67 · Cited by 18
Bouton, C. E. (2020) · Handbook of clinical neurology · doi:10.1016/b978-0-444-63934-9.00022-6 · Cited by 18
Schroeder, K. E., Irwin, Z. T., Bullard, A. J., Thompson, D. E., Bentley, J. N., Stacey, W. C., Patil, P. G., & Chestek, C. A. (2017) · Journal of Neural Engineering · doi:10.1088/1741-2552/aa7329 · Cited by 17
Khorasani, A., Foodeh, R., Shalchyan, V., & Daliri, M. R. (2017) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2017.2751579 · Cited by 17
Flexible 3D carbon nanotubes cuff electrodes as a peripheral nerve interface
Tian, P. W., Yi, W., Chen, C., Hu, J., Qi, J., Zhang, B., & Cheng, M. M. (2018) · Biomedical Microdevices · doi:10.1007/s10544-018-0268-6 · Cited by 17
Brain–computer interface control along instructed paths
Sadtler, P. T., Ryu, S. I., Tyler‐Kabara, E. C., Yu, B. M., & Batista, A. P. (2015) · Journal of Neural Engineering · doi:10.1088/1741-2560/12/1/016015 · Cited by 17
EEG control of an industrial robot manipulator
Garcia, A. P., Schjølberg, I., & Gale, S. (2013) · IEEE International Conference on Cognitive Infocommunications · doi:10.1109/coginfocom.2013.6719280 · Cited by 17
Simultaneous and independent control of a brain-computer interface and contralateral limb movement
Milovanovic, I. P., Robinson, R., Fetz, E. E., & Moritz, C. T. (2015) · Brain-Computer Interfaces · doi:10.1080/2326263x.2015.1080961 · Cited by 18
Yao, L., Li, P., & Je, M. (2015) · 2015 IEEE Asian Solid-State Circuits Conference (A-SSCC) · doi:10.1109/asscc.2015.7387478 · Cited by 16
Intracortical brain-computer interfaces in primates: a review and outlook
Rouzitalab, A., Boulay, C., Park, J., & Sachs, A. J. (2023) · Biomedical Engineering Letters · doi:10.1007/s13534-023-00286-8 · Cited by 16
Advancing brain-machine interfaces: moving beyond linear state space models
Rouse, A. G., & Schieber, M. H. (2015) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2015.00108 · Cited by 18
Control of Redundant Kinematic Degrees of Freedom in a Closed-Loop Brain-Machine Interface
Moorman, H. G., Gowda, S., & Carmena, J. M. (2016) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2016.2593696 · Cited by 16
Towards a circuit mechanism for movement tuning in motor cortex
Harrison, T. C., & Murphy, T. H. (2013) · Frontiers in Neural Circuits · doi:10.3389/fncir.2012.00127 · Cited by 17
Corbett, E. A., Sachs, N. A., Kording, K. P., & Perreault, E. J. (2014) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00123 · Cited by 16
Central nervous system microstimulation: Towards selective micro-neuromodulation
Urdaneta, M. E., Koivuniemi, A. S., & Otto, K. J. (2017) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2017.09.012 · Cited by 16
Context-dependent tactile texture-sensitivity in monkey M1 and S1 cortex
Jiang, W., Tremblay, F., & Chapman, C. E. (2018) · Journal of Neurophysiology · doi:10.1152/jn.00081.2018 · Cited by 17
Thin-film implants for bioelectronic medicine
Oldroyd, P., Hadwe, S. E., Barone, D. G., & Malliaras, G. G. (2024) · MRS Bulletin · doi:10.1557/s43577-024-00786-7 · Cited by 15
Generalizability of EMG decoding using local field potentials
Krasoulis, A., Hall, T. M., Vijayakumar, S., Andrew, J. O., & Nazarpour, K. (2014) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2014.6943917 · Cited by 15
Feature Selection Methods for Robust Decoding of Finger Movements in a Non-human Primate
Padmanaban, S., Baker, J. J., & Greger, B. E. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00022 · Cited by 16
