Presentation | 2018-01-26 Brain functional connectivity network flexibility predicts individual variability in learning ability Akiyoshi Akiyama, Eiko Soejima, Toshimasa Yamazaki, Takahiko Yamamoto, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(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) |
Keyword(in English) | foreign language learning / EEG / brain functional connectivity network / multilayer modularity / flexibility |
Paper # | NC2017-52 |
Date of Issue | 2018-01-19 (NC) |
Conference Information | |
Committee | MBE / NC / NLP |
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Conference Date | 2018/1/26(2days) |
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, |
Chair | Kazuki Nakajima(Univ. of Toyama) / Masafumi Hagiwara(Keio Univ.) / Masaharu Adachi(Tokyo Denki Univ.) |
Vice Chair | Masaki Kyoso(TCU) / Yutaka Hirata(Chubu Univ.) / Norikazu Takahashi(Okayama Univ.) |
Secretary | Masaki Kyoso(Toyama Pref. Univ.) / Yutaka Hirata(Kindai Univ.) / Norikazu Takahashi(Tokyo Inst. of Tech.) |
Assistant | Kim Juhyon(Univ. of Toyama) / Takumi Kobayashi(YNU) / Yoshihisa Shinozawa(Keio Univ.) / Keiichiro Inagaki(Chubu Univ.) / Toshihiro Tachibana(Shonan Inst. of Tech.) / Masayuki Kimura(Kyoto Univ.) |
Paper Information | |
Registration To | Technical Committee on ME and Bio Cybernetics / Technical Committee on Neurocomputing / Technical Committee on Nonlinear Problems |
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Language | JPN |
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 |
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) |
Date | 2018-01-26 |
Paper # | NC2017-52 |
Volume (vol) | vol.117 |
Number (no) | NC-417 |
Page | pp.pp.11-16(NC), |
#Pages | 6 |
Date of Issue | 2018-01-19 (NC) |