Even as viewpoint changes with eye movements, postural changes, or self-motions, we perceive the world as stable based on the visual system’s environmental coordinate representation. It remains unclear which coordinate system is responsible for the contextual cueing effect, an implicit learning phenomenon for spatial arrangements. We investigated whether the contextual cueing effect is based on the environmental coordinate system or the body coordinate system when posture changes around the roll axis before and after learning. In our experiment, body position was changed between sitting and lying on one’s side before and after learning a task involving repeated visual search. The learning effect remained when the arrangement of objects was matched to the body coordinate system. Furthermore, we evaluated whether a natural image presented as a background could enhance the effect of the environmental coordinate system because it gives the spatial cue of the environment. The contextual cues that matched environmental coordinates were not used even if there is a background image; it is important that the background and contextual cues are matched to body coordinates in the learning and test phases.

The influence of social factors on visual attention is an increasingly important area in experimental psychology. However, there has been a little investigation of how self-construal affects how spatial attention selects visual information. Therefore, the purpose of this study was to examine the influence of self-construal on the breadth of attentional spotlight. The Eriksen flanker task was employed to ascertain whether the interference from task-irrelevant stimuli flanking a to-be-identified target is changed following self-construal manipulations. Furthermore, the interstimulus distances between flankers were varied in order to measure the extent to which the breadth of the attentional spotlight is modulated after the self-construal manipulations. Results suggest that changes in self-construal modulate the breadth of the attentional spotlight. Moreover, the findings cast new light on how attentional selection can be modulated by high-level, social factors.

Hierarchical Bayesian modeling is a powerful and promising tool that aids experimental psychologists to flexibly build and evaluate interpretable statistical models that consider inter-individual and inter-trial variability. This article offers several examples of hierarchical Bayesian modeling to introduce the idea and to show its implementation with R and Stan. As a tutorial, it uses data from well-known experimental paradigms in perceptual and cognitive psychology. Specifically, I present linear models for correct response time data from a mental rotation task, probit models for binary choice data from two psychophysical tasks, and drift diffusion models for both response time and binary choice data from an Eriksen flanker task. The R and Stan scripts and data are available on the Open Science Framework repository at https://doi.org/10.17605/osf.io/2zxs6. The importance of model selection and the potential functions of open data practices in statistical modeling are also briefly discussed.

This note is a short report on the activity of the Young Researchers Committee of the Japanese Psychonomic Society (JPS). As the highlighted activity of the committee, we have held the oral session of the annual meeting of JPS seven times. We also have opened a social networking account and created a portal site for psychonomic labs across the country to increase interaction. We continue to update the committee members and their selection process to increase the mobility of the members. We are developing new activities to target a wider range of young or early career researchers. In the future, this committee should become a more open, diverse, and impartial organization.