Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Harnessing Prefrontal Cognitive Signals for Brain-Machine Interfaces

Authors
Min, Byoung-KyongChavarriaga, RicardoMillan, Jose del R.
Issue Date
7월-2017
Publisher
ELSEVIER SCIENCE LONDON
Keywords
brain–machine interface; cognition; electroencephalography; prefrontal cortex
Citation
TRENDS IN BIOTECHNOLOGY, v.35, no.7, pp.585 - 597
Indexed
SCIE
SCOPUS
Journal Title
TRENDS IN BIOTECHNOLOGY
Volume
35
Number
7
Start Page
585
End Page
597
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/82986
DOI
10.1016/j.tibtech.2017.03.008
ISSN
0167-7799
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.
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > Department of Brain and Cognitive Engineering > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE