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| Presentation | 2019-06-17 15:00 Meta-analysis fMRI data helps robust source reconstruction of MEG measurements Keita Suzuki (NAIST), Okito Yamashita (ATR)  NC2019-5 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) are the major recording means of brain activity. FMRI records brain activity with high spatial resolution but its temporal resolution is low due to slow hemodynamic responses to neural activity. Conversely, MEG has characteristics that the temporal resolution is high but spatial resolution is low. One of the solution is combining both records of fMRI and MEG so that we can estimate high spatio-temporal brain activity. However, taking into consideration the measurement cost and the burden on the subject, it is difficult to obtain high quality measurement data of both modalities. Therefore, we propose combining MEG data with meta-analysis fMRI instead of measured one. And also, we developed realistic simulation framework to evaluate our proposal. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | MEG / source reconstruction / variational Bayesian / meta-analysis / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 88, NC2019-5, pp. 21-25, June 2019. | |
| Paper # | NC2019-5 | |
| Date of Issue | 2019-06-10 (NC) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | NC2019-5 |
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| Conference Information | |
| Committee | NC IBISML IPSJ-MPS IPSJ-BIO |
| Conference Date | 2019-06-17 - 2019-06-19 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Okinawa Institute of Science and Technology |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Neurocomputing, Machine Learning Approach to Biodata Mining, and General |
| Paper Information | |
| Registration To | NC |
| Conference Code | 2019-06-NC-IBISML-MPS-BIO |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Meta-analysis fMRI data helps robust source reconstruction of MEG measurements |
| Sub Title (in English) | |
| Keyword(1) | MEG |
| Keyword(2) | source reconstruction |
| Keyword(3) | variational Bayesian |
| Keyword(4) | meta-analysis |
| Keyword(5) | |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Keita Suzuki |
| 1st Author's Affiliation | Nara Institute of Science and Technology (NAIST) |
| 2nd Author's Name | Okito Yamashita |
| 2nd Author's Affiliation | Advanced Telecommunications Research Institute International (ATR) |
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| Speaker | Author-1 |
| Date Time | 2019-06-17 15:00:00 |
| Presentation Time | 25 minutes |
| Registration for | NC |
| Paper # | NC2019-5 |
| Volume (vol) | vol.119 |
| Number (no) | no.88 |
| Page | pp.21-25 |
| #Pages | 5 |
| Date of Issue | 2019-06-10 (NC) |
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