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Learning to Control a Brain–Machine Interface for Reaching and Grasping by Primates
Open accessAbstract
Reaching and grasping in primates depend on the coordination of neural activity in large frontoparietal ensembles. Here we demonstrate that primates can learn to reach and grasp virtual objects by controlling a robot arm through a closed-loop brain-machine interface (BMIc) that uses multiple mathematical models to extract several motor parameters (i.e., hand position, velocity, gripping force, and the EMGs of multiple arm muscles) from the electrical activity of frontoparietal neuronal ensembles. As single neurons typically contribute to the encoding of several motor parameters, we observed that high BMIc accuracy required recording from large neuronal ensembles. Continuous BMIc operation by monkeys led to significant improvements in both model predictions and behavioral performance. Using visual feedback, monkeys succeeded in producing robot reach-and-grasp movements even when their arms did not move. Learning to operate the BMIc was paralleled by functional reorganization in multiple cortical areas, suggesting that the dynamic properties of the BMIc were incorporated into motor and sensory cortical representations.
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“In our context, the perhaps most interesting observation in this experiment (see Carmena et al., 2003, for details) is how the monkey gradually begins to neglect his original arm, which is, after all, a part of his biological body.”
From Empirical perspectives from the self-model theory of subjectivity: a brief summary with examples (2007) · cites this paper as Carmena et al., 2003
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“Another similar, overstated extrapolation regards evidence from invasive and semi-invasive BCI, where learning and co-adaptation have been well documented [19,23,24,57–59].”
From The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users (2018) · cites this paper as [58]
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Cites
Guide for the Care and Use of Laboratory Animals: Eighth Edition
(2011) · doi:10.17226/12910 · Cited by 16,199
The 1996 Guide for the Care and Use of Laboratory Animals
Clark, J. D., Gebhart, G. F., Gonder, J. C., Keeling, M. E., & Kohn, D. F. (1997) · ILAR Journal · doi:10.1093/ilar.38.1.41 · Cited by 4,429
Direct isolation of human central nervous system stem cells
Uchida, N., Buck, D. W., He, D., Reitsma, M. J., Masek, M., Phan, T. V., Tsukamoto, A. S., Gage, F. H., & Weissman, I. L. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.26.14720 · Cited by 1,829
A spelling device for the paralysed
Birbaumer, N., Ghanayim, N., Hinterberger, T., Iversen, I., Kotchoubey, B., Kübler, A., Perelmouter, J., Taub, E., & Flor, H. (1999) · Nature · doi:10.1038/18581 · Cited by 1,577
Direct Cortical Control of 3D Neuroprosthetic Devices
Taylor, D. M., Tillery, S. I. H., & Schwartz, A. B. (2002) · Science · doi:10.1126/science.1070291 · Cited by 1,542
Real-time prediction of hand trajectory by ensembles of cortical neurons in primates
Wessberg, J., Stambaugh, C. R., Kralik, J. D., Beck, P. D., Laubach, M., Chapin, J. K., Kim, J., Biggs, S. J., Srinivasan, M. A., & Nicolelis, M. A. L. (2000) · Nature · doi:10.1038/35042582 · Cited by 1,491
Self-citationInstant neural control of a movement signal
Serruya, M. D., Hatsopoulos, N. G., Paninski, L., Fellows, M. R., & Donoghue, J. P. (2002) · Nature · doi:10.1038/416141a · Cited by 1,415
Coding of modified body schema during tool use by macaque postcentral neurones
lriki, A., Tanaka, M., & Iwamura, Y. (1996) · NeuroReport · doi:10.1097/00001756-199610020-00010 · Cited by 1,274 · cited 2×
“It is also supported by the results that cortical neurons may modulate their firing rate either during use of tools (Iriki et al. 1996), according to cursor movement on the screen rather than underlying arm movements (Alexander and Crutcher 1990; Shen and Alexander 1997), or in relation to the…”
ResultReal-time control of a robot arm using simultaneously recorded neurons in the motor cortex
Chapin, J. K., Moxon, K. A., Markowitz, R. S., & Nicolelis, M. A. L. (1999) · Nature Neuroscience · doi:10.1038/10223 · Cited by 1,173
Self-citationTemporal structure in neuronal activity during working memory in macaque parietal cortex
Pesaran, B., Pezaris, J. S., Sahani, M., Mitra, P. P., & Andersen, R. A. (2002) · Nature Neuroscience · doi:10.1038/nn890 · Cited by 1,071
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Neurofeedback Therapy for Enhancing Visual Attention: State-of-the-Art and Challenges
Ordikhani-Seyedlar, M., Lebedev, M., Sørensen, H. B. D., & Puthusserypady, S. K. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2016.00352 · Cited by 65
Self-citationClassification of different reaching movements from the same limb using EEG
Shiman, F., López‐Larraz, E., Sarasola-Sanz, A., Irastorza-Landa, N., Spüler, M., Birbaumer, N., & Ramos‐Murguialday, A. (2017) · Journal of Neural Engineering · doi:10.1088/1741-2552/aa70d2 · Cited by 67
Can Electrocorticography (ECoG) Support Robust and Powerful Brain-Computer Interfaces?
