鹿児島大学 · 理工学研究科 · 教授

研究关键词inferotemporal cortex・object representation・view-invariant recognition・neural population dynamics・machine learning for neuroscience・three-dimensional object recognition

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• 王 鋼 . 側頭連合野細胞活動を用いた機械学習による物体像分類 . 電気学会論文誌C（電子・情報・システム部門誌） 145 ( 5 ) 514 - 519 2025年5月 詳細を見る 担当区分： 責任著者 記述言2025 · 担当区分： 責任著者 記述言語： 日本語 DOI： 10.1541/ieejeiss.145.514
• Okamura J.y., Fukano D., Murakami K., Wang G. . View-invariant object representation in anterior and posterior inferotemporal cortex: A machine learning approach . Ibro Neuroscience Re2025 · 記述言語： 日本語 出版者・発行元： Ibro Neuroscience Reports Inferotemporal (IT) cortex is the final visual area in the ventral stream where object information is processed. Previous electrophysiological studies showed viewing angle tolerance of 30–60° of single IT cells to the objects experienced in discrimination at each of several viewing angles, and to the objects experienced in learning association of different views. IT is divided into anterior (cytoarchitectonic area TE) and posterior (TEO) parts. It was reported that single cells in area TE showed the viewing angle tolerance while those in area TEO did not. In the present study population activities were compared between cell populations in area TE and those in area TEO using machine learning algorithm. An object set consisted of four similar objects created by deforming a prototype object, and four views each separated by 30°. A population vector was created by aligning responses of the cells to each object image. A classifier was trained by support vector machine (SVM) to create a hyperplane that separated one object from the other three objects at the same viewing angles, and then tested by response vectors to the object images at different viewing angles. In area TE, dynamics of the performance evaluated by d’ showed viewing angle tolerance of 30–90° to the objects with prior experience in learning association of different views. In area TEO, populations of the cells showed the viewing angle tolerance of 30°. Significant increase of the d’ values in area TE in the late time period for the objects with prior experience in learning association of different views may suggest view-invariance is more represented in late time period than early time period. These results suggest that viewpoint invariance is expressed more strongly in the TE region, and expressed in part in the population of the TEO cells. DOI： 10.1016/j.ibneur.2025.07.010 Scopus PubMed
• T. Wang, M. Kino, G. Wang2024 · 担当区分： 責任著者
• ワン ライディ, 岡村 純也, 王 鋼 . 三次元物体弁別学習に伴う事象関連電位の変化とその発生源 . 電気学会論文誌Ｃ（電子・情報・システム部門誌）142 ( 5 ) 522 - 529 2022年5月 詳細を見る 記述言語： 日本語 出版者・発2022 · 記述言語： 日本語 出版者・発行元： 一般社団法人 電気学会 To understand the underlying neuronal representation for object recognition, we designed this study to investigate the changes in N1, the first negative event-related potential component, accompanied by object discrimination learning. Subjects were asked to train themselves to recognize novel computer-made objects by performing an object discrimination task, in which an object had to be discriminated from others regardless of the change in viewing angle. Such object discrimination did not cause any significant change in either the averaged N1 amplitude or the averaged amplitude delay over the subjects. However, the dipole source analysis for N1 found statistically significant displacement of estimated dipole location caused by object discrimination training in the right hemisphere. The source obtained after training located significantly laterally than that obtained before training. The finding demonstrates the difference in neuronal representations of the experienced objects before and after view-invariant object discrimination learning, and suggests the different neuronal representations for object recognition with novel objects and familiar objects. DOI： 10.1541/ieejeiss.142.522 Scopus CiNii Research

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