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Visual attention and eye movements
Abstract
This chapter reviews the evidence linking attention and saccadic eye movements
... Visual attention is a fundamental cognitive function that enables organisms to selectively process some sensory information and ignore the rest. At the behavioral level, attended stimuli are associated with improved perceptual judgements and faster reaction times, compared to unattended [1][2][3][4][5]. At the neuronal level, attended stimuli are associated with increased spiking activity and decreased spike-count correlations compared to unattended [6][7][8][9][10]. ...
... The model replicates key behaviors observed in NHP experiments. When trained on a cued orientation-change detection task [11,48], the model exhibits enhanced performance and faster reaction times for cued stimuli compared to uncued ones [1][2][3][4][5]. Manipulating model attention affects perfor-mance in qualitatively similar ways to experimental manipulations in primate frontal eye fields (FEF) [49] and superior colliculus (SC) [50,51]. ...
... By training the model using reinforcement learning with reward feedback [47], we emulated how attentional biases can be shaped by reward contingencies, mirroring learning processes in the brain. The NNMVA exhibits key behavioral signatures of visual attention observed in experimental studies, such as improved performance and faster reaction times for cued stimuli compared to uncued ones [1][2][3][4][5]. Furthermore, we found that the self-attention map demonstrated priority map-like configuration from which we could easily measure and manipulate the bias towards some representations over others. ...
We present a neural network model of visual attention (NNMVA) that integrates biased competition and reinforcement learning to capture key aspects of attentional behavior. The model combines self-attention mechanisms from Vision Transformers (ViTs), Long Short-Term Memory (LSTM) networks for working memory, and an actor critic reinforcement learning framework to map visual inputs to behavioral outputs. The self-attention mechanism simulates biased competition among artificial neural representations, determining their influence on working memory, which in turn provides top-down feedback to guide attention. Trained end-to-end with reinforcement learning using reward feedback paralleling learning processes in non-human primates the NNMVA replicates key behavioral signatures of attention, such as improved performance and faster reaction times for cued stimuli. Manipulating the model's attention mechanisms affects performance in ways analogous to experimental manipulations in primate frontal eye fields and superior colliculus. Additionally, artificially inducing attentional biases alters value estimates and temporal difference (TD) errors, offering predictions about how attention may interact with dopamine related learning signals in the brain. Our findings suggest that reward-driven behavior alone can account for several key correlates of attention, providing a computational framework to explore the interplay between attention and reinforcement learning in both biological and artificial systems.
... Eye tracking studies revealed that the temporal aspect of visuals within a text provides a context that primes readers' mind for new or important information (Gegenfurtner et al., 2011;Hoffman, 2016), which facilitates better comprehension (Huth et al., 2024;Lee and Révész, 2018;Loewen and Inceoglu, 2016). These visual cues also act as cognitive anchors, aiding information retention (Pjesivac et al., 2021). ...
... On the other hand, its sparsity in its field stands observable despite its prevalence in studies. Extensive research on eye tracking in traditional settings has produced insightful findings, particularly regarding its impact on multimodal texts (Gegenfurtner et al., 2011;Hoffman, 2016;Huth et al., 2024;Lee and Révész, 2018;Loewen and Inceoglu, 2016). Additionally, the extent of the demographics of the participants includes dyslexics (Hyönä and Olson, 1995;Jones et al., 2008) and children with ADHD (Karatekin and Asarnow, 1998). ...
This mini-review advocates for the role of eye-tracking research in understanding readers’ engagement with multimodal texts. Synthesizing findings from a variety of studies, the review reveals how eye-tracking gives insights into sophisticated interactions between the textual, visual, and auditory elements within reading environments that assist both cognitive processing and comprehension. Several gaps were revealed: limited demographic scope, integration of advanced technologies, and substantial impact to the area of eye tracking and multimodal literacy. Future directions must therefore include studies across diverse populations, innovative technologies, and cross-discipline research studies. These directions are critical for advancing literacy development in an increasingly multimodal digital world.