Schalk, G. (2010) · Frontiers in Neuroengineering · doi:10.3389/fneng.2010.00009 · Cited by 65
CUDAICA: GPU Optimization of Infomax-ICA EEG Analysis
Raimondo, F., Kamienkowski, J. E., Sigman, M., & Slezak, D. F. (2012) · Computational Intelligence and Neuroscience · doi:10.1155/2012/206972 · Cited by 65
Prediction of Muscle Activities from Electrocorticograms in Primary Motor Cortex of Primates
Shin, D., Watanabe, H., Kambara, H., Nambu, A., Isa, T., Nishimura, Y., & Koike, Y. (2012) · PLoS ONE · doi:10.1371/journal.pone.0047992 · Cited by 66
Chao, Z. C., Bakkum, D. J., & Potter, S. M. (2007) · Journal of Neural Engineering · doi:10.1088/1741-2560/4/3/015 · Cited by 65
Hermes, D., Vansteensel, M. J., Albers, A. M., Bleichner, M. G., Benedictus, M. R., Méndez‐Orellana, C., Aarnoutse, E. J., & Ramsey, N. F. (2011) · Journal of Neural Engineering · doi:10.1088/1741-2560/8/2/025007 · Cited by 64
Westwick, D. T., Pohlmeyer, E. A., Solla, S. A., Miller, L. E., & Perreault, E. J. (2005) · Neural Computation · doi:10.1162/089976606775093855 · Cited by 65
What limits the performance of current invasive brain machine interfaces?
Baranauskas, G. (2014) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2014.00068 · Cited by 65
Volitional activation of remote place representations with a hippocampal brain–machine interface
Lai, C., Tanaka, S., Harris, T. D., & Lee, A. K. (2023) · Science · doi:10.1126/science.adh5206 · Cited by 70
Minimum requirements for accurate and efficient real-time on-chip spike sorting
Navajas, J., Barsakcioglu, D. Y., Eftekhar, A., Andrew, J. O., Constandinou, T. G., & Quiroga, R. Q. (2014) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2014.04.018 · Cited by 68
Cortical Modulations Increase in Early Sessions with Brain-Machine Interface
Zacksenhouse, M., Lebedev, M., Carmena, J. M., O’Doherty, J. E., Henriquez, C. S., & Nicolelis, M. A. L. (2007) · PLoS ONE · doi:10.1371/journal.pone.0000619 · Cited by 64
Self-citationPatient-Specific Pose Estimation in Clinical Environments
Chen, K., Gabriel, P., Alasfour, A., Gong, C., Doyle, W., Devinsky, O., Friedman, D. J., Dugan, P. C., Melloni, L., Thesen, T., et al. (2018) · IEEE Journal of Translational Engineering in Health and Medicine · doi:10.1109/jtehm.2018.2875464 · Cited by 66
Flavopiridol reduces the impedance of neural prostheses in vivo without affecting recording quality
Purcell, E. K., Thompson, D. E., Ludwig, K. A., & Kipke, D. R. (2009) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2009.06.026 · Cited by 62
Brain-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
Vourvopoulos, A., & Liarokapis, F. (2013) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2013.10.009 · Cited by 62
Motor cortical control of movement speed with implications for brain-machine interface control
Golub, M. D., Yu, B. M., Schwartz, A. B., & Chase, S. M. (2014) · Journal of Neurophysiology · doi:10.1152/jn.00391.2013 · Cited by 67
Feature Extraction for Multi-class BCI using Canonical Variates Analysis
Galán, F., Ferrez, P. W., Oliva, F., Guàrdia‐Olmos, J., & Millán, J. D. R. (2007) · IEEE International Symposium on Intelligent Signal Processing, · doi:10.1109/wisp.2007.4447615 · Cited by 62
Dissociating motor cortex from the motor
Schieber, M. H. (2011) · The Journal of Physiology · doi:10.1113/jphysiol.2011.215814 · Cited by 65
Cassar, I. R., Yu, C., Sambangi, J., Lee, C. D., Whalen, J. J., Petrossians, A., & Grill, W. M. (2019) · Biomaterials · doi:10.1016/j.biomaterials.2019.03.017 · Cited by 63
Schalk, G. (2008) · Journal of Neural Engineering · doi:10.1088/1741-2560/5/1/p01 · Cited by 63
Direct Comparison of the Task-Dependent Discharge of M1 in Hand Space and Muscle Space
