A fMRI dataset in response to large number of short natural dynamic facial expression videos

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