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research article

Harnessing prefrontal cognitive signals for brain-machine interfaces

Min, Byoung-Kyong
•
Chavarriaga, Ricardo  
•
Millán, José del R.  
2017
Trends in Biotechnology

Brain-machine interfaces (BMIs) enable humans to interact with devices by modulating their brain signals. Despite impressive technological advancements, several obstacles remain. The most commonly used BMI control signals are derived from the brain areas involved in primary sensory- or motor-related processing. However, these signals only reflect a limited range of human intentions. Therefore, additional sources of brain activity for controlling BMIs need to be explored. In particular, higher-order cognitive brain signals, specifically those encoding goal-directed intentions are natural candidates for enlarging the repertoire of BMI control signals and making them more efficient and intuitive. Thus, this paper identifies the prefrontal brain area as a key target region for future BMIs, given its involvement in higher-order, goal-oriented cognitive processes.

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Type
research article
DOI
10.1016/j.tibtech.2017.03.008
Web of Science ID

WOS:000403246400005

Author(s)
Min, Byoung-Kyong
Chavarriaga, Ricardo  
Millán, José del R.  
Date Issued

2017

Publisher

Elsevier

Published in
Trends in Biotechnology
Volume

35

Issue

7

Start page

585

End page

597

Subjects

brain-machine interface

•

cognition

•

electroencephalography

•

prefrontal cortex

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
CNP  
CNBI  
NCCR-ROBOTICS  
Available on Infoscience
March 27, 2017
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/135797
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