Functional network reorganization during learning in a brain-computer interface paradigm
Open accessAbstract
Efforts to study the neural correlates of learning are hampered by the size of the network in which learning occurs. To understand the importance of learning-related changes in a network of neurons, it is necessary to understand how the network acts as a whole to generate behavior. Here we introduce a paradigm in which the output of a cortical network can be perturbed directly and the neural basis of the compensatory changes studied in detail. Using a brain-computer interface, dozens of simultaneously recorded neurons in the motor cortex of awake, behaving monkeys are used to control the movement of a cursor in a three-dimensional virtual-reality environment. This device creates a precise, well-defined mapping between the firing of the recorded neurons and an expressed behavior (cursor movement). In a series of experiments, we force the animal to relearn the association between neural firing and cursor movement in a subset of neurons and assess how the network changes to compensate. We find that changes in neural activity reflect not only an alteration of behavioral strategy but also the relative contributions of individual neurons to the population error signal.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Evidence from invasive and semi-invasive BCI shows that learning and co-adaptation have been well documented.
“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 [24]
Cites
The Organization of Behavior; A Neuropsychological Theory.
Attneave, F., B., M., & Hebb, D. O. (1950) · The American Journal of Psychology · doi:10.2307/1418888 · Cited by 5,146 · see citing works
The Organization of Behavior: A Neuropsychological Theory
(1950) · JAMA · doi:10.1001/jama.1950.02910470083028 · Cited by 4,271 · see citing works
Neuronal ensemble control of prosthetic devices by a human with tetraplegia
Hochberg, L. R., Serruya, M. D., Friehs, G. M., Mukand, J. A., Saleh, M., Caplan, A. H., Branner, A., Chen, D., Penn, R. D., & Donoghue, J. P. (2006) · Nature · doi:10.1038/nature04970 · Cited by 3,295 · see citing works
Georgopoulos, A. P., Kalaska, J. F., Caminiti, R., & Massey, J. (1982) · Journal of Neuroscience · doi:10.1523/jneurosci.02-11-01527.1982 · Cited by 2,133 · see citing works
CORTICAL PLASTICITY: From Synapses to Maps
Buonomano, D. V., & Merzenich, M. M. (1998) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.21.1.149 · Cited by 2,083 · cited 1× · see citing works
“f==bo+mcoso, [1]”
Steps toward Artificial Intelligence
Minsky, M. (1961) · Proceedings of the IRE · doi:10.1109/jrproc.1961.287775 · Cited by 1,706 · see citing works
The Handbook of Artificial Intelligence
Salveter, S. C. (1982) · Elsevier eBooks · doi:10.1016/c2013-0-07691-8 · Cited by 1,703 · see citing works
Cortical control of a prosthetic arm for self-feeding
Velliste, M., Perel, S., Spalding, M. C., Whitford, A. S., & Schwartz, A. B. (2008) · Nature · doi:10.1038/nature06996 · Cited by 1,591 · see citing works
Self-citationDirect 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 · see citing works
Self-citationReal-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 · see citing works
Plasticity and Primary Motor Cortex
Sanes, J. N., & Donoghue, J. P. (2000) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.23.1.393 · Cited by 1,202 · see citing works
Georgopoulos, A. P., Kettner, R., & Schwartz, A. (1988) · Journal of Neuroscience · doi:10.1523/jneurosci.08-08-02928.1988 · Cited by 835 · see citing works
Self-citationA high-performance brain–computer interface
Santhanam, G., Ryu, S. I., Yu, B. M., Afshar, A., & Shenoy, K. V. (2006) · Nature · doi:10.1038/nature04968 · Cited by 698 · see citing works
Cognitive Control Signals for Neural Prosthetics
Musallam, S., Corneil, B. D., Greger, B., Scherberger, H., & Andersen, R. A. (2004) · Science · doi:10.1126/science.1097938 · Cited by 663 · see citing works
Schwartz, A., Kettner, R. E., & Georgopoulos, A. P. (1988) · Journal of Neuroscience · doi:10.1523/jneurosci.08-08-02913.1988 · Cited by 565 · see citing works
