Threat-related attentional bias in subjects with different looming cognitive styles: Evidence based on eye-tracking study

Deployment stressors—most notably exposure to combat (1)—have profound effects on mental health (2). It is estimated that approximately 20% of military veterans develop posttraumatic stress disorder (PTSD) (3), while approximately 7%210% develop alcohol use disorders and 17% experience major depressive disorder (4). These mental health issues have profound effects on social functioning and the ability to work, and they increase utilization of health care services (5). Standardized behavioral treatments are helpful but have limited effect size (6), and exposurebased interventions seem best suited for combat-related PTSD (7). Yet a significant gap between treatment need and availability remains. Computerized treatment techniques might be able to address this gap. These methods are firmly rooted in cognitive science and provide a useful approach to specifically treat basic cognitive processing dysfunctions in PTSD. In this issue, Badura-Brack and colleagues (8) address a critical question, i.e., For individuals with PTSD, is it better to train paying attention to safe instead of threat stimuli or to increase control of attention to both safe and threat stimuli? and provide a provocative answer. The “classical” answer has been that it is better to train individuals with anxiety disorders to pay more attention to “safe” stimuli (9).YetPTSD isdifferent,withdifferent studies finding both increased and decreased bias toward threat, respectively.Moreover, PTSD individuals seem to fluctuate between a focus on threat and a focus away from threat (avoidance), which has been termed attention bias variability. Badura-Brack and colleagues conducted a randomized controlled trial using an attentional task to examine the efficacy of attention bias modification versus attention control training. In fact, Badura-Brack and colleagues (8) report on two randomized controlled trials with different number of sessions and different stimulus materials, which ultimately provided the same answer. Study 1 focused on 144 treatment-seeking individuals with combat-related PTSD from the Israel Defense Forces, of whom 52 were included in the study. Study 2 involved 76 veterans from Iraq and Afghanistan who had been screened for PTSD, of whom 46 participated in the study. For both studies, participants completed particular versions of the dot-probe task, one of which targeted attention bias to threat, while the other served as an attention control. To understand the findings, it is important to consider what the specific task demands are and how individuals are being trained on the dot-probe task. First, during the dotprobe task an individual is asked to focus on the center of a computer screen. Second, twowords (angry or neutral faces in study 2) are presented simultaneously above or below the center of the screen. Third, the person pushes a button as quickly as possible when he or she sees a target stimulus (letter E or F in study 1, “,” or “.” in study 2), which is presented in the same location as either the threat-relatedor neutral word (or face). If the person has no bias, then the reaction time should be the samewhether the target appears at the location of either word (or face). However, if the person’s brain is more engaged in processing the threatrelated word (or angry face) relative to the “safe” word (or neutral face), then the individual should be faster to respond to the target that appears in the same location as the threat word. Two measures provide an index of bias and variability. Threat-related attention bias is thedifference in reaction time followinga target at the threat versus the safe location. Attention bias variability is the variability of this measure across trials. The same dot-probe procedure described above is also used for training. However, for attention bias modification and unbeknownst to the individual, the target only appears at the location of the neutral word (neutral face). Thus, attentionbiasmodification implicitly trains individuals to focus their attentionmore toward theneutral (rather than the threat) stimulus. In comparison, during attention control training, individuals see the target at either the location of the threat word or the location of the safe word in a counterbalanced manner. The authors found that all groups got better (had fewer PTSD symptoms), but the individuals undergoing attentional control training were significantly better than those undergoing attention bias modification. This effect was specific to PTSD-related symptoms and did not extend to depression symptoms, although there was a small effect on a depression measure in study 2. Moreover, in both studies, the attention Computerized treatment techniques... are firmly rooted in cognitive science and provide a useful approach to specifically treat basic cognitive processing dysfunctions in PTSD.

