Giuliana Macedo¹, Martin Wiener¹; ¹George Mason University

Visual stimuli are known to vary in their perceived duration, with a variety of features, including both high and low level, shaping temporal responses. For example, the size, memorability, or numerosity of stimuli lead to longer perceived intervals, thus highlighting the malleability of time perception. However, beyond stimulus size, the influence of stimulus curvature or angularity has on time perception, has yet to be explored. To investigate this, we had human participants (n=35) perform a sub-second visual temporal bisection task, in which they categorized visual stimuli with different levels of curvature into short and long duration categories. For visual stimuli, we employed the well-known “bouba-kiki” shapes, characterized by high curvature and high angularity, respectively, along with three linearly interpolated shapes between them (5 levels total). Studies on the bouba-kiki effect, which is the association of naming curved shapes "bouba" and angular shapes “kiki”, has been proven robust across languages and cultures (Cwiek, et al. 2021). Here, we hypothesized that more angular “kiki”-like shapes would dilate time. We additionally explored if these shapes with linguistic associations (“bouba” for curved, “kiki for angular) had any impact on time perception. As an additional control, we had subjects initially equalize the internal area of the shapes, to ensure no influence of size on time judgments. Finally, after the bisection task, we asked participants to name the shapes according to the “bouba-kiki” naming system to look for the influence of language on shape preference. Surprisingly, we found no dilation effects; instead, we discovered a linear increase in precision (as indexed by the coefficient of variation), as well as faster reaction times for progressively more angular stimuli, with no impact of naming preference. These findings suggest that the angularity of shape stimuli drives faster and more precise time judgments, which we interpret using an information-processing framework.