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

Cited by (1,000)

Items 501–600 of 1,000

  1. Embedding a Panoramic Representation of Infrared Light in the Adult Rat Somatosensory Cortex through a Sensory Neuroprosthesis
    Konstantin Hartmann, Eric E. Thomson, Ivan Zea, Richy Yun, Peter Mullen, Jay Canarick, Albert Huh, Miguel A. L. Nicolelis · 2016 · Journal of Neuroscience
  2. Continuous Force Decoding from Local Field Potentials of the Primary Motor Cortex in Freely Moving Rats
    Abed Khorasani, Nargess Heydari Beni, Vahid Shalchyan, Mohammad Reza Daliri · 2016 · Scientific Reports
  3. Parsing learning in networks using brain–machine interfaces
    Amy L. Orsborn, Bijan Pesaran · 2017 · Current Opinion in Neurobiology
  4. Network neuroscience for optimizing brain–computer interfaces
    Fabrizio De Vico Fallani, Danielle S. Bassett · 2019 · Physics of Life Reviews
  5. Exploiting co-adaptation for the design of symbiotic neuroprosthetic assistants
    Justin C. Sanchez, Babak Mahmoudi, Jack DiGiovanna, José Carlos Príncipe · 2009 · Neural Networks
  6. A system for recording neural activity chronically and simultaneously from multiple cortical and subcortical regions in nonhuman primates
    Joseph Feingold, Theresa M. Desrochers, Naotaka Fujii, Ray Harlan, Patrick L. Tierney, Hideki Shimazu, Ken‐ichi Amemori, Ann M. Graybiel · 2011 · Journal of Neurophysiology
  7. A Feedback Information-Theoretic Approach to the Design of Brain–Computer Interfaces
    Cyrus Omar, Abdullah Akce, Miles Johnson, Timothy Wolfe Bretl, Rui Ma, Edward L. Maclin, Martin McCormick, Todd P. Coleman · 2010 · International Journal of Human-Computer Interaction
  8. Physiological properties of brain-machine interface input signals
    Marc W. Slutzky, Robert D. Flint · 2017 · Journal of Neurophysiology
  9. In vivo characterization of regenerative peripheral nerve interface function
    Ursu, Daniel C, Urbanchek, Melanie G, Nedic, Andrej, Cederna, Paul S, Gillespie, R Brent · 2016 · Journal of Neural Engineering
  10. Brain-Computer Interface for a Prosthetic Hand Using Local Machine Control and Haptic Feedback
    Ander Ramos‐Murguialday, Vikram Aggarwal, Aniruddha Chatterjee, Yoonju Cho, Robert G. Rasmussen, Brandon O'Rourke, Soumyadipta Acharya, Nitish V. Thakor · 2007 · International Conference on Rehabilitation Robotics
  11. A Survey of Interactive Systems based on Brain-Computer Interfaces
    Alessandro Luiz Stamatto Ferreira, Leonardo Cunha de Miranda, Erica Esteves Cunha de Miranda, Sarah Gomes Sakamoto · 2013 · Journal on Interactive Systems
  12. Developing a Three- to Six-State EEG-Based Brain–Computer Interface for a Virtual Robotic Manipulator Control
    Yuriy Mishchenko, Murat Kaya, Erkan Özbay, Hilmi Yanar · 2018 · IEEE Transactions on Biomedical Engineering
  13. Brain–Machine Interfaces: Basis and Advances
    Jonathan Becedas · 2012 · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)
  14. Agency, authorship, and illusion
    Eddy Nahmias · 2005 · Consciousness and Cognition
  15. The role of ECoG magnitude and phase in decoding position, velocity, and acceleration during continuous motor behavior
    Hammer, Jiri, Fischer, Jörg, Ruescher, Johanna, Schulze-Bonhage, Andreas, Aertsen, Ad, Ball, Tonio · 2013 · Frontiers in Neuroscience
  16. Improving brain–machine interface performance by decoding intended future movements
    Francis R. Willett, Aaron J. Suminski, Andrew H. Fagg, Nicholas G. Hatsopoulos · 2013 · Journal of Neural Engineering
