Rchr
J-GLOBAL ID:201101087181903320   Update date: Feb. 29, 2024

Nishida Satoshi

ニシダ サトシ | Nishida Satoshi
Affiliation and department:
Job title: Senior Researcher
Other affiliations (2):
  • Osaka University  Graduate School of Frontier Biosciences   Guest Associate Professor
  • Hokkaido University  Center for Human Nature, Artificial Intelligence, and Neuroscience   Visiting Researcher
Homepage URL  (2): https://sites.google.com/site/satnishida/https://sites.google.com/site/satnishida/english-top
Research field  (4): Cognitive neuroscience ,  Experimental psychology ,  Cognitive sciences ,  Neuroscience - general
Research keywords  (16): Semantic processing ,  Affection ,  Vision ,  Consciousness ,  personality ,  fMRI ,  Neural decoding ,  Artificial intelligence ,  Deep learning ,  Neurophenomenology ,  Attention ,  Visual search ,  Decision Making ,  Working memory ,  Electrophysiology ,  包括脳ネットワーク
Research theme for competitive and other funds  (18):
  • 2024 - 2027 Narrative Consciousness Studies: Pioneering a new framework for consciousness
  • 2020 - 2025 Developing a technique to evaluate trustworthiness of AI systems using brain information
  • 2023 - 2024 コーヒーの味わいに対する先入観と知覚のメカニズム
  • 2023 - 2024 不気味の谷現象の脳内機序解明に向けた計算神経科学的研究
  • 2023 - 2024 意味表現の個人差可視化を実現にする人工知能(AI)と脳情報統合技術の革新
Show all
Papers (28):
  • Haruka Kawasaki, Satoshi Nishida, Ichiro Kobayashi. Exploring Hierarchical Changes in Functional Brain Network Hubs Through Brain-Activity Prediction with Convolutional Neural Networks. Proceedings of 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 2023. 4740-4745
  • Matsumoto Y, Nishida S, Hayashi R, Son S, Murakami A, Yoshikawa N, Ito H, Oishi N, Masuda N, Murai T, et al. Disorganization of semantic brain networks in schizophrenia revealed by fMRI. Schizophrenia Bulletin. 2022. sbac157
  • Kawasaki H, Nishida S, Kobayashi I. Hierarchical Processing of Visual and Language Information in the Brain. The proceedings of AACL-IJCNLP 2022. 2022. 405-410
  • Ryoichi Shinkuma, Satoshi Nishida, Naoya Maeda, Masataka Kado, Shinji Nishimoto. Reduction of Information Collection Cost for Inferring Brain Model Relations From Profile Information Using Machine Learning. IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2022. 52. 7. 4057-4068
  • Takuya Niikawa, Katsunori Miyahara, Hiro Taiyo Hamada, Satoshi Nishida. Functions of consciousness: conceptual clarification. Neuroscience of Consciousness. 2022. 2022. 1
more...
MISC (25):
  • Jiaxin Wang, Kiichi Kawahata, Antoine Blanc, Naoya Maeda, Shinji Nishimoto, Satoshi Nishida. Asymmetric representation of symmetric semantic information in the human brain. bioRxiv. 2024. 10.1101/2024.02.09.579613
  • Satoshi Nishida. Behavioral and neural evidence for the underestimated attractiveness of faces synthesized using an artificial neural network. bioRxiv. 2023. 2023.02.07.527403
  • 西田知史. AIへの脳融合. NICT NEWS. 2022. 496. 12-13
  • 西田知史. 日常的な認知に関わる脳情報処理のモデル化と人工脳への応用. 情報通信研究機構研究報告. 2022. 68. 1. 11-19
  • Kiichi Kawahata, Jiaxin Wang, Antoine Blanc, Naoya Maeda, Shinji Nishimoto, Satoshi Nishida. Decoding Individual Differences in Mental Information from Human Brain Response Predicted by Convolutional Neural Networks. bioRxiv. 2022
more...
Patents (9):
  • 脳応答空間生成装置、評価装置、及び脳応答空間生成方法
  • 脳活動予測装置、知覚認知内容推定システム、及び脳活動予測方法
  • Material evaluation method and material evaluation device
  • Material evaluation method and material evaluation device
  • 情報処理装置、情報処理システム、脳活動予測方法、及びプログラム
more...
Lectures and oral presentations  (162):
  • fMRI signals in the superior temporal cortex separately reflect inter- and intra-individual variations in music preferences
    (The 9th CiNet Conference: Cutting Edges of Cognitive and Action Information Processing 2024)
  • Masked Auto Encoder と対照学習を用いたfMRI データの次元圧縮法と脳媒介パターン認識への応用
    (ニューロコンピューティング研究会 2024)
  • Variations in Personal Music Tastes are Reflected in the Synchronization of fMRI Signals across Individuals
    (脳と心のメカニズム第23回冬のワークショップ 2024)
  • Localization and Representation of Visual and Language Information in the Human Brain
    (International Symposium on Advanced Intelligent Systems (ISIS) 2023 2023)
  • 意味・感性に関わる脳内情報の可視化とその応用
    (JEITA感性のセンシング・インタラクション技術分科会 2023)
more...
Education (2):
  • 2010 - 2014 Kyoto University Graduate School of Medicine
  • 2008 - 2010 Nara Institute of Science and Technology Graduate School of Information Science
Professional career (1):
  • PhD (Kyoto University)
Work history (8):
  • 2023/10 - 現在 Hokkaido University Center for Human Nature, Artificial Intelligence, and Neuroscience Visiting Researcher
  • 2021/04 - 現在 National Institute of Information and Communications Technology Advanced ICT Research Institute Center for Information and Neural Networks Senior Researcher
  • 2020/04 - 現在 Osaka University Graduate School of Frontier Biosciences Guest Associate Professor
  • 2020/12 - 2022/03 Japan Science and Technology Agency PRESTO Researcher
  • 2019/04 - 2021/03 National Institute of Information and Communications Technology Center for Information and Neural Networks Senior Researcher
Show all
Committee career (5):
  • 2023 - 現在 電子情報通信学会 ニューロコンピューティング研究専門委員会 専門委員
  • 2021/06 - 2023/05 電子情報通信学会 ニューロコンピューティング(NC)研究専門委員会 幹事
  • 2021/07 - 2022/12 Creative Destruction Lab (CDL) Neuro Mentor
  • 2022 - 電子情報通信学会 FIT2022 担当委員・プログラム委員
  • 2022 - 電子情報通信学会 2022年総合大会 プログラム編成委員
Awards (19):
  • 2023/12 - The 24th International Symposium on Advanced Intelligent Systems Best Presentation Award Localization and Representation of Visual and Language Information in the Human Brain
  • 2023/09 - Japanese Neural Network Society Excellent Research Award
  • 2022/07 - 人工知能学会 2022年度全国大会優秀賞
  • 2021/12 - The 22nd International Symposium on Advanced Intelligent Systems Best Session Award A Deep Generative Model imitating Predictive Coding in the Human Brain
  • 2020/07 - 人工知能学会 2020年度全国大会優秀賞
Show all
Association Membership(s) (4):
Society for Neuroscience ,  JAPANESE NEURAL NETWORK SOCIETY ,  THE JAPAN NEUROSCIENCE SOCIETY ,  The Japanese Society for Artificial Intelligence
※ Researcher’s information displayed in J-GLOBAL is based on the information registered in researchmap. For details, see here.

Return to Previous Page