Impact of emotional working memory training on threat-related attentional bias in social anxiety: Evidence from eye movements.

Deep learning synthesis of DBT features from mammography for breast cancer diagnosis.

Background: This study investigated whether visuo-spatial cognitive load modulates threat-related attentional bias during an experimentally induced stress state. Specifically, we examined whether increasing task demand influences threat-related attentional bias, as well as orientation and disengagement components.Methods: Seventy-two undergraduate participants were randomly assigned to either a stress-induction group or a control group. After viewing a road-traffic-accident video, participants completed a dot-probe task incorporating three levels of visuo-spatial task demand (no load, low load, high load). From this task, a standard Attentional Bias Index (sABI), an Orientation Index (OI), and a Disengagement Index (DI) were calculated.Results: The main effect of group was significant for both sABI and OI, indicating that across all visuo-spatial load conditions, the stress-induction group demonstrated greater threat-related attentional bias and stronger orientation toward threat than the control group. In contrast, neither the main effect of visuo-spatial task demand nor the Group×Demand interaction reached significance for sABI or OI. For DI, there were no significant group differences, no main effect of visuo-spatial task demand, and no significant interaction, suggesting that disengagement from threat did not differ between groups and was not influenced by cognitive load.Conclusions: Under stress induction, the stress-induction group consistently showed heightened threat-related attentional bias and increased orientation toward threat compared with the control group, regardless of visuo-spatial load level. These findings carry theoretical and clinical implications, underscoring the importance of distinguishing among attentional-bias components—particularly orientation—when conceptualizing and addressing stress-related attentional processes.

Objectives: Women with Premenstrual Syndrome (PMS) tend to exhibit an excessive attention bias toward negative stimuli during the luteal phase. This study intends to investigate the effect of regular yoga on attention bias of women with PMS during the luteal phase and explore the mechanisms underlying such changes. Methods: Sixty-four women with PMS were recruited, coded and randomly assigned to either a 12-week yoga group (n = 32) or a control group (n = 32). The dot-probe task was used to assess attention bias at baseline and 12 weeks later. Data analysis was performed using SPSS 27.0 software, with analytical methods including descriptive statistics, repeated-measures analysis of variance (RM-ANOVA), simple effect analysis, cluster-based permutation test and Pearson correlation analysis. The Holm–Bonferroni method was used to correct for multiple comparison errors. Results: RM-ANOVA revealed significant time × group interaction effects for attention orientation, attention disengagement, P1 component, and P3 component. Simple effect analysis indicated that, compared with the control group, the yoga group exhibited significant modulations in attention orientation (t = −7.33, p < 0.001), P1 (t = 8.94, p < 0.001), attention disengagement (t = 6.89, p < 0.001), and P3 (t = 4.42, p = 0.002) after 12 weeks of intervention. Cluster-based permutation tests demonstrated that the yoga group showed significant reductions in P1 and P3 amplitudes after 12 weeks. Pearson correlation analysis indicated that attention orientation was significantly negatively correlated with P1 amplitude, while attention disengagement was significantly positively correlated with P3 amplitude. Conclusion: Regular yoga can regulate the behavioral indicators and electroencephalographic (EEG) indicators related to attention bias and exerts a positive effect on modulating attention bias toward negative stimuli in women with PMS during the luteal phase.

The effect of transcranial direct current stimulation and nutritional counseling therapy on attentional bias to food cues: a randomized clinical trial.

Food cues that appear in the visual field capture our attention easily and can influence eating behavior. The current study investigated the influence of food-related stimuli on visual attention, considering the macronutrient composition of food items. Images representing sweet and savory foods were employed, the latter consisting primarily of high-protein foods. The participants were primed with these images prior to performing the attentional task. We found that both sets of food images elicited an emotional attentional blink (EAB), but a stronger EAB was observed for the high-protein foods, and this observation was further supported by a negative correlation between the attentional bias (ABias) and the proportion of protein consumed by the participants before the experiment, with participants who consumed less protein exhibiting a stronger ABias toward high-protein foods. These findings suggest that an ABias might also arise to facilitate the consumption of high-protein foods when prior consumption of this macronutrient is low.

