Neuroscience 2005 Abstract
| Presentation Number: | 771.12 |
|---|---|
| Abstract Title: | Analysis of language priming in cognition level using MEG pattern analysis. |
| Authors: |
Matani, A.*1
; Hayakawa, T.
; Fujimaki, N.
1Univ. of Tokyo, Kashiwa, Japan |
| Primary Theme and Topics |
Cognition and Behavior - Human Cognition, Behavior, and Anatomy -- Language |
| Secondary Theme and Topics | Techniques in Neuroscience<br />- Data Analysis and Statistics |
| Session: |
771. Language IV Poster |
| Presentation Time: | Tuesday, November 15, 2005 4:00 PM-5:00 PM |
| Location: | Washington Convention Center - Hall A-C, Board # OO11 |
| Keywords: | LANGUAGE, MAGNETOENCEPHALOGRAPHY, COGNITION |
We have proposed an MEG pattern analysis method, called virtual beamformer (VB), for comparing two MEG data [1,2]. MEG data of semantic priming for visually presented words were analyzed with VB. A prime and a target words respectively consisting of three and five Japanese katakana characters were presented (duration: 100ms, ISI: 900ms). Subjects with informed consent were asked for a categorization task for the target words by pressing a yes/no button. There were four combination among the prime and target words, #1) in-category/target, #2) out-category/target, #3) out-category/nontarget, and #4) in-category/nontarget. In VB analysis MEG spatio-temporal pattern, which worked like a conventional filtering kernel, was first leaned from the target MEG data #1 excluding the button-pressing MEG response. The other target MEG data were then analyzed with the pattern. As a result, only VB output #2 revealed a conspicuous peak around latency of 500ms. In the case of the pattern learning in the same way except from #3, only VB output #4 had the same kind of peak. These results imply that yes/no answer can be distinguished only from MEG data. The relationship between the prime and target was also investigated using VB. The pattern was learned from the prime MEG data #1, and then the target MEG data #1 and #4 were scanned with VB. As a result, only VB output #4 had a conspicuous peak. This may indicate that a neuronal activity is activated by the semantic incongruity. Therefore VB can be a potential tool for MEG recognition to understand human cognition.
This work was partially supported by a Grant-in-Aid from the Ministry of Education, Culture, Sports, Science and Technology (No. 16300083).
[1] A. Matani, Y. Masuda, H. Okubo, and K. Chihara, Hierarchical Clustering and Filtering in Half-inverse Space for MEG and/or EEG Hypothesis-free Analysis. IEEE Trans. on SP, 51(2), 350-361, 2003.
[2] A. Matani, T. Hayakawa, S. Munetsuna, and N. Fujimaki, MEG Latency Difference Measurement for Priming Experiments. J. Neurology and Clinical Neurophysiology, Online J., 2004.
This work was partially supported by a Grant-in-Aid from the Ministry of Education, Culture, Sports, Science and Technology (No. 16300083).
[1] A. Matani, Y. Masuda, H. Okubo, and K. Chihara, Hierarchical Clustering and Filtering in Half-inverse Space for MEG and/or EEG Hypothesis-free Analysis. IEEE Trans. on SP, 51(2), 350-361, 2003.
[2] A. Matani, T. Hayakawa, S. Munetsuna, and N. Fujimaki, MEG Latency Difference Measurement for Priming Experiments. J. Neurology and Clinical Neurophysiology, Online J., 2004.
Sample Citation:
[Authors]. [Abstract Title]. Program No. XXX.XX. 2005 Neuroscience Meeting Planner. Washington, DC: Society for Neuroscience, 2005. Online.
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