An important aspect to an immersive experience in Virtual Reality is vection, defined as the illusion of self-motion. Much of the literature to date has explored strategies to maximize vection through manipulations of the visual stimulus (e.g., increasing speed) or the experimental context (e.g., framing of the study instructions). However, the role of individual differences (e.g., age, biological sex) in vection susceptibility has received little attention. The objective of the current study was to investigate the influence of individual-difference factors on vection perception in younger and older adults. Forty-six younger adults (M age = 25.1) and 39 older adults (M age = 72.4) completed assessments of personality traits, field dependence, and visual attention prior to observing a moving visual stimulus aimed at inducing circular vection. Vection was measured using self-reports of onset latency, duration, and intensity. Results indicated that, in both age groups, females experienced longer-lasting vection compared to males. Additionally, the level of field dependence was related to vection intensity and duration in males but not in females. Variability in vection intensity was best explained by a mixture of biological, perceptual, cognitive, and personality variables. Taken together, these findings suggest that individual factors are important for understanding differences in vection susceptibility.

Individuals\' abilities to perform goal-directed spatial deployments of attention are distinguishable from their broader preferences for how they use spatial attention when circumstances do not compel a specific deployment strategy. Although these preferences are likely to play a major role in how we interact with the visual world during daily life, they remain relatively understudied. This exploratory study investigated two key questions about these preferences: firstly, are individuals consistent in their preferences for how they deploy their spatial attention when making shifts of attention versus adopting an attentional breadth? Secondly, which other factors are associated with these preferences? Across two experiments, we measured how participants preferred to deploy both attentional breadth (using an adapted Navon task) and eye movements (using a free-viewing task). We also measured participants\' working memory capacities (Experiment 1), and their personalities and world beliefs (Experiment 2). In both experiments, there were consistent individual differences in preference for attentional breadth and eye movement characteristics, but these two kinds of preference were unrelated to each other. Working memory capacity was not linked to these preferences. Conversely, the personality trait of Openness to Experience robustly predicted two aspects of eye movement behavior preference, such that higher levels of Openness predicted smaller saccades and shorter scan paths. This suggests that personality dimensions may predict preferences for more absorbed engagement with visual information. However, it appears that individuals\' preferences for shifts of attention during scene viewing do not necessarily relate to the breadth of attention they choose to adopt.

Compared to the abundance of research on cognition in various nonhuman primate species, studies of gibbons -- often called \"the small apes\" -- remain limited, despite the importance of gibbons for understanding evolutionary processes in humans and other apes. Over the past decade, eye tracking techniques have been established in chimpanzees and other nonhuman primates using the free-participation method, which requires no physical restraint of the subjects. We investigated the feasibility of using the same method to record visual scanpaths in gibbons. We attempted to measure the eye movements of three adult gibbons while they spontaneously viewed images, with no prior fixation training. Calibration was successful in all three individuals, with errors of less than one degree. In total, 24 stimuli were used, with landscape and nonhuman primate face photographs presented on one-quarter of the screen, to test the prediction that gibbons would change their viewing time depending on image category. All three gibbons viewed the images for longer than the background, and primate face images for longer than landscapes. These results are consistent with previous findings in other primate species that faces attract more attention than non-face stimuli, suggesting that this effect is common across primates. This study demonstrates the feasibility of using eye tracking with gibbons. Further studies on gibbon visual exploration and cognition may enhance our understanding of the phylogenetic origins of hominid intelligence as well as the unique evolution of gibbons.

UNASSIGNED: L-theanine is a non-protein-forming amino acid found in tea. Limited evidence suggests that it improves selective attention. Sleep deprivation impairs attention and psychomotor reactions, affecting automobile driving. We aimed to determine whether L-theanine improves neurobehavioral measures of visual attention in acutely sleep-deprived healthy adults in a traffic-scene-based attention task.
UNASSIGNED: In a double-blind, placebo-controlled, counterbalanced, two-way crossover study, we compared the effects of a 200-mg dose of L-theanine with a placebo (150 ml of distilled water) on a computerised, traffic-scene-based visual recognition reaction task in 24 healthy volunteers (age 20-25 years; 13 males) sleep-deprived overnight. The participants made speeded button-presses to imminent accident scenes (i.e. hits), while ignoring safe scenes. They were tested pre-dose and 45 min post-dose, each treatment administered one week apart.
UNASSIGNED: Hit rates were more than 90% in all sessions, and were similar in two treatments, pre- vs post-dose. L-theanine significantly reduced false alarms (i.e. responses to safe scenes) (p = 0.014) and increased A\' (i.e. target-distractor discriminability) (p = 0.009), whereas placebo did not (p > 0.05). L-theanine reduced hit reaction time by 38.65 ms (p = 0.007), and placebo by 19.08 ms (p = 0.016), however reaction time changes from baseline were not significantly different between treatments (p > 0.05).
UNASSIGNED: L-theanine in high doses appears to improve selective visual attention by concurrently improving information processing speed and target-distractor discriminability in acutely sleep-deprived individuals. This is consistent with previous functional neuroimaging findings, where L-theanine suppressed distractor-processing and default-mode-network activity in visual selective attention tasks.

