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) |
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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) |
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Keyword(1) |
foreign language learning |
Keyword(2) |
EEG |
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brain functional connectivity network |
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multilayer modularity |
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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 |
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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 |
6 |
Date of Issue |
2018-01-19 (NC) |
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