The DOI matches its Crossref record; 49 of the 50 references it cites were found in a registry or an index.
Virtual typing by people with tetraplegia using a self-calibrating intracortical brain-computer interface
Open accessAbstract
Individuals with tetraplegia are able to type self-paced for hours across multiple days using a self-calibrating point-and-click intracortical brain-computer interface.
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“Prior BCI studies have shown that the motor intention for gross motor skills, such as reaching, grasping or moving a computer cursor, remains neurally encoded in motor cortex after paralysis1–7.”
From High-performance brain-to-text communication via handwriting (2021) · cites this paper as [6]
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“any differences in average firing rates observed between two behaviors collected in separate blocks could be due to spurious drifts in firing rates known to occur across time63,64.”
From Inner speech in motor cortex and implications for speech neuroprostheses (2025) · cites this paper as [63]
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“While the ‘isolated ’verbal behavior experiments (section 3) allowed us to explore a large number of behaviors, it did not allow us to assess differences in neural representation between behaviors, because any differences between blocks could also be caused by spurious neural nonstationarity known to be occur in microelectrode array recordings63,64.”
From Inner speech in motor cortex and implications for speech neuroprostheses (2025) · cites this paper as [63]
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Citations
Cites
Isolated Hand Paresis: A Case Series
Alstadhaug, K. B., & Sjulstad, A. S. (2013) · Cerebrovascular Diseases Extra · doi:10.1159/000350708 · Cited by 4,090
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
Self-citationReach 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
Localization of the motor hand area to a knob on the precentral gyrus. A new landmark
Yousry, T. A. (1997) · Brain · doi:10.1093/brain/120.1.141 · Cited by 1,840
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
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
Brain–Computer InterfacesPrinciples and Practice
Wolpaw, J. R., & Wolpaw, E. W. (2012) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195388855.001.0001 · Cited by 1,134
ERD/ERS patterns reflecting sensorimotor activation and deactivation
Neuper, C., Woertz, M., & Pfurtscheller, G. (2006) · Progress in brain research · doi:10.1016/s0079-6123(06)59014-4 · Cited by 822
Spectral Changes in Cortical Surface Potentials during Motor Movement
Miller, K. J., Leuthardt, E. C., Schalk, G., Rao, R. P. N., Anderson, N., Moran, D. W., Miller, J. W., & Ojemann, J. G. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.3886-06.2007 · Cited by 743
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1 of the 50 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- S. Kim F. Wood M. Fellows J. P. Donoghue M. J. Black Statistical analysis of the non-stationarity of neural population codes in First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics Pisa Italy 20 to 22 February 2006 pp. 811–816.
- M. Golub S. Chase B. M. Yu in Proceedings of the 30th International Conference on Machine Learning (ICML-13) Atlanta GA 16 to 21 June 2013 pp. 606–614.
- N. Even-Chen S. D. Stavisky J. C. Kao S. I. Ryu K. V. Shenoy in IEEE Engineering in Medicine and Biology Society Milan Italy 25 to 29 August 2015.
