About the Contributors

Biography

About the Contributors     

About the Contributors

Note

About the Contributors     

The development of executive functioning and theory of mind. A comparison of Chinese and U.S. preschoolers

Preschoolers' theory-of-mind development follows a similar age trajectory across many cultures. To determine whether these similarities are related to similar underlying ontogenetic processes, we examined whether the relation between theory of mind and executive function commonly found among U.S. preschoolers is also present among Chinese preschoolers. Preschoolers from Beijing, China (N= 109), were administered theory-of-mind and executive-functioning tasks, and their performance was compared with that of a previously studied sample of U.S. preschoolers (N= 107). The Chinese preschoolers outperformed their U.S. counterparts on all measures of executive functioning, but were not similarly advanced in theory-of-mind reasoning. Nonetheless, individual differences in executive functioning predicted theory of mind for children in both cultures. Thus, the relation between executive functioning and theory of mind is robust across two disparate cultures. These findings shed light on why executive functioning is important for theory-of-mind development.     

A comparison of statistical selection strategies for univariate and bivariate log‐linear models

In this study, eight statistical selection strategies were evaluated for selecting the parameterizations of log‐linear models used to model the distributions of psychometric tests. The selection strategies included significance tests based on four chi‐squared statistics (likelihood ratio, Pearson, Freeman–Tukey, and Cressie–Read) and four additional strategies (Akaike information criterion (AIC), Bayesian information criterion (BIC), consistent Akaike information criterion (CAIC), and a measure attributed to Goodman). The strategies were evaluated in simulations for different log‐linear models of univariate and bivariate test‐score distributions and two sample sizes. Results showed that all eight selection strategies were most accurate for the largest sample size considered. For univariate distributions, the AIC selection strategy was especially accurate for selecting the correct parameterization of a complex log‐linear model and the likelihood ratio chi‐squared selection strategy was the most accurate strategy for selecting the correct parameterization of a relatively simple log‐linear model. For bivariate distributions, the likelihood ratio chi‐squared, Freeman–Tukey chi‐squared, BIC, and CAIC selection strategies had similarly high selection accuracies.     

Gamma flicker elicits positive affect without awareness

High-frequency oscillations emerged as a neural code for both positive affect and fluent attentional processing from evolutionary simulations with artificial neural networks. Visual 50 Hz flicker, which entrains neural oscillations in the gamma band, has been shown to foster attentional switching, but can it also elicit positive affect? A three-faces display (2-female/1-male or 2-male/1-female) was preceded by a 50, 25, or 0 Hz flicker on the position of the odd-one-out (i.e., the target). Participants decided on the gender (Block 1) or on the subjective valence (Block 2) of this neutral target in an approach-avoidance task, which served as an implicit affective measure. Only the detection of 25 Hz flicker, but not of 50 Hz flicker, was above chance (Block 3). Faces primed by invisible 50 Hz flicker were explicitly evaluated more positively than with 25 Hz or 0 Hz. This gamma flicker also facilitated approach reactions, and inhibited avoidance reactions relative to 25 Hz and 0 Hz flicker in Blocks 1 and 2. Attentional switching was, moreover, enhanced by the 50 Hz flicker. According to the Affect–Gamma hypothesis, also in biological neural networks, high-frequency gamma oscillations may code for positive affect.