... Peripheral vision involves a loss of visual acuity and entails costly attention crowding. It is unlikely to take place in a laboratory setting, particularly when the task has a clear purpose(Hoffman 1998;Rosenholtz 2016). ...
Scholars often face a choice when designing conjoint experiments: to allow for or to exclude “odd” combinations of attribute levels in the randomized conjoint profiles shown to respondents (such as a profile of a Democratic candidate who does not support abortion rights or an individual who is a medical doctor but does not have a graduate degree). While previous work has studied the statistical and theoretical implications of this decision, there has been little effort to analyze how it impacts the behavior of survey respondents. Utilizing eye-tracking, this study considers how respondents’ attention, information search behavior, and choice patterns respond to odd combinations of attributes included in conjoint profiles. We find that the impact of odd attribute-level combinations is minimal. They do not impact attention, search, or choice behavior substantially or consistently. Our conclusion is that scholars should prioritize other considerations—such as statistical, theoretical, and substantive considerations—when designing conjoint experiments.
... Studies that have used eye-tracking to examine gaze shifting as a behavioral marker of attention show differences in visual attention to social stimuli compared with nonsocial stimuli in both children and adults (e.g., Fletcher-Watson et al., 2008;Kikuchi et al., 2009;Ro et al., 2001;Slessor et al., 2016). Different patterns of visual attention to faces are also related to differences in emotion processing and emotion recognition (Hoffman, 1998). For example, visual attention to faces varies as a function of emotion, with more attention allocated to faces that depict fear than happy or neutral faces across development (e.g., Bannerman et al., 2009; for a review, see Vaish et al., 2008). ...
Rapid and accurate emotion recognition is a crucial skill for social interactions, and visual attention to informative social cues in the environment can facilitate emotion recognition. Studies have found that emotion recognition is also associated with underlying cardiac autonomic responses. The current study examined (1) visual attention and cardiac response (change in heart rate) to emotionally-expressive faces and houses (as a nonsocial control image), and (2) associations between these responses and emotion recognition on the Reading the Mind in the Eyes Test (RMET) in college students. Results showed increased overall attention, but shorter first fixation durations, to faces as compared to houses. Across faces, attention was greater to eyes than mouth, but the magnitude of this difference was dependent on emotion. Analysis of cardiac responses revealed greater heart rate deceleration to happy and fearful faces as compared to neutral faces and houses. Better emotion recognition accuracy on the RMET was related to greater attention to faces, and eyes specifically, as well as greater heart rate deceleration to faces relative to houses. No relations between visual attention and cardiac response were found. The current work points to variations in visual attention and cardiac responses while viewing emotional faces that can be markers of emotion processing ability.
... Conversely, the results from the 7 participants who negatively commented on the herbal garden suggested that faster eye movement speed correlated with a deterioration in attitudes and emotions towards the garden. Eye movement speed is related to visual attention (Bakan and Shotland, 1969;Hoffman, 2016), and visual attention is also related to changes in mood caused by visual stimuli (H€ uttermann and Memmert, 2015;Wadlinger and Isaacowitz, 2006). Therefore, two possibilities exist for the increase in eye movement speed. ...
Purpose
The design of Japanese gardens is a naturalistic style, and previous studies have shown the relaxation effects by viewing a Japanese garden. The purpose of this study is to find a trend of eye movement in viewing a Japanese garden and elucidate the relationship between eye movements and relaxation effects compared to a geometric garden.
Design/methodology/approach
A Japanese-style garden and a geometrically designed herbal garden were selected for the experiment. Participants' eye movement and heart rate were measured during their 5-min observation of the garden to assess their physiological responses. Additionally, POMS-SF was used to assess their psychological responses.
Findings
Pearson correlation analysis revealed a stronger significant correlation between eye movement data and relaxation mechanisms in the Japanese garden. Compared to the herbal garden, the Japanese garden had more fixations and faster eye movement speed, and better relaxation effects.
