The face inversion effect—Parts and wholes: Individual features and their configuration

Abstract

The face inversion effect (FIE) is a reduction in recognition performance for inverted faces (compared to upright faces) that is greater than that typically observed with other stimulus types (e.g., houses). The work of Diamond and Carey, suggests that a special type of configural information, “second-order relational information” is critical in generating this inversion effect. However, Tanaka and Farah concluded that greater reliance on second-order relational information did not directly result in greater sensitivity to inversion, and they suggested that the FIE is not entirely due to a reliance on this type of configural information. A more recent review by McKone and Yovel provides a meta-analysis that makes a similar point. In this paper, we investigated the contributions made by configural and featural information to the FIE. Experiments 1a and1b investigated the link between configural information and the FIE. Remarkably, Experiment 1b showed that disruption of all configural information of the type considered in Diamond and Carey's analysis (both first and second order) was effective in reducing recognition performance, but did not significantly impact on the FIE. Experiments 2 and 3 revealed that face processing is affected by the orientation of individual features and that this plays a major role in producing the FIE. The FIE was only completely eliminated when we disrupted the single feature orientation information in addition to the configural information, by using a new type of transformation similar to Thatcherizing our sets of scrambled faces. We conclude by noting that our results for scrambled faces are consistent with an account that has recognition performance entirely determined by the proportion of upright facial features within a stimulus, and that any ability to make use of the spatial configuration of these features seems to benefit upright and inverted normal faces alike.

Keywords:

• Inversion effect
• Configural information
• Face recognition
• Expertise