Online shopping has become a primary form of consumption in daily life, inevitably accompanied by the emergence of problematic online shopping. Attentional bias towards online shopping cues influences individuals' online shopping behavior. This study examined attentional bias mechanisms in problematic online shoppers using two experiments. This study combines the dot-probe task and eye-tracking technology to explore attentional bias and temporal dynamics toward shopping-related cues among problematic online shoppers. Experiment 1 recruited 84 participants to investigate attentional bias toward proximal cues, while Experiment 2 recruited 76 participants to examine attentional bias toward distal cues. The results of Experiment 1 showed that both problematic online shoppers and control individuals exhibited shorter first fixation latency, longer gaze duration, and total fixation duration toward proximal cues. And only problematic online shoppers exhibited slower first exit saccade velocity and average exit saccade velocity. The results of Experiment 2 indicated that problematic online shoppers exhibited longer gaze duration and total fixation duration, as well as faster first entry saccade velocity toward distal cues. In summary, problematic online shoppers exhibit similar attentional bias toward both shopping proximal and distal cues, which are presented as the vigilance-maintenance pattern. For problematic online shoppers, distal cues have gradually acquired incentive value comparable to that of proximal cues. However, it should be noted that control individuals also exhibited attentional bias toward proximal cues.

Attentional processing biases to threat in schizophrenia: Evidence from a free-viewing task with emotional scenes

Background: Dominant models of posttraumatic stress disorder (PTSD) implicate threat-related attention biases in both the development and maintenance of posttraumatic stress symptoms. However, the ability to better understand and modify threat-related attention biases in PTSD has been hampered by the low reliability of attention bias measures more generally. Methods: The current study adopts a new approach to calculate attention bias from a dot-probe task, response-based attention bias (RB-AB) computation, in a sample of 689 individuals reporting significantly elevated PTSD symptoms who participated in a clinical trial of threat-related attention bias modification training. Results: RB-AB is a reliable strategy for deriving threat-related attention bias scores that correlate with both PTSD severity and anxiety. On the other hand, scores from the traditional approach were unreliable and not associated with clinical symptoms. Attention training led to reductions in RB-AB indices of attention bias, but not the traditional index, although attention bias training conditions did not appear to moderate these effects. Conclusions: Taken together, these findings support evidence that threat-related attention biases may be a feature of PTSD and that RB-AB computation is a more reliable and valid approach for studying reaction-time-based attentional processes. Using the RB-AB approach to assess attention bias could allow us to better understand threat-related attention biases in PTSD and to ultimately develop more precise interventions to reduce threat-related attentional biases in PTSD and other disorders.

Increasing cognitive load attenuates the moderating effect of attentional inhibition on the relationship between posttraumatic stress symptoms and threat-related attention bias variability

Eyes tell all: Dissecting attentional bias in social anxiety through emotional faces.

Previous literatures demonstrate that clinically anxious patients are very sensitive to threatening stimuli.Further,it is easier for them to be engaged in threatening stimuli,after which they find it hard to shift their attention to other kinds of stimuli in the situation.However,not many studies have been conducted to demonstrate the attentional bias of high trait anxious(HTA)individuals,which was the subject of the present study.Are these individuals more sensitive to threat? Is it easy for them to be engaged in threat,and is it hard to distract their attention? What is the underlying mechanism in such cases of attentional bias? Two experiments were designed according to the paradigm "odd-one-out search task" to test whether HTA individuals are more vigilant to threats or whether it is hard to distract their attention from the threat.In experiment 1,20 HTA individuals and 20 low trait anxious(LTA)individuals selected from among 400 college students by using the Chinese version of the State-Trait Anxiety Inventory(STAI-T)1983,developed by Spielberger et al.They participated in the test under peaceful conditions(no anxiety-eliciting task).The participants were asked to ascertain whether there was any different face in the square containing 12 faces as soon as possible.In order to test attentional sensitivity to threatening(or unthreatening)stimuli,the participants were required to discriminate an angry face(or a happy face)from among 12 faces in a square(1 emotional face with 11 neutral faces).In order to test attentional distraction from threatening(or unthreatening)stimuli,the participants were required to discriminate a neutral face from among 12 faces in a square(1 neutral face with 11 angry or happy faces).The experiment measured the time of judgment and emotional change in the meanwhile.In experiment 2,19 HTA and 19 LTA participants selected from among 300 college students by using the STAI-T were tested through the "odd-one-out search task" after an anxiety-eliciting task.The results revealed the following.(1)Under peaceful conditions,both the HTA and LTA groups were found to be more susceptible to a happy face than to an angry face.It was difficult to distract both groups from angry faces.However,as compared to the LTA group,it was more difficult to disengage the attention of the HTA group from angry faces.(2)It was more difficult to disengage the HTA group's attention from the angry faces than from happy faces when they were in highly anxious mood.On the other hand,it was harder to disengage the attention of the LTA group from the happy faces than from the anger faces.There was no significant difference in the HTA group's attentional sensitivity to happy and angry faces;meanwhile,the LTA group was more sensitive to happy face than to anger face.It can be concluded that HTA individuals were not particularly attention-sensitive to threatening stimulus,but they were much more difficult to disengage their attention from threatening stimuli.Meanwhile,the LTA individuals were more attention-sensitive to pleasant stimuli and were easily engaged in pleasant stimuli.The study further suggested that a higher degree of anxiety and the fact that is easier to elicit an anxious mood in HTA subjects would play a key role in the attentional bias.

