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Data Sheet 1_Visual exposure to masked faces benefits personally familiar but not famous face recognition.pdf

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Data_Sheet_1_Visual_exposure_to_masked_faces_benefits_personally_familiar_but_not_famous_face_recognition_pdf/32044161
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IntroductionThe introduction of face masks during the recent COVID-19 pandemic presented a potential challenge for human face perception and recognition. Our exploratory study investigates the effect of face masks in face recognition by probing the neuropsychological mechanisms of the same. We also aim to explicate the effect of general exposure to masked faces and visual experience with specific masked faces of personally familiar individuals on face recognition ability. MethodsParticipants detected personally familiar, famous, and unfamiliar Indian faces in masked and unmasked conditions in a 2-back test. ResultsStatistical analyses revealed significant main effects of familiarity and mask conditions on performance accuracy and reaction time (RT). The highest performance accuracy in correctly detecting the target face was observed for familiar and unmasked faces, and the lowest for unfamiliar and masked ones. Notably, RTs were not different between unmasked and masked personally familiar faces, while masked famous faces elicited significantly greater RT than their unmasked counterpart. EEG analysis was consistent with behavioral results. Specifically, we show neural evidence for increased effort in processing masked famous faces that is similar to that for masked unfamiliar faces, but absent for masked familiar faces. This increased effort to process masked faces of unfamiliar or famous individuals is suggestive of a beneficial effect of visual exposure to, and experience with, specific masked faces. ConclusionIn sum, our study presents behavioral and neural evidence that personal familiarity with masked faces aids perceptual learning and eventual recognition, and this learning does not generalize to otherwise well-known faces.
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2026-04-17
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