Publications
- Orima, T*., Wakita, S., & Motoyoshi, I. (2025). Neural Basis of Perceptual Surface Qualities and Materials: Evidence from Electroencephalogram Decoding. Journal of Cognitive Neuroscience, 37(4), 815-839. (Peer reviewed) [link]
- Orima, T.*, & Motoyoshi, I. (2023). Spatiotemporal cortical dynamics for visual scene processing as revealed by EEG decoding. Frontiers in Neuroscience, 17, 1167719. (Peer reviewed) [link]
- Wakita, S.*, Orima, T., & Motoyoshi, I. (2021). Photorealistic reconstruction of visual texture from EEG signals. Frontiers in Computational Neuroscience, 15, 754587. (Peer reviewed) [link]
- Kurosawa, F., Orima, T., Okada, K., & Motoyoshi, I.* (2021). Textures vs Non-Textures: A Simple Computational Method for Classifying Perceived ‘Texturality’in Natural Images. i-Perception, 12(5), 20416695211054540. (Peer reviewed) [link]
- Orima, T.*, & Motoyoshi, I. (2021). Analysis and synthesis of natural texture perception from visual evoked potentials. Frontiers in Neuroscience, 876. (Peer reviewed) [link]
- * : corresponding author
Awards
- Orima, T. (2024) Japanese Psychonomic Society 43rd Annual Meeting Outstanding Presentation Award [link]
- Orima, T. (2023) Japanese Psychonomic Society 42nd Annual Meeting Outstanding Presentation Award [link]
- Orima, T. (2022) Japanese Psychonomic Society 41st Annual Meeting Outstanding Presentation Award [link]
- Orima, T. (2022) Vision Society of Japan Best Presentation Award [link]
- Orima, T. (2020) Vision Society of Japan Best Presentation Award [link]
- Orima, T. (2019) Asia-Pacific Conference on Vision 2019 Student Travel Award [link]
Invited Talks
- Orima, T. (2024). Material perception based on statistical image features. (Vision Forum 2024, Japan, Domestic) [link]
- Orima, T. (2022). Surface quality perception and image statistics. (Grad Students' and Faculty/Staff Members' Mini-lecture Program The 18th Session.) [link]
- Orima, T. (2021). Analysis of texture and scene perception based on EEG. (Takuetsu colloquium) [no link]
Research Fellowship & Grants
- Orima, T. (2025-2028). Investigation of the whole structure of natural scene perception in our daily lives.（JSPS Grants-in-Aid for Early-Career Scientists: Grant 3,700,000 JPY）[link]
- Orima, T. (2024-2027). Elucidation of Neural Representations Underlying Perceptual Realness and Development of Techniques for Reconstructing Perceptual Experiences.（JSPS research fellow PD: Salary 13,032,000 JPY/Grant 3,000,000 JPY）[link]
- Orima, T. (2021-2024). Integrative Study of Visual Cognition Mechanisms Based on Correlation Analysis and Synthesis of EEG, Image Features, and Ratings.（JSPS research fellow DC1: Salary 7,200,000 JPY/Grant 2,200,000 JPY）[link]
International Conferences (First author)
- Orima, T., Kurosawa, F. & Motoyoshi, I. (2024). Natural scene processing based on texture information : psychophysics and EEG. (ECVP2024, Poster) [link]
- Orima, T., Kurosawa, F. & Motoyoshi, I. (2024). Texture-based scene processing in humans : psychophysics and EEG decoding. (Neuro2024, Poster) [link]
- Orima, T., Wakita, S. & Motoyoshi, I. (2024). Neural representation underlying textural quality in perception: Evidence from EEG-based image reconstruction. (ASSC27, Poster) [link]
- Orima, T., & Motoyoshi, I. (2023). Neural dynamics of natural scene processing across cortical areas as revealed by EEG decoding. Journal of Vision, 23(9), 5228-5228. (VSS 2023 Annual Meeting, Poster) [link]