Self-citationLi, C.-S. R., Padoa‐Schioppa, C., & Bizzi, E. (2001) · Neuron · doi:10.1016/s0896-6273(01)00301-4 · Cited by 422 · see citing works
Scott, S. H., & Kalaska, J. F. (1997) · Journal of Neurophysiology · doi:10.1152/jn.1997.77.2.826 · Cited by 403 · see citing works
The Handbook of Artificial Intelligence
(1982) · Elsevier eBooks · doi:10.1016/c2013-0-07692-x · Cited by 277 · see citing works
Primary Motor Cortex Tuning to Intended Movement Kinematics in Humans with Tetraplegia
Truccolo, W., Friehs, G. M., Donoghue, J. P., & Hochberg, L. R. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.4415-07.2008 · Cited by 273 · see citing works
Amplification of Trial-to-Trial Response Variability by Neurons in Visual Cortex
Carandini, M. (2004) · PLoS Biology · doi:10.1371/journal.pbio.0020264 · Cited by 210 · see citing works
Cortical correlates of learning in monkeys adapting to a new dynamical environment
Gandolfo, F., Li, C.-S. R., Benda, B. J., Schioppa, C. P., & Bizzi, E. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.040567097 · Cited by 209 · see citing works
Preparatory activity in motor cortex reflects learning of local visuomotor skills
Paz, R., Boraud, T., Natan, C., Bergman, H., & Vaadia, E. (2003) · Nature Neuroscience · doi:10.1038/nn1097 · Cited by 199 · see citing works
Changes in motor cortical activity during visuomotor adaptation
Wise, S. P., Moody, S. L., Blomstrom, K. J., & Mitz, A. R. (1998) · Experimental Brain Research · doi:10.1007/s002210050462 · Cited by 180 · see citing works
Learning-related synaptic plasticity: LTP and LTD
Siegelbaum, S. A., & Kandel, E. R. (1991) · Current Opinion in Neurobiology · doi:10.1016/0959-4388(91)90018-3 · Cited by 168 · see citing works
Fiete, I. R., Fee, M. S., & Seung, H. S. (2007) · Journal of Neurophysiology · doi:10.1152/jn.01311.2006 · Cited by 167 · see citing works
Extraction algorithms for cortical control of arm prosthetics
Schwartz, A. B., Taylor, D. M., & Tillery, S. I. H. (2001) · Current Opinion in Neurobiology · doi:10.1016/s0959-4388(01)00272-0 · Cited by 150 · see citing works
Self-citationNeuronal activity in the supplementary motor area of monkeys adapting to a new dynamic environment.
Padoa-Schioppa, C., Li, C., & Bizzi, E. (2004) · Journal of Neurophysiology · doi:10.1152/jn.00876.2002 · Cited by 147 · see citing works
On the Relationship Between Joint Angular Velocity and Motor Cortical Discharge During Reaching
Reina, G. A., Moran, D. W., & Schwartz, A. B. (2001) · Journal of Neurophysiology · doi:10.1152/jn.2001.85.6.2576 · Cited by 145 · see citing works
Self-citationRemapping Hand Movements in a Novel Geometrical Environment
Mosier, K. M., Scheidt, R. A., Acosta, S., & Mussa-Ivaldi, F. A. (2005) · Journal of Neurophysiology · doi:10.1152/jn.00380.2005 · Cited by 133 · see citing works
Alopex: A Correlation-Based Learning Algorithm for Feedforward and Recurrent Neural Networks
Unnikrishnan, K. P., & Venugopal, K. P. (1994) · Neural Computation · doi:10.1162/neco.1994.6.3.469 · Cited by 113 · see citing works
Mazzoni, P., Andersen, R. A., & Jordan, M. I. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.4.293 · Cited by 86 · see citing works
Paz, R., & Vaadia, E. (2004) · PLoS Biology · doi:10.1371/journal.pbio.0020045 · Cited by 77 · see citing works
Liu, X., & Scheidt, R. A. (2008) · Journal of Neurophysiology · doi:10.1152/jn.01044.2007 · Cited by 49 · see citing works
Viewing and doing: similar cortical mechanisms for perceptual and motor learning
Paz, R., Wise, S. P., & Vaadia, E. (2004) · Trends in Neurosciences · doi:10.1016/j.tins.2004.04.013 · Cited by 39 · see citing works
Flagged first, then by citations
2 of the 36 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Reach and grasp by people with tetraplegia using a neurally controlled robotic arm
Hochberg, L. R., Bacher, D., Jarosiewicz, B., Masse, N. Y., Simeral, J. D., Vogel, J., Haddadin, S., Liu, J., Cash, S. S., van der Smagt, P., et al. (2012) · Nature · doi:10.1038/nature11076 · Cited by 2,719 · see citing works
