Stereotypical Processing of Emotional Faces: Perceptual and Decisional Components

People tend to associate anger with male faces and happiness or surprise with female faces. This angry-men-happy-women bias has been ascribed to either top-down (e.g., well-learned stereotypes) or bottom-up (e.g., shared morphological cues) processes. The dissociation between these two theoretical alternatives has proved challenging. The current effort addresses this challenge by harnessing two complementary metatheoretical approaches to dimensional interaction: Garner's logic of inferring informational structure and General Recognition Theory—a multidimensional extension of signal detection theory. Conjoint application of these two rigorous methodologies afforded us to: (a) uncover the internal representations that generate the angry-men-happy-women phenomenon, (b) disentangle varieties of perceptual (bottom-up) and decisional (top-down) sources of interaction, and (c) relate operational and theoretical meanings of dimensional independence. The results show that the dimensional interaction between emotion and gender is generated by varieties of perceptual and decisional biases. These outcomes document the involvement of both bottom-up (e.g., shared morphological structures) and top-down (stereotypes) factors in social perception.

Sensitivity vs. Awareness Curve: A Novel Model-Based Analysis to Uncover the Processes Underlying Nonconscious Perception

In this study, we present a novel model-based analysis of the association between awareness and perceptual processing based on a multidimensional version of signal detection theory (general recognition theory, or GRT). The analysis fits a GRT model to behavioral data and uses the estimated model to construct a sensitivity vs. awareness (SvA) curve, representing sensitivity in the discrimination task at each value of relative likelihood of awareness. This approach treats awareness as a continuum rather than a dichotomy, but also provides an objective benchmark for low likelihood of awareness. In two experiments, we assessed nonconscious facial expression recognition using SvA curves in a condition in which emotional faces (fearful vs. neutral) were rendered invisible using continuous flash suppression (CFS) for 500 and 700 milliseconds. We predicted and found sub-conscious processing of face emotion, in the form of higher than chance-level sensitivity in the area of low likelihood of awareness.