Attention To Patterns Research Articles

Attention Paid by Children of Rural Mapuche, Urban Mapuche and Non-Indigenous Chilean Backgrounds to Interactions Directed at Others.

This study aimed to establish differences in third-party attention through a toy-building activity among children between 9 and 11 years old from three cultural backgrounds: Rural Mapuche, Urban Mapuche and non-Indigenous Chilean. It was also examined whether third-party attention is related to learning a previously observed activity. Third-party attention involves maintaining two or more foci of interest simultaneously without losing attention and or interrupting the course of a task. It is of interest to study because it may undergo changes as a result of exposure to schooling. Given that these groups differ in cultural practices and years of formal schooling, the hypothesis was that it might be possible to identify differences in their attention patterns. The results showed that it seems like practices of Rural Mapuche families encourage third-party attention much more so than the other groups; therefore, the learning of skills arises in constellations of cultural practices that involve children's living conditions and guide their development.

Hyper-focus, sticky attention, and springy attention in young autistic children: Associations with sensory behaviors and cognitive ability.

The autistic-developed monotropism account suggests that atypical, domain-general attentional hyper-focus on interests is a central aspect of autism, but domain-general attention differences in autism can manifest differently. Prior research suggests autistic children are often slow to disengage attention from stimuli-a pattern often called "sticky attention"-and that they can show reduced novelty preference. These attentional patterns could influence sensory experiences and learning. We used eye-tracking to investigate novelty preference and "sticky attention" in young autistic children; we also examined whether attentional patterns were related to cognitive abilities and caregiver-reported sensory responsiveness. A total of 46 autistic and 28 nonautistic participants, aged between 2 and 4 years, provided usable data. We found no evidence that autistic children exhibited greater "sticky attention" than nonautistics, but "sticky attention" in autism was associated with more caregiver-reported sensory hyper-responsiveness, seeking/interests, and enhanced perception. Autistic children also nonsignificantly trended toward exhibiting reduced novelty preference. Unexpectedly, the time-course of this trending novelty preference difference implied it was not driven by reduced orienting to novelty, but increased returning to already-familiarized stimuli: what we call "springy attention." Exploratory analyses of data from the attentional disengagement task suggest autistic participants may have exhibited greater "springy attention," though further research with paradigms optimized for measuring this construct should confirm this. Importantly, "springy attention" was robustly related to reduced cognitive abilities and greater caregiver-reported hypo-responsiveness. Thus, this study illuminates two distinct domain-general attentional patterns, each with distinct correlates in young autistic children, which could have important implications for understanding autistic children's learning, development, and experiences.

Atypical and variable attention patterns reveal reduced contextual priors in children with autism spectrum disorder.

Accumulating evidence suggests that individuals with autism spectrum disorder (ASD) show impairments in using contextual priors to predict others' actions and make intention inference. Yet less is known about whether and how children with ASD acquire contextual priors during action observation and how contextual priors relate to their action prediction and intention inference. To form proper contextual priors, individuals need to observe the social scenes in a reliable manner and focus on socially relevant information. By employing a data-driven scan path method and areas of interest (AOI)-based analysis, the current study investigated how contextual priors would relate to action prediction and intention understanding in 4-to-9-year-old children with ASD (N = 56) and typically developing (TD) children (N = 50) during free viewing of dynamic social scenes with different intentions. Results showed that children with ASD exhibited higher intra-subject variability when scanning social scenes and reduced attention to socially relevant areas. Moreover, children with high-level action prediction and intention understanding showed lower intra-subject variability and increased attention to socially relevant areas. These findings suggest that altered fixation patterns might restrain children with ASD from acquiring proper contextual priors, which has cascading downstream effects on their action prediction and intention understanding.

Determining the Perception Created by Health Warnings on Plain Cigarette Packs with Visual Attention: Eye-Tracking Technique

This study examines the effects of the plain packaging policy implemented in Türkiye, analyzing how different demographic groups perceive health warnings on cigarette packaging. Employing advanced eye-tracking technology, the research identifies distinct visual attention patterns between smokers and non-smokers when exposed to ‘Anxiety’ and ‘Disturbing’ visual cues. Detailed metrics, including fixation counts, durations, and saccade amplitudes, are used to measure and analyze the responses of these groups to the health warnings. The findings reveal that non-smokers significantly focus more on textual warnings, suggesting that text-based elements are more impactful for this group. Conversely, smokers tend to either avoid or become desensitized to disturbing imagery. Additionally, the study finds that female participants exhibit higher saccade amplitudes compared to males, indicating a more thorough examination of the packaging. This gender-specific difference is especially pronounced in their responses to ‘Disturbing’ images, where females show greater engagement, pointing to an increased sensitivity to such stimuli. These insights not only advance our understanding of effective health communication but also underscore the importance of designing public health interventions that cater to the unique responses of different demographic groups. This research significantly enriches the field of tobacco control, providing evidence-based strategies to enhance the effectiveness of visual warnings, thereby supporting targeted smoking cessation efforts.

