Neuroimaging-based approaches in the brain-computer interface

被引:98
作者
Min, Byoung-Kyong [1 ]
Marzelli, Matthew J. [2 ]
Yoo, Seung-Schik [1 ]
机构
[1] Harvard Univ, Brigham & Womens Hosp, Dept Radiol, Sch Med, Boston, MA 02115 USA
[2] Stanford Univ, Dept Psychiat & Behav Sci, Sch Med, Stanford, CA 94305 USA
关键词
NEAR-INFRARED SPECTROSCOPY; FUNCTIONAL MRI; MOTOR IMAGERY; EEG; NEUROFEEDBACK; ACTIVATION; BCI; CLASSIFICATION; STIMULATION; CORTEX;
D O I
10.1016/j.tibtech.2010.08.002
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Techniques to enable direct communication between the brain and computers/machines, such as the brain computer interface (BCI) or the brain-machine interface (BMI), are gaining momentum in the neuroscientific realm, with potential applications ranging from medicine to general consumer electronics. Noninvasive BCI techniques based on neuroimaging modalities are reviewed in terms of their methodological approaches as well as their similarities and differences. Trends in automated data interpretation through machine learning algorithms are also introduced. Applications of functional neuromodulation techniques to BCI systems would allow for bidirectional communication between the brain and the computer. Such bidirectional interfaces can relay information directly from one brain to another using a computer as a medium, ultimately leading to the concept of a brain-to-brain interface (BM).
引用
收藏
页码:552 / 560
页数:9
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