Cortical neuroprosthetics from a clinical perspective
Tsu, A., Burish, M. J., Godlove, J. M., & Ganguly, K. (2015) · Neurobiology of Disease · doi:10.1016/j.nbd.2015.07.015 · Cited by 16
Knudsen, E. B., & Moxon, K. A. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00715 · Cited by 16
Neural Operant Conditioning as a Core Mechanism of Brain-Machine Interface Control
Sakurai, Y., & Song, K. (2016) · Technologies · doi:10.3390/technologies4030026 · Cited by 14
Barra, B., Roux, C., Kaeser, M., Schiavone, G., Lacour, S. P., Bloch, J., Courtine, G., Rouiller, E. M., Schmidlin, E., & Capogrosso, M. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8512554 · Cited by 14
Neural Decoding and Applications in Bioelectronic Medicine
Bouton, C. E. (2015) · Bioelectronic Medicine · doi:10.15424/bioelectronmed.2014.00012 · Cited by 14
Brain–Machine Interfaces in Stroke Neurorehabilitation
Soekadar, S. R., Silvoni, S., Cohen, L. G., & Birbaumer, N. (2014) · Springer eBooks · doi:10.1007/978-4-431-55037-2_1 · Cited by 15
Procházka, A. (2018) · Comprehensive physiology · doi:10.1002/cphy.c180006 · Cited by 15
Effects of iron accumulation and its chelation on oxidative stress in intracortical implants
Franklin, M. E., Grant, J. L., Lee, G. M., Álvarez-Ciara, A., Bennett, C., Mattis, S., Gallardo, N., Corrales, N., Cui, X. T., Capadona, J. R., et al. (2025) · Acta Biomaterialia · doi:10.1016/j.actbio.2025.05.026 · Cited by 13
Innovations in Electrical Stimulation Harness Neural Plasticity to Restore Motor Function
Peng, X., Hickman, J. L., Bowles, S. G., Donegan, D., & Welle, C. G. (2018) · Bioelectronics in Medicine · doi:10.2217/bem-2019-0002 · Cited by 13
Grani, F., Soto‐Sánchez, C., Farfán, F. D., Alfaro, A., Grima, M. D., Doblado, A. R., & Fernández, E. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac801d · Cited by 15
Continuous decoding of grasping tasks for a prospective implantable cortical neuroprosthesis
Carpaneto, J., Raos, V., Umiltà, M. A., Fogassi, L., Murata, A., Gallese, V., & Micera, S. (2012) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-9-84 · Cited by 13
Recovering Motor Activation with Chronic Peripheral Nerve Computer Interface
Eggers, T. E., Dweiri, Y. M., McCallum, G. A., & Durand, D. M. (2018) · Scientific Reports · doi:10.1038/s41598-018-32357-7 · Cited by 13
Spatio-temporal transformers for decoding neural movement control
Candelori, B., Bardella, G., Spinelli, I., Ramawat, S., Pani, P., Ferraina, S., & Scardapane, S. (2025) · Journal of Neural Engineering · doi:10.1088/1741-2552/adaef0 · Cited by 15
Regional specialization of movement encoding across the primate sensorimotor cortex
Borgognon, S., Macellari, N., Hickey, A. M., Perich, M. G., Javaheri, H., Ornelas-Kobayashi, R., Delacombaz, M., Hitz, C., Fallegger, F., Lacour, S. P., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-61172-8 · Cited by 14
Wang, M., Nikaido, K., Kim, Y., Ji, B., Tian, H., Kang, X., Yang, C., Yang, B., Chen, X., Wang, X., et al. (2017) · IEEE International Conference on Micro Electro Mechanical Systems (MEMS) · doi:10.1109/memsys.2017.7863453 · Cited by 12
Zhang, Q., Yang, M., Wu, L., Xiang, X., & Xiong, C. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2019.101843 · Cited by 12
Lan, Y., Yao, J., & Dewald, J. P. A. (2017) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2017.00039 · Cited by 12