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Items 301–342 of 342
Huang, J., Narasimha, S. M., Patel, A. N., Sristi, R. D., Mishne, G., & Gilja, V. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.02.715749 · Cited by 1
Self-citationBryson, J. B., & Greensmith, L. (2017) · Cambridge University Press eBooks · doi:10.1017/9781107281875.023
Algorithms for Neural Prosthetic Applications
Padmanaban, S. (2017)
Cryptographic decoding of movement
Gilja, V. (2017) · Nature Biomedical Engineering · doi:10.1038/s41551-017-0175-9
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Tzogia, M., & Papageorgiou, D. (2019) · Health & Research Journal · doi:10.12681/healthresj.19634
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Chen, D., So, R. Q., Ding, Y., & Guan, C. (2019) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner.2019.8717063
Zaidi, S. M. T., Kocatürk, S., Baykaş, T., & Kocatürk, M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.01.24.427325
Low-power machine learners for implantable decoding
Shaikh, S. D. (2021) · DR-NTU (Nanyang Technological University) · doi:10.32657/10356/146463
Stephens, T., Cafaro, J., MacRae, R., & Simons, S. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.18.444641
Millán, J. D. R., & Perdikis, S. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-818422-6.00059-9
Motor BMIs Have Entered the Clinical Realm
Caldwell, D. J., Herron, J. A., Ko, A. L., & Ojemann, J. G. (2023) · Handbook of Neuroengineering · doi:10.1007/978-981-16-5540-1_108
Colachis, S. C., Ganzer, P. D., Friedenberg, D. A., & Sharma, G. (2023) · Handbook of Neuroengineering · doi:10.1007/978-981-16-5540-1_119
Wan, Z., Liu, T., Ran, X., Liu, P., Chen, W., & Zhang, S. (2023) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2023.1135783 · Cited by 1
Nikam, P. L., Gayke, A. U., Avhad, P. S., Bhabad, R. B., & Malviya, R. (2023) · Wiley eBooks · doi:10.1002/9781394200344.ch10
Chen, K., Forrest, A., González‐Burgos, G., & Kozai, T. D. Y. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.11.06.565852
Decoding the Spike-Band Subthreshold Motor Cortical Activity
Okatan, M., & Kocatürk, M. (2023) · Journal of Motor Behavior · doi:10.1080/00222895.2023.2280263
Brain-Body Interfaces to Assist and Restore Motor Functions in People with Paralysis
Losanno, E., Badi, M., Roussinova, E., Bogaard, A. R., Delacombaz, M., Shokur, S., & Micera, S. (2023) · Springer briefs in electrical and computer engineering · doi:10.1007/978-3-031-49457-4_7
Neuromorphic model-based neural decoders for brain-computer interfaces: a comparative study
Weng, Y., Qi, Y., Wang, Y., & Pan, G. (2024) · IEEE Biomedical Circuits and Systems Conference (BioCAS) · doi:10.1109/biocas61083.2024.10798332
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Khan, S., Ali, K. U., Qadri, A. R. A., & Rizvi, M. (2025) · IEEE International Conference on AI in Cybersecurity (ICAIC) · doi:10.1109/icaic63015.2025.10849081
Differential motor neuron activity in rats during successful and failed grasping
Viaro, R., Bernardi, D., Maggiolini, E., D’Ausilio, A., Ferroni, C. G., Parmiani, P., & Fadiga, L. (2025) · Cerebral Cortex · doi:10.1093/cercor/bhaf032
Noninvasive BCI for Communication
Chaudhary, U. (2025) · Springer eBooks · doi:10.1007/978-3-031-78991-5_4
InfiniMind: A Learning-Optimized Large-Scale Brain-Computer Interface
Jang, Y., Jung, D., Song, S., Lee, H., & Kim, J. (2025) · Proceedings - International Symposium on Computer Architecture/Proceedings · doi:10.1145/3695053.3731067
Silva, L., Atencio, A. C., & Delisle-Rodríguez, D. (2025) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-3-031-94934-0_81
Andrade, P., Mercado, R. R. P. S., Jiménez, F., & Visser-Vandewalle, V. E. R. M. (2026) · Die Chirurgie · doi:10.1007/s00104-025-02436-3
An, S., Meng, Z., & Li, X. (2025) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm66473.2025.11356351
Wang, F., Chen, Y., Wang, P., Gong, A., Xu, J., & Fu, Y. (2026) · Scientific Data · doi:10.1038/s41597-026-06708-3 · Cited by 2
Stability of neural manifolds at minimal dimensionality despite motor representational driftPreprint
Abdulla, M. U., Clarke, S. E., Jun, E. J., & Nuyujukian, P. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.01.30.702162
Analysis of cortical activity for the development of brain-computer interfaces for speech