Seeing Wrongness

Abstract This paper examines the plausibility of an attention-based version of moral perceptualism (amp). According to amp, our perception of moral properties is characterized by perceptual attentional patterns that reflect a sensitivity to morally salient features. First, I argue that the explanation for the empirical evidence offered to support amp primarily hinges on cognitive processes rather than perceptual ones. Second, while I acknowledge the critical importance of attention in recognizing moral properties, I contend that we must expand amp’s explanatory scope to address the question of what drives this attention. I propose an account of our (in)sensitivity to wrongness that builds on amp’s core statement. In this account, the notion of salience structure of information, defined by the varying accessibility of both perceptual and cognitive representations, plays a central explanatory role.

Relationship between Visual Attention Patterns and Subjective Evaluations in Housing Sales Information: A Study Using Eye-Tracking Technology

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.

Heterophily-aware graph attention network

Graph Neural Networks (GNNs) have shown remarkable success in graph representation learning. Unfortunately, current weight assignment schemes in standard GNNs, such as the calculation based on node degrees or pair-wise representations, can hardly be effective in processing the networks with heterophily, in which the connected nodes usually possess different labels or features. Existing heterophilic GNNs tend to ignore the modeling of heterophily of each edge, which is also a vital part in tackling the heterophily problem. In this paper, we first propose a heterophily-aware attention scheme and reveal the benefits of modeling the edge heterophily, i.e., if a GNN assigns different weights to edges according to different heterophilic types, it can learn effective local attention patterns, enabling nodes to acquire appropriate information from distinct neighbors. Then, we propose a novel Heterophily-Aware Graph Attention Network (HA-GAT) by fully exploring and utilizing the local distribution as the underlying heterophily, to handle the networks with different homophily ratios. To demonstrate the effectiveness of the proposed HA-GAT, we analyze the proposed heterophily-aware attention scheme and local distribution exploration, by seeking an interpretation from their mechanism. Extensive results demonstrate that our HA-GAT achieves state-of-the-art performances on eight datasets with different homophily ratios in both the supervised and semi-supervised node classification tasks.

Do autistic adults spontaneously reason about belief? A detailed exploration of alternative explanations.

Southgate et al.'s (Southgate 2007 Psychol. Sci. 18, 587-92 (doi:10.1111/j.1467-9280.2007.01944.x)) anticipatory-looking paradigm has presented exciting yet inconclusive evidence surrounding spontaneous mentalizing in autism. The present study aimed to develop this paradigm to address alternative explanations for the lack of predictive eye movements on false-belief tasks by autistic adults. This was achieved through implementing a multi-trial design with matched true-belief conditions, and both high and low inhibitory demand false-belief conditions. We also sought to inspect if any group differences were related to group-specific patterns of attention on key events. Autistic adults were compared with non-autistic adults on this adapted implicit mentalizing task and an established explicit task. The two groups performed equally well in the explicit task; however, autistic adults did not show anticipatory-looking behaviour in the false-belief trials of the implicit task. Critically, both groups showed the same attentional distribution in the implicit task prior to action prediction, indicating that autistic adults process information from social cues in the same way as non-autistic adults, but this information is not then used to update mental representations. Our findings further document that many autistic people struggle to spontaneously mentalize others' beliefs, and this non-verbal paradigm holds promise for use with a wide range of ages and abilities.

Negative images, regardless of task relevance, distract younger more than older adults.

Older adults, compared to younger adults, tend to prioritize positive information more and negative information less. We recently observed this "positivity effect" pattern in an emotion-induced blindness task, which measures attention allocated to task-irrelevant emotional stimuli in the way participants are distracted by them. Older adults were less distracted by negative images compared to younger adults. This could represent an age-related priority shift away from negative emotions. However, it could also be that older adults simply do not see negative images presented at a fast rate. A similar possibility is that older adults to fail to engage with negative stimuli because of their complex nature, rather than due to age-related changes in emotional preference per se. In the present study, we tested this possibility by manipulating the required degree of engagement with emotional distractors. Participants completed a modified emotion-induced blindness task, with emotional distractors that were either task irrelevant (younger: n = 48; older: n = 46) or task relevant (younger: n = 48; older: n = 45). The task relevance of distractors did not affect performance. Even though older adults could quickly perceive the negative images, they were less distracted by them compared to younger adults. Current theories of the positivity effect fail to fully account for these positivity effect patterns in attention, especially those that propose mechanisms requiring a substantial time to enact. The current results may require rethinking previous accounts of the positivity effect and highlight the benefits of probing the positivity effect in early cognitive processing stages. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

