Exposure to linguistic labels during childhood modulates the neural architecture of race categorical perception

Perceptually categorizing a face to its racial belonging may have important consequences on interacting with people. However, race categorical perception (CP) has been scarcely investigated nor its developmental pathway. In this study, we tested the neurolinguistics rewiring hypothesis, stating that language acquisition modulates the brain processing of social perceptual categories. Accordingly, we investigated the electrophysiological correlates of race CP in a group of adults and children between 3 and 5 years of age. For both groups we found a greater modulation of the N400 connected with the processing of between category boundaries (i.e., faces belonging to different race groups) than within-category boundaries (i.e., different faces belonging to the same race group). This effect was the same in both adults and children, as shown by the comparable between-group amplitude of the differential wave (DW) elicited by the between-category faces. Remarkably, this effect was positively correlated with racial-labels acquisition, but not with age, in children. Finally, brain source analysis revealed the activation of a more modularized cortical network in adults than in children, with unique activation of the left superior temporal gyrus (STG) and the inferior frontal gyrus (IFG), which are areas connected to language processing. These are the first results accounting for an effect of language in rewiring brain connectedness when processing racial categories

Handbook of Digital Face Manipulation and Detection

This open access book provides the first comprehensive collection of studies dealing with the hot topic of digital face manipulation such as DeepFakes, Face Morphing, or Reenactment. It combines the research fields of biometrics and media forensics including contributions from academia and industry. Appealing to a broad readership, introductory chapters provide a comprehensive overview of the topic, which address readers wishing to gain a brief overview of the state-of-the-art. Subsequent chapters, which delve deeper into various research challenges, are oriented towards advanced readers. Moreover, the book provides a good starting point for young researchers as well as a reference guide pointing at further literature. Hence, the primary readership is academic institutions and industry currently involved in digital face manipulation and detection. The book could easily be used as a recommended text for courses in image processing, machine learning, media forensics, biometrics, and the general security area