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

<p>Facial expression is among the most natural methods for human beings to convey their emotional information in daily life. Although the neural mechanism of facial expression has been extensively studied employing lab-controlled images and a small number of lab-controlled video stimuli, how the human brain processes natural&nbsp;facial expressions still needs to be investigated. To our knowledge, this type of data specifically on large<span>-scale</span> natural&nbsp;facial expression videos&nbsp;is currently missing.&nbsp;We describe here the natural Facial Expressions Dataset (NFED), a fMRI dataset&nbsp;including responses to 1,320 short (3-second) natural&nbsp;facial expression video clips. These video clips is annotated&nbsp;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.&nbsp;NFED&nbsp;provides researchers with fMRI data for understanding of the visual processing of large number of natural&nbsp;facial expression videos.</p>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0