How does the brain code the race of faces?

Abstract

High-level perceptual aftereffects have revealed that faces are coded relative to norms, supposedly via some sort of opponent coding mechanism that is dynamically updated by experience. The nature of these norms and the advantage of such a norm-based representation, however, are not yet fully understood. Here, we used high-level adaptation techniques to get insight into the perception of faces of different race categories. We compared the size of identity aftereffects (AEs) for pairs of adapt and test faces that were taken from different morph trajectories, based on potential norms for Asian and Caucasian faces. Larger aftereffects were found following exposure to anti-faces created relative to averages of the race of the target identities, than to anti-faces created using a generic average. Since adapt-test pairs lying opposite to each other in face space generate larger identity AEs than non-opposite test pairs, this suggests that Asian and Caucasian faces are coded using race-specific norms, rather than a generic one. Moreover, we find that identification performance is better for face morphs that are created using these race-specific norms, independent of their actual identity strength. To our knowledge, this is the first evidence for a functional benefit of norms in face recognition