Morrow, M. M., Jordan, L. R., & Miller, L. E. (2006) · Journal of Neurophysiology · doi:10.1152/jn.00150.2006 · Cited by 62
Progress in the Field of Micro-Electrocorticography
Shokoueinejad, M., Park, D., Jung, Y. H., Brodnick, S. K., Novello, J., Dingle, A. M., Swanson, K. I., Baek, D.-H., Suminski, A. J., Lake, W. B., et al. (2019) · Micromachines · doi:10.3390/mi10010062 · Cited by 65
A Method for Detection and Classification of Events in Neural Activity
Bokil, H., Pesaran, B., Andersen, R. A., & Mitra, P. P. (2006) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2006.877802 · Cited by 62
Real-time estimation and biofeedback of single-neuron firing rates using local field potentials
Hall, T. M., Nazarpour, K., & Jackson, A. (2014) · Nature Communications · doi:10.1038/ncomms6462 · Cited by 61
A High-Performance Keyboard Neural Prosthesis Enabled by Task Optimization
Nuyujukian, P., Fan, J. M., Kao, J. C., Ryu, S. I., & Shenoy, K. V. (2014) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2014.2354697 · Cited by 61
Arduin, P.-J., Frégnac, Y., Shulz, D. E., & Ego‐Stengel, V. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.2744-12.2013 · Cited by 62
Selective Activation of Ipsilateral Motor Pathways in Intact Humans
Tazoe, T., & Pérez, M. A. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.1648-14.2014 · Cited by 61
Learning in Closed-Loop Brain–Machine Interfaces: Modeling and Experimental Validation
Héliot, R., Ganguly, K., Jimenez, J., & Carmena, J. M. (2009) · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) · doi:10.1109/tsmcb.2009.2036931 · Cited by 62
Self-citationBrain–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
Volitional Modulation of Primary Visual Cortex Activity Requires the Basal Ganglia
Neely, R., Koralek, A. C., Athalye, V. R., Costa, R. M., & Carmena, J. M. (2018) · Neuron · doi:10.1016/j.neuron.2018.01.051 · Cited by 62
Self-citationClosing the Loop: Stimulation Feedback Systems for Embodied MEA Cultures
Potter, S. M., Wagenaar, D. A., & DeMarse, T. B. (2006) · Springer eBooks · doi:10.1007/0-387-25858-2_9 · Cited by 63
Millán, J. D. R. (2013) · Wiley eBooks · doi:10.1002/9781118628522.ch12 · Cited by 61
Closed-Loop Brain–Machine–Body Interfaces for Noninvasive Rehabilitation of Movement Disorders
Broccard, F. D., Mullen, T. R., Chi, Y. M., Peterson, D., Iversen, J. R., Arnold, M., Kreutz-Delgado, K., Jung, T., Makeig, S., Howard Poizner, A., et al. (2014) · Annals of Biomedical Engineering · doi:10.1007/s10439-014-1032-6 · Cited by 62
Carpaneto, J., Umiltà, M. A., Fogassi, L., Murata, A., Gallese, V., Micera, S., & Raos, V. (2011) · Neuroscience · doi:10.1016/j.neuroscience.2011.04.062 · Cited by 61
Control of a vehicle with EEG signals in real-time and system evaluation
Choi, K. (2011) · European Journal of Applied Physiology · doi:10.1007/s00421-011-2029-6 · Cited by 60
Brain–machine interfaces for rehabilitation of poststroke hemiplegia
Ushiba, J., & Soekadar, S. R. (2016) · Progress in brain research · doi:10.1016/bs.pbr.2016.04.020 · Cited by 60
Electroencephalogram-Based Brain–Computer Interface and Lower-Limb Prosthesis Control: A Case Study
Murphy, D. P., Bai, O., Gorgey, A. S., Fox, J., Lovegreen, W. T., Burkhardt, B., Atri, R., Marquez, J. S., Li, Q., & Fei, D.-Y. (2017) · Frontiers in Neurology · doi:10.3389/fneur.2017.00696 · Cited by 65
Thermal Considerations for the Design of an Implanted Cortical Brain–Machine Interface (BMI)
Reichert, W. M. (2007) · CRC Press eBooks · doi:10.1201/9781420009309-11 · Cited by 60
Subpixel image scaling for color‐matrix displays
Klompenhouwer, M. A., & de Haan, G. (2003) · Journal of the Society for Information Display · doi:10.1889/1.1831726 · Cited by 60
