Every day, people perceive other people performing interactive actions. Retaining these actions of human agents in working memory (WM) plays a pivotal role in a normal social life. However, whether the semantic knowledge embedded in the interactive actions has a pervasive impact on the storage of the actions in WM remains unknown. In the current study, we investigated two opposing hypotheses: (a) that WM stores the interactions individually (the individual-storage hypothesis) and (b) that WM stores the interactions as chunks (the chunk-storage hypothesis). We required participants to memorize a set of individual actions while ignoring the underlying social interactions. We found that although the social-interaction aspect was task irrelevant, the interactive actions were stored in WM as chunks that were not affected by memory load (Experiments 1 and 2); however, inverting the human actions vertically abolished this chunking effect (Experiment 3). These results suggest that WM automatically and efficiently used semantic knowledge about interactive actions to store them and support the chunk-storage hypothesis.

Most gestural interaction studies on gesture elicitation have focused on hand gestures, and few have considered the involvement of other body parts. Moreover, most of the relevant studies used the frequency of the proposed gesture as the main index, and the participants were not familiar with the design space. In this study, we developed a gesture set that includes hand and non-hand gestures by combining the indices of gesture frequency, subjective ratings, and physiological risk ratings. We first collected candidate gestures in Experiment 1 through a user-defined method by requiring participants to perform gestures of their choice for 15 most commonly used commands, without any body part limitations. In Experiment 2, a new group of participants evaluated the representative gestures obtained in Experiment 1. We finally obtained a gesture set that included gestures made with the hands and other body parts. Three user characteristics were exhibited in this set: a preference for one-handed movements, a preference for gestures with social meaning, and a preference for dynamic gestures over static gestures.

Maintaining an appropriate level of trust in automated driving (AD) is critical to safe driving. However, few studies have explored factors affecting trust in AD in general, and no study, as far as is known, has directly investigated whether driver personality influences driver trust in an AD system. The current study investigates the relation between driver personality and driver trust in AD, focusing on Level 2 AD. Participants were required to perform a period of AD in a driving simulator, during which their gaze and driving behavior were recorded, as well as their subjective trust scores after driving. In three distinct measures, a significant correlation between Openness and driver trust in the AD system is found: participants with higher Openness traits tend to have less trust in the AD system. No significant correlations between driver trust in AD and other personality traits are found. The findings suggest that driver personality has an impact on driver trust in AD. Theoretical and practical implications of this finding are discussed.

Microsaccades are small, involuntary eye movements that occur during fixation. Since the 1950s, researchers have conducted extensive research on the role of microsaccades in visual information processing, and found that they also play an important role in human advanced visual cognitive activities. Research over the past 20 years further suggested that there is a close relationship between microsaccades and visual attention, yet lacking a timely review. The current article aims to provide a state-of-the-art review and bring microsaccades studies into the sight of attention research. We firstly introduce basic characteristics about microsaccades, then summarized the empirical evidence supporting the view that microsaccades can reflect both external (perception) and internal (working memory) attention shifts. We finally conclude and highlight three promising avenues for future research.