Harnessing Prefrontal Cognitive Signals for Brain–Machine Interfaces

Byoung-Kyong Min, Ricardo Chavarriaga, José del R. Millán

Research output: Contribution to journalReview articlepeer-review

24 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)585-597
Number of pages13
JournalTrends in Biotechnology
Issue number7
Publication statusPublished - 2017 Jul

Bibliographical note

Funding Information:
This work was supported by the Basic Science Research program funded by the Ministry of Science, ICT, and Future Planning through the National Research Foundation of Korea (grant number 2015R1A1A1A05027233) and the Swiss National Center of Competence in Research (NCCR) Robotics.

Publisher Copyright:
© 2017 Elsevier Ltd


  • brain–machine interface
  • cognition
  • electroencephalography
  • prefrontal cortex

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering


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