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Graph-Enhanced Emotion Neural Decoding | |
Huang Zhongyu(黄中昱)1,2; Du Changde(杜长德)1![]() ![]() ![]() | |
发表期刊 | IEEE Transactions on Medical Imaging
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ISSN | 1558-254X |
2023 | |
卷号 | 42期号:8页码:2262 - 2273 |
摘要 | Brain signal-based emotion recognition has recently attracted considerable attention since it has powerful potential to be applied in human-computer interaction. To realize the emotional interaction of intelligent systems with humans, researchers have made efforts to decode human emotions from brain imaging data. The majority of current efforts use emotion similarities (e.g., emotion graphs) or brain region similarities (e.g., brain networks) to learn emotion and brain representations. However, the relationships between emotions and brain regions are not explicitly incorporated into the representation learning process. As a result, the learned representations may not be informative enough to benefit specific tasks, e.g., emotion decoding. In this work, we propose a novel idea of graph-enhanced emotion neural decoding, which takes advantage of a bipartite graph structure to integrate the relationships between emotions and brain regions into the neural decoding process, thus helping learn better representations. Theoretical analyses conclude that the suggested emotion-brain bipartite graph inherits and generalizes the conventional emotion graphs and brain networks. Comprehensive experiments on visually evoked emotion datasets demonstrate the effectiveness and superiority of our approach. |
关键词 | Brain region emotion graph neural networks neural decoding representation |
DOI | 10.1109/TMI.2023.3246220 |
URL | 查看原文 |
收录类别 | SCI |
语种 | 英语 |
WOS记录号 | WOS:001042097000011 |
是否为代表性论文 | 否 |
七大方向——子方向分类 | 脑机接口 |
国重实验室规划方向分类 | 认知机理与类脑学习 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/51624 |
专题 | 脑图谱与类脑智能实验室_神经计算与脑机交互 |
通讯作者 | He Huiguang(何晖光) |
作者单位 | 1.Laboratory of Brain Atlas and Brain-Inspired Intelligence, State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China 2.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China 3.Department of Computer Science, Cornell University |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Huang Zhongyu,Du Changde,Wang Yingheng,et al. Graph-Enhanced Emotion Neural Decoding[J]. IEEE Transactions on Medical Imaging,2023,42(8):2262 - 2273. |
APA | Huang Zhongyu,Du Changde,Wang Yingheng,Fu Kaicheng,&He Huiguang.(2023).Graph-Enhanced Emotion Neural Decoding.IEEE Transactions on Medical Imaging,42(8),2262 - 2273. |
MLA | Huang Zhongyu,et al."Graph-Enhanced Emotion Neural Decoding".IEEE Transactions on Medical Imaging 42.8(2023):2262 - 2273. |
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TMI2023_Graph-Enhanc(6049KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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