Own child\'s face is one of the most socially salient stimuli for parents, and a faster search for it than for other children\'s faces may help provide warmer and more sensitive care. However, it has not been experimentally examined whether parents find their child\'s face faster. In addition, although own child\'s face is specially processed, the search time for own child\'s face may be similar to that for other socially salient stimuli, such as own or spouse\'s faces. This study tested these possibilities using a visual search paradigm. Participants (parents) searched for their child\'s, own, spouse\'s, other child\'s, same-sex adult\'s, or opposite-sex adult\'s faces as search targets. Our findings indicate that both mothers and fathers identified their child\'s face more quickly than other children\'s faces. Similarly, parents found their own and spouse\'s faces more quickly than other adults\' faces. Moreover, the search time for family members\' faces increased with the number of faces on the search display, suggesting an attentional serial search. These results suggest that robust face representations learned within families and close relationships can support reduced search times for family members\' faces.

The way people create social connections and access information has been altered greatly by technology in recent decades. Online browsing of visual profiles has become a common means for seeking potential partners for both short- and long-term relationships. Little is known, however, about how people prioritize mate quality information while viewing online profiles. Using eye-tracking methods and self-report, this study investigated how people evaluated profile-based facial attractiveness and text-based financial resources information, represented by income and occupation. Heterosexual male and female participants, aged between 18 and 27 years, viewed opposite-sex profiles while their eye-movements were recorded using a remote eye-tracking camera. In line with current theory, resources information had little effect on men\'s overall attention to women\'s faces, whereas women\'s overall attention to men\'s faces varied depending on the level of income and occupation. Women evaluated men\'s faces more when income and occupation were low, regardless of attractiveness. Unexpectedly, however, men marginally increased their attention toward unattractive women who showed a high-level of income and more esteemed occupation. Men self-reported a higher interest in women for a short-term relationship and women self-reported a higher interest in men for a long-term relationship. This work provides a foundation to further examine how people browse profile-based information and to investigate the mate selection process, with real-world implications for online dating app users, profile design, and content.

OBJECTIVE: E-cigarette marketing exposure on social media influences perceptions; however, limited knowledge exists regarding marketing features attracting the most visual attention. This study examined visual attention to features of social media marketing for disposable e-cigarettes and related product perceptions.
METHODS: Participants viewed 32 disposable marketing post images from social media (Instagram) using computer-based eye-tracking technology to assess standardized attention metrics of marketing features. They then completed a survey assessing positive product perceptions. The study took place in New Jersey, USA, June-September 2022, comprising young adults (aged 18-29) who do not use tobacco (n = 72) or who smoke cigarettes (n = 42).
METHODS: We examined associations between 14 marketing features (e.g. product package, personal item, fruit/candy descriptor, social media account) and standardized attention metrics of dwell time (fixation duration) and entry time (time to first fixation). Then, we assessed attention metrics for each feature in relation to positive product perceptions (appeal and positive use expectancy).
RESULTS: Among all participants, dwell time was the longest for the product descriptor [marginal means (MM) = 1.77; 95% confidence interval (CI) = 1.69, 1.86], social media account (MM = 1.76; 95% CI = 1.67, 1.85) and fruit/candy descriptor features (MM = 1.56; 95% CI = 1.41, 1.70); entry time was the shortest for the social media account (MM = 0.35; 95% CI = 0.26, 0.46), personal item (MM = 0.36; 95% CI = 0.17, 0.56) and human model features (MM = 0.40; 95% CI = 0.08, 0.72). Two use status groups had comparable dwell and entry times, except for the product descriptor feature. Longer dwell time for the product package feature increased positive product perceptions among both use status groups [regression coefficient (β) = 0.44 and 2.61]. Longer dwell time for fruit/candy descriptor (β = 1.80) and price promotion features (β = 4.04) increased positive product perceptions among those who smoke.
CONCLUSIONS: US young adults appear to be particularly visually engaged by disposable e-cigarette marketing that uses social media account features (account profile pictures, information about the products marketed and relevant hashtags) and features enhancing the products\' personal relatability. Disposable product packages, fruit/candy descriptors and price promotions may increase the influence of social media marketing among various use status groups.

BACKGROUND: Falls are common in a range of clinical cohorts, where routine risk assessment often comprises subjective visual observation only. Typically, observational assessment involves evaluation of an individual\'s gait during scripted walking protocols within a lab to identify deficits that potentially increase fall risk, but subtle deficits may not be (readily) observable. Therefore, objective approaches (e.g., inertial measurement units, IMUs) are useful for quantifying high resolution gait characteristics, enabling more informed fall risk assessment by capturing subtle deficits. However, IMU-based gait instrumentation alone is limited, failing to consider participant behaviour and details within the environment (e.g., obstacles). Video-based eye-tracking glasses may provide additional insight to fall risk, clarifying how people traverse environments based on head and eye movements. Recording head and eye movements can provide insights into how the allocation of visual attention to environmental stimuli influences successful navigation around obstacles. Yet, manual review of video data to evaluate head and eye movements is time-consuming and subjective. An automated approach is needed but none currently exists. This paper proposes a deep learning-based object detection algorithm (VARFA) to instrument vision and video data during walks, complementing instrumented gait.
METHODS: The approach automatically labels video data captured in a gait lab to assess visual attention and details of the environment. The proposed algorithm uses a YoloV8 model trained on with a novel lab-based dataset.
RESULTS: VARFA achieved excellent evaluation metrics (0.93 mAP50), identifying, and localizing static objects (e.g., obstacles in the walking path) with an average accuracy of 93%. Similarly, a U-NET based track/path segmentation model achieved good metrics (IoU 0.82), suggesting that the predicted tracks (i.e., walking paths) align closely with the actual track, with an overlap of 82%. Notably, both models achieved these metrics while processing at real-time speeds, demonstrating efficiency and effectiveness for pragmatic applications.
CONCLUSIONS: The instrumented approach improves the efficiency and accuracy of fall risk assessment by evaluating the visual allocation of attention (i.e., information about when and where a person is attending) during navigation, improving the breadth of instrumentation in this area. Use of VARFA to instrument vision could be used to better inform fall risk assessment by providing behaviour and context data to complement instrumented e.g., IMU data during gait tasks. That may have notable (e.g., personalized) rehabilitation implications across a wide range of clinical cohorts where poor gait and increased fall risk are common.

Caregiver-infant interactions shape infants\' early visual experience; however, there is limited work from low-and middle-income countries (LMIC) in characterizing the visual cognitive dynamics of these interactions. Here, we present an innovative dyadic visual cognition pipeline using machine learning methods which captures, processes, and analyses the visual dynamics of caregiver-infant interactions across cultures. We undertake two studies to examine its application in both low (rural India) and high (urban UK) resource settings. Study 1 develops and validates the pipeline to process caregiver-infant interaction data captured using head-mounted cameras and eye-trackers. We use face detection and object recognition networks and validate these tools using 12 caregiver-infant dyads (4 dyads from a 6-month-old UK cohort, 4 dyads from a 6-month-old India cohort, and 4 dyads from a 9-month-old India cohort). Results show robust and accurate face and toy detection, as well as a high percent agreement between processed and manually coded dyadic interactions. Study 2 applied the pipeline to a larger data set (25 6-month-olds from the UK, 31 6-month-olds from India, and 37 9-month-olds from India) with the aim of comparing the visual dynamics of caregiver-infant interaction across the two cultural settings. Results show remarkable correspondence between key measures of visual exploration across cultures, including longer mean look durations during infant-led joint attention episodes. In addition, we found several differences across cultures. Most notably, infants in the UK had a higher proportion of infant-led joint attention episodes consistent with a child-centered view of parenting common in western middle-class families. In summary, the pipeline we report provides an objective assessment tool to quantify the visual dynamics of caregiver-infant interaction across high- and low-resource settings.

The visual system operates rhythmically, through timely coordinated perceptual and attentional processes, involving coexisting patterns in the alpha range (7-13 Hz) at ∼10 Hz, and theta (3-6 Hz) range, respectively. Here we aimed to disambiguate whether variations in task requirements, in terms of attentional demand and side of target presentation, might influence the occurrence of either perceptual or attentional components in behavioral visual performance, also uncovering possible differences in the sampling mechanisms of the two cerebral hemispheres. To this aim, visuospatial performance was densely sampled in two versions of a visual detection task where the side of target presentation was fixed (Task 1), with participants monitoring one single hemifield, or randomly varying across trials, with participants monitoring both hemifields simultaneously (Task 2). Performance was analyzed through spectral decomposition, to reveal behavioral oscillatory patterns. For Task 1, when attentional resources where focused on one hemifield only, the results revealed an oscillatory pattern fluctuating at ∼10 Hz and ∼6-9 Hz, for stimuli presented to the left and the right hemifield, respectively, possibly representing a perceptual sampling mechanism with different efficiency within the left and the right hemispheres. For Task 2, when attentional resources were simultaneously deployed to the two hemifields, a ∼5 Hz rhythm emerged both for stimuli presented to the left and the right, reflecting an attentional sampling process, equally supported by the two hemispheres. Overall, the results suggest that distinct perceptual and attentional sampling mechanisms operate at different oscillatory frequencies and their prevalence and hemispheric lateralization depends on task requirements.