Kibleur, P., Ramalingasetty, S. T., Greiner, N., Conti, S., Barra, B., Zhuang, K., Kaeser, M., Ijspeert, A. J., & Capogrosso, M. (2020) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2020.2986491 · Cited by 14
Restoration of complex movement in the paralyzed upper limb
Hasse, B. A., Sheets, D. E. G., Holly, N. L., Gothard, K. M., & Fuglevand, A. J. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac7ad7 · Cited by 14
Bouton, C. E. (2019) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a034306 · Cited by 12
Transhemispheric cortex remodeling promotes forelimb recovery after spinal cord injury
Wu, W., Nguyen, T., Ordaz, J. D., Zhang, Y., Liu, N., Hu, X., Liu, Y., Ping, X., Han, Q., Wu, X., et al. (2022) · JCI Insight · doi:10.1172/jci.insight.158150 · Cited by 11
Pellot-Cestero, J. E., Herring, E. Z., Graczyk, E. L., Memberg, W. D., Kirsch, R. F., Ajiboye, A. B., & Miller, J. P. (2023) · Neurosurgery · doi:10.1227/neu.0000000000002561 · Cited by 11
Sakurai, Y. (2014) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2014.00104 · Cited by 11
Micro-Hermetic Packaging Technology for Active Implantable Neural Interfaces
Nagarkar, K. R., Hou, X., Stoffel, N. C., Davis, E. L., Ashe, J. M., & Borton, D. A. (2017) · IEEE Electronic Components and Technology Conference (ECTC) · doi:10.1109/ectc.2017.340 · Cited by 11
Adaptive neuron-to-EMG decoder training for FES neuroprostheses
Éthier, C., Acuna, D. E., Solla, S. A., & Miller, L. E. (2016) · Journal of Neural Engineering · doi:10.1088/1741-2560/13/4/046009 · Cited by 12
Self-citationIntracortical Brain–Machine Interfaces
Oby, E. R., Hennig, J. A., Batista, A. P., Yu, B. M., & Chase, S. M. (2020) · Springer eBooks · doi:10.1007/978-3-030-43395-6_5 · Cited by 10
Self-citationBrain Co-processors: Using AI to Restore and Augment Brain Function
Rao, R. P. N. (2021) · Handbook of Neuroengineering · doi:10.1007/978-981-15-2848-4_32-1 · Cited by 10
Nason, S. R., Mender, M. J., Kennedy, E., Lambrecht, J. M., Kilgore, K. L., Chiravuri, S., Kumar, N. G., Kung, T. A., Willsey, M. S., Chestek, C. A., et al. (2023) · Journal of Neural Engineering · doi:10.1088/1741-2552/accf36 · Cited by 10
Rizzoglio, F., Altan, E., Ma, X., Bodkin, K. L., Dekleva, B. M., Solla, S. A., Kennedy, A., & Miller, L. E. (2023) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad038e · Cited by 12
Self-citationAcceptability Study of A3-K3 Robotic Architecture for a Neurorobotics Painting
Tramonte, S., Sorbello, R., Guger, C., & Chella, A. (2019) · Frontiers in Neurorobotics · doi:10.3389/fnbot.2018.00081 · Cited by 10
Zhuang, K., Lebedev, M., & Nicolelis, M. A. L. (2014) · Journal of Neurophysiology · doi:10.1152/jn.00031.2013 · Cited by 10
An emerging view of neural geometry in motor cortex supports high-performance decodingPreprint
Perkins, S. M., Amematsro, E. A., Cunningham, J. P., Wang, Q., & Churchland, M. M. (2023) · eLife · doi:10.7554/elife.89421 · Cited by 12
Neurally controlled robotic arm enables tetraplegic patient to drink coffee of her own volition
Kingwell, K. (2012) · Nature Reviews Neurology · doi:10.1038/nrneurol.2012.101 · Cited by 9
Development of flexible multi-channel muscle interfaces with advanced sensing function
Wang, J., Xiang, Z., Gammad, G. G. L., Thakor, N. V., Yen, S.-C., & Lee, C. (2016) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2016.07.034 · Cited by 9
Barra, B., Badi, M., Perich, M. G., Conti, S., Salehian, S. S. M., Moreillon, F., Bogaard, A. R., Wurth, S. M., Kaeser, M., Passeraub, P., et al. (2019) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab4c77 · Cited by 9
