Learning to Control a Brain–Machine Interface for Reaching and Grasping by Primates

Carmena, Jose M, Lebedev, Mikhail A, Crist, Roy E, O'Doherty, Joseph E, Santucci, David M, Dimitrov, Dragan F, Patil, Parag G, Henriquez, Craig S, Nicolelis, Miguel A. L·2003·PLoS Biology
DOI 10.1371/journal.pbio.0000042

Cited by (1,000)

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  1. Local field potentials allow accurate decoding of muscle activity
    Robert D. Flint, Christian Éthier, Emily R. Oby, Lee E. Miller, Marc W. Slutzky · 2012 · Journal of Neurophysiology
  2. Model-Based Neural Decoding of Reaching Movements: A Maximum Likelihood Approach
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  3. How feedback, motor imagery, and reward influence brain self‐regulation using real‐time fMRI
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  4. Brain-Machine Interfaces: A Tale of Two Learners
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  5. Brain-computer interfaces — the key for the conscious brain locked into a paralyzed body
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  6. Effects of Robotic Knee Exoskeleton on Human Energy Expenditure
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  7. A fully implantable 96-channel neural data acquisition system
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  8. A Symbiotic Brain-Machine Interface through Value-Based Decision Making
    Babak Mahmoudi, Justin C. Sanchez · 2011 · PLoS ONE
  9. Brain-computer interfaces (BCIs) for communication and control
    Jonathan R. Wolpaw · 2007 · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS)
  10. Beyond the body schema: Visual, prosthetic, and technological contributions to bodily perception and awareness
    Nicholas P. Holmes, Charles J. Spence · 2006
  11. Performance measurement for brain–computer or brain–machine interfaces: a tutorial
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  12. The Emergence of Single Neurons in Clinical Neurology
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  13. Continuous low-frequency EEG decoding of arm movement for closed-loop, natural control of a robotic arm
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  14. Neuronal Assembly Detection and Cell Membership Specification by Principal Component Analysis
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  15. Visual evoked potential-based brain–machine interface applications to assist disabled people
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  16. Cognitive neuroscience and robotics: Advancements and future research directions
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  17. Information Systems Opportunities in Brain–Machine Interface Decoders
    Jonathan C. Kao, Sergey D. Stavisky, David Sussillo, Paul Nuyujukian, K.V. Shenoy · 2014 · Proceedings of the IEEE
  18. Brain–Machine and Brain–Computer Interfaces
    Gerhard M. Friehs, Vasilios A. Zerris, Catherine L. Ojakangas, Mathew R. Fellows, John P. Donoghue · 2004 · Stroke
  19. Inferring hand movement kinematics from MEG, EEG and intracranial EEG: From brain-machine interfaces to motor rehabilitation
    Karim Jerbi, Juan R. Vidal, Jérémie Mattout, Emmanuel Maby, Françoise Lecaignard, Tomás Ossandón, Carlos M. Hamamé, Sarang S. Dalal, Romain Bouet, J.-P. Lachaux et al. · 2011 · IRBM
  20. Brain-computer interfaces: military, neurosurgical, and ethical perspective
