A Study on the Application of a Linearly-constrained Adaptive Beamformer to fMRI-MEG Integrative Analysis
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- OHASHI Shumpei
- Faculty of Engineering, Graduate School of Kyoto University
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- INNAMI Yasuyuki
- Faculty of Engineering, Graduate School of Kyoto University
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- JUNG Jiuk
- Faculty of Engineering, Graduate School of Kyoto University
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- HAMADA Shoji
- Faculty of Engineering, Graduate School of Kyoto University
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- KOBAYASHI Tetsuo
- Faculty of Engineering, Graduate School of Kyoto University
Bibliographic Information
- Other Title
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- fMRI-MEG統合解析への線形制約付きアダプティブビームフォーマの適用に関する検討
- fMRI MEG トウゴウ カイセキ エノ センケイ セイヤク ツキ アダプティブ ビームフォーマ ノ テキヨウ ニ カンスル ケントウ
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Abstract
Focusing on the application of linearly-constrained adaptive beamformer techniques to fMRI-MEG integrative analysis, we have examined an approach which determines the center of gravity in each fMRI activated cluster as the location of the linear constraints. First, we simulated MEG data generated from two sources distributed in circular forms placed at visual areas V2 and V5, which are temporally strongly correlated. Two fMRI activated clusters are assumed to cover the two sources. The linear constraints for the voxels in a cluster are defined to suppress the power from the source at the center of gravity of the other cluster. The spatial distributions and the time courses of the two correlated sources at V2 and V5 are successfully reconstructed. We applied the approach to data obtained during an apparent motion perception task and were able to confirm its availability. These results demonstrate that the proposed approach based on linearly-constrained adaptive beamformer techniques is promising as an fMRI-MEG integrative analysis.
Journal
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- Transactions of Japanese Society for Medical and Biological Engineering
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Transactions of Japanese Society for Medical and Biological Engineering 44 (4), 722-727, 2006
Japanese Society for Medical and Biological Engineering
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Details 詳細情報について
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- CRID
- 1390001205267916160
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- NII Article ID
- 110006249836
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- NII Book ID
- AA11633569
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- ISSN
- 18814379
- 1347443X
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- NDL BIB ID
- 8788199
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed