EXPRESS: Understanding Lateral and Vertical Biases in Consumer Attention: An In-Store Ambulatory Eye-Tracking Study

Given the conventional wisdom that “unseen is unsold,” retail practitioners are keenly interested in understanding consumers’ attention to products in the store. Using in-store ambulatory eye-tracking, we investigate the extent to which lateral and vertical biases drive consumers’ attention in a grocery store environment. Our dataset offers a complete picture of not only where the shopper is located, but also the shopper’s field of view and visual fixations during the trip. Using our novel dataset, we address two research questions: First, do shoppers have a higher propensity to pay attention to products on their left or right side as they traverse an aisle (i.e., is the right side the “right side”)? Second, do shoppers tend to pay more attention to products at their eye level (i.e., is eye-level “buy-level”)? We utilize the exogenous variations in the direction by which shoppers traverse an aisle (northward vs southward), obtainable from their shopping paths, to identify lateral bias. The exogenous variation of shoppers’ eye-level positions, due to their differences in height, is used to identify vertical bias. We find that shoppers pay more attention to products on their right side when traversing an aisle, and this bias holds for both right- and left-handed shoppers. Contrary to many practitioners’ belief, we find that eye-level is not “buy-level”; rather, the product level that has the highest propensity to capture shoppers’ attention is about 14.7 inches below eye-level (which is around chest level). Further, this vertical bias becomes more prominent during the latter part of a shopping trip.

Bilateral Differences in Dancers' Dynamic Postural Stability During Jump Landings

Although traditional dance training aims to train dancers' legs equally, the recognized practice of predominately starting and repeating exercises on one side more than the other has led to suggestions that technique classes may cause lateral bias. Such an imbalance could lead to a greater risk of injury; however, despite this potential risk, little is known about the effects of bilateral differences on dancers' postural stability during jump landings, a key dynamic action in dance. Therefore, the aim of this study was to examine the effects of possible bilateral differences on dynamic postural stability during single-leg landing using a time-to-stabilization protocol. Thirty-two injury-free female university undergraduate dancers (19 ± 1.9 years; 164.8 ± 6.7 cm; 62.6 ± 13.6 kg) volunteered for the study. They completed a two-foot to one-foot jump over a bar onto a force platform while stabilizing as quickly as possible. The landing leg was randomly assigned, and participants completed three trials for each leg. No significant differences in dynamic postural stability between right and left legs were revealed, and poor effect size was noted (p > 0.05): MLSI: t = -.04, df = 190, p = 0.940 (CI = -.04, .04, r2 = 0); APSI: t = .65, df = 190, p = 0.519 (CI = -.06-, .12, r2 = .09); VSI: t = 1.85, df = 190, p = 0.066 (CI = -.02, .68, r2 = .27); DPSI: t = 1.88, df = 190, p = 0.061 (CI = -.02, .70, r2 = .27). The results of this study do not support the notion that dance training may cause lateral bias with its associated risk of injury. Furthermore, dancers' self-perceptions of leg dominance did not correlate with their ability to balance in single-leg landings or to absorb the ground reaction forces often associated with injury. Even when biased training exists, it may not have detrimental effects on the dancer's postural stability.

Numerical magnitude, rather than individual bias, explains spatial numerical association in newborn chicks

We associate small numbers with the left and large numbers with the right side of space. Recent evidence from human newborns and non-human animals has challenged the primary role assigned to culture, in determining this spatial numerical association (SNA). Nevertheless, the effect of individual spatial biases has not been considered in previous research. Here, we tested the effect of numerical magnitude in SNA and we controlled for itablendividual biases. We trained 3-day-old chicks (Gallus gallus) on a given numerical magnitude (5). Then chicks could choose between two identical, left or right, stimuli both representing either 2, 8, or 5 elements. We computed the percentage of Left-sided Choice (LC). Numerical magnitude, but not individual lateral bias, explained LC: LC2 vs. 2>LC5 vs. 5>LC8 vs. 8. These findings suggest that SNA originates from pre-linguistic precursors, and pave the way to the investigation of the neural correlates of the number space association.

Laterality as a Tool for Assessing Breed Differences in Emotional Reactivity in the Domestic Cat, Felis silvestris catus

Cat breeds differ enormously in their behavioural disposition, a factor that can impact on the pet-owner relationship, with indirect consequences for animal welfare. This study examined whether lateral bias, in the form of paw preference, can be used as a tool for assessing breed differences in emotional reactivity in the cat. The paw preferences of 4 commonly owned breeds were tested using a food-reaching challenge. Cats were more likely to be paw-preferent than ambilateral. Maine Coons, Ragdolls and Bengals were more likely to be paw-preferent than ambilateral, although only the Bengals showed a consistent preference for using one paw (left) over the other. The strength of the cats’ paw use was related to cat breed, with Persians being more weakly lateralised. Direction of paw use was unrelated to feline breed, but strongly sex-related, with male cats showing a left paw preference and females displaying a right-sided bias. We propose that paw preference measurement could provide a useful method for assessing emotional reactivity in domestic cats. Such information would be of benefit to individuals considering the acquisition of a new cat, and, in the longer term, may help to foster more successful cat-owner relationships, leading to indirect benefits to feline welfare.

Global visual salience of competing stimuli

Current computational models of visual salience accurately predict the distribution of fixations on isolated visual stimuli. It is not known, however, whether the global salience of a stimulus, that is its effectiveness in the competition for attention with other stimuli, is a function of the local salience or an independent measure. Further, do task and familiarity with the competing images influence eye movements? Here, we investigated the direction of the first saccade to characterize and analyze the global visual salience of competing stimuli. Participants freely observed pairs of images while eye movements were recorded. The pairs balanced the combinations of new and already seen images, as well as task and task-free trials. Then, we trained a logistic regression model that accurately predicted the location---left or right image---of the first fixation for each stimulus pair, accounting too for the influence of task, familiarity and lateral bias. The coefficients of the model provided a reliable measure of global salience, which we contrasted with two distinct local salience models, GBVS and Deep Gaze. The lack of correlation of the behavioral data with the former and the small correlation with the latter indicate that global salience cannot be explained by the feature-driven local salience of images. Further, the influence of task and familiarity was rather small and we reproduced the previously reported left-sided bias. Summarized, we showed that natural stimuli have an intrinsic global salience related to the human initial gaze direction, independent of the local salience and little influenced by task and familiarity.

Systematic misperceptions of 3D motion explained by Bayesian inference

People make surprising but reliable perceptual errors. Here, we provide a unified explanation for errors in the perception of three-dimensional (3D) motion. To do so, we characterized the retinal motion signals produced by objects moving with arbitrary trajectories through arbitrary locations in 3D. Next, we developed a Bayesian model, treating 3D motion perception as optimal inference given sensory noise and the geometry of 3D viewing. The model predicts a wide array of systematic perceptual errors, that depend on stimulus distance, contrast, and eccentricity. We then used a virtual reality (VR) headset as well as a standard 3D display to test these predictions in both traditional psychophysical and more naturalistic settings. We found evidence that people make many of the predicted errors, including a lateral bias in the perception of motion trajectories, a dependency of this bias on stimulus contrast, viewing distance, and eccentricity, and a surprising tendency to misreport approaching motion as receding and vice versa. In sum, we developed a quantitative model that provides a parsimonious account for a range of systematic misperceptions of motion in naturalistic environments.