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Harnessing Prefrontal Cognitive Signals for Brain-Machine Interfaces.
Journal article

Harnessing Prefrontal Cognitive Signals for Brain-Machine Interfaces.

  • Min BK Department of Brain and Cognitive Engineering, Korea University, Seoul 02841, Republic of Korea. Electronic address: min_bk@korea.ac.kr.
  • Chavarriaga R Defitech Chair in Brain-Machine Interface, Center for Neuroprosthetics, School of Engineering, École Polytechnique Fédérale de Lausanne, 1202, Genève, Switzerland.
  • Millán JDR Defitech Chair in Brain-Machine Interface, Center for Neuroprosthetics, School of Engineering, École Polytechnique Fédérale de Lausanne, 1202, Genève, Switzerland.
  • 2017-04-09
Published in:
  • Trends in biotechnology. - 2017
brain–machine interface
cognition
electroencephalography
prefrontal cortex
Animals
Brain Waves
Brain-Computer Interfaces
Cognition
Humans
Prefrontal Cortex
English 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, here, we identify the prefrontal brain area as a key target region for future BMIs, given its involvement in higher-order, goal-oriented cognitive processes.
Language
  • English
Open access status
closed
Identifiers
Persistent URL
https://sonar.ch/global/documents/99523
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