 Brain-Computer Interfaces
"Brain-Computer Interfaces" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
Instrumentation consisting of hardware and software that communicates with the BRAIN. The hardware component of the interface records brain signals, while the software component analyzes the signals and converts them into a command that controls a device or sends a feedback signal to the brain.
| Descriptor ID |
D062207
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| MeSH Number(s) |
E07.305.076
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| Concept/Terms |
Brain-Computer Interfaces- Brain-Computer Interfaces
- Brain Computer Interfaces
- Interface, Brain-Computer
- Interfaces, Brain-Computer
- Brain-Computer Interface
- Brain Computer Interface
Brain-Machine Interfaces- Brain-Machine Interfaces
- Brain Machine Interfaces
- Brain-Machine Interface
- Interface, Brain-Machine
- Interfaces, Brain-Machine
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Below are MeSH descriptors whose meaning is more general than "Brain-Computer Interfaces".
Below are MeSH descriptors whose meaning is more specific than "Brain-Computer Interfaces".
This graph shows the total number of publications written about "Brain-Computer Interfaces" by people in this website by year, and whether "Brain-Computer Interfaces" was a major or minor topic of these publications.
To see the data from this visualization as text, click here.
| Year | Major Topic | Minor Topic | Total |
|---|
| 2012 | 1 | 0 | 1 | | 2013 | 4 | 2 | 6 | | 2014 | 0 | 3 | 3 | | 2015 | 4 | 0 | 4 | | 2016 | 3 | 1 | 4 |
To return to the timeline, click here.
Below are the most recent publications written about "Brain-Computer Interfaces" by people in Profiles.
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Nakagame S, Gorges J, Nathan K, Contreras-Vidal JL. Unscented Kalman filter for neural decoding of human treadmill walking from non-invasive electroencephalography. Conf Proc IEEE Eng Med Biol Soc. 2016 Aug; 2016:1548-1551.
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Agashe HA, Paek AY, Contreras-Vidal JL. Multisession, noninvasive closed-loop neuroprosthetic control of grasping by upper limb amputees. Prog Brain Res. 2016; 228:107-28.
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Bowsher K, Civillico EF, Coburn J, Collinger J, Contreras-Vidal JL, Denison T, Donoghue J, French J, Getzoff N, Hochberg LR, Hoffmann M, Judy J, Kleitman N, Knaack G, Krauthamer V, Ludwig K, Moynahan M, Pancrazio JJ, Peckham PH, Pena C, Pinto V, Ryan T, Saha D, Scharen H, Shermer S, Skodacek K, Takmakov P, Tyler D, Vasudevan S, Wachrathit K, Weber D, Welle CG, Ye M. Brain-computer interface devices for patients with paralysis and amputation: a meeting report. J Neural Eng. 2016 Apr; 13(2):023001.
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Buccino AP, Keles HO, Omurtag A. Hybrid EEG-fNIRS Asynchronous Brain-Computer Interface for Multiple Motor Tasks. PLoS One. 2016; 11(1):e0146610.
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Marsh BT, Tarigoppula VS, Chen C, Francis JT. Toward an autonomous brain machine interface: integrating sensorimotor reward modulation and reinforcement learning. J Neurosci. 2015 May 13; 35(19):7374-87.
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Bae J, Sanchez Giraldo LG, Pohlmeyer EA, Francis JT, Sanchez JC, PrÃncipe JC. Kernel temporal differences for neural decoding. Comput Intell Neurosci. 2015; 2015:481375.
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He Y, Contreras-Vidal JL. Classification of finger vibrotactile input using scalp EEG. Conf Proc IEEE Eng Med Biol Soc. 2015; 2015:4717-20.
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Jiang T, Ince NF, Jiang T, Wang T, Mei S, Li Y, Wang X, Sha Z. Local spatial correlation analysis of hand flexion/extension using intraoperative high-density ECoG. Conf Proc IEEE Eng Med Biol Soc. 2015; 2015:6190-3.
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Li L, Brockmeier AJ, Choi JS, Francis JT, Sanchez JC, PrÃncipe JC. A tensor-product-kernel framework for multiscale neural activity decoding and control. Comput Intell Neurosci. 2014; 2014:870160.
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Agashe HA, Contreras-Vidal JL. Observation-based training for neuroprosthetic control of grasping by amputees. Conf Proc IEEE Eng Med Biol Soc. 2014; 2014:3989-92.
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