Improve accuracy of BCI by detecting intention-related brain activity from EEG and MEG data
| Project/Area Number |
23700499
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Fusional brain recording science
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| Research Institution | Advanced Telecommunications Research Institute International |
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Principal Investigator |
TAKEDA Yusuke 株式会社国際電気通信基礎技術研究所, 脳情報通信総合研究所, 専任研究員 (60505981)
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| Project Period (FY) |
2011-04-28 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2014: ¥260,000 (Direct Cost: ¥200,000、Indirect Cost: ¥60,000)
Fiscal Year 2013: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2012: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2011: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
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| Keywords | ブレイン－コンピュータ・インタフェース（BCI） / 脳波 / 脳磁図 / 運動想像 / 運動意図 / 自発脳活動 / レスティングステート / fMRI / 意図 / 想像 / BCI |
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| Outline of Final Research Achievements |
The purpose of this study is to improve the accuracy of brain-computer interface (BCI) by detecting intention-related brain activities from EEG and MEG data. To this end, from EEG during motor imagery, we revealed waveforms that occur with unknown delays after stimulus onset (unlocked waveform). We proposed a procedure to examine the roles of unlocked waveforms. Furthermore, we proposed a method to estimate repetitive spatiotemporal patterns from resting-state brain activity data.
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Report
(5 results)
Research Products
(8 results)
