Argument Types Affect Children's Acquisition of a Novel Argument Structure.

Acquisition of an argument structure may be affected by the diversity of lexical types that appear in that structure (Conwell et al., 2011; Yang, 2016). Seventy-two 5- and 6-year-old English-speaking children completed a learning study where they were exposed to a novel argument structure and then tested on their ability to comprehend it.

Children are sensitive to mutual information in intermediate-complexity face and non-face features.

Understanding developmental changes in children's use of specific visual information for recognizing object categories is essential for understanding how experience shapes recognition. Research on the development of face recognition has focused on children's use of low-level information (e.g.

Children's use of local and global visual features for material perception.

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.

Neural Sensitivity to Mutual Information in Intermediate-Complexity Face Features Changes during Childhood.

One way in which face recognition develops during infancy and childhood is with regard to the visual information that contributes most to recognition judgments. Adult face recognition depends on critical features spanning a hierarchy of complexity, including low-level, intermediate, and high-level visual information. To date, the development of adult-like information biases for face recognition has focused on low-level features, which are computationally well-defined but low in complexity, and high-level features, which are high in complexity, but not defined precisely.

Perceiving Animacy in Own-and Other-Species Faces.

Though artificial faces of various kinds are rapidly becoming more and more life-like due to advances in graphics technology (Suwajanakorn et al., 2015; Booth et al., 2017), observers can typically distinguish real faces from artificial faces.

The Impact of Face Inversion on Animacy Categorization.

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.