    Ivan S. Kotchetkov, Brian Y. Hwang, Geoffrey Appelboom, Christopher Paul Kellner, Edward Sander Connolly · 2010 · Neurosurgical FOCUS
  21. Closing the loop in cortically-coupled computer vision: a brain–computer interface for searching image databases
    Eric A. Pohlmeyer, Jun Wang, David C. Jangraw, Bin Lou, Shih‐Fu Chang, Paul Sajda · 2011 · Journal of Neural Engineering
  22. Expanding the primate body schema in sensorimotor cortex by virtual touches of an avatar
    Solaiman Shokur, Joseph E. O’Doherty, Jesse Winans, Hannes Bleuler, Mikhail Lebedev, Miguel A. L. Nicolelis · 2013 · Proceedings of the National Academy of Sciences
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    William M. Reichert · 2007 · CRC Press eBooks
  24. A State-Space Analysis for Reconstruction of Goal-Directed Movements Using Neural Signals
    Lakshminarayan Srinivasan, Uri T. Eden, Alan S. Willsky, Emery N. Brown · 2006 · Neural Computation
  25. Augmentation-related brain plasticity
    Giovanni Di Pino, Angelo Maravita, Loredana Zollo, Eugenio Guglielmelli, Vincenzo Di Lazzaro · 2014 · Frontiers in Systems Neuroscience
  26. Wireless Cortical Brain-Machine Interface for Whole-Body Navigation in Primates
    Sankaranarayani Rajangam, Po-He Tseng, Allen S. Yin, Gary Lehew, David Schwarz, Mikhail Lebedev, Miguel A. L. Nicolelis · 2016 · Scientific Reports
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    Cassie Bennett, Farrah S. Mohammed, Anabel Álvarez-Ciara, Michelle A. Nguyen, W. Dalton Dietrich, Suhrud M. Rajguru, Wolfgang J. Streit, Abhishek Prasad · 2018 · Biomaterials
  28. Robust, long-term control of an electrocorticographic brain-computer interface with fixed parameters
    Tim M. Blakely, Kai Joshua Miller, Stavros P. Zanos, Rajesh P. N. Rao, Jeffrey G. Ojemann · 2009 · Neurosurgical FOCUS
  29. Kalman filter control of a model of spatiotemporal cortical dynamics
    Steven J. Schiff, TIMOTHY D. SAUER · 2007 · Journal of Neural Engineering
  30. Review of Research and Development of Supernumerary Robotic Limbs
    Yuchuang Tong, Jinguo Liu · 2021 · IEEE/CAA Journal of Automatica Sinica
  31. State-based decoding of hand and finger kinematics using neuronal ensemble and LFP activity during dexterous reach-to-grasp movements
    Vikram Aggarwal, Mohsen Mollazadeh, Adam G. Davidson, Marc H. Schieber, Nitish V. Thakor · 2013 · Journal of Neurophysiology
  32. Toward More Versatile and Intuitive Cortical Brain–Machine Interfaces
    Richard A. Andersen, Spencer Kellis, Christian Klaes, Tyson Aflalo · 2014 · Current Biology
  33. Methods for estimating neural firing rates, and their application to brain–machine interfaces
    John Patrick Cunningham, Vikash Gilja, Stephen I. Ryu, K.V. Shenoy · 2009 · Neural Networks
  34. A high-performance brain–computer interface for finger decoding and quadcopter game control in an individual with paralysis
    Matthew S. Willsey, Nishal P. Shah, Donald T. Avansino, Nick V. Hahn, Ryan M. Jamiolkowski, Foram B. Kamdar, Leigh R. Hochberg, Francis R. Willett, Jaimie M. Henderson · 2025 · Nature Medicine
  35. Correlations Between the Same Motor Cortex Cells and Arm Muscles During a Trained Task, Free Behavior, and Natural Sleep in the Macaque Monkey
    Andrew Jackson, Jaideep Mavoori, Eberhard E. Fetz · 2006 · Journal of Neurophysiology
