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Paper Abstract and Keywords
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
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

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  
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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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