Self-citationHigh-performance neuroprosthetic control by an individual with tetraplegia
Collinger, J. L., Wodlinger, B., Downey, J. E., Wang, W., Tyler-Kabara, E. C., Weber, D. J., McMorland, A. J., Velliste, M., Boninger, M. L., & Schwartz, A. B. (2013) · The Lancet · doi:10.1016/s0140-6736(12)61816-9 · Cited by 1,848 · see citing works
Self-citationExplicit and implicit contributions to learning in a sensorimotor adaptation task
Taylor, J. A., Krakauer, J. W., & Ivry, R. B. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.3619-13.2014 · Cited by 768 · see citing works
Computation Through Neural Population Dynamics
Vyas, S., Golub, M. D., Sussillo, D., & Shenoy, K. V. (2020) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-092619-094115 · Cited by 671 · see citing works
Neural constraints on learning
Sadtler, P. T., Quick, K. M., Golub, M. D., Chase, S. M., Ryu, S. I., Tyler-Kabara, E. C., Yu, B. M., & Batista, A. P. (2014) · Nature · doi:10.1038/nature13665 · Cited by 713 · see citing works
Self-citationEmergence of a stable cortical map for neuroprosthetic control
Ganguly, K., & Carmena, J. M. (2009) · PLoS Biology · doi:10.1371/journal.pbio.1000153 · Cited by 578 · see citing works
Simeral, J. D., Kim, S.-P., Black, M. J., Donoghue, J. P., & Hochberg, L. R. (2011) · Journal of Neural Engineering · doi:10.1088/1741-2560/8/2/025027 · Cited by 496 · see citing works
Restoring sensorimotor function through intracortical interfaces: progress and looming challenges
Bensmaia, S. J., & Miller, L. E. (2014) · Nature Reviews Neuroscience · doi:10.1038/nrn3724 · Cited by 368 · see citing works
Jarosiewicz, B., Sarma, A. A., Bacher, D., Masse, N. Y., Simeral, J. D., Sorice, B., Oakley, E. M., Blabe, C., Pandarinath, C., Gilja, V., et al. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.aac7328 · Cited by 340 · see citing works
Self-citationA cortical neural prosthesis for restoring and enhancing memory
Berger, T. W., Hampson, R. E., Song, D. B., Goonawardena, A. V., Marmarelis, V. Z., & Deadwyler, S. A. (2011) · Journal of Neural Engineering · doi:10.1088/1741-2560/8/4/046017 · Cited by 316 · see citing works
Closed-Loop Decoder Adaptation Shapes Neural Plasticity for Skillful Neuroprosthetic Control
Orsborn, A. L., Moorman, H. G., Overduin, S. A., Shanechi, M. M., Dimitrov, D. F., & Carmena, J. M. (2014) · Neuron · doi:10.1016/j.neuron.2014.04.048 · Cited by 280 · see citing works
Competing Roles of Slow Oscillations and Delta Waves in Memory Consolidation versus Forgetting
Kim, J., Gulati, T., & Ganguly, K. (2019) · Cell · doi:10.1016/j.cell.2019.08.040 · Cited by 254 · see citing works
Learning by neural reassociation
Golub, M. D., Sadtler, P. T., Oby, E. R., Quick, K. M., Ryu, S. I., Tyler‐Kabara, E. C., Batista, A. P., Chase, S. M., & Yu, B. M. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0095-3 · Cited by 274 · see citing works
Self-citationPerge, J. A., Homer, M. L., Malik, W. Q., Cash, S., Eskandar, E., Friehs, G., Donoghue, J. P., & Hochberg, L. R. (2013) · Journal of Neural Engineering · doi:10.1088/1741-2560/10/3/036004 · Cited by 243 · see citing works
Tuning pathological brain oscillations with neurofeedback: a systems neuroscience framework
Ros, T., Baars, B. J., Lanius, R. A., & Vuilleumier, P. O. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.01008 · Cited by 263 · see citing works
Reversible large-scale modification of cortical networks during neuroprosthetic control
Ganguly, K., Dimitrov, D. F., Wallis, J. D., & Carmena, J. M. (2011) · Nature Neuroscience · doi:10.1038/nn.2797 · Cited by 259 · see citing works
Andersen, R. A., Hwang, E. J., & Mulliken, G. H. (2009) · Annual Review of Psychology · doi:10.1146/annurev.psych.093008.100503 · Cited by 238 · see citing works
New neural activity patterns emerge with long-term learning
Oby, E. R., Golub, M. D., Hennig, J. A., Degenhart, A. D., Tyler-Kabara, E. C., Yu, B. M., Chase, S. M., & Batista, A. P. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1820296116 · Cited by 221 · see citing works
“This would result in neural tuning changes that are coordinated across the population (6, 29).”