  36. A Real-Time Brain-Machine Interface Combining Motor Target and Trajectory Intent Using an Optimal Feedback Control Design
    Maryam Modir Shanechi, Ziv M. Williams, Gregory W. Wornell, Rollin C. Hu, Marissa E. Powers, Emery N. Brown · 2013 · PLoS ONE
  37. Mental tasks-based brain–robot interface
    Eduardo Iáñez, José María Azorín, Andrés Úbeda, José Manuel Ferrández Vicente, Eduardo Fernández · 2010 · Robotics and Autonomous Systems
  38. Brain-Machine Interfaces: Powerful Tools for Clinical Treatment and Neuroscientific Investigations
    Marc W. Slutzky · 2018 · The Neuroscientist
  39. Learning is shaped by abrupt changes in neural engagement
    Jay A. Hennig, Emily R. Oby, Matthew D. Golub, Lindsay Bahureksa, Patrick T. Sadtler, Kristin M. Quick, Stephen I. Ryu, Elizabeth C. Tyler‐Kabara, Aaron P. Batista, Steven M. Chase et al. · 2021 · Nature Neuroscience
  40. A dynamical systems view of motor preparation
    K.V. Shenoy, Matthew Tyler Kaufman, Maneesh Sahani, Mark M. Churchland · 2011 · Progress in brain research
  41. The science and engineering behind sensitized brain-controlled bionic hands
    Chethan Pandarinath, Sliman J. Bensmaı̈a · 2021 · Physiological Reviews
  42. Defining brain–machine interface applications by matching interface performance with device requirements
    Oliver Tonet, Martina Marinelli, Luca Citi, Paolo Maria Rossini, Luca Rossini, Giuseppe Megali, Paolo Dario · 2007 · Journal of Neuroscience Methods
  43. Low-latency multi-threaded processing of neuronal signals for brain-computer interfaces
    Jörg W. Fischer, Tomislav Milekovic, Gerhard M. Schneider, Carsten Mehring · 2014 · Frontiers in Neuroengineering
  44. Neurobionics and the brain–computer interface: current applications and future horizons
    Jeffrey Victor Rosenfeld, Yan T. Wong · 2017 · The Medical Journal of Australia
  45. All My Circuits: Using Multiple Electrodes to Understand Functioning Neural Networks
    Miller, Earl K., Wilson, Matthew A. · 2008 · Neuron
  46. Decoding Local Field Potentials for Neural Interfaces
    J. Oxenham Andrew, Thomas M. Hall · 2016 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
  47. A High-Performance Neural Prosthesis Incorporating Discrete State Selection With Hidden Markov Models
    Jonathan C. Kao, Paul Nuyujukian, Stephen I. Ryu, K.V. Shenoy · 2016 · IEEE Transactions on Biomedical Engineering
  48. Classification of upper limb center-out reaching tasks by means of EEG-based continuous decoding techniques
    Andrés Úbeda, José María Azorín, Ricardo Chavarriaga, José del R. Millán · 2017 · Journal of NeuroEngineering and Rehabilitation
  49. In vivo evaluation of a neural stem cell-seeded prosthesis
    Purcell, E K, Seymour, J P, Yandamuri, S, Kipke, D R · 2009 · Journal of Neural Engineering
  50. Attentional Modulation of Vision Versus Proprioception During Action
    Jakub Limanowski, Karl John Friston · 2019 · Cerebral Cortex
  51. Toward an Autonomous Brain Machine Interface: Integrating Sensorimotor Reward Modulation and Reinforcement Learning
    Brandi T. Marsh, Venkata S Aditya Tarigoppula, Chen Chen, Joseph Thachil Francis · 2015 · Journal of Neuroscience
  52. Using Reinforcement Learning to Provide Stable Brain-Machine Interface Control Despite Neural Input Reorganization
    Eric A. Pohlmeyer, Babak Mahmoudi, Shijia Geng, Noeline W. Prins, Justin C. Sanchez · 2014 · PLoS ONE