Inhibitory control deficits are associated with cocaine use disorder (CUD) development and maintenance. Additionally, drug use and inhibitory control can be negatively affected by depressive symptoms, including somatic factors like sleep disturbance and fatigue. The current study assessed the relationship between inhibitory control and depressive symptoms among individuals initiating CUD treatment. We examined associations among anti-saccade response inhibition performance, total scores on the Beck Depression Inventory-II (BDI-II), and individual BDI-II items. N = 101 patients enrolled in a clinical trial for CUD completed drug-specific anti-saccade and depression (BDI-II) measures prior to treatment. Generalized linear models tested the associations of anti-saccade error rate with stimulus type (cocaine, neutral) and with BDI-II total score. Penalized regression then modeled the error rate among the entire set of BDI-II items to select the most relevant symptom correlates. Anti-saccade error rates were higher on cocaine relative to neutral trials (p < 0.001), confirming attentional bias. Error rates were positively associated with BDI-II total scores, controlling for demographic and recent cocaine use variables (p < 0.001); this association did not differ by stimulus content (p = 0.742). Among BDI-II items, Loss of Pleasure, Crying, Agitation, Changes in Sleeping Pattern, Concentration Difficulty, Tiredness, and Loss of Interest in Sex were retained by the penalized regression of error rates. Attentional bias was drug-specific, and overall error rates were strongly related to somatic factors underlying depression in CUD. The association between inhibitory control and depression in CUD may be driven by physiological symptomatology, including sleep impairment and fatigue. gov:NCT02896712.

Intrasexual competition is when members of the same sex compete for access to desirable mates. In women, the use of non-physical strategies, such as verbal and indirect aggression, are often preferred to mitigate potential risks of being targeted or to prevent partner desertion. To act accordingly, women have to attend to cues, such as facial expressions, to be able to discern if an individual is a potential threat. The current study (N = 136) aimed at investigating the role of women's intrasexual competition and rival derogation strategies in women's visual attention and vigilance to angry, happy, and neutral facial expressions. Using an eye-tracking paradigm, women viewed images of women's emotional facial expressions in pairs (e.g., angry-neutral, angry-happy, happy-neutral) followed by rating faces for their perceived levels of threat. Women who reported higher levels of intrasexual competition demonstrated attentional biases to angry and neutral facial expressions, while rival derogation strategies also moderated the relationship between facial expressions and visual attention. These findings demonstrate the proximate mechanisms involved in women's intrasexual competition when scanning images of potential intrasexual rivals.

With AI agents increasingly deployed, their failures demand strategies to sustain user forgiveness. While post-failure remedies are well-studied, there is still limited literature on how kindchenschema cuteness facilitate user forgiveness to ensure an opportunity for system improvement and user maintenance. Grounded in evolutionary psychology, this study examines how kindchenschema cuteness affects forgiveness toward failing AI agents. Using multi-method approach (behavioral experiments, eye-tracking, ECG), we reveal: (1) kindchenschema cuteness triggers dual forgiveness pathways: enhancing emotional empathy via perceived warmth while boosting cognitive tolerance via perceived competence; (2) novice personality framing strengthens this effect, particularly for high severity failures; and (3) physiological evidence confirms users' attentional bias toward kindchenschema features (prolonged fixation) and increased emotional arousal (higher ECG changes). These findings bridge evolutionary psychology with human-AI interaction by validating biologically rooted kindchenschema cute response mechanisms. For practitioners, we offer insights for designing failure resistant AI agents through strategic anthropomorphism and personality framing.

Harmful social connection: Partner maltreatment & health.