  17. Comparing temporal aspects of visual, tactile, and microstimulation feedback for motor control
    Jason M. Godlove, Erin O. Whaite, Aaron P. Batista · 2014 · Journal of Neural Engineering
  18. Neurobiology: A case study of the imminent militarization of biology
    Mark L. Wheelis, Malcolm Dando · 2005 · International Review of the Red Cross
  19. Neural correlates of learning and trajectory planning in the posterior parietal cortex
    Elizabeth Barbara Torres, Rodrigo Quian Quiroga, He Cui, Christopher A. Buneo · 2013 · Frontiers in Integrative Neuroscience
  20. Current Challenges Facing the Translation of Brain Computer Interfaces from Preclinical Trials to Use in Human Patients
    Maxwell D. Murphy, David J. Guggenmos, David T. Bundy, Randolph J. Nudo · 2016 · Frontiers in Cellular Neuroscience
  21. An ovine model of cerebral catheter venography for implantation of an endovascular neural interface
    Thomas James Oxley, Nicholas Lachlan Opie, Gil Simon Rind, Kishan Liyanage, Sam Emmanuel John, Stephen M. Ronayne, Alan James McDonald, Anthony Dornom, Timothy John Haynes Lovell, Peter John Mitchell et al. · 2017 · Journal of neurosurgery
  22. Intrinsic Variable Learning for Brain-Machine Interface Control by Human Anterior Intraparietal Cortex
    Sofia Sakellaridi, Vassilios N. Christopoulos, Tyson Aflalo, Kelsie Pejsa, Emily Rose Rosario, Debra S. Ouellette, Nader Pouratian, Richard A. Andersen · 2019 · Neuron
  23. Decoding Movement Intent From Human Premotor Cortex Neurons for Neural Prosthetic Applications
    Catherine L. Ojakangas, Ammar Shaikhouni, Gerhard M. Friehs, Abraham H. Caplan, Mijail Demian Serruya, Maryam Saleh, Daniel S. Morris, John P. Donoghue · 2006 · Journal of Clinical Neurophysiology
  24. Local Regression and Likelihood
    Partha P. Mitra, Hemant Bokil · 2007 · Oxford University Press eBooks
  25. Do Corticomotoneuronal Cells Predict Target Muscle EMG Activity?
    Darcy M. Griffin, Heather M. Hudson, Abderraouf Belhaj-Saı̈f, Brian J. McKiernan, Paul D. Cheney · 2007 · Journal of Neurophysiology
  26. Social Cognitive and Affective Neuroscience in Human–Machine Systems: A Roadmap for Improving Training, Human–Robot Interaction, and Team Performance
    Travis J. Wiltshire, Stephen M. Fiore · 2014 · IEEE Transactions on Human-Machine Systems
  27. Cortical and subcortical mechanisms of brain‐machine interfaces
    Silvia Marchesotti, Roberto Martuzzi, Aaron Schurger, Maria Laura Blefari, José del R. Millán, Hannes Bleuler, Olaf Blanke · 2017 · Human Brain Mapping
  28. Sampling representational plasticity of simple imagined movements across days enables long-term neuroprosthetic control
    Nikhilesh Natraj, Sarah Seko, Reza Abiri, Runfeng Miao, Hongyi Yan, Yasmin Graham, Adelyn Tu-Chan, Edward F. Chang, Karunesh Ganguly · 2025 · Cell
  29. Continuous Closed-Loop Decoder Adaptation with a Recursive Maximum Likelihood Algorithm Allows for Rapid Performance Acquisition in Brain-Machine Interfaces
    Siddharth Dangi, Suraj Gowda, Helene G. Moorman, Amy L. Orsborn, Kelvin So, Maryam Modir Shanechi, Jose M. Carmena · 2014 · Neural Computation
  30. Prediction of arm trajectory from a small number of neuron activities in the primary motor cortex
    Yasuharu Koike, Hideaki Hirose, Yoshio Sakurai, Toshio Iijima · 2006 · Neuroscience Research
  31. Adaptive Kalman filtering for closed-loop Brain-Machine Interface systems
    Siddharth Dangi, Suraj Gowda, Rodolphe Héliot, Jose M. Carmena · 2011 · International IEEE/EMBS Conference on Neural Engineering
