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Paper Abstract and Keywords
Presentation 2018-01-26 13:50
Brain functional connectivity network flexibility predicts individual variability in learning ability
Akiyoshi Akiyama (KyuTech), Eiko Soejima (Jyoto High School), Toshimasa Yamazaki (KyuTech), Takahiko Yamamoto (Jyoto High School) NC2017-52
Abstract (in Japanese) (See Japanese page) 
(in English) This study addresses itself to clarify the relationship between structural changes of brain functional connectivity network (BFCN), which are constructed using scalp-recorded EEGs, and individual English language learning ability. 19-ch EEGs were recorded before and after English word learning in 15 Japanese students. We constructed a two-layer network consisting of the BFCN by EEGs during the English words whose Japanese meanings were not recalled both before and after the learning, and that by those whose meanings were not before the learning but recalled after the learning. The connectivity between any two nodes (electrodes) were calculated by Phase Lag Index. Then, the network was divided into non-overlapping modules by multilayer, and BFCN flexibility was defined to be the number of times that a node changed modular assignment. Finally, individual English word learning ability was quantified by the flexibility.
Keyword (in Japanese) (See Japanese page) 
(in English) foreign language learning / EEG / brain functional connectivity network / multilayer modularity / flexibility / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 417, NC2017-52, pp. 11-16, Jan. 2018.
Paper # NC2017-52 
Date of Issue 2018-01-19 (NC) 
ISSN Print edition: ISSN 0913-5685    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 NC2017-52

Conference Information
Committee MBE NC NLP  
Conference Date 2018-01-26 - 2018-01-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyushu Institute of Technology 
Topics (in Japanese) (See Japanese page) 
Topics (in English) ME, generalImplementation of Neuro Computing,Analysis and Modeling of Human Science, 
Paper Information
Registration To NC 
Conference Code 2018-01-MBE-NC-NLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Brain functional connectivity network flexibility predicts individual variability in learning ability 
Sub Title (in English)  
Keyword(1) foreign language learning  
Keyword(2) EEG  
Keyword(3) brain functional connectivity network  
Keyword(4) multilayer modularity  
Keyword(5) flexibility  
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1st Author's Name Akiyoshi Akiyama  
1st Author's Affiliation Kyushu Institute of Technology (KyuTech)
2nd Author's Name Eiko Soejima  
2nd Author's Affiliation Jyoto High School (Jyoto High School)
3rd Author's Name Toshimasa Yamazaki  
3rd Author's Affiliation Kyushu Institute of Technology (KyuTech)
4th Author's Name Takahiko Yamamoto  
4th Author's Affiliation Jyoto High School (Jyoto High School)
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Speaker Author-1 
Date Time 2018-01-26 13:50:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2017-52 
Volume (vol) vol.117 
Number (no) no.417 
Page pp.11-16 
#Pages
Date of Issue 2018-01-19 (NC) 


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