A cortical–spinal prosthesis for targeted limb movement in paralysed primate avatars
Shanechi, M. M., Hu, R. C., & Williams, Z. M. (2014) · Nature Communications · doi:10.1038/ncomms4237 · Cited by 62
The ethics of species: an introduction
(2013) · Choice Reviews Online · doi:10.5860/choice.50-5585 · Cited by 60
Muscle synergies evoked by microstimulation are preferentially encoded during behavior
Overduin, S. A., d’Avella, A., Carmena, J. M., & Bizzi, E. (2014) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2014.00020 · Cited by 61
Self-citationWang, D., Zhang, Q., Li, Y., Wang, Y., Zhu, J., Zhang, S., & Zheng, X. (2014) · Journal of Neural Engineering · doi:10.1088/1741-2560/11/3/036009 · Cited by 60
Decoding the rat forelimb movement direction from epidural and intracortical field potentials
Slutzky, M. W., Jordan, L. R., Lindberg, E. W., Lindsay, K. E., & Miller, L. E. (2011) · Journal of Neural Engineering · doi:10.1088/1741-2560/8/3/036013 · Cited by 59
Shanechi, M. M., Wornell, G. W., Williams, Z. M., & Brown, E. N. (2012) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2012.2221743 · Cited by 58
Internal models for interpreting neural population activity during sensorimotor control
Golub, M. D., Yu, B. M., & Chase, S. M. (2015) · eLife · doi:10.7554/elife.10015 · Cited by 61
Livezey, J. A., Bouchard, K. E., & Chang, E. F. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007091 · Cited by 62
Brain–computer interface use is a skill that user and system acquire together
McFarland, D. J., & Wolpaw, J. R. (2018) · PLoS Biology · doi:10.1371/journal.pbio.2006719 · Cited by 64
Bidirectional brain-computer interfaces
Hughes, C. L., Herrera, A. J., Gaunt, R. A., & Collinger, J. L. (2020) · Handbook of clinical neurology · doi:10.1016/b978-0-444-63934-9.00013-5 · Cited by 65
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Narayanan, N. S., & Laubach, M. (2008) · Methods in molecular biology · doi:10.1007/978-1-59745-543-5_7 · Cited by 55
Brain–computer interfaces: a powerful tool for scientific inquiry
Wander, J. D., & Rao, R. P. N. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2013.11.013 · Cited by 59
Error-related electrocorticographic activity in humans during continuous movements
Milekovic, T., Ball, T., Schulze‐Bonhage, A., Aertsen, A., & Mehring, C. (2012) · Journal of Neural Engineering · doi:10.1088/1741-2560/9/2/026007 · Cited by 58
Closed-loop cortical control of direction using support vector machines
Olson, B., Si, J., Hu, J. F., & He, J. (2005) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2004.843174 · Cited by 57
Computing Arm Movements with a Monkey Brainet
Ramakrishnan, A., Ifft, P. J., Pais-Vieira, M., Byun, Y. W., Zhuang, K. Z., Lebedev, M. A., & Nicolelis, M. A. L. (2015) · Scientific Reports · doi:10.1038/srep10767 · Cited by 54
Self-citationMilekovic, T., Ball, T., Schulze‐Bonhage, A., Aertsen, A., & Mehring, C. (2013) · PLoS ONE · doi:10.1371/journal.pone.0055235 · Cited by 57
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Andrew, J. O., & Fetz, E. E. (2011) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2011.2158586 · Cited by 57
Oby, E. R., Éthier, C., & Miller, L. E. (2012) · Journal of Neurophysiology · doi:10.1152/jn.00331.2012 · Cited by 57
Wen, S., Yin, A. S., Furlanello, T., Perich, M. G., Miller, L. E., & Itti, L. (2021) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00811-z · Cited by 56
A Probabilistic Strategy for Understanding Action Selection
Kim, B., & Basso, M. A. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.1730-09.2010 · Cited by 56
The use of tungsten as a chronically implanted material