  32. Exploring representations of human grasping in neural, muscle and kinematic signals
    Andreea Ioana Sburlea, Gernot Müller-Putz · 2018 · Scientific Reports
  33. Motor cortical prediction of EMG: evidence that a kinetic brain-machine interface may be robust across altered movement dynamics
    Anil Cherian, Max Ostrinsky Krucoff, Lee E. Miller · 2011 · Journal of Neurophysiology
  34. The Muscle Activation Method: An Approach to Impedance Control of Brain-Machine Interfaces Through a Musculoskeletal Model of the Arm
    Hyun Koo Kim, Jose M. Carmena, S. James Biggs, Timothy Hanson, Miguel A. L. Nicolelis, Mandayam A. Srinivasan · 2007 · IEEE Transactions on Biomedical Engineering
  35. Neurotechnologies to restore hand functions
    Elena Losanno, Matthew J. Mender, Cynthia A. Chestek, Solaiman Shokur, Silvestro Micera · 2023 · Nature Reviews Bioengineering
  36. Decoding bipedal locomotion from the rat sensorimotor cortex
    Jacopo Rigosa, Alessandro Panarese, Nadia Dominici, Lucia Friedli, Rubia van den Brand, Jacopo Carpaneto, Jack DiGiovanna, Grégoire Courtine, Silvestro Micera · 2015 · Journal of Neural Engineering
  37. Prediction of Hand Trajectory from Electrocorticography Signals in Primary Motor Cortex
    Chao Chen, Duk Shin, Hidenori Watanabe, Yasuhiko Nakanishi, Hiroyuki Kambara, Natsue Yoshimura, Atsushi Nambu, Tadashi Isa, Yukio Nishimura, Yasuharu Koike · 2013 · PLoS ONE
  38. Electrical impedance, electrochemistry, mechanical stiffness, and hardness tunability in glassy carbon MEMS μECoG electrodes
    Sam Kassegne, Maria Vomero, Roberto Gavuglio, Mieko Hirabayashi, Emre Özyilmaz, Sebastien Doan Ky Nam Nguyen, Jesús Rodríguez, Eda Özyilmaz, Pieter van Niekerk, Ajit Khosla · 2014 · Microelectronic Engineering
  39. Reconstructing hand kinematics during reach to grasp movements from electroencephalographic signals
    Harshavardhan A. Agashe, Jose Luis Contreras-Vidal · 2011 · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
  40. Subcortical Neuronal Ensembles: An Analysis of Motor Task Association, Tremor, Oscillations, and Synchrony in Human Patients
    Timothy Hanson, A. M. Fuller, Mikhail Lebedev, Dennis A. Turner, Miguel A. L. Nicolelis · 2012 · Journal of Neuroscience
  41. Leveraging neural dynamics to extend functional lifetime of brain-machine interfaces
    Jonathan C. Kao, Stephen I. Ryu, K.V. Shenoy · 2017 · Scientific Reports
  42. Decoding hand kinematics from population responses in sensorimotor cortex during grasping
    Elizaveta V. Okorokova, James M Goodman, Nicholas G. Hatsopoulos, Sliman J. Bensmaı̈a · 2020 · Journal of Neural Engineering
  43. Brain-Machine Interface Engineering
    Justin C. Sanchez, José Carlos Príncipe · 2007 · Synthesis lectures on biomedical engineering
  44. Prediction of Imagined Single-Joint Movements in a Person With High-Level Tetraplegia
    A. Bolu Ajiboye, John D. Simeral, John P. Donoghue, Leigh R. Hochberg, Robert F. Kirsch · 2012 · IEEE Transactions on Biomedical Engineering
  45. A Brain Implantable Microsystem with Hybrid RF/IR Telemetry for Advanced Neuroengineering Applications
    Yoon‐Kyu Song, William R. Patterson, Christopher W. Bull, David A. Borton, Yanqiu Li, Arto V Nurmikko, John D. Simeral, John P. Donoghue · 2007 · Conference proceedings
  46. Error-related EEG potentials in brain-computer interfaces
    Pierre W. Ferrez, José del R. Millán · 2007 · reroDoc Digital Library
  47. Toward Ubiquitous BCIs
    Brendan Z. Allison · 2009 · The frontiers collection
