Harnessing Prefrontal Cognitive Signals for Brain-Machine Interfaces
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Min, Byoung-Kyong | - |
dc.contributor.author | Chavarriaga, Ricardo | - |
dc.contributor.author | Millan, Jose del R. | - |
dc.date.accessioned | 2021-09-03T04:32:28Z | - |
dc.date.available | 2021-09-03T04:32:28Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2017-07 | - |
dc.identifier.issn | 0167-7799 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/82986 | - |
dc.description.abstract | 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. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCIENCE LONDON | - |
dc.subject | POSTERIOR PARIETAL CORTEX | - |
dc.subject | COMPUTER INTERFACES | - |
dc.subject | MOTOR IMAGERY | - |
dc.subject | EEG | - |
dc.subject | POTENTIALS | - |
dc.subject | NEUROFEEDBACK | - |
dc.subject | AUTISM | - |
dc.subject | COMMUNICATION | - |
dc.subject | ASSOCIATION | - |
dc.subject | INTENTION | - |
dc.title | Harnessing Prefrontal Cognitive Signals for Brain-Machine Interfaces | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Min, Byoung-Kyong | - |
dc.identifier.doi | 10.1016/j.tibtech.2017.03.008 | - |
dc.identifier.scopusid | 2-s2.0-85017342837 | - |
dc.identifier.wosid | 000403246400005 | - |
dc.identifier.bibliographicCitation | TRENDS IN BIOTECHNOLOGY, v.35, no.7, pp.585 - 597 | - |
dc.relation.isPartOf | TRENDS IN BIOTECHNOLOGY | - |
dc.citation.title | TRENDS IN BIOTECHNOLOGY | - |
dc.citation.volume | 35 | - |
dc.citation.number | 7 | - |
dc.citation.startPage | 585 | - |
dc.citation.endPage | 597 | - |
dc.type.rims | ART | - |
dc.type.docType | Review | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Biotechnology & Applied Microbiology | - |
dc.relation.journalWebOfScienceCategory | Biotechnology & Applied Microbiology | - |
dc.subject.keywordPlus | POSTERIOR PARIETAL CORTEX | - |
dc.subject.keywordPlus | COMPUTER INTERFACES | - |
dc.subject.keywordPlus | MOTOR IMAGERY | - |
dc.subject.keywordPlus | EEG | - |
dc.subject.keywordPlus | POTENTIALS | - |
dc.subject.keywordPlus | NEUROFEEDBACK | - |
dc.subject.keywordPlus | AUTISM | - |
dc.subject.keywordPlus | COMMUNICATION | - |
dc.subject.keywordPlus | ASSOCIATION | - |
dc.subject.keywordPlus | INTENTION | - |
dc.subject.keywordAuthor | brain–machine interface | - |
dc.subject.keywordAuthor | cognition | - |
dc.subject.keywordAuthor | electroencephalography | - |
dc.subject.keywordAuthor | prefrontal cortex | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
145 Anam-ro, Seongbuk-gu, Seoul, 02841, Korea+82-2-3290-2963
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.