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Dr. R. Omar Chavez-Garcia Postdoctoral Researcher IDSIA, IDSIA Funding: Matching funds

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Harnessing prefrontal cognitive signals for brain-machine interfaces

  • Authors: Min, Byoung-Kyong; Chavarriaga, Ricardo; Millán, José del R.

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.

Posted on: March 27, 2017