Idil, A. S., & Donaldson, N. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aaa502 · Cited by 55
Chan, S. S., & Moran, D. W. (2006) · Journal of Neural Engineering · doi:10.1088/1741-2560/3/4/010 · Cited by 55
Making the lifetime connection between brain and machine for restoring and enhancing function
Kennedy, P., Andreasen, D. S., Bartels, J., Ehirim, P., Mao, H., Velliste, M., Wichmann, T., & Wright, J. (2011) · Progress in brain research · doi:10.1016/b978-0-444-53815-4.00020-0 · Cited by 53
O’Shea, D. J., Trautmann, E. M., Chandrasekaran, C., Stavisky, S. D., Kao, J. C., Sahani, M., Ryu, S. I., Deisseroth, K. A., & Shenoy, K. V. (2016) · Experimental Neurology · doi:10.1016/j.expneurol.2016.08.003 · Cited by 54
Interfacing to the brain’s motor decisions
Mirabella, G., & Lebedev, M. (2016) · Journal of Neurophysiology · doi:10.1152/jn.00051.2016 · Cited by 55
Self-citationMeng, J., Streitz, T. D., Gulachek, N., Suma, D., & He, B. (2018) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2018.2872855 · Cited by 59
Kobler, R. J., Sburlea, A. I., & Müller-Putz, G. (2018) · Scientific Reports · doi:10.1038/s41598-018-36326-y · Cited by 54
Distinct types of neural reorganization during long-term learning
Zhou, X., Tien, R. N., Ravikumar, S., & Chase, S. M. (2019) · Journal of Neurophysiology · doi:10.1152/jn.00466.2018 · Cited by 52
Hiremath, S. V., Chen, W., Wang, W., Foldes, S., Yang, Y., Tyler-Kabara, E. C., Collinger, J. L., & Boninger, M. L. (2015) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2015.00040 · Cited by 53
Encoding of speed and direction of movement in the human supplementary motor area
Tankus, A., Yeshurun, Y., Flash, T., & Fried, I. (2009) · Journal of neurosurgery · doi:10.3171/2008.10.jns08466 · Cited by 53
Toward a whole-body neuroprosthetic
Lebedev, M., & Nicolelis, M. A. L. (2011) · Progress in brain research · doi:10.1016/b978-0-444-53815-4.00018-2 · Cited by 53
Self-citationBeyond Therapy and Enhancement: The Alteration of Human Nature
Jotterand, F. (2008) · NanoEthics · doi:10.1007/s11569-008-0025-z · Cited by 53
Spike Train Decoding Without Spike Sorting
Ventura, V. (2007) · Neural Computation · doi:10.1162/neco.2008.02-07-478 · Cited by 54
Creating new functional circuits for action via brain-machine interfaces
Orsborn, A. L., & Carmena, J. M. (2013) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2013.00157 · Cited by 55
Self-citationNeural control of finger movement via intracortical brain–machine interface
Irwin, Z. T., Schroeder, K. E., Vu, P. P., Bullard, A. J., Tat, D. M., Nu, C. S., Vaskov, A. K., Nason, S. R., Thompson, D. E., Bentley, J. N., et al. (2017) · Journal of Neural Engineering · doi:10.1088/1741-2552/aa80bd · Cited by 56
Self-citationAffective brain-computer interfaces as enabling technology for responsive psychiatric stimulation
Widge, A. S., Dougherty, D. D., & Moritz, C. T. (2014) · Brain-Computer Interfaces · doi:10.1080/2326263x.2014.912885 · Cited by 51
Decoding fingertip trajectory from electrocorticographic signals in humans
Nakanishi, Y., Yanagisawa, T., Shin, D., Chen, C., Kambara, H., Yoshimura, N., Fukuma, R., Kishima, H., Hirata, M., & Koike, Y. (2014) · Neuroscience Research · doi:10.1016/j.neures.2014.05.005 · Cited by 52
Nambu, I., Osu, R., Sato, M.-A., Ando, S., Kawato, M., & Naito, E. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.04.050 · Cited by 52
Hammer, J., Pistohl, T., Fischer, J. W., Kršek, P., Tomášek, M., Marusič, P., Schulze‐Bonhage, A., Aertsen, A., & Ball, T. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw033 · Cited by 55