BackgroundSelf-citationWolpaw, J. R. (2013) · Handbook of clinical neurology · doi:10.1016/b978-0-444-52901-5.00006-x · Cited by 222 · see citing works
Neural Interface Technology for Rehabilitation: Exploiting and Promoting Neuroplasticity
Wang, W., Collinger, J. L., Pérez, M. A., Tyler‐Kabara, E. C., Cohen, L. G., Birbaumer, N., Brose, S. W., Schwartz, A. B., Boninger, M. L., & Weber, D. J. (2009) · Physical Medicine and Rehabilitation Clinics of North America · doi:10.1016/j.pmr.2009.07.003 · Cited by 208 · see citing works
Self-citationCombining Decoder Design and Neural Adaptation in Brain-Machine Interfaces
Shenoy, K. V., & Carmena, J. M. (2014) · Neuron · doi:10.1016/j.neuron.2014.08.038 · Cited by 175 · see citing works
The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
Perdikis, S., Tonin, L., Saeedi, S., Schneider, C., & Millán, J. D. R. (2018) · PLOS Biology · doi:10.1371/journal.pbio.2003787 · Cited by 166 · see citing works
Orsborn, A. L., Dangi, S., Moorman, H. G., & Carmena, J. M. (2012) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2012.2185066 · Cited by 171 · see citing works
Intracortical recording stability in human brain–computer interface users
Downey, J. E., Schwed, N., Chase, S. M., Schwartz, A. B., & Collinger, J. L. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aab7a0 · Cited by 149 · see citing works
Self-citationVolitional modulation of optically recorded calcium signals during neuroprosthetic learning
Clancy, K. B., Koralek, A. C., Costa, R. M., Feldman, D. E., & Carmena, J. M. (2014) · Nature Neuroscience · doi:10.1038/nn.3712 · Cited by 169 · see citing works
Challenges and Opportunities for Next-Generation Intracortically Based Neural Prostheses
Gilja, V., Chestek, C. A., Diester, I., Henderson, J. M., Deisseroth, K. A., & Shenoy, K. V. (2011) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2011.2107553 · Cited by 157 · see citing works
Rapid calibration of an intracortical brain–computer interface for people with tetraplegia
Brandman, D. M., Hosman, T., Saab, J., Burkhart, M. C., Shanahan, B. E., Ciancibello, J. G., Sarma, A. A., Milstein, D., Vargas-Irwin, C. E., Franco, B., et al. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aa9ee7 · Cited by 152 · see citing works
Self-citationLearning to move machines with the mind
Green, A. M., & Kalaska, J. F. (2010) · Trends in Neurosciences · doi:10.1016/j.tins.2010.11.003 · Cited by 154 · see citing works
Recording from the same neurons chronically in motor cortex
Fraser, G. W., & Schwartz, A. B. (2011) · Journal of Neurophysiology · doi:10.1152/jn.01012.2010 · Cited by 149 · see citing works
Self-citationHörzer, G. M., Legenstein, R. A., & Maass, W. (2012) · Cerebral Cortex · doi:10.1093/cercor/bhs348 · Cited by 135 · see citing works
Kozai, T. D. Y., Du, Z. J., Gugel, Z. V., Smith, M. A., Chase, S. M., Bodily, L., Caparosa, E. M., Friedlander, R. M., & Cui, X. T. (2014) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2014.12.010 · Cited by 135 · see citing works
Self-citationEvolution of brain-computer interfaces: going beyond classic motor physiology