  53. Design and validation of a real-time spiking-neural-network decoder for brain–machine interfaces
    Julie Dethier, Paul Nuyujukian, Stephen I. Ryu, K.V. Shenoy, Kwabena A. Boahen · 2013 · Journal of Neural Engineering
  54. Adaptive Classification for Brain Computer Interfaces
    Julie Blumberg, Jörn Rickert, Stephan Waldert, Andreas Schulze‐Bonhage, Ad Aertsen, Carsten Mehring · 2007 · Conference proceedings
  55. Decoding arm speed during reaching
    Yoh Inoue, Hongwei Mao, Steven B. Suway, Josue Orellana, Andrew B. Schwartz · 2018 · Nature Communications
  56. Deep learning approaches for neural decoding across architectures and recording modalities
    Jesse A. Livezey, Joshua I. Glaser · 2020 · Briefings in Bioinformatics
  57. Decoding the brain: From neural representations to mechanistic models
    Mackenzie Weygandt Mathis, Adriana Perez Rotondo, Edward F. Chang, Andreas Savas Tolias, Alexander Mathis · 2024 · Cell
  58. Decoding human motor activity from EEG single trials for a discrete two-dimensional cursor control
    Dandan Huang, Peter T. Lin, Ding-Yu Fei, Xuedong Chen, Ou Bai · 2009 · Journal of Neural Engineering
  59. Neural Decoding of Hand Motion Using a Linear State-Space Model With Hidden States
    Wei Li Wu, Jayant E. Kulkarni, Nicholas G. Hatsopoulos, Liam Paninski · 2009 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
  60. General-Purpose Filter Design for Neural Prosthetic Devices
    Lakshminarayan Srinivasan, Uri T. Eden, Sanjoy K. Mitter, Emery N. Brown · 2007 · Journal of Neurophysiology
  61. Dynamic Encoding of Movement Direction in Motor Cortical Neurons
    Jörn Rickert, Alexa Riehle, Ad Aertsen, Stefan Rotter, Martin Paul Nawrot · 2009 · Journal of Neuroscience
  62. Assimilation of virtual legs and perception of floor texture by complete paraplegic patients receiving artificial tactile feedback
    Solaiman Shokur, Simone Gallo, Renan C. Moioli, Ana R. C. Donati, Edgard Morya, Hannes Bleuler, Miguel A. L. Nicolelis · 2016 · Scientific Reports
  63. Extracting kinetic information from human motor cortical signals
    Robert D. Flint, Po T. Wang, Zachary A. Wright, Christine King, Max Ostrinsky Krucoff, Stephan Schuele, Joshua M. Rosenow, Frank P. K. Hsu, Charles Yu Liu, Jack J. Lin et al. · 2014 · NeuroImage
  64. High Accuracy Decoding of Movement Target Direction in Non-Human Primates Based on Common Spatial Patterns of Local Field Potentials
    Nuri F. Ince, Rahul Gupta, Sami Arıca, Ahmed H. Tewfik, James Ashe, Giuseppe Pellizzer · 2010 · PLoS ONE
  65. Decoding Individuated Finger Movements Using Volume-Constrained Neuronal Ensembles in the M1 Hand Area
    Soumyadipta Acharya, Francesco V. Tenore, Vikram Aggarwal, Ralph Etienne‐Cummings, Marc H. Schieber, Nitish V. Thakor · 2008 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
  66. Signal Processing Challenges for Neural Prostheses
    Michael D. Linderman, Gopal Santhanam, Caleb T. Kemere, Vikash Gilja, Stephen O’Driscoll, Byron M. Yu, Afsheen Afshar, Stephen I. Ryu, K.V. Shenoy, Teresa H. -Y. Meng · 2008 · IEEE Signal Processing Magazine
  67. Single reach plans in dorsal premotor cortex during a two-target task
    Brian M Dekleva, Konrad Paul Kording, Lee E. Miller · 2018 · Nature Communications
  68. Single trial prediction of self-paced reaching directions from EEG signals
    Eileen Y. L. Lew, Ricardo Chavarriaga, Stefano Silvoni, José del R. Millán · 2014 · Frontiers in Neuroscience