The aim of this study was to elucidate individual difference factors that modulate the attentional processing of game stimuli to explain the heterogeneity of extant findings. The current study examined whether individual differences in components of attentional control (AC-shifting and AC-focusing) moderated the link between internet gaming addiction symptom and attentional engagement to and disengagement biases from game-relevant cues. A total of 75 male undergraduate students who have played League of Legend (LOL) for more than 2 years completed well-established self-report questionnaires of internet gaming disorder symptoms and attentional control. The attentional bias toward game stimuli was measured for attentional engagement and disengagement using the attentional response to the distal vs. proximal emotional information (ARDPEI) task. The results revealed that attentional control was a significant moderator of the relationship between internet game addiction symptoms and attentional disengagement bias. Further analyses revealed a positive relationship between internet game addiction symptoms and attentional disengagement bias only among those with low levels of AC-shifting ability. Contrary to our expectations, AC-shifting also moderated the relationship between internet gaming disorder and attentional engagement bias. The positive relationship between internet game addiction symptoms and attentional engagement bias only appeared among those with low levels of AC-shifting ability. Individual differences in AC-focusing did not moderate the relationship between internet gaming disorder and any attentional bias. This study confirmed that the greater the symptoms of game addiction, the stronger the attentional bias, especially in individuals with low AC-shifting ability. Therefore, it is necessary to examine sub-factors of AC in understanding the nature of attentional bias mechanisms in the development of internet game addiction and consider it as a psychological intervention to improve attentional bias.

Threat-related attentional bias in individuals with different looming cognitive styles: An ERP study.

Threat-related attentional biases represent a basic survival mechanism. These biases include an engagement bias involving rapid direction of attention toward threat and a disengagement bias involving slow direction of attention away from threat. The exact nature of these biases in healthy and anxious individuals remains controversial because of the challenges associated with accurately isolating each of these attentional biases. Combining a cognitive attentional task with classical conditioning using electric stimulation, we created a new paradigm that makes it possible to more clearly isolate these attentional biases. Utilizing this novel paradigm, we detected both types of attentional bias and differentiated between levels of trait anxiety, in which low- and high-trait anxiety individuals showed equal levels of engagement bias, but only high-trait anxiety individuals showed impaired disengagement from threat.

Threat-Related Attention Bias in the Early Stages of Cognitive-Behavior Therapy Action for Panic Disorder

Background and objectivesIt is well established that attention bias and interpretation bias each have a key role in the development and continuation of anxiety. How the biases may interact with one another in anxiety is, however, poorly understood. Using cognitive bias modification techniques, the present study examined whether training a more positive interpretation bias or attention bias resulted in transfer of effects to the untrained cognitive domain. Differences in anxiety reactivity to a real-world stressor were also assessed. MethodsNinety-seven first year undergraduates who had self-reported anxiety were allocated to one of four groups: attention bias training (n = 24), interpretation bias training (n = 26), control task training (n = 25) and no training (n = 22). Training was computer-based and comprised eight sessions over four weeks. Baseline and follow-up measures of attention and interpretation bias, anxiety and depression were taken. ResultsA significant reduction in threat-related attention bias and an increase in positive interpretation bias occurred in the attention bias training group. The interpretation bias training group did not exhibit a significant change in attention bias, only interpretation bias. The effect of attention bias training on interpretation bias was significant as compared with the two control groups. There were no effects on self-report measures. LimitationsThe extent to which interpretive training can modify attentional processing remains unclear. ConclusionsFindings support the idea that attentional training might have broad cognitive consequences, impacting downstream on interpretive bias. However, they do not fully support a common mechanism hypothesis, as interpretive training did not impact on attentional bias.