Leuthardt, E. C., Schalk, G., Roland, J. L., Rouse, A. G., & Moran, D. W. (2009) · Neurosurgical FOCUS · doi:10.3171/2009.4.focus0979 · Cited by 135 · see citing works
Neural Population Dynamics Underlying Motor Learning Transfer
Vyas, S., Even-Chen, N., Stavisky, S. D., Ryu, S. I., Nuyujukian, P., & Shenoy, K. V. (2018) · Neuron · doi:10.1016/j.neuron.2018.01.040 · Cited by 138 · see citing works
Cortical preparatory activity indexes learned motor memories
Sun, X., O’Shea, D. J., Golub, M. D., Trautmann, E. M., Vyas, S., Ryu, S. I., & Shenoy, K. V. (2022) · Nature · doi:10.1038/s41586-021-04329-x · Cited by 137 · see citing works
Movement: How the Brain Communicates with the World
Schwartz, A. B. (2016) · Cell · doi:10.1016/j.cell.2016.02.038 · Cited by 131 · see citing works
Self-citationLegenstein, R. A., Chase, S. M., Schwartz, A. B., & Maass, W. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.4284-09.2010 · Cited by 132 · see citing works
Self-citationParietofrontal integrity determines neural modulation associated with grasping imagery after stroke
Buch, E. R., Shanechi, A. M., Fourkas, A. D., Weber, C., Birbaumer, N., & Cohen, L. G. (2012) · Brain · doi:10.1093/brain/awr331 · Cited by 132 · see citing works
Sensors and Decoding for Intracortical Brain Computer Interfaces
Homer, M. L., Nurmikko, A. V., Donoghue, J. P., & Hochberg, L. R. (2013) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-071910-124640 · Cited by 121 · see citing works
Neural reactivations during sleep determine network credit assignment
Gulati, T., Guo, L., Ramanathan, D. S., Bodepudi, A., & Ganguly, K. (2017) · Nature Neuroscience · doi:10.1038/nn.4601 · Cited by 114 · see citing works
Chase, S. M., Kass, R. E., & Schwartz, A. B. (2012) · Journal of Neurophysiology · doi:10.1152/jn.00371.2011 · Cited by 127 · see citing works
Self-citationBrain-Machine Interfaces beyond Neuroprosthetics
Moxon, K. A., & Foffani, G. (2015) · Neuron · doi:10.1016/j.neuron.2015.03.036 · Cited by 125 · see citing works
Gulati, T., Ramanathan, D., Wong, C. C., & Ganguly, K. (2014) · Nature Neuroscience · doi:10.1038/nn.3759 · Cited by 122 · see citing works
Preparatory activity and the expansive null-space
Churchland, M. M., & Shenoy, K. V. (2024) · Nature reviews. Neuroscience · doi:10.1038/s41583-024-00796-z · Cited by 126 · see citing works
Real neuroscience in virtual worlds
Dombeck, D. A., & Reiser, M. B. (2011) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2011.10.015 · Cited by 114 · see citing works
Stavisky, S. D., Kao, J. C., Ryu, S. I., & Shenoy, K. V. (2017) · Neuron · doi:10.1016/j.neuron.2017.05.023 · Cited by 111 · see citing works
Emergence of Coordinated Neural Dynamics Underlies Neuroprosthetic Learning and Skillful Control
Athalye, V. R., Ganguly, K., Costa, R. M., & Carmena, J. M. (2017) · Neuron · doi:10.1016/j.neuron.2017.01.016 · Cited by 105 · see citing works
Design and analysis of closed-loop decoder adaptation algorithms for brain-machine interfaces
Dangi, S., Orsborn, A. L., Moorman, H. G., & Carmena, J. M. (2013) · Neural Computation · doi:10.1162/neco_a_00460 · Cited by 103 · see citing works
Extraction of Network Topology From Multi-Electrode Recordings: Is there a Small-World Effect?
