Decoding the temporal representation of facial expression in face-selective regions
文献类型:期刊论文
作者 | Zhang, Zhihao5,6; Chen, Tong3,4; Liu, Ye5,6; Wang, Chongyang2; Zhao, Ke5,6; Liu, Chang Hong1; Fu, Xiaolan5,6 |
刊名 | NEUROIMAGE |
出版日期 | 2023-12-01 |
卷号 | 283页码:15 |
通讯作者邮箱 | zhaoh@psych.ac.cn (k. zhao) ; fuxl@psych.ac.cn (x. fu) |
ISSN号 | 1053-8119 |
关键词 | Facial expression Magnetoencephalography (MEG) Pairwise classification Representational similarity analysis CNN |
DOI | 10.1016/j.neuroimage.2023.120442 |
产权排序 | 1 |
文献子类 | 实证研究 |
英文摘要 | The ability of humans to discern facial expressions in a timely manner typically relies on distributed face selective regions for rapid neural computations. To study the time course in regions of interest for this process, we used magnetoencephalography (MEG) to measure neural responses participants viewed facial expressions depicting seven types of emotions (happiness, sadness, anger, disgust, fear, surprise, and neutral). Analysis of the time-resolved decoding of neural responses in face-selective sources within the inferior parietal cortex (IPfaces), lateral occipital cortex (LO-faces), fusiform gyrus (FG-faces), and posterior superior temporal sulcus (pSTS-faces) revealed that facial expressions were successfully classified starting from-100 to 150 ms after stimulus onset. Interestingly, the LO-faces and IP-faces showed greater accuracy than FG-faces and pSTS-faces. To examine the nature of the information processed in these face-selective regions, we entered with facial expression stimuli into a convolutional neural network (CNN) to perform similarity analyses against human neural responses. The results showed that neural responses in the LO-faces and IP-faces, starting-100 ms after the stimuli, were more strongly correlated with deep representations of emotional categories than with image level information from the input images. Additionally, we observed a relationship between the behavioral performance and the neural responses in the LO-faces and IP-faces, but not in the FG-faces and lpSTS-faces. Together, these results provided a comprehensive picture of the time course and nature of information involved in facial expression discrimination across multiple face-selective regions, which advances our understanding of how the human brain processes facial expressions. |
收录类别 | SCI |
WOS关键词 | OBJECT RECOGNITION ; SPATIOTEMPORAL DYNAMICS ; NEURAL FRAMEWORK ; PATTERN-ANALYSIS ; EMOTION ; MEG ; INFORMATION ; PERCEPTION ; ABILITY ; MODELS |
资助项目 | National Natural Science Foundation of China[62061136001] ; National Natural Science Foundation of China[32071055] |
WOS研究方向 | Neurosciences & Neurology ; Radiology, Nuclear Medicine & Medical Imaging |
语种 | 英语 |
出版者 | ACADEMIC PRESS INC ELSEVIER SCIENCE |
WOS记录号 | WOS:001111569600001 |
资助机构 | National Natural Science Foundation of China |
源URL | [http://ir.psych.ac.cn/handle/311026/46576] |
专题 | 心理研究所_脑与认知科学国家重点实验室 |
通讯作者 | Zhao, Ke; Fu, Xiaolan |
作者单位 | 1.Bournemouth Univ, Dept Psychol, Poole, Dorset, England 2.Tsinghua Univ, Dept Comp Sci & Technol, Beijing 100084, Peoples R China 3.Chongqing Key Lab Artificial Intelligence & Serv R, Chongqing 400715, Peoples R China 4.Southwest Univ, Chongqing Key Lab Nonlinear Circuit & Intelligent, Chongqing 400715, Peoples R China 5.Univ Chinese Acad Sci, Dept Psychol, Beijing 100049, Peoples R China 6.Chinese Acad Sci, Inst Psychol, State Key Lab Brain & Cognit Sci, Beijing 100101, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, Zhihao,Chen, Tong,Liu, Ye,et al. Decoding the temporal representation of facial expression in face-selective regions[J]. NEUROIMAGE,2023,283:15. |
APA | Zhang, Zhihao.,Chen, Tong.,Liu, Ye.,Wang, Chongyang.,Zhao, Ke.,...&Fu, Xiaolan.(2023).Decoding the temporal representation of facial expression in face-selective regions.NEUROIMAGE,283,15. |
MLA | Zhang, Zhihao,et al."Decoding the temporal representation of facial expression in face-selective regions".NEUROIMAGE 283(2023):15. |
入库方式: OAI收割
来源:心理研究所
其他版本
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。