Cognitive Bias Modification: An Intervention Approach Worth Attending To

Understanding the factors influencing food choice is critical for developing effective strategies to promote healthier eating habits and creating policies that support public health. Attentional bias, the inclination to focus attention on specific stimuli, plays a significant role in shaping food preferences by affecting how individuals perceive and react to various food-related elements. Various methodologies exist to examine attentional bias, including the dot-probe task, which measures reaction times to probes appearing after paired stimuli (eg, novel vs familiar food images); eye-tracking, which tracks gaze patterns and fixations to determine visual attention; and electroencephalography, which records brain activity, capturing early and late neural responses (eg, N100, P300) linked to attention processing; however, integrated approaches combining these methods to assess bias toward familiar versus novel foods remain underexplored. This study aims to examine differences in attention toward familiar versus novel food stimuli using integrated eye-tracking, dot-probe, and electroencephalography methods, and to explore associations with self-reported food choice. A total of 40 healthy adult participants will be recruited. Participants will be presented with pairs of familiar or novel food images, while their visual attention and brain activity are recorded concurrently. Eye-tracking metrics, including time to first fixation and total fixation duration, will be used to assess visual attention. Electroencephalography data will be collected to measure the amplitude of event-related potential components, such as P300 and N100, associated with attentional processing. Reaction times will also be recorded as a behavioral measure of attentional engagement with familiar versus novel food items. Data analysis will involve repeated measures ANOVA to examine the effects of food familiarity and novelty on attentional bias metrics. Correlation analyses will also be conducted to explore the relationships between eye-tracking, electroencephalography, and dot-probe measures. This study was approved by the Ethics Committee of the Iran University of Medical Sciences in February 2021 and funded in January 2022. Data collection began in November 2022 and is expected to be completed in July 2025. As of the submission of this study, 36 individuals have been recruited. Data analysis has not yet commenced, but it is planned to begin upon the completion of data collection. The results are anticipated to be published by December 2025. The protocol was registered with the Open Science Framework in September 2024. The main outcome of this study is identifying differences in attentional bias metrics toward familiar versus novel food stimuli at different presentation times. These findings will provide preliminary data on the application of an integrated approach for capturing attentional bias to food-based stimuli based on their familiarity or novelty, and how these biases may be linked to food choice behaviors. DERR1-10.2196/69541.

BACKGROUND Understanding the factors influencing food choice is critical for developing effective strategies to promote healthier eating habits and creating policies that support public health. Attentional bias, the inclination to focus attention on specific stimuli, plays a significant role in shaping food preferences by affecting how individuals perceive and react to various food-related elements. Various methodologies exist to examine attentional bias, including the dot-probe task, which measures reaction times to probes appearing after paired stimuli (eg, novel vs familiar food images); eye-tracking, which tracks gaze patterns and fixations to determine visual attention; and electroencephalography, which records brain activity, capturing early and late neural responses (eg, N100, P300) linked to attention processing; however, integrated approaches combining these methods to assess bias toward familiar versus novel foods remain underexplored. OBJECTIVE This study aims to examine differences in attention toward familiar versus novel food stimuli using integrated eye-tracking, dot-probe, and electroencephalography methods, and to explore associations with self-reported food choice. METHODS A total of 40 healthy adult participants will be recruited. Participants will be presented with pairs of familiar or novel food images, while their visual attention and brain activity are recorded concurrently. Eye-tracking metrics, including time to first fixation and total fixation duration, will be used to assess visual attention. Electroencephalography data will be collected to measure the amplitude of event-related potential components, such as P300 and N100, associated with attentional processing. Reaction times will also be recorded as a behavioral measure of attentional engagement with familiar versus novel food items. Data analysis will involve repeated measures ANOVA to examine the effects of food familiarity and novelty on attentional bias metrics. Correlation analyses will also be conducted to explore the relationships between eye-tracking, electroencephalography, and dot-probe measures. RESULTS This study was approved by the Ethics Committee of the Iran University of Medical Sciences in February 2021 and funded in January 2022. Data collection began in November 2022 and is expected to be completed in July 2025. As of the submission of this study, 36 individuals have been recruited. Data analysis has not yet commenced, but it is planned to begin upon the completion of data collection. The results are anticipated to be published by December 2025. The protocol was