The DOI matches its Crossref record; 34 of the 36 references it cites were found in a registry or an index.
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.
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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 [24]
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Self-citationDirect Cortical Control of 3D Neuroprosthetic Devices
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Self-citationReal-time prediction of hand trajectory by ensembles of cortical neurons in primates
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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
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
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
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
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
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Metadata
- 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
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