Gerhard, F., Pipa, G., Lima, B., Neuenschwander, S., & Gerstner, W. (2011) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2011.00004 · Cited by 105 · see citing works
Jarosiewicz, B., Masse, N. Y., Bacher, D., Cash, S. S., Eskandar, E. N., Friehs, G. M., Donoghue, J. P., & Hochberg, L. R. (2013) · Journal of Neural Engineering · doi:10.1088/1741-2560/10/4/046012 · Cited by 106 · see citing works
Self-citationReview: Human Intracortical Recording and Neural Decoding for Brain–Computer Interfaces
Brandman, D. M., Cash, S. S., & Hochberg, L. R. (2017) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2017.2677443 · Cited by 102 · see citing works
Moran, D. W. (2010) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2010.09.010 · Cited by 103 · see citing works
Brain–computer interfaces for dissecting cognitive processes underlying sensorimotor control
Golub, M. D., Chase, S. M., Batista, A. P., & Yu, B. M. (2016) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2015.12.005 · Cited by 98 · see citing works
Self-citationInvasive or Noninvasive: Understanding Brain-Machine Interface Technology [Conversations in BME
Millán, J. D. R., & Carmena, J. M. (2010) · IEEE Engineering in Medicine and Biology Magazine · doi:10.1109/memb.2009.935475 · Cited by 101 · see citing works
Interfacing the Somatosensory System to Restore Touch and Proprioception: Essential Considerations
Weber, D. J., Friesen, R., & Miller, L. E. (2012) · Journal of Motor Behavior · doi:10.1080/00222895.2012.735283 · Cited by 98 · see citing works
Decoding Three-Dimensional Reaching Movements Using Electrocorticographic Signals in Humans
Bundy, D. T., Pahwa, M., Szrama, N., & Leuthardt, E. (2016) · Journal of Neural Engineering · doi:10.1088/1741-2560/13/2/026021 · Cited by 101 · see citing works
From thought to action: The brain–machine interface in posterior parietal cortex
Andersen, R. A., Aflalo, T., & Kellis, S. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1902276116 · Cited by 90 · see citing works
Flint, R. D., Scheid, M. R., Wright, Z. A., Solla, S. A., & Slutzky, M. W. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.2339-15.2016 · Cited by 93 · see citing works
Intracortical Recording Interfaces: Current Challenges to Chronic Recording Function
Gunasekera, B., Saxena, T. K., Bellamkonda, R. V., & Karumbaiah, L. (2015) · ACS Chemical Neuroscience · doi:10.1021/cn5002864 · Cited by 92 · see citing works
Volitional Control of Neural Activity Relies on the Natural Motor Repertoire
Hwang, E. J., Bailey, P. M., & Andersen, R. A. (2013) · Current Biology · doi:10.1016/j.cub.2013.01.027 · Cited by 91 · see citing works
Brain-Machine Interfaces: A Tale of Two Learners
Perdikis, S., & Millán, J. D. R. (2020) · IEEE Systems Man and Cybernetics Magazine · doi:10.1109/msmc.2019.2958200 · Cited by 87 · see citing works
Hampson, R. E., Song, D. B., Chan, R. H. M., Sweatt, A. J., Riley, M. R., Gerhardt, G. A., Shin, D. C., Marmarelis, V. Z., Berger, T. W., & Deadwyler, S. A. (2012) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2012.2189163 · Cited by 89 · see citing works
The Emergence of Single Neurons in Clinical Neurology
Cash, S. S., & Hochberg, L. R. (2015) · Neuron · doi:10.1016/j.neuron.2015.03.058 · Cited by 86 · see citing works
Brain–Computer Interfaces in Neurorecovery and Neurorehabilitation
Young, M. J., Lin, D. J., & Hochberg, L. R. (2021) · Seminars in Neurology · doi:10.1055/s-0041-1725137 · Cited by 89 · see citing works
Information Systems Opportunities in Brain–Machine Interface Decoders
Kao, J. C., Stavisky, S. D., Sussillo, D., Nuyujukian, P., & Shenoy, K. V. (2014) · Proceedings of the IEEE · doi:10.1109/jproc.2014.2307357 · Cited by 84 · see citing works
Augmentation-related brain plasticity
Pino, G. D., Maravita, A., Zollo, L., Guglielmelli, E., & Lazzaro, V. D. (2014) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2014.00109 · Cited by 81 · see citing works
