Face animacy perception is categorical: Gradual changes in the real/artificial appearance of a face lead to nonlinear behavioral responses. Neural markers of face processing are also sensitive to face animacy, further suggesting that these are meaningful perceptual categories. Artificial faces also appear to be an “out-group” relative to real faces such that behavioral markers of expert-level processing are less evident with artificial faces than real ones. In the current study, we examined how categorical processing of real versus doll faces was impacted by the face inversion effect, which is one of the most robust markers of expert face processing. We examined how explicit categorization of faces drawn from a real/doll morph continuum was affected by face inversion (Experiment 1) and also how the response properties of the N170 were impacted by face animacy and inversion. We found that inversion does not change the position or steepness of the category boundary measured behaviorally. Further, neural markers of face processing are equally impacted by inversion regardless of whether they are elicited by real faces or doll faces. On balance, our results indicate that inversion has a limited impact on the categorical perception of face animacy.

Adults can rapidly recognize material properties in natural images, and children's performance in material categorization tasks suggests that this ability develops slowly during childhood. In the current study, we further examined the information children use to recognize materials during development by asking how the use of local versus global visual features for material perception changes in middle childhood. We recruited adults and 5-to 10-year-old children for three experiments that required participants to distinguish between shape-matched images of real and artificial food. Accurate performance in this task requires participants to distinguish between a wide range of material properties characteristic of each category, thus testing material perception abilities broadly. In two tasks, we applied distinct methods of image scrambling (block scrambling and diffeomorphic scrambling) to parametrically disrupt global appearance while preserving features in small spatial neighborhoods. In the third task, we used image blurring to parametrically disrupt local feature visibility. Our key question was whether or not participant age affected performance differently when local versus global appearance was disrupted. We found that although image blur led to disproportionately poorer performance in young children, this effect was reduced or absent when diffeomorphic scrambling was used. We interpret this outcome as evidence that the ability to recruit large-scale visual features for material perception may develop slowly during middle childhood.

Children’s ability to recognize emotional expressions from faces and bodies develops during childhood. However, the low-level features that support accurate body emotion recognition during development have not been well characterized. This is in marked contrast to facial emotion recognition, which is known to depend upon specific spatial frequency and orientation sub-bands during adulthood, biases that develop during childhood. Here, we examined whether children’s reliance on vertical vs. horizontal orientation energy for recognizing emotional expressions in static images of bodies changed during middle childhood (5 to 10 years old). We found that while children of all ages had an adult-like bias favoring vertical orientation energy, this effect was larger at younger ages. We conclude that in terms of information use, a key feature of the development of emotion recognition is improved performance with sub-optimal features for recognition – that is, learning to use less diagnostic features of the image is a slower process than learning to use more useful features.

Uncovering when children learn to use specific visual information for recognizingobject categories is essential for understanding how experience shapes recognition.Research on the development of face recognition has focused on children’s use oflow-level information (e.g. orientation sub-bands), or on children's use of high-levelinformation, namely, configural or holistic information. Do children also useintermediate complexity features for categorizing faces and objects, and if so, atwhat age? Intermediate-complexity features bridge the gap between low- and high- level processing: they have computational benefits for object detection and segmentation, and are known to drive neural responses in the ventral visual system.Here, we asked when children develop sensitivity to diagnostic category information in intermediate-complexity features. We presented children (5-10 years old) and adults with image fragments of faces (Experiment 1) and cars (Experiment 2) varying in their mutual information, which quantities a fragment's diagnosticity of a specific category. Our goal was to determine whether children were sensitive to the amount of mutual information in these fragments, and if their information usage is different from adults’. We found that despite better overall categorization performance in adults, all children were sensitive to fragment diagnosticity in both categories, suggesting that intermediate representations of appearance are established early in childhood. Moreover, children's usage of mutual information was not limited to face fragments, suggesting the extracting intermediate complexity features is a process that is not specific only to faces. We discuss the implications of our findings for developmental theories of face and object recognition.