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210512 ||| eng |
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|a 978-2-88945-614-7
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|a 9782889456147
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|a Manuel F. Casanova
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|a Augmentation of Brain Function: Facts, Fiction and Controversy. Volume I: Brain-Machine Interfaces
|h Elektronische Ressource
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| 260 |
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|b Frontiers Media SA
|c 2018
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| 300 |
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|a 1 electronic resource (666 p.)
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| 653 |
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|a TMS
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| 653 |
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|a implants
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| 653 |
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|a neural networks
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| 653 |
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|a tDCStranscranial direct current stimulation
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| 653 |
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|a Neurosciences / bicssc
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| 653 |
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|a nootropics
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| 653 |
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|a Brain machine interface (BMI)
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| 653 |
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|a microcircuits
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| 653 |
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|a neuroprosthesis
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| 700 |
1 |
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|a Ioan Opris
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| 700 |
1 |
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|a Mikhail Lebedev
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 490 |
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|a Frontiers Research Topics
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
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| 028 |
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|a 10.3389/978-2-88945-614-7
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| 856 |
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|u https://directory.doabooks.org/handle/20.500.12854/41576
|z DOAB: description of the publication
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| 856 |
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|u https://www.frontiersin.org/research-topics/1563/augmentation-of-brain-function-facts-fiction-and-controversy#overview
|7 0
|x Verlag
|3 Volltext
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|a 580
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|a Volume I, entitled "Augmentation of Brain Functions: Brain-Machine Interfaces", is a collection of articles on neuroprosthetic technologies that utilize brain-machine interfaces (BMIs). BMIs strive to augment the brain by linking neural activity, recorded invasively or noninvasively, to external devices, such as arm prostheses, exoskeletons that enable bipedal walking, means of communication and technologies that augment attention. In addition to many practical applications, BMIs provide useful research tools for basic science. Several articles cover challenges and controversies in this rapidly developing field, such as ways to improve information transfer rate. BMIs can be applied to the awake state of the brain and to the sleep state, as well. BMIs can augment action planning and decision making. Importantly, BMI operations evoke brain plasticity, which can have long-lasting effects. Advanced neural decoding algorithms that utilize optimal feedback controllers are key to the BMI performance. BMI approach can be combined with the other augmentation methods; such systems are called hybrid BMIs. Overall, it appears that BMI will lead to many powerful and practical brain-augmenting technologies in the future.
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