Emerging holistic properties at face value: Assessing characteristics of face perception

Holistic face recognition refers to the ability of human cognitive systems to deal in an integrative manner with separate face features. A holistic mental representation of a face is not a simple sum of face parts. It possesses unitary properties and corresponds to the whole face appearance better than to any of its constituent parts. A single face feature is better recognized in the learned face context (e.g. Bill's nose in Bill's face) than in isolation or in a new face context (e.g. Bill's nose in Joe's face; Tanaka & Sengco, 1997). The major goal of this study is to provide a rigorous test of the structure and organization of cognitive processes in the holistic perception of faces. Participants performed in two types of face categorization tasks that utilized either a self-terminating or an exhaustive rule for search (OR and AND conditions). Category membership was determined by the manipulation of two configural properties: eye-separation and lips-position. In the first part of each study, participants learned two groups of faces, and we monitored the changes in the face recognition system architecture and capacity. In the second part, the participants' task was to recognize the learned configurations of face features, presented in different face contexts: in the old learned faces, in a new face background and in isolation. Using the systems factorial theory tests, combined with statistical analyses and model simulations, we were able to reveal the exact organization of the mental processes underlying face perception. The findings supported a view that holism is an emergent property which develops with learning. Overall, processing exhibited a parallel architecture with positive interdependency between features in both the OR and AND conditions. We also found that face units are better recognized in the learned face condition than in both the new face context and isolation conditions. We showed that faces are recognized not as a set of independent face features, but as whole units. We revealed that the cognitive mechanism of positive dependence between face features is responsible for forming holistic faces, and provided a simulation that produced behaviors similar to the experimental observations.