  48. Differential roles of high gamma and local motor potentials for movement preparation and execution
    Aysegul Gunduz, Peter Brunner, Mohit Sharma, Eric C. Leuthardt, Anthony L. Ritaccio, Bijan Pesaran, Gerwin Schalk · 2016 · Brain-Computer Interfaces
  49. From Parametric Representation to Dynamical System: Shifting Views of the Motor Cortex in Motor Control
    Tianwei Wang, Yun Chen, He Cui · 2022 · Neuroscience Bulletin
  50. Neuronal correlates of signal detection in the posterior parietal cortex of rats performing a sustained attention task
    John I. Broussard, Martin F. Sarter, Bennet S. Givens · 2006 · Neuroscience
  51. Multiple Types of Movement-Related Information Encoded in Hindlimb/Trunk Cortex in Rats and Potentially Available for Brain–Machine Interface Controls
    Weiguo Song, Arun Ramakrishnan, Ubong Ime Udoekwere, Simon F. Giszter · 2009 · IEEE Transactions on Biomedical Engineering
  52. Non-invasive estimation of local field potentials for neuroprosthesis control
    Rolando Grave de Peralta Menéndez, Sara L. Gonzalez Andino, Lucas Perez, Pierre W. Ferrez, José del R. Millán · 2005 · Cognitive Processing
  53. Braided multi-electrode probes: mechanical compliance characteristics and recordings from spinal cords
    Taegyo Kim, Almut Branner, Tanuj Gulati, Simon F. Giszter · 2013 · Journal of Neural Engineering
  54. The dynamics of motor learning through the formation of internal models
    Camilla Pierella, Maura Casadio, Sara A. Solla, Ferinando A. Mussa-Ivaldi · 2019 · PLoS Computational Biology
  55. Functional disconnection of associative cortical areas predicts performance during BCI training
    Marie‐Constance Corsi, Mario Chávez, Denis Schwartz, Nathalie George, Laurent Hugueville, Ari E. Kahn, Sophie Dupont, Danielle S. Bassett, Fabrizio De Vico Fallani · 2020 · NeuroImage
  56. Viewing and doing: similar cortical mechanisms for perceptual and motor learning
    Rony Paz, Steven P Wise, Eilon Vaadia · 2004 · Trends in Neurosciences
  57. Cognition Enhancement
    Anders Sandberg · 2011 · Wiley eBooks
  58. Task-driven neural network models predict neural dynamics of proprioception
    Alessandro Marin Vargas, Axel Bisi, Alberto Silvio Chiappa, Christopher Versteeg, Lee E. Miller, Alexander Mathis · 2024 · Cell
  59. Representation of continuous hand and arm movements in macaque areas M1, F5, and AIP: a comparative decoding study
    Veera Katharina Menz, Stefan Schaffelhofer, Hansjörg Scherberger · 2015 · Journal of Neural Engineering
  60. Neurofeedback Control in Parkinsonian Patients Using Electrocorticography Signals Accessed Wirelessly With a Chronic, Fully Implanted Device
    Preeya Khanna, Nicole C. Swann, Coralie de Hemptinne, Svjetlana Miocinovic, Andrew M. Miller, Philip A. Starr, Jose M. Carmena · 2016 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
  61. EXiO—A Brain-Controlled Lower Limb Exoskeleton for Rhesus Macaques
    Tristan Vouga, Katie Zhuang, Jérémy Olivier, Mikhail Lebedev, Miguel A. L. Nicolelis, Mohamed Bouri, Hannes Bleuler · 2017 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
  62. Optimizing the learning rate for adaptive estimation of neural encoding models
    Han-Lin Hsieh, Maryam Modir Shanechi · 2018 · PLoS Computational Biology
  63. Exploring Cognition with Brain–Machine Interfaces
    Richard A. Andersen, Tyson Aflalo, Luke Bashford, David A. Bjånes, Spencer Kellis · 2022 · Annual Review of Psychology
  64. A design framework to model retinas
    Christian A. Morillas, Samuel F. Romero, Antonio Martínez-Álvarez, Francisco J. Pelayo, Eduardo Ros, Eduardo Fernández · 2006 · Biosystems