He, B., Gao, S., Yuan, H., & Wolpaw, J. R. (2012) · Springer eBooks · doi:10.1007/978-1-4614-5227-0_2 · Cited by 84 · see citing works
Toward More Versatile and Intuitive Cortical Brain–Machine Interfaces
Andersen, R. A., Kellis, S., Klaes, C., & Aflalo, T. (2014) · Current Biology · doi:10.1016/j.cub.2014.07.068 · Cited by 81 · see citing works
Brain-Machine Interfaces: Powerful Tools for Clinical Treatment and Neuroscientific Investigations
Slutzky, M. W. (2018) · The Neuroscientist · doi:10.1177/1073858418775355 · Cited by 84 · see citing works
A dynamical systems view of motor preparation
Shenoy, K. V., Kaufman, M. T., Sahani, M., & Churchland, M. M. (2011) · Progress in brain research · doi:10.1016/b978-0-444-53355-5.00003-8 · Cited by 81 · see citing works
Chirimuuta, M. (2024) · The MIT Press eBooks · doi:10.7551/mitpress/13804.001.0001 · Cited by 81 · see citing works
Xie, H. B., Liu, Y., Zhu, Y., Ding, X., Yang, Y., & Guan, J. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1316808111 · Cited by 78 · see citing works
Pohlmeyer, E. A., Mahmoudi, B., Geng, S., Prins, N. W., & Sanchez, J. C. (2014) · PLoS ONE · doi:10.1371/journal.pone.0087253 · Cited by 76 · see citing works
Decoding arm speed during reaching
Inoue, Y., Mao, H., Suway, S. B., Orellana, J., & Schwartz, A. B. (2018) · Nature Communications · doi:10.1038/s41467-018-07647-3 · Cited by 70 · see citing works
Self-citationDecoding the brain: From neural representations to mechanistic models
Mathis, M. W., Rotondo, A. P., Chang, E. F., Tolias, A. S., & Mathis, A. (2024) · Cell · doi:10.1016/j.cell.2024.08.051 · Cited by 82 · see citing works
Neural basis of sensorimotor learning: modifying internal models
Lalazar, H., & Vaadia, E. (2008) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2008.11.003 · Cited by 76 · see citing works
Single reach plans in dorsal premotor cortex during a two-target task
Dekleva, B. M., Kording, K. P., & Miller, L. E. (2018) · Nature Communications · doi:10.1038/s41467-018-05959-y · Cited by 70 · see citing works
Statistical assessment of the stability of neural movement representations
Stevenson, I. H., Cherian, A., London, B. M., Sachs, N. A., Lindberg, E. W., Reimer, J., Slutzky, M. W., Hatsopoulos, N. G., Miller, L. E., & Kording, K. P. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00626.2010 · Cited by 72 · see citing works
Neuronal Correlates of Memory Formation in Motor Cortex after Adaptation to Force Field
Arce‐McShane, F. I., Novick, I., Mandelblat-Cerf, Y., & Vaadia, E. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.1603-10.2010 · Cited by 69 · see citing works
Neural reinforcement: re-entering and refining neural dynamics leading to desirable outcomes
Athalye, V. R., Carmena, J. M., & Costa, R. M. (2019) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2019.11.023 · Cited by 63 · see citing works
Intention estimation in brain–machine interfaces
Fan, J. M., Nuyujukian, P., Kao, J. C., Chestek, C. A., Ryu, S. I., & Shenoy, K. V. (2014) · Journal of Neural Engineering · doi:10.1088/1741-2560/11/1/016004 · Cited by 68 · see citing works
Robust Neuroprosthetic Control from the Stroke Perilesional Cortex
Gulati, T., Won, S. J., Ramanathan, D., Wong, C. C., Bodepudi, A., Swanson, R. A., & Ganguly, K. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.5007-14.2015 · Cited by 67 · see citing works
Electrophysiological recordings from behaving animals—going beyond spikes
Chorev, E., Epsztein, J., Houweling, A. R., Lee, A. K., & Brecht, M. (2009) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2009.08.005 · Cited by 67 · see citing works
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 61 · see citing works
Brain–Machine Interface Control Algorithms
Shanechi, M. M. (2016) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2016.2639501 · Cited by 60 · see citing works
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 · see citing works
