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Paper Abstract and Keywords
Presentation 2021-03-04 09:50
Evaluation of effect of source noise on magnetoencephalography source estimation using a structured sparse model
Kai Miyazaki, Shun Nirasawa, Kazuaki Akamatsu, Yoichi Miyawaki (UEC) NC2020-56
Abstract (in Japanese) (See Japanese page) 
(in English) Magnetoencephalography (MEG) is a method to acquire human brain activity at a high temporal resolution, but its spatial resolution is insufficient to examine active cortical locations. Previous studies have shown that source estimation methods identify active cortical locations with reasonable accuracy and are thus used in various applications of human functional neuroimaging. However, our recent studies suggest that the combination of the source estimation and multivariate pattern analysis (for example, neural decoding) produces “information spreading,” a false positive phenomenon in terms of the identification of informative cortical areas. To resolve this problem, we proposed the application of grouped automatic relevance determination (gARD) that implements functional parcellation of the human brain, showing its better performance to analyze task-relevant brain activity than conventional source estimations. In this study, we further examined the effect of task-irrelevant components such as spontaneous activity on source estimation accuracy and the extent of suppression of information spreading. Results showed that gARD achieved better performance in suppressing information spreading and identifying informative cortical locations while showing source estimation performance equivalent to the conventional method under the noise condition close to real data. These results suggest that our method might be useful for identifying task-relevant source activity and analyzing the corresponding information representation under a mixture of a variety of task-irrelevant cortical activity.
Keyword (in Japanese) (See Japanese page) 
(in English) MEG source estimation / structured sparse model / gARD / information spreading / source noise / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 403, NC2020-56, pp. 77-82, March 2021.
Paper # NC2020-56 
Date of Issue 2021-02-24 (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 NC2020-56

Conference Information
Committee NC MBE  
Conference Date 2021-03-03 - 2021-03-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Neuro Computing, Medical Engineering, etc. 
Paper Information
Registration To NC 
Conference Code 2021-03-NC-MBE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Evaluation of effect of source noise on magnetoencephalography source estimation using a structured sparse model 
Sub Title (in English)  
Keyword(1) MEG source estimation  
Keyword(2) structured sparse model  
Keyword(3) gARD  
Keyword(4) information spreading  
Keyword(5) source noise  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Kai Miyazaki  
1st Author's Affiliation The University of Electro-Communications (UEC)
2nd Author's Name Shun Nirasawa  
2nd Author's Affiliation The University of Electro-Communications (UEC)
3rd Author's Name Kazuaki Akamatsu  
3rd Author's Affiliation The University of Electro-Communications (UEC)
4th Author's Name Yoichi Miyawaki  
4th Author's Affiliation The University of Electro-Communications (UEC)
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Speaker Author-1 
Date Time 2021-03-04 09:50:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2020-56 
Volume (vol) vol.120 
Number (no) no.403 
Page pp.77-82 
#Pages 6 
Date of Issue 2021-02-24 (NC) 

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