  65. Noninvasive Brain-Computer Interface: Decoding Arm Movement Kinematics and Motor Control
    Neethu Robinson, A. P. Vinod · 2016 · IEEE Systems Man and Cybernetics Magazine
  66. Brain–Machine Interfaces: Closed-Loop Control in an Adaptive System
    Ethan Sorrell, Michael E. Rule, Timothy O’Leary · 2021 · Annual Review of Control Robotics and Autonomous Systems
  67. Volitional Walking via Upper Limb Muscle-Controlled Stimulation of the Lumbar Locomotor Center in Man
    Syusaku Sasada, Kenji H. Kato, S. Kadowaki, Stefan Jun Groiss, Yoshikazu Ugawa, Tomoyoshi Komiyama, Yukio Nishimura · 2014 · Journal of Neuroscience
  68. Multiscale modeling and decoding algorithms for spike-field activity
    Han-Lin Hsieh, Yan T. Wong, Bijan Pesaran, Maryam Modir Shanechi · 2018 · Journal of Neural Engineering
  69. Brain-controlled muscle stimulation for the restoration of motor function
    Christian Éthier, Lee E. Miller · 2014 · Neurobiology of Disease
  70. Brain-controlled serious games for cultural heritage
    Athanasios Vourvopoulos, Fotis Liarokapis, Panagiotis Petridis · 2012 · International Conference on Virtual Systems and Multimedia (VSMM)
  71. Error-Related EEG Potentials in Brain-Computer Interfaces
    Pierre W. Ferrez, José del R. Millán · 2007 · The MIT Press eBooks
  72. Cognitive-motor brain–machine interfaces
    Ariel Tankus, Itzhak Fried, Shy Shoham · 2013 · Journal of Physiology-Paris
  73. Ensembles of gustatory cortical neurons anticipate and discriminate between tastants in a single lick
    Jennifer R. Stapleton · 2007 · Frontiers in Neuroscience
  74. Dynamic range adaptation in primary motor cortical populations
    Robert G. Rasmussen, Andrew B. Schwartz, Steven M. Chase · 2017 · eLife
  75. Augmenting intracortical brain-machine interface with neurally driven error detectors
    Nir Even-Chen, Sergey D. Stavisky, Jonathan C. Kao, Stephen I. Ryu, K.V. Shenoy · 2017 · Journal of Neural Engineering
  76. Distance- and speed-informed kinematics decoding improves M/EEG based upper-limb movement decoder accuracy
    Reinmar J. Kobler, Andreea Ioana Sburlea, Valeria Mondini, Masayuki Hirata, Gernot Müller-Putz · 2020 · Journal of Neural Engineering
  77. Robot Navigation Using Brain-Computer Interfaces
    Athanasios Vourvopoulos, Fotis Liarokapis · 2012 · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
  78. Restoring motor function with bidirectional neural interfaces
    Eberhard E. Fetz · 2015 · Progress in brain research
  79. Analysis of Nonstationarities in EEG Signals for Improving Brain-Computer Interface Performance
    Johannes Matthias Krauledat · 2008 · DepositOnce
  80. Place Cell-Like Activity in the Primary Sensorimotor and Premotor Cortex During Monkey Whole-Body Navigation
    Allen S. Yin, Po-He Tseng, Sankaranarayani Rajangam, Mikhail Lebedev, Miguel A. L. Nicolelis · 2018 · Scientific Reports
  81. Life Before Earth
    Alexei A. Sharov, Richard Gordon · 2018 · Elsevier eBooks
  82. Latent Inputs Improve Estimates of Neural Encoding in Motor Cortex
    Steven M. Chase, Andrew B. Schwartz, Robert E. Kass · 2010 · Journal of Neuroscience
  83. Rapid acquisition of novel interface control by small ensembles of arbitrarily selected primary motor cortex neurons
    Andrew J. J. Law, Gil Rivlis, Marc H. Schieber · 2014 · Journal of Neurophysiology
  84. Eliciting naturalistic cortical responses with a sensory prosthesis via optimized microstimulation
