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对大规模短的自然动态面部表情视频的 fMRI 数据集。

An fMRI dataset in response to large-scale short natural dynamic facial expression videos.

机构信息

Henan Key Laboratory of Imaging and Intelligent Processing, PLA Strategic Support Force Information Engineering University, Zhengzhou, 450000, China.

出版信息

Sci Data. 2024 Nov 19;11(1):1247. doi: 10.1038/s41597-024-04088-0.

Abstract

Facial expression is among the most natural methods for human beings to convey their emotional information in daily life. Although the neural mechanisms of facial expression have been extensively studied employing lab-controlled images and a small number of lab-controlled video stimuli, how the human brain processes natural dynamic facial expression videos still needs to be investigated. To our knowledge, this type of data specifically on large-scale natural facial expression videos is currently missing. We describe here the natural Facial Expressions Dataset (NFED), an fMRI dataset including responses to 1,320 short (3-second) natural facial expression video clips. These video clips are annotated with three types of labels: emotion, gender, and ethnicity, along with accompanying metadata. We validate that the dataset has good quality within and across participants and, notably, can capture temporal and spatial stimuli features. NFED provides researchers with fMRI data for understanding of the visual processing of large number of natural facial expression videos.

摘要

面部表情是人类在日常生活中传达情感信息最自然的方式之一。尽管已经使用实验室控制的图像和少量实验室控制的视频刺激广泛研究了面部表情的神经机制,但人类大脑如何处理自然动态面部表情视频仍需要研究。据我们所知,目前缺少关于大规模自然面部表情视频的此类数据。我们在这里描述自然面部表情数据集(NFED),这是一个 fMRI 数据集,包括对 1320 个短(3 秒)自然面部表情视频片段的反应。这些视频片段带有三种类型的标签:情绪、性别和种族,以及伴随的元数据。我们验证了该数据集在参与者内部和之间具有良好的质量,并且特别能够捕捉到时间和空间刺激特征。NFED 为研究人员提供了 fMRI 数据,用于理解大量自然面部表情视频的视觉处理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b75/11576863/6730b10ca20c/41597_2024_4088_Fig1_HTML.jpg

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