An efficient Transformer with neighborhood contrastive tokenization for hyperspectral images classification

The success of vision Transformers (ViTs) relies heavily on the self-attention mechanism, which requires support from appropriate patch tokenization. However, hyperspectral image (HSI) often suffer from significant noise distortions and spectral uncertainty, which result in unstable attention patterns and overfitting due to equivocal tokenization. In this paper, we propose a neighborhood contrastive tokenization task (NeiCoT) to learn compact, semantically meaningful, and context-sensitive tokens for efficient Transformer encoding. Specifically, we employ a predictor on patch embedding to maximize the mutual information between local individuals and their global average anchor. This encourages neighboring tokens’ relevance and active participation in feature learning. Next, we revise a token-level contrastive loss to align predictions with local individuals and distinguish them from other samples in a mini-batch to enhance tokens rich in contextual semantics. Furthermore, we apply a Gaussian weighting to the tokens’ contrastive loss to balance the neighborhood contribution. Finally, we propose a sequence-specific MAE framework with NeiCoT to achieve HSI representation, and additionally validate NeiCoT on a supervised Transformer backbone. The results demonstrate that NeiCoT consistently enhances the robustness and generalization of the Transformer, achieving accurate object recognition and boundary localization even with limited training samples. Our code will be available at https://github.com/zoegnov07/NeiCoT.

Attentional Processes in Pain: The Importance of Context and Attentional Alignment

The attentional bias literature has consistently failed to take context into account. We developed a novel paradigm in immersive virtual reality (VR) with pain stimuli where it would be adaptive or nonadaptive to attend to the stimuli. Participants had to indicate the location of the stimuli. Seventy participants were recruited. The VR-attention task assessed overall attentional bias (the tendency to prioritize pain compared with nonpain stimuli) and attentional alignment (the tendency to attend to pain more in adaptive than nonadaptive situations). Pain tolerance and threshold were measured using electrocutaneous stimulation and thermal pain. We conducted 2 (context: adaptive vs nonadaptive) × 2 (congruence: congruent vs incongruent) Analysis of Covariance, controlling for threat. Participants responded to pain probes more quickly in adaptive than nonadaptive contexts. There was an overall bias away from pain-related stimuli (avoidance) in reaction time to the target. There was also an interaction where avoidance was greater in nonadaptive contexts, indicative of attentional alignment. For gaze behavior, both attentional alignment and attentional bias were observed for latency to first fixation on the target, such that participants showed vigilance for pain particularly in the adaptive context. Attentional alignment was correlated with threshold and tolerance from electrocutaneous stimulation but not thermal pain. In conclusion, we found overall attentional biases indicating vigilance (latency to first fixation) and avoidance (response to target). We also found that participants evidenced a pattern of attention favoring adaptive over nonadaptive contexts (attentional alignment). It was attentional alignment, but not overall attentional bias, that predicted pain tolerance and threshold. PerspectiveThe study explored attentional processes in pain through a novel paradigm designed in VR. The results found that positive attentional alignment, or the tendency to attend to pain more in adaptive contexts rather than nonadaptive contexts, predicted pain outcomes.

Social media engagement of supportive care publications in oncology

ImportanceThere is an increasing number of cancer ‘survivors’ and increasing research into supportive care. However, it is unknown how patterns of attention and citation differ between supportive and non-supportive cancer care research. We sought to estimate the engagement of high-impact studies of supportive compared to non-supportive cancer care papers. MethodsIn a cross-sectional review of top oncology journals (2016–2023), we reviewed studies examining supportive care strategies and a frequency-matched random sampling of studies on non-supportive interventions. We compared data on social engagement metrics, as represented by Altmetric scores and citations and funding status, by supportive care or non-supportive care articles. ResultsWe found overall Altmetric scores were no different between articles that did not test supportive care and those that did, with a numerically higher score for supportive care articles (86.0 vs 102; p=0.416). Other bibliometric statistics (such as the number of blogs, number of X users, and the number of X posts) obtained from Altmetric did not differ significantly between the two groups. Non-supportive cancer care papers had a significantly higher number of citations than supportive cancer care papers (45.6 in supportive care vs 141 in non-supportive care papers; p<0.001). A greater proportion of non-supportive cancer care papers were also supported by pharmaceutical companies compared to supportive cancer care papers (54.2 % vs 15.3 %; p<0.001). ConclusionThough social media engagement is similar between supportive and non-supportive cancer care papers in high-impact journals, there is a significant difference in support from pharmaceutical companies and the number of citations.