Roussel, P. (2021) · theses.fr (ABES) · doi:10.70675/809449c4z0d5az4ed2zb815z6c2c02ce8521
Shibah, S. R. M. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6481180
Zhou, B., & Basu, A. (2026) · Neuromorphic Computing and Engineering · doi:10.1088/2634-4386/ae6728
Premotor cortex uses a compositional neural geometry to plan wordsPreprint
Meschede-Krasa, B., Kunz, E. M., Kamdar, F. B., Avansino, D. T., Hahn, N. V., Singh, A., Card, N. S., Wairagkar, M., Iacobacci, C., Hochberg, L. R., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.27.721195
Self-citationMelby, S. R., Kumar, J. N. A., Bigus, E. R., & Kellis, S. (2026) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2026.1771146 · Cited by 1
Tang, G. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-38398-3_20
Decoding hindlimb movement states before and after spinal cord injury using local field potentials
Zhao, Z., Chen, D., Mao, H., Li, X., Li, W., Li, Q., & Zhang, P. (2026) · Brain Horizons · doi:10.1016/j.bhoriz.2026.07.001
Raza, I., Hussain, S. A., Jamal, M. H., & Ashraf, I. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2703893 · Cited by 4
Assistive algorithms influence neural representations in motor brain-computer interfaces
Rajeswaran, P., Payeur, A., Lajoie, G., & Orsborn, A. L. (2026) · Nature Communications · doi:10.1038/s41467-026-76109-y · Cited by 11
Huggins, J. E., Mattia, D., Aarnoutse, E. J., Allison, B. Z., Berezutskaya, J., Bianchi, L., Chavarriaga, R., Corsi, M., Dean, H., Fernandes, F., et al. (2026) · Research in Biomedical Engineering and Technology · doi:10.1080/29960355.2026.2731643
Generalizable neural decoding for clinically scalable brain-computer interfaces
Gu, Y., Yin, H., Wang, Y., Woon, Y.-Q.-V., Wang, Y., Teng, M., Lu, C., Lü, Z., & Chen, J. (2026) · npj Biomedical Innovations. · doi:10.1038/s44385-026-00119-0
Wu, Y., Chang, T., Chen, S., Quan, Y., Sun, Q., Hulle, M. M. V., Liu, Y., Jiang, N., Farina, D., Yang, Y., et al. (2026) · Science Advances · doi:10.1126/sciadv.adx5564
Xing, B., Zhang, L., & Tu, W.-J. (2026) · Frontiers in Neuroscience · doi:10.3389/fnins.2026.1994636
Metadata
- Authors
- Jarosiewicz, B., Sarma, A. A., Bacher, D., Masse, N. Y., Simeral, J. D., Sorice, B., Oakley, E. M., Blabe, C., Pandarinath, C., Gilja, V., Cash, S. S., Eskandar, E. N., Friehs, G., Henderson, J. M., Shenoy, K. V., Donoghue, J. P., & Hochberg, L. R.
- Affiliations
- Brown University (US)
- Massachusetts General Hospital (US)
- Stanford Medicine (US)
- Harvard University (US)
- Rhode Island Hospital (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Jarosiewicz, Beata
- Friehs, Gerhard
- Donoghue, John P.
- ORCID
- Venue
- Science Translational Medicine
- Published
- 2015-11-11
- Volume
- 7
- Issue
- 313
- Pages
- 313ra179-313ra179
- ISSN
- 1946-6234 (ISSN-L)
- 1946-6242
- PMC
- PMC4765319
- OpenAlex
- W2243428647
- Cited by
- 340
- References
- 50
- Citations by year
- 2026: 26 · 2025: 31 · 2024: 34 · 2023: 35 · 2022: 25 · 2021: 29 · 2020: 44 · 2019: 23 · 2018: 32 · 2017: 39 · 2016: 21 · 2015: 1
- FWCI
- 18.65
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science Translational Medicine (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- NIH: National Institute on Deafness and Other Communication Disorders (R01DC009899, R01DC014034)
- National Institute of Neurological Disorders and Stroke (RO1NS066311-S1)
- NICHD (RC1HD063931)
- Doris Duke Charitable Foundation
- Craig H. Neilsen Foundation
- Massachusetts General Hospital (MGH)
- Office of Research and Development, Rehabilitation R&D Service, Department of Veterans Affairs (B6310W, B6453R, B6459L, A6779I)
- National Institute of Child Health and Human_National Center for Medical Rehabilitation Research (NICHD-NCMRR) (N01HD53403)
- Joseph Martin Prize for Basic Research
- Katie Samson Foundation
- Stanford Institute for Neuro-Innovation and Translational Neuroscience
- Stanford BioX-NeuroVentures
- Garlick Family
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Keywords
- intracortical brain-computer interfaces, tetraplegia, self-calibration, neural decoding, augmentative and alternative communication, paralysis
- MeSH terms
- Amyotrophic Lateral Sclerosis, Calibration, Female, Humans, Male, Motor Cortex, Quadriplegia, Self-Help Devices, Stroke, Brain-Computer Interfaces
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