Practical implications
This study suggests that exploring the relationship between design, eye movement, and relaxation mechanisms from different perspectives of landscape design is feasible. For example, our results demonstrate that the layout of landscape elements, texture, details, and maintenance in the Japanese garden hold participants' longer attention, resulting in a better relaxation effect.
Originality/value
This study clarified how a garden design can manipulate eye movements to induce relaxing effects.
... While eye tracking captures various fixation movements, most studies focus on saccadic movements-rapid shifts between fixation points [27,28]. These visual patterns, analyzed in terms of ocular fixations [28], provide insights into visual attention allocated to stimuli [29]. Marketing studies establish a relationship between fixation patterns and increased interest or processing effort during observation [30][31][32]. ...
Traditionally, studies analyzing consumer preferences in real estate have focused on measuring subjective user responses, neglecting associated physiological responses. This study investigates the relationship between visual attention patterns and subjective evaluations of home sales information. Eye-tracking technology was used to record two characteristics of 21 participants’ visual behavior while viewing stimuli containing information about home sales (First Fixation Time and Total Fixation Duration). Additionally, participants evaluated their level of satisfaction with nine dwelling characteristics based on a questionnaire adapted for this research (1, quality and finishes of the dwelling; 2, size of the dwelling; 3, dwelling floor level; 4, bright and outdoor orientation of the dwelling; 5, flexible layout; 6, peaceful atmosphere; 7, smart and secure character; 8, privacy; and 9, original and luxurious character). The results demonstrated significant correlations between fixation time on specific areas of the stimulus and subjective ratings of features such as size, quality, finishes, layout, and orientation of the homes. Furthermore, differences based on gender and participants’ architecture experience level were observed in visual behavior during image observation. These findings underscore the importance of visual design and presentation in home marketing, as visual attention can influence perceptions of home characteristics and, ultimately, purchase decisions.
People visiting different destinations around the world demand that tourist attractions be showcased before being visited. This drives us to study which types of adventure tourist attractions arouse greater interest among potential visitors, with the aim of optimizing communication in the city of Baños de Agua Santa in Ecuador. An eye-tracking-based design was used with 42 male and female participants, who were shown adventure images according to visual path-oriented pairings. Among all fixations, it is men who prevail in visual scanning, focusing on action elements, while women contribute with greater peripheral fluency in visual elements and their processing. There is a marked coincidence in the visual attraction of rafting between both sexes, as a group activity within the set of sports considered adventure sports. Thus, the data set shows a certain dominance by the male target in fixations on adventure images, probably rooted in competitive culture, defined by the covert action around the practice of these sports, which involves adventure and nature.
While the visual world is rich and complex, importantly, it nevertheless contains many statistical regularities. For example, environmental feature distributions tend to remain relatively stable from one moment to the next. Recent findings have shown how observers can learn surprising details of environmental color distributions, even when the colors belong to actively ignored stimuli such as distractors in visual search. Our aim was to determine whether such learning influences orienting in the visual environment, measured with saccadic eye movements. In two visual search experiments, observers had to find an odd-one-out target. Firstly, we tested cases where observers selected targets by fixating them. Secondly, we measured saccadic eye movements when observers made judgments on the target and responded manually. Trials were structured in blocks, containing learning trials where distractors came from the same color distribution (uniform or Gaussian) while on subsequent test trials, the target was at different distances from the mean of the learning distractor distribution. For both manual and saccadic measures, performance improved throughout the learning trials and was better when the distractor colors came from a Gaussian distribution. Moreover, saccade latencies during test trials depended on the distance between the color of the current target and the distractors on learning trials, replicating results obtained with manual responses. Latencies were slowed when the target color was within the learning distractor color distribution and also revealed that observers learned the difference between uniform and Gaussian distributions. The importance of several variables in predicting saccadic and manual reaction times was studied using random forests, revealing similar rankings for both modalities, although previous distractor color had a higher impact on free eye movements. Overall, our results demonstrate learning of detailed characteristics of environmental color distributions that affects early attentional selection rather than later decisional processes.
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