Face shape information used to classify identity and expression is highly precise, flexible and context-specific

We classify faces every day to help us gauge social situations, facilitate communication, and retain relationships. A goal of face perception research is to understand what specific face features are important during such tasks, and how shape information specific to one task (e.g., identity recognition) is influenced by that specific to another (e.g., expression recognition). One way to accomplish this is through the recovery of observer templates, which summarize what parts of an image are considered useful by the visual system to solve a particular task. Templates can be estimated through psychophysical techniques like reverse correlation. We use reverse correlation to estimate identity and expression templates by presenting participants with pairs of faces randomly sampled from a space of face shape parameters. By averaging chosen noise patterns, we obtained the template estimates. Although previous studies have superimposed noise by altering pixel luminance, we manipulate stimulus noise in face shape space using a three-dimensional face modeling toolbox. Our new approach allows us to directly visualize interactions between identity and expression through face model rendering and constrain interpretations to a simple and comprehensible stimulus space for faces. Permutation tests revealed that features informative for identity and expression recognition are distributed across the entire face. More importantly, we assessed invariance at the level of templates to find whether the shape information used to identify levels of one dimension (e.g., identity) does not vary with changes in another dimension (e.g., expression), a type of perceptual invariance known as template separability. Additional permutation tests found significant violations of template separability for both dimensions across all groups, suggesting that information sampling during face recognition is highly context-specific. Our results imply that the information used by the visual system during recognition of face identity and expression is highly precise, flexible, and context-specific.