Nine-year-old children use norm-based coding to visually represent facial expression.

Abstract

Children are less skilled than adults at making judgments about facial expression. This could be because they have not yet developed adult-like mechanisms for visually representing faces. Adults are thought to represent faces in a multidimensional face-space, and have been shown to code the expression of a face relative to the norm or average face in face-space. Norm-based coding is economical and adaptive, and may be what makes adults more sensitive to facial expression than children. This study investigated the coding system that children use to represent facial expression. An adaptation aftereffect paradigm was used to test 24 adults and 18 children (9 years 2 months to 9 years 11 months old). Participants adapted to weak and strong antiexpressions. They then judged the expression of an average expression. Adaptation created aftereffects that made the test face look like the expression opposite that of the adaptor. Consistent with the predictions of norm-based but not exemplar-based coding, aftereffects were larger for strong than weak adaptors for both age groups. Results indicate that, like adults, children's coding of facial expressions is norm-based.

Face-Space: A Unifying Concept in Face Recognition Research

“…Typically, two-pool models have been employed to account for what appears to be opponent processing (e.g. Over, 1971) and have been successfully Consistently, many face after-effects are found to be larger for strong (e.g., extremely large or unusual) than weak adaptors indicating norm-based coding for many facial attributes (Burton, Jeffery, Skinner, Benton, & Rhodes, 2013 results have recently been modeled (Ross et al, 2014) indicating that an exemplar-based model of face-space can account for after-effects.…”

Norms are Not the Norm: Testing Theories of Sensory Encoding Using Visual Aftereffects

“…Reduced face aftereffects in children with autism spectrum disorder have been taken as evidence for deficiencies in norm-based face encoding in such groups (Ewing, Leach, Pellicano, Jeffery, & Rhodes, 2013;Pellicano, Jeffery, Burr, & Rhodes, 2007;Rhodes, Jeffery, Taylor, & Ewing, 2013;Rhodes, Maloney, et al, 2007;Walsh, Maurer, Vida, Rhodes, & Jeffery, 2015). Similarly, the early development of face aftereffects in children has been taken as evidence for the early maturation of normbased facial encoding (Burton et al, 2013;Jeffery et al, 2010Jeffery et al, , 2011Nishimura, Maurer, Jeffery, Pellicano, & Rhodes, 2008;Pimperton, Pellicano, Jeffery, & Rhodes, 2009). If face aftereffects do not arise from an inherently norm-based representational system, but from an exemplar-based representation, these findings will need to be re-interpreted.…”

“…It has been suggested that shifts in neutral category boundaries can differentiate locally repulsive from renormalising aftereffects if one compares the magnitudes of shifts induced by different 'strengths' of adaptor (Burton, Jeffery, Skinner, Benton, & Rhodes, 2013;Jeffery et al, 2010Jeffery et al, , 2011McKone et al, 2014;Pond et al, 2013;Skinner & Benton, 2010, 2012Zhao et al, 2011). A continuum of facial images morphing between different genders (for example) can be thought of as a one-dimensional slice through an artificial face space.…”

“…The first studies to test these predictions used only two different levels of adaptor strength, such as a weak and strong version of the same facial expression (Burton et al, 2013;Skinner & Benton, 2010), configural distortion (Jeffery et al, 2010), or facial identity . In all cases the more extreme adaptor induced a larger shift in the category boundary between two perceived expressions, distortions, or identities than the more neutral adaptor.…”

“…If gender were encoded by two opponent channels (as depicted in Figure 3), then an extremely masculine face should induce a larger renormalisation than a moderately masculine face, and therefore induce a larger change in the appearance of previously-neutral faces, as measured via a binary classification task. Alternatively, if gender were encoded by multiple channels tuned relatively narrowly to particular gender levels (as depicted in Figure 2), then the aftereffect measured near neutral test faces might initially increase as an adaptor becomes more extreme, but then diminish as the distance between adapting and test stimuli exceeds the limited range of local repulsion.The first studies to test these predictions used only two different levels of adaptor strength, such as a weak and strong version of the same facial expression (Burton et al, 2013;Skinner & Benton, 2010), configural distortion (Jeffery et al, 2010), or facial identity . In all cases the more extreme adaptor induced a larger shift in the category boundary between two perceived expressions, distortions, or identities than the more neutral adaptor.…”