Author Correction: Early social adversity modulates the relation between attention biases and socioemotional behaviour in juvenile macaques

One account of the characteristic holistic processing of facesand objects of expertise posits that it arises from a learned attention to the whole, rendering it difficult to attend only to parts of stimuli. We tested whether task-context-induced attentional biases for the top or bottom part of a stimulus alter holistic processing of faces. We induced attentional biases by manipulating the probability (75% or 25%) that the top or bottom part would be task-relevant in a modified composite part-judgement task. Manipulating the proportion of trials in which the top/bottom region was task-relevant (i.e., whether the top/bottom was cued) induced the expected attention bias, with increased sensitivity for the part more likely to be cued. Despite this, there was limited evidence of an impact on holistic face processing, with the probabilistic cueing manipulation failing to impact the congruency effect. In a second experiment, we investigated whether this finding extends to stimulus-driven holistic processing of line patterns rich in Gestalt cues. Here, the only evidence of an impact on holistic processing was the attenuation of a greater congruency effect for bottom, over top, judgements in the bottom-bias condition. However, this was primarily the result of a reduction in a general bias to process the top region, present for face and non-face stimuli, rather than a direct impact on holistic processing. Thus, holistic processing for both stimulus types was relatively robust to the influence of task context-based attentional biases. However, there was some evidence of greater flexibility in stimulus-driven, compared to more experience-driven, processing more generally.

While previous studies have shown memory enhancement for items with statistical regularities, it remains unclear whether this advantage persists when people are not anticipating the need to recall that information. Here, we used the attribute amnesia paradigm to examine whether statistical regularities influence working memory encoding in the absence of intentional memorization. In Experiment 1, participants reported the location of a colored target that appeared more frequently in one color. On a surprise trial probing target color, participants who saw the target in the frequent color were significantly more likely to answer correctly than those who saw it in a less frequent color. More importantly, regardless of which color was actually shown, participants across both groups tended to choose the frequent color as target color, suggesting a response bias, rather than enhanced encoding, driven by statistical regularities. Experiment 2 inserted a separate visual search task with equalized color probabilities and found an attentional bias toward the frequent color, confirming its attentional prioritization. Experiment 3 extended the above findings to task-irrelevant, yet physically salient and attention-grabbing distractors. Together, these findings indicate that although statistical regularities do not enhance working memory encoding, participants implicitly extract summary statistics of attended item attributes across trials, which in turn shapes their subsequent decisions.

Major depressive disorder (MDD) represents a prevalent mental health condition characterized by prominent attentional biases, particularly toward negative stimuli. While extensive research has established the significance of negative attentional bias in depression, critical gaps remain in understanding the temporal dynamics and valence-specificity of these biases. This study employed eye-tracking technology to systematically examine the attentional processing of emotional faces (happy, fearful, sad) in MDD patients (n = 61) versus healthy controls (HC, n = 47), assessing both the initial orientation (initial gaze preference) and sustained attention (first dwell time). Key findings revealed the following: (1) while both groups showed an initial vigilance toward threatening faces (fearful/sad), only MDD patients displayed an additional attentional capture by happy faces; (2) a significant emotion main effect (F (2, 216) = 10.19, p < 0.001) indicated a stronger initial orientation to fearful versus happy faces, with Bayesian analyses (BF < 0.3) confirming the absence of group differences; and (3) no group disparities emerged in sustained attentional maintenance (all ps > 0.05). These results challenge conventional negativity-focused models by demonstrating valence-specific early-stage abnormalities in MDD, suggesting that depressive attentional dysfunction may be most pronounced during initial automatic processing rather than later strategic stages. The findings advance the theoretical understanding of attentional bias in depression while highlighting the need for stage-specific intervention approaches.

Attentional bias modification treatment for obsessive-compulsive disorder: a randomized clinical trial.