Influence of Material and Decoration on Design Style, Aesthetic Performance, and Visual Attention in Chinese-Style Chairs

Abstract Chinese-style chairs are appreciated by many consumers for their elegant design. The material and decoration have a significant impact on the design of Chinese-style chairs. Exploring the influence of these two factors on design styles and aesthetic expressions, as well as the related visual attention patterns, is of great importance for the design of Chinese-style chairs. This study aimed to investigate the impact of material (wood/metal) and decoration (pattern/no pattern) on the design style, aesthetic performance, and visual attention patterns of Chinese-style chairs. Fifty-six Chinese university students wore eye-tracking glasses to view four types of chair designs and completed subjective rating scales. The results show that material and decoration have both independent and interactive effects. Wood chairs exhibit a traditional design style and superior aesthetic performance compared to metal chairs. Traditional Chinese patterns enhance design style and aesthetic performance, particularly when applied to wooden chairs. Visual attention was not significantly different across chair designs, except for wooden chairs with traditional patterns on the backrest, which attracted more attention. These research findings provide reference for designers to design Chinese-style chairs.

Neurotourism Insights: Eye Tracking and Galvanic Analysis of Tourism Destination Brand Logos and AI Visuals

This pioneering study explores the intersection between Neurotourism, defined as the integration of neurosciences in tourism, and the perception of tourism Brand Personality (BP) through the advanced use of psychophysiology techniques, specifically Eye-Tracking (ET) and Galvanic Skin Response (GSR). It analyses how tourism destination brand logos/combination marks and images generated by artificial intelligence (AI) influence consumer attention and emotional response. Focusing on the five dimensions of BP proposed by Aaker (1997) - sincerity, excitement, sophistication, competence, and ruggedness - this study highlights significant differences in how men and women process and react to brand values associated with specific cities. Employing a rigorous methodological approach and the application of non-parametric statistical analyses, the findings reveal distinct patterns of visual attention and emotional responses across genders, emphasising the importance of considering BP in the marketing and design of tourism destination brand logos/combination marks. This work not only advances theoretical understanding of tourist consumer behaviour but also offers relevant practical implications for tourism marketing and destination management.

CELA-MFP: a contrast-enhanced and label-adaptive framework for multi-functional therapeutic peptides prediction.

Functional peptides play crucial roles in various biological processes and hold significant potential in many fields such as drug discovery and biotechnology. Accurately predicting the functions of peptides is essential for understanding their diverse effects and designing peptide-based therapeutics. Here, we propose CELA-MFP, a deep learning framework that incorporates feature Contrastive Enhancement and Label Adaptation for predicting Multi-Functional therapeutic Peptides. CELA-MFP utilizes a protein language model (pLM) to extract features from peptide sequences, which are then fed into a Transformer decoder for function prediction, effectively modeling correlations between different functions. To enhance the representation of each peptide sequence, contrastive learning is employed during training. Experimental results demonstrate that CELA-MFP outperforms state-of-the-art methods on most evaluation metrics for two widely used datasets, MFBP and MFTP. The interpretability of CELA-MFP is demonstrated by visualizing attention patterns in pLM and Transformer decoder. Finally, a user-friendly online server for predicting multi-functional peptides is established as the implementation of the proposed CELA-MFP and can be freely accessed at http://dreamai.cmii.online/CELA-MFP.

LDCT image biomarkers that matter most for the deep learning classification of indeterminate pulmonary nodules.