Perel, S., Sadtler, P. T., Oby, E. R., Ryu, S. I., Tyler‐Kabara, E. C., Batista, A. P., & Chase, S. M. (2015) · Journal of Neurophysiology · doi:10.1152/jn.00293.2014 · Cited by 55
Collinger, J. L., Gaunt, R. A., & Schwartz, A. B. (2018) · Current Opinion in Biomedical Engineering · doi:10.1016/j.cobme.2018.11.005 · Cited by 53
Decoding Movements from Cortical Ensemble Activity Using a Long Short-Term Memory Recurrent Network
Tseng, P.-H., Urpí, N. A., Lebedev, M., & Nicolelis, M. A. L. (2019) · Neural Computation · doi:10.1162/neco_a_01189 · Cited by 50
Self-citationContinuous sensorimotor rhythm based brain computer interface learning in a large population
Stieger, J., Engel, S. A., & He, B. (2021) · Scientific Data · doi:10.1038/s41597-021-00883-1 · Cited by 65
Network-based brain–computer interfaces: principles and applications
Gonzalez-Astudillo, J., Cattai, T., Bassignana, G., Corsi, M., & Fallani, F. D. V. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/abc760 · Cited by 60
A Synthesis of the Many Errors and Learning Processes of Visuomotor AdaptationPreprint
Morehead, J. R., & de Xivry, J. O. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.14.435278 · Cited by 55
Vidal, G. W. V., Rynes, M. L., Kelliher, Z., & Goodwin, S. J. (2016) · Scientifica · doi:10.1155/2016/8956432 · Cited by 54
Wang, Y., Wang, F., Xu, K., Zhang, Q., Zhang, S., & Zheng, X. (2014) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2014.2341275 · Cited by 51
Independent Mobility Achieved through a Wireless Brain-Machine Interface
Libedinsky, C., So, R. Q., Xu, Z., Kyar, T. K., Ho, D., Lim, C., Chan, L., Chua, Y., Yao, L., Cheong, J. H., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0165773 · Cited by 52
Decoding gripping force based on local field potentials recorded from subthalamic nucleus in humans
Tan, H., Pogosyan, A. H., Ashkan, K., Green, A. L., Aziz, T. Z., Foltynie, T., Limousin, P. D., Zrinzo, L. U., Hariz, M. I., & Brown, P. (2016) · eLife · doi:10.7554/elife.19089 · Cited by 50
Decoding Cognitive Processes from Neural Ensembles
Wallis, J. D. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.09.002 · Cited by 58
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Metadata
- Authors
- 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.
- Affiliations
- Duke University (US)
- Corresponding author
- Nicolelis, Miguel A. L
- Venue
- PLoS Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2003-10-13
- Volume
- 1
- Issue
- 2
- Pages
- e42
- ISSN
- 1544-9173 (ISSN-L)
- 1545-7885
- PMC
- PMC261882
- OpenAlex
- W2041248708
- Cited by
- 1,761
- References
- 43
- Citations by year
- 2026: 28 · 2025: 65 · 2024: 37 · 2023: 49 · 2022: 50 · 2021: 56 · 2020: 61 · 2019: 62 · 2018: 79 · 2017: 60 · 2016: 97 · 2015: 93 · 2014: 132 · 2013: 112 · 2012: 101
- FWCI
- 29.81
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, other-oa)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Science Foundation
- James S. McDonnell Foundation
- Defense Advanced Research Projects Agency
- Advanced Research Projects Agency
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Keywords
- brain-computer interface, reach-to-grasp, primate motor control, feedback control, motor learning, visual feedback
- MeSH terms
- Animals, Arm, Artificial Intelligence, Behavior, Animal, Biomechanical Phenomena, Biophysics, Brain, Brain Mapping, Electromyography, Electrophysiology, Female, Hand, Learning, Macaca, Models, Neurological, Models, Theoretical, Motor Activity, Motor Cortex, Movement, Neurons, Primates, Psychomotor Performance, Robotics, Somatosensory Cortex, Space Perception, Time Factors, Models, Statistical, Hand Strength, Biophysical Phenomena
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