Presentation 2022-01-21
A System for Estimating Individual Differences of Perceptual Information in the Brain via Brain-activity Prediction by Convolutional Neural Networks
Kiichi Kawahata, Antoine Blanc, Naoya Maeda, Shinji Nishimoto, Satoshi Nishida,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Our brains shape individual differences of perception by responding to sensory inputs differently across individuals. This study aimed to develop a computational system that estimates such individual differences of perceptual information in the brain with no brain measurement. For this purpose, we employed the method we previously developed to predict brain response to arbitrary movie inputs using convolutional neural networks. This method requires no brain measurement once computational models for predicting brain response are trained using measured brain data. We evaluated the inter-subject dissimilarity of perceptual information decoded separately from predicted and measured brain responses to movies. We found that the inter-subject dissimilarity decoded from predicted response was significantly correlated with that decoded from measured response for 80/86 items to be decoded. Our finding suggests that our computational system can estimate individual differences of perceptual information in the brain.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Deep Learning / Brain / Perception / Individual Differences / Neuroimaging
Paper # NC2021-31
Date of Issue 2022-01-14 (NC)

Conference Information
Committee NLP / MICT / MBE / NC
Conference Date 2022/1/21(3days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Takuji Kosaka(Chukyo Univ.) / Eisuke Hanada(Saga Univ.) / Ryuhei Okuno(Setsunan Univ.) / Rieko Osu(Waseda Univ.)
Vice Chair Akio Tsuneda(Kumamoto Univ.) / Hirokazu Tanaka(Hiroshima City Univ.) / Daisuke Anzai(Nagoya Inst. of Tech.) / Junichi Hori(Niigata Univ.) / Hiroshi Yamakawa(Univ of Tokyo)
Secretary Akio Tsuneda(Kagawa Univ.) / Hirokazu Tanaka(Sojo Univ.) / Daisuke Anzai(Yokohama National Univ.) / Junichi Hori(KISTEC) / Hiroshi Yamakawa(Osaka Electro-Communication Univ)
Assistant Hideyuki Kato(Oita Univ.) / Yuichi Yokoi(Nagasaki Univ.) / Takahiro Ito(Hiroshima City Univ) / Kento Takabayashi(Okayama Pref. Univ.) / Takuya Nishikawa(National Cerebral and Cardiovascular Center Hospital) / Jun Akazawa(Meiji Univ. of Integrative Medicine) / Emi Yuda(Tohoku Univ) / Nobuhiko Wagatsuma(Toho Univ.) / Tomoki Kurikawa(KMU)

Paper Information
Registration To Technical Committee on Nonlinear Problems / Technical Committee on Healthcare and Medical Information Communication Technology / Technical Committee on ME and Bio Cybernetics / Technical Committee on Neurocomputing
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A System for Estimating Individual Differences of Perceptual Information in the Brain via Brain-activity Prediction by Convolutional Neural Networks
Sub Title (in English)
Keyword(1) Deep Learning
Keyword(2) Brain
Keyword(3) Perception
Keyword(4) Individual Differences
Keyword(5) Neuroimaging
1st Author's Name Kiichi Kawahata
1st Author's Affiliation Osaka University(Osaka Univ.)
2nd Author's Name Antoine Blanc
2nd Author's Affiliation Institute, National Institute of Information and Communications Technology(NICT)
3rd Author's Name Naoya Maeda
3rd Author's Affiliation NTT DATA Corporation(NTT Data)
4th Author's Name Shinji Nishimoto
4th Author's Affiliation Osaka University(Osaka Univ.)
5th Author's Name Satoshi Nishida
5th Author's Affiliation Institute, National Institute of Information and Communications Technology(NICT)
Date 2022-01-21
Paper # NC2021-31
Volume (vol) vol.121
Number (no) NC-338
Page pp.pp.1-6(NC),
#Pages 6
Date of Issue 2022-01-14 (NC)