CASIA OpenIR  > 多模态人工智能系统全国重点实验室  > 自然语言处理
An fMRI Dataset for Concept Representation with Semantic Feature Annotations
Wang, Shaonan1,2; Zhang, Yunhao1,2; Zhang, Xiaohan1,2; Sun, Jingyuan1,2; Lin, Nan3,4; Zhang, Jiajun1,2; Zong, Chengqing1,2
Source PublicationSCIENTIFIC DATA
2022-11-24
Volume9Issue:1Pages:9
Corresponding AuthorWang, Shaonan(shaonan.wang@nlpr.ia.ac.cn)
AbstractThe neural representation of concepts is a focus of many cognitive neuroscience studies. Prior works studying concept representation with neural imaging data have been largely limited to concrete concepts. The use of relatively small and constrained sets of stimuli leaves open the question of whether the findings can generalize other concepts. We share an fMRI dataset in which 11 participants thought of 672 individual concepts, including both concrete and abstract concepts. The concepts were probed using words paired with images in which the words were selected to cover a wide range of semantic categories. Furthermore, according to the componential theories of concept representation, we collected the 54 semantic features of the 672 concepts comprising sensory, motor, spatial, temporal, affective, social, and cognitive experiences by crowdsourcing annotations. The quality assessment results verify this as a high-quality neuroimaging dataset. Such a dataset is well suited to study how the brain represents different semantic features and concepts, creating the essential condition to investigate the neural representation of individual concepts.
DOI10.1038/s41597-022-01840-2
Indexed BySCI
Language英语
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000887909800001
PublisherNATURE PORTFOLIO
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/50777
Collection多模态人工智能系统全国重点实验室_自然语言处理
Corresponding AuthorWang, Shaonan
Affiliation1.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Psychol, Key Lab Behav Sci, Beijing, Peoples R China
4.Univ Chinese Acad Sci, Dept Psychol, Beijing, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Wang, Shaonan,Zhang, Yunhao,Zhang, Xiaohan,et al. An fMRI Dataset for Concept Representation with Semantic Feature Annotations[J]. SCIENTIFIC DATA,2022,9(1):9.
APA Wang, Shaonan.,Zhang, Yunhao.,Zhang, Xiaohan.,Sun, Jingyuan.,Lin, Nan.,...&Zong, Chengqing.(2022).An fMRI Dataset for Concept Representation with Semantic Feature Annotations.SCIENTIFIC DATA,9(1),9.
MLA Wang, Shaonan,et al."An fMRI Dataset for Concept Representation with Semantic Feature Annotations".SCIENTIFIC DATA 9.1(2022):9.
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