  69. Neuronal network coherent with hand kinematics during fast repetitive hand movements
    Mathieu Bourguignon, Veikko Jousmäki, Marc Op De Beeck, Patrick Van Bogaert, Serge Goldman, Xavier De Tiège · 2011 · NeuroImage
  70. Cognitive neural prosthetics
    Bijan Pesaran, Sam Musallam, Richard A. Andersen · 2006 · Current Biology
  71. Robust and accurate decoding of hand kinematics from entire spiking activity using deep learning
    Ahmadi, Nur, Constandinou, Timothy G, Bouganis, Christos-Savvas · 2021 · Journal of Neural Engineering
  72. Virtual Active Touch Using Randomly Patterned Intracortical Microstimulation
    Joseph E. O’Doherty, Mikhail Lebedev, Zheng Li, Miguel A. L. Nicolelis · 2011 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
  73. An online brain–machine interface using decoding of movement direction from the human electrocorticogram
    Tomislav Milekovic, Jörg W. Fischer, Tobias Pistohl, Johanna Ruescher, Andreas Schulze‐Bonhage, Ad Aertsen, Jörn Rickert, Tonio Ball, Carsten Mehring · 2012 · Journal of Neural Engineering
  74. A single-chip signal processing and telemetry engine for an implantable 96-channel neural data acquisition system
    Michael Rizk, Iyad Obeid, Stephen H Callender, Patrick D. Wolf · 2007 · Journal of Neural Engineering
  75. Collaborative Approach in the Development of High‐Performance Brain–Computer Interfaces for a Neuroprosthetic Arm: Translation from Animal Models to Human Control
    Collinger, Jennifer L., Kryger, Michael A., Barbara, Richard, Betler, Timothy, Bowsher, Kristen, Brown, Elke H. P., Clanton, Samuel T., Degenhart, Alan D., Foldes, Stephen T., Gaunt, Robert A. et al. · 2014 · Clinical and Translational Science
  76. Fundamental processes in sensorimotor learning: Reasoning, refinement, and retrieval
    Jonathan Sanching Tsay, Hyosub E. Kim, Samuel D. McDougle, Jordan A. Taylor, Adrian Mark Haith, Guy Avraham, John W. Krakauer, Anne Gabrielle Eva Collins, Richard B. Ivry · 2024 · eLife
  77. Microstimulation in auditory cortex provides a substrate for detailed behaviors
    Kevin John Otto, Patrick J Rousche, Daryl R. Kipke · 2005 · Hearing Research
  78. The utility of multichannel local field potentials for brain–machine interfaces
    Eun Jung Hwang, Richard A. Andersen · 2013 · Journal of Neural Engineering
  79. Dendritic calcium signals in rhesus macaque motor cortex drive an optical brain-computer interface
    Eric M. Trautmann, Daniel J. O’Shea, Xulu Sun, James H. Marshel, Ailey Crow, Brian Hsueh, Sam S. Vesuna, Lucas B. Cofer, Gergő Bohner, Will Allen et al. · 2021 · Nature Communications
  80. Going beyond primary motor cortex to improve brain–computer interfaces
    Juan Álvaro Gallego, Tamar R. Makin, Samuel D. McDougle · 2022 · Trends in Neurosciences
  81. Volitional control of single cortical neurons in a brain–machine interface
    Chet T. Moritz, Eberhard E. Fetz · 2011 · Journal of Neural Engineering
  82. Biomimetic Brain Machine Interfaces for the Control of Movement
    Andrew H. Fagg, Nicholas G. Hatsopoulos, Víctor de Lafuente, Karen Anne Moxon, Shamim Nemati, James M. Rebesco, Ranulfo Romo, Sara A. Solla, Jake Reimer, Dennis C. Tkach et al. · 2007 · Journal of Neuroscience
  83. Free-paced high-performance brain–computer interfaces
    Neil Achtman, Afsheen Afshar, Gopal Santhanam, Byron M. Yu, Stephen I. Ryu, K.V. Shenoy · 2007 · Journal of Neural Engineering