- Orima, T., & Motoyoshi, I. Decoding of material perception: analysis and synthesis from EEG via DNN model. Program No. 297.13. 2022 Neuroscience Meeting Planner. San Diego, CA: Society for Neuroscience, 2022. Online. (Poster) [link]
- Orima, T., & Motoyoshi, I. (2022). Recognition, estimation, and reconstruction of surface materials by EEG. Journal of Vision, 22(14), 3916-3916. (V-VSS 2022 Annual Meeting, Poster) [link]
- Orima, T., Wakita, S. & Motoyoshi, I. (2021). Cortical dynamics of texture information processing: an EEG study. The 44th Annual Meeting of the Japan Neuroscience Society / The 1st CJK International Meeting (Poster) [link]
- Orima, T., & Motoyoshi, I. (2020). Analysis and synthesis of natural texture perception by EEG. Journal of Vision, 20(11), 648-648. (V-VSS 2020 Annual Meeting, Oral) [link]
- Orima, T., & Motoyoshi, I. (2019, September). Reverse Correlation AnalysIs of Visual Evoked Potentials for Natural Texture Statistics. In I-PERCEPTION (Vol. 10, pp. 158-158). 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND: SAGE PUBLICATIONS LTD. (APCV 2019, Poster) [link]
- Orima, T., , & Motoyoshi, I. (2019). Image-statistics correlates of visual evoked potentials to natural texture images. Journal of Vision, 19(10), 123c-123c. (VSS 2019 Annual Meeting, Poster) [link]
Domestic Conferences (Japan, First author)
- 織間大気・黒澤史弥・関本大勢・本吉勇 (2024). 自然情景・物体の認知における統計的情報の役割. 日本基礎心理学会第43回大会．
- 織間大気・黒澤史弥・本吉勇 (2024). テクスチャ情報に基づく情景認知. 日本視覚学会2024年冬季大会．
- 織間大気・本吉勇 (2023). 脳波による自然情景知覚の時空間皮質ダイナミクスの分析. 日本基礎心理学会第42回大会．
- 織間大気・本吉勇 (2023). 情景処理に関する皮質マップの時空間的展開: EEGNetによる解析. 第46回日本神経科学大会．
- 織間大気・本吉勇 (2022). 視覚誘発電位による物体表面質感の再構成と符号化過程の解析. 日本基礎心理学会第41回大会．
- 織間大気・本吉勇 (2022). 脳波による自然情景カテゴリの分類とその符号化過程の分析．日本視覚学会2022年夏季大会．
- 織間大気・本吉勇 (2022). クオリアの復号化: 脳波からの表面画像の再構成と材質分類．NEURO2022(第45回日本神経科学大会)．
- 織間大気・本吉勇 (2022). 脳波からの表面質感の特性評価，材質分類，および画像復元．第24回日本ヒト脳機能マッピング学会．
- 織間大気・本吉勇 (2022). 脳波による物体表面の材質認識，質感評価，および画像合成．日本視覚学会2022年冬季大会．
- 織間大気・本吉勇 (2020). 視覚誘発電位によるテクスチャ統計量符号化機構の解析．日本視覚学会2020年冬季大会．
- 織間大気・本吉勇 (2019). 視覚誘発電位に基づく自然テクスチャ画像の特徴解析と合成．日本基礎心理学会第38回大会．
Education
| 2024.03. | Department of Life Sciences, the University of Tokyo (Ph.D. of Arts and Sciences, The First National High School Memorial Award) |
| 2021.03. | Department of Life Sciences, the University of Tokyo (Master of Arts and Sciences, Outstanding Student Award) |
| 2019.03. | Faculty of Arts and Sciences, the University of Tokyo (Bachelor of Arts and Sciences) |
| 2015.03. | Graduated from Kaisei Academy (High school) |
Job History
| 2024.04.- | Japan Society for the Promotion of Science (JSPS) Research fellow PD (Dr. Ban group) |
| 2021.04.-2024.03. | Japan Society for the Promotion of Science (JSPS) Research fellow DC1 (Prof. Motoyoshi Lab) |
| 2019.04.-2024.03. | Teaching assistant (TA) at The University of Tokyo: Preparation for the class, Lecture and grade for 2-hour class |
Skills & Achievements
- Programming: Matlab, Python, HTML
- Completed the Future Faculty Program (FFP) at the University of Tokyo 18th gen.
- Tetsuryokukai former Math teacher (8th-12th grade students, over 1,500 hours for lectures)
- Coursera: Machine Learning, Deep Learning Specialization, AI for Everyone (by Andrew Ng), Computational Neuroscience
- Languages: Japanese, English, Puedo hablar español un poco...
- Others: TeX, Microsoft Word, Excel, Powepoint