Continued improvement in deep learning methodologies has increased the rate at which deep neural networks are being evaluated for medical applications, including diagnosis of lung cancer. However, there has been limited exploration of the underlying radiological characteristics that the network relies on to identify lung cancer in computed tomography (CT) images. In this study, we used a combination of image masking and saliency activation maps to systematically explore the contributions of both parenchymal and tumor regions in a CT image to the classification of indeterminate lung nodules. We selected individuals from the National Lung Screening Trial (NLST) with solid pulmonary nodules 4-20 mm in diameter. Segmentation masks were used to generate three distinct datasets; 1) an Original Dataset containing the complete low-dose CT scans from the NLST, 2) a Parenchyma-Only Dataset in which the tumor regions were covered by a mask, and 3) a Tumor-Only Dataset in which only the tumor regions were included. The Original Dataset significantly outperformed the Parenchyma-Only Dataset and the Tumor-Only Dataset with an AUC of 80.80 ± 3.77% compared to 76.39 ± 3.16% and 78.11 ± 4.32%, respectively. Gradient-weighted class activation mapping (Grad-CAM) of the Original Dataset showed increased attention was being given to the nodule and the tumor-parenchyma boundary when nodules were classified as malignant. This pattern of attention remained unchanged in the case of the Parenchyma-Only Dataset. Nodule size and first-order statistical features of the nodules were significantly different with the average malignant and benign nodule maximum 3d diameter being 23mm and 12mm, respectively. We conclude that network performance is linked to textural features of nodules such as kurtosis, entropy and intensity, as well as morphological features such as sphericity and diameter. Furthermore, textural features are more positively associated with malignancy than morphological features.

Teaching Eye Tracking: Challenges and Perspectives

Eye tracking studies are more complicated to design, conduct, and to evaluate than traditional studies solely based on performance measures like error rates and response times. This is typically due to the more complex hardware setup, the calibration procedures, and the spatio-temporal nature of the recorded data that must be analyzed, visualized, or statistically evaluated. As a benefit, eye movement data contains patterns of visual attention over space and time that are not observable in standard error rates, completion times, and qualitative feedback. Students in the field of visualization, human-computer interaction, and user experience represent an interest group that would benefit from the application of eye tracking during their studies and in their future careers. Consequently, instructing them how to design, setup, conduct, and evaluate an eye tracking study is of special interest to current researchers involved in teaching. We describe education in eye tracking in five courses with 79 students from bachelor, master, and PhD levels. We outline our concept and discuss the challenges to raise people with no experience in eye tracking to a level of knowledge that allows them to apply this emerging technology to different scenarios including visual stimuli and related research questions. We discuss our teaching strategy in two course setups (summer school and traditional university lecture), the results of the students' eye tracking studies, and which challenges they and the teachers faced during the course.

Exploring the impact of autistic traits and anxiety on visual attentional response to angry faces in adults with high autistic traits: An eye-movement study

This study investigated the impact of autistic traits and anxiety on the visual attentional response to angry faces among individuals with varying levels of autistic traits in the general population. Two experiments were conducted. In Experiment 1, eye-tracking methodology was used to compare 26 participants with high autistic traits to 26 individuals with low autistic traits. The latency of the first fixation on images of angry faces, neutral faces, and objects during a free viewing task was measured. Anxiety levels were assessed using the Self-rating Anxiety Scale. Experiment 2 utilized an overlap task to examine attentional response patterns toward angry faces in individuals with high and low autistic traits. The findings revealed that participants with high autistic traits displayed a longer latency to first fixation on angry faces during the free-viewing task compared to those with low autistic traits. However, no significant differences were observed for neutral faces and objects. In the overlap task, the group with high autistic traits demonstrated a significantly prolonged latency to first fixation on angry faces in peripheral positions when the central stimulus was a neutral face and the peripheral stimulus was an angry face, relative to the group with low autistic traits. Importantly, when taking anxiety traits into account as a covariate in both experiments, the previously observed group effects no longer remained significant. These results were discussed within the frameworks of social motivation theory and the autism continuum hypothesis.

Do Australian police engage in racial profiling? A method for identifying racial profiling in the absence of police data

ABSTRACT Expanding on a technique developed by Epp, C. R., Maynard-Moody, S., & Haider-Markel, D. (2014). Pulled over: How police stops define race and citizenship, this study develops a methodology for identifying racial profiling from the descriptions of police stops obtained from a survey of members of the public. The analysis subjects 981 accounts of police stops in Victoria described in a survey conducted in 2018–2019 to a ‘threshold’ analysis followed by a multinomial regression controlling for age, gender, LGBITQ status and disability. The results provide strong evidence that race is associated with decision-making by police in Victoria about who to subject to high discretion stops and unjustified post-stop conduct and a consistent pattern of unjustified law enforcement attention on and treatment of racialised compared with white people. This is particularly apparent for Aboriginal, African, Pasifika and Middle-Eastern/Muslim appearing people. The unjustified nature of this policing provides evidence that it is racial appearance, not crime, that is triggering police attention and subsequent behaviour.

94. Patterns of Social Attention in Autistic Children: Influence of Co-Occurring ADHD Diagnosis

94. Patterns of Social Attention in Autistic Children: Influence of Co-Occurring ADHD Diagnosis