An emerging view of neural geometry in motor cortex supports high-performance decoding
Perkins, S. M., Amematsro, E. A., Cunningham, J. P., Wang, Q., & Churchland, M. M. (2025) · eLife · doi:10.1101/2023.04.05.535396 · Cited by 12
“Messing with the mind”: evolutionary challenges to human brain augmentation
Saniotis, A., Henneberg, M., Kumaratilake, J., & Grantham, J. P. (2014) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2014.00152 · Cited by 9
Wang, D., Zhang, Q., Li, Y., Wang, Y., Zhu, J., Zhang, S., & Zheng, X. (2014) · Journal of Neural Engineering · doi:10.1088/1741-2560/11/4/049501 · Cited by 9
Verma, N., Oh, J., Bedoy, E. H., Chetty, N., Steele, A. G., Park, S. J., Guerrero, J. R., Faraji, A. H., Weber, D. J., & Sayenko, D. G. (2025) · Journal of Neurophysiology · doi:10.1152/jn.00422.2024 · Cited by 9
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Zhang, S., Tan, R., Meng, S., Zhang, K., & Hu, J. (2025) · Advanced Science · doi:10.1002/advs.202502831 · Cited by 8
Lucas, T. H., Liu, X., Zhang, M., Sritharan, S., Planell-Mendez, I., Ghenbot, Y. G., Maldonado, S. T., Brandon, C., der Spiegel, J. V., & Richardson, A. G. (2017) · Neurosurgery · doi:10.1093/neuros/nyx367 · Cited by 8
The touch in action: exploring sensorimotor interactions with motor imagery
Ali, Y., Montani, V., & Cesari, P. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad123 · Cited by 8
Decoding of the spike timing of primary afferents during voluntary arm movements in monkeys
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Jackson, A. (2012) · Nature · doi:10.1038/485317a · Cited by 9
Augmentation of Sensorimotor Functions with Neural Prostheses
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BRAIN-COMPUTER INTERFACE FOR THE AUGMENTATION OF BRAIN FUNCTIONS
Lebedev, M. (2016) · Science and Innovations in Medicine · doi:10.35693/2500-1388-2016-0-3-11-27 · Cited by 7
Metadata
- Authors
- Ethier, C., Oby, E. R., Bauman, M. J., & Miller, L. E.
- Affiliations
- Northwestern University (US)
- University of Pittsburgh (US)
- Corresponding author
- Miller, L. E.
- Venue
- Nature
- Published
- 2012-04-18
- Volume
- 485
- Issue
- 7398
- Pages
- 368-371
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3358575
- OpenAlex
- W1988067967
- Cited by
- 485
- References
- 26
- Citations by year
- 2026: 9 · 2025: 22 · 2024: 24 · 2023: 27 · 2022: 24 · 2021: 33 · 2020: 29 · 2019: 28 · 2018: 42 · 2017: 44 · 2016: 46 · 2015: 38 · 2014: 55 · 2013: 46 · 2012: 18
- FWCI
- 20.69
- 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)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Institute of Neurological Disorders and Stroke (R01NS053603, F31NS071737, #NS053603)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Health Sciences › Medicine › Clinical Neurology › Spinal Cord Injury Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- brain-computer interface, functional electrical stimulation, paralysis, spinal cord injury, motor cortex, neural prostheses, hand grasping, rhesus monkeys, tetraplegia, hand function recovery, prosthetic hand control
- MeSH terms
- Animals, Electric Stimulation, Electrodes, Implanted, Hand, Macaca mulatta, Microelectrodes, Motor Cortex, Movement, Muscles, Nerve Block, Paralysis, Quadriplegia, Spinal Cord Injuries, Hand Strength, Prostheses and Implants
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