    John S Choi, Austin J. Brockmeier, David McNiel, Lee M. von Kraus, José Carlos Príncipe, Joseph Thachil Francis · 2016 · Journal of Neural Engineering
  85. Using noise to shape motor learning
    Elias B. Thorp, Konrad Paul Kording, Ferdinando A. Mussa-Ivaldi · 2016 · Journal of Neurophysiology
  86. Deep learning multimodal fNIRS and EEG signals for bimanual grip force decoding
    Pablo Ortega, A. Aldo Faisal · 2021 · Journal of Neural Engineering
  87. Closed-loop neuromodulation for studying spontaneous activity and causality
    Michal Ramot, Alex D. Martin · 2022 · Trends in Cognitive Sciences
  88. Mapping broadband electrocorticographic recordings to two-dimensional hand trajectories in humans
    Aysegul Gunduz, Justin C. Sanchez, Paul Richard Carney, José Carlos Príncipe · 2009 · Neural Networks
  89. EMG-Based Position and Force Estimates in Coupled Human-Robot Systems: Towards EMG-Controlled Exoskeletons
    Panagiotis Artemiadis, Kostas J. Kyriakopoulos · 2009 · Springer tracts in advanced robotics
  90. Wavelet Transform for Real-Time Detection of Action Potentials in Neural Signals
    Adam Quotb, Yannick Bornat, Sylvie Renaud · 2011 · Frontiers in Neuroengineering
  91. Neural Plasticity in Sensorimotor Brain–Machine Interfaces
    Maria C. Dadarlat, Ryan A. Canfield, Amy L. Orsborn · 2023 · Annual Review of Biomedical Engineering
  92. An Implantable Neural Sensing Microsystem with Fiber-Optic Data Transmission and Power Delivery
    Sunmee Park, David A. Borton, Mingyu Kang, Arto V Nurmikko, Yoon‐Kyu Song · 2013 · Sensors
  93. Reliability of motor and sensory neural decoding by threshold crossings for intracortical brain–machine interface
    Jun Dai, Peng Zhang, Hongji Sun, Xin Qiao, Yuwei Zhao, Jinxu Ma, Shaohua Li, Jin Zhou, Changyong Wang · 2019 · Journal of Neural Engineering
  94. Hardware-Software Co-Design for Brain-Computer Interfaces
    Ioannis Karageorgos, Karthik Sriram, Ján Veselý, Michael Wu, Marc P. Powell, David A. Borton, Rajit Manohar, Abhishek Bhattacharjee · 2020 · Proceedings - International Symposium on Computer Architecture/Proceedings
  95. A Power-Efficient Brain-Machine Interface System With a Sub-mw Feature Extraction and Decoding ASIC Demonstrated in Nonhuman Primates
    Hyochan An, Samuel R. Nason, Jongyup Lim, Kyumin Kwon, Matthew S. Willsey, Parag G. Patil, Hun-Seok Kim, Dennis Sylvester, Cynthia A. Chestek, David T. Blaauw · 2022 · IEEE Transactions on Biomedical Circuits and Systems
  96. A simple method for efficient spike detection in multiunit recordings
    T. Borghi, Riccardo Gusmeroli, Alessandro Sottocornola Spinelli, Gytis Baranauskas · 2007 · Journal of Neuroscience Methods
  97. Brain–Computer Interfaces for the Operation of Robotic and Prosthetic Devices
    Dennis J. McFarland, Jonathan R. Wolpaw · 2010 · Advances in computers
  98. A wireless subdural-contained brain–computer interface with 65,536 electrodes and 1,024 channels
    Tae‐Sung Jung, Nanyu Zeng, Jason D. Fabbri, Guy Eichler, Zhe Li, Erfan Zabeh, Anup Das, Konstantin F. Willeke, Katie Wingel, Agrita Dubey et al. · 2025 · Nature Electronics
  99. A binary method for simple and accurate two-dimensional cursor control from EEG with minimal subject training
    Turan A. Kayagil, Ou Bai, Craig S. Henriquez, Peter T. Lin, Stephen J Furlani, Sherry Vorbach, Mark Hallett · 2009 · Journal of NeuroEngineering and Rehabilitation
  100. Bypassing stroke-damaged neural pathways via a neural interface induces targeted cortical adaptation
    Kenji Kato, Masahiro Sawada, Yukio Nishimura · 2019 · Nature Communications