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 61 · see citing works
Self-recalibrating classifiers for intracortical brain–computer interfaces
Bishop, W. E., Chestek, C. A., Gilja, V., Nuyujukian, P., Foster, J. D., Ryu, S. I., Shenoy, K. V., & Yu, B. M. (2014) · Journal of Neural Engineering · doi:10.1088/1741-2560/11/2/026001 · Cited by 61 · see citing works
Feedback control policies employed by people using intracortical brain–computer interfaces
Willett, F. R., Pandarinath, C., Jarosiewicz, B., Murphy, B. A., Memberg, W. D., Blabe, C. H., Saab, J., Walter, B. L., Sweet, J. A., Miller, J. P., et al. (2016) · Journal of Neural Engineering · doi:10.1088/1741-2560/14/1/016001 · Cited by 61 · see citing works
Self-citationInternal 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 59 · see citing works
Self-citationInterfacing With the Computational Brain
Andrew, J. O., & Fetz, E. E. (2011) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2011.2158586 · Cited by 54 · see citing works
Oby, E. R., Éthier, C., & Miller, L. E. (2012) · Journal of Neurophysiology · doi:10.1152/jn.00331.2012 · Cited by 54 · see citing works
Mechanisms of Neurofeedback: A Computation-theoretic Approach
Davelaar, E. J. (2017) · Neuroscience · doi:10.1016/j.neuroscience.2017.05.052 · Cited by 56 · see citing works
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 51 · see citing works
Self-citationHiremath, 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 · see citing works
Donor/recipient enhancement of memory in rat hippocampus
Deadwyler, S. A., Berger, T. W., Sweatt, A. J., Song, D., Chan, R. H. M., Opris, I., Gerhardt, G. A., Marmarelis, V. Z., & Hampson, R. E. (2013) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2013.00120 · Cited by 64 · see citing works
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 52 · see citing works
Myoelectric control with abstract decoders
Dyson, M., Barnes, J., & Nazarpour, K. (2018) · Journal of Neural Engineering · doi:10.1088/1741-2552/aacbfe · Cited by 52 · see citing works
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 49 · see citing works
Learning to control a BMI-driven wheelchair for people with severe tetraplegia
Tonin, L., Perdikis, S., Kuzu, T. D., Pardo, J., Orset, B., Lee, K., Aach, M., Schildhauer, T. A., Martínez, R., & Millán, J. D. R. (2022) · iScience · doi:10.1016/j.isci.2022.105418 · Cited by 50 · see citing works
Brain computer interface to enhance episodic memory in human participants
Burke, J. F., Merkow, M. B., Jacobs, J., Kahana, M. J., & Zaghloul, K. A. (2015) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.01055 · Cited by 51 · see citing works
- Authors
- Jarosiewicz, B., Chase, S. M., Fraser, G. W., Velliste, M., Kass, R. E., & Schwartz, A. B.
- Affiliations
- University of Pittsburgh (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2008-12-09
- Volume
- 105
- Issue
- 49
- Pages
- 19486-19491
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC2614787
- OpenAlex
- W2128675085
- Cited by
- 302
- References
- 36
- Citations by year
- 2026: 5 · 2025: 12 · 2024: 15 · 2023: 8 · 2022: 11 · 2021: 9 · 2020: 10 · 2019: 19 · 2018: 19 · 2017: 18 · 2016: 19 · 2015: 29 · 2014: 34 · 2013: 22 · 2012: 24
- FWCI
- 8.27
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r01eb005847-04)
- National Institute of Neurological Disorders and Stroke (NS-2-2346)
- National Institute of Biomedical Imaging and Bioengineering (EB005847, R01-EB005847)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Keywords
- neural learning, brain-computer interface, motor cortex, single-unit recording, behavioral strategies, neural correlates of learning, monkeys
- MeSH terms
- Algorithms, Animals, Association Learning, Electrodes, Implanted, Macaca mulatta, Male, Models, Neurological, Motor Cortex, Neuronal Plasticity, Psychomotor Performance, User-Computer Interface, Neural Networks, Computer, Prostheses and Implants
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
