Date: Wednesday, 16.11.22 15:20 CET
Abstract:
Face processing plays a central role in everyday human life. Here, we investigate the nature of face representation and processing in the brain, by adapting and developing appropriate machine learning and computer vision methods. For example, using the Active Appearance Model, which has recently been shown to have latent features encoded by face processing neurons in the primate brain, we show that human social trait perception has both a linear component and a quadratic component, with the latter specifically related to the statistical typicality of a face. We relate this typicality element to the coding cost of neural representation, and its implications for learning and exploration. In the cognitive domain, we examine how attentional modulation affects face representation and perception. In the social domain, we examine how facial processing affects social perception and judgment, with implications for gender and racial biases. Finally, in the psychiatric domain, we examine how depression and anxiety in an individual interact with face perception and face-based decision making.