Attentional bias significantly influences the development, persistence, and exacerbation of anxiety disorders in individuals with high trait anxiety (HTA). Although attention encompasses both temporal and spatial aspects, temporal attentional bias remains underexplored. Traditional views often negatively generalize attentional biases, neglecting their distinct cognitive vulnerabilities and biological adaptive functions. This study aims to explore temporal bias, focusing on its unique characteristics and significance. We used the rapid serial visual presentation (RSVP) task to measure temporal attentional engagement and disengagement precisely in two EEG experiments. Experiment 1 examined attentional engagement by presenting neutral T1 followed by negative or neutral T2 stimuli. Experiment 2 assessed disengagement using negative or neutral T1 followed by neutral T2 stimuli. Behaviorally, typical attentional blink effects were observed in both experiments. Electrophysiologically, Experiment 1 (Engagement) revealed significantly larger P3b and late positive potential (LPP) amplitudes for negative compared with neutral T2 stimuli, specifically in the HTA group, suggesting enhanced engagement. The LTA group showed larger early posterior negativity (EPN) to negative T2 at lag 2 than the HTA group. Experiment 2 (disengagement) showed distinct T2-elicited LPP patterns: HTA participants exhibited significantly smaller LPP amplitudes following negative versus neutral T1 stimuli, whereas LTA participants showed no such difference, indicating greater difficulty disengaging from negative information in HTA. For T1 processing, LTA showed larger EPN to negative versus neutral T1, while HTA did not. Increased engagement with negative stimuli may be a common human trait, as evidenced by increased sensitivity in both high- and low-anxiety individuals. However, difficulties in disengaging attention from negative stimuli are particularly evident in individuals with HTA. These findings have important implications for the prediction, assessment, and prevention of anxiety disorders.

No heightened temporal attentional bias towards food or overweight bodies in adolescents with obesity.

Attentional bias in people with moderate-to-severe cannabis use disorder

Testing the utility of Mouseview.js for measuring associations between alcohol related attentional bias and problematic alcohol use

Camouflaged Object Segmentation (COS) faces significant challenges due to the scarcity of annotated data, where meticulous pixel-level annotation is both labor-intensive and costly, primarily due to the intricate object-background boundaries. Addressing the core question, "Can COS be effectively achieved in a zero-shot manner without manual annotations for any camouflaged object?", we propose an affirmative solution. We examine the learned attention patterns for camouflaged objects and introduce a robust zero-shot COS framework. Our findings reveal that while transformer models for salient object segmentation (SOS) prioritize global features in their attention mechanisms, camouflaged object segmentation exhibits both global and local attention biases. Based on these findings, we design a framework that adapts with the inherent local pattern bias of COS while incorporating global attention patterns and a broad semantic feature space derived from SOS. This enables efficient zero-shot transfer for COS. Specifically, We incorporate a Masked Image Modeling (MIM) based image encoder optimized for Parameter-Efficient Fine-Tuning (PEFT), a Multimodal Large Language Model (M-LLM), and a Multi-scale Fine-grained Alignment (MFA) mechanism. The MIM encoder captures essential local features, while the PEFT module learns global and semantic representations from SOS datasets. To further enhance semantic granularity, we leverage the M-LLM to generate caption embeddings conditioned on visual cues, which are meticulously aligned with multi-scale visual features via MFA. This alignment enables precise interpretation of complex semantic contexts. Moreover, we introduce a learnable codebook to represent the M-LLM during inference, significantly reducing computational demands while maintaining performance. Our framework demonstrates its versatility and efficacy through rigorous experimentation, achieving state-of-the-art performance in zero-shot COS with $F_{\beta }^{w}$Fβw scores of 72.9% on CAMO and 71.7% on COD10K. By removing the M-LLM during inference, we achieve an inference speed comparable to that of traditional end-to-end models, reaching 18.1 FPS. Additionally, our method excels in polyp segmentation, and underwater scene segmentation, outperforming challenging baselines in both zero-shot and supervised settings, thereby implying its potentiality in various segmentation tasks.