  84. Neural reinforcement: re-entering and refining neural dynamics leading to desirable outcomes
    Vivek R. Athalye, Jose M. Carmena, Rui M. Costa · 2019 · Current Opinion in Neurobiology
  85. Definitions of state variables and state space for brain-computer interface
    Walter Freeman · 2006 · Cognitive Neurodynamics
  86. Brain control of bimanual movement enabled by recurrent neural networks
    Darrel R. Deo, Francis R. Willett, Donald T. Avansino, Leigh R. Hochberg, Jaimie M. Henderson, K.V. Shenoy · 2024 · Scientific Reports
  87. Frontal and parietal cortical ensembles predict single‐trial muscle activity during reaching movements in primates
    David M. Santucci, Jerald D. Kralik, Mikhail Lebedev, Miguel A. L. Nicolelis · 2005 · European Journal of Neuroscience
  88. Continuous decoding of human grasp kinematics using epidural and subdural signals
    Robert D. Flint, Joshua M. Rosenow, Matthew C. Tate, Marc W. Slutzky · 2016 · Journal of Neural Engineering
  89. Cortical neurons multiplex reward-related signals along with sensory and motor information
    Arjun Ramakrishnan, Yoon Woo Byun, Kyle Rand, Christian E. Pedersen, Mikhail Lebedev, Miguel A. L. Nicolelis · 2017 · Proceedings of the National Academy of Sciences
  90. Constraints on neural redundancy
    Jay A. Hennig, Matthew D. Golub, Peter J Lund, Patrick T. Sadtler, Emily R. Oby, Kristin M. Quick, Stephen I. Ryu, Elizabeth C. Tyler‐Kabara, Aaron P. Batista, Byron M. Yu et al. · 2018 · eLife
  91. The “sewing machine” for minimally invasive neural recording
    Timothy Hanson, Camilo A. Diaz-Botia, Viktor Kharazia, Michel M. Maharbiz, Philip N. Sabes · 2019 · bioRxiv (Cold Spring Harbor Laboratory)
  92. Intention estimation in brain–machine interfaces
    Joline M. Fan, Paul Nuyujukian, Jonathan C. Kao, Cynthia A. Chestek, Stephen I. Ryu, K.V. Shenoy · 2014 · Journal of Neural Engineering
  93. Non-invasive transmission of sensorimotor information in humans using an EEG/focused ultrasound brain-to-brain interface
    Wonhye Lee, Suji Kim, Byeongnam Kim, Chungki Lee, Yong An Chung, Laehyun Kim, Seung‐Schik Yoo · 2017 · PLoS ONE
  94. Evidence for a neural law of effect
    Vivek R. Athalye, Fernando J. Santos, Jose M. Carmena, Rui M. Costa · 2018 · Science
  95. Neurons in the Rostral Cingulate Motor Area Monitor Multiple Phases of Visuomotor Behavior With Modest Parametric Selectivity
    Eiji Hoshi, Hiromasa Sawamura, Jun Tanji · 2005 · Journal of Neurophysiology
  96. Robust Neuroprosthetic Control from the Stroke Perilesional Cortex
    Tanuj Gulati, Seok Joon Won, Dhakshin Ramanathan, Chelsea C. Wong, Anitha Bodepudi, Raymond A. Swanson, Karunesh Ganguly · 2015 · Journal of Neuroscience
  97. Selective visual attention to drive cognitive brain–machine interfaces: from concepts to neurofeedback and rehabilitation applications
    Elaine Ästrand, Claire Wardak, Suliann Ben Hamed · 2014 · Frontiers in Systems Neuroscience
  98. Motor Cortex in Voluntary Movements
    2004 · Frontiers in neuroscience
  99. Motor-Sensory Confluence in Tactile Perception
    Avraham Saig, Goren Gordon, Eldad Assa, Amos Arieli, Ehud Ahissar · 2012 · Journal of Neuroscience
  100. Performance sustaining intracortical neural prostheses
    Paul Nuyujukian, Jonathan C. Kao, Joline M. Fan, Sergey D. Stavisky, Stephen I. Ryu, K.V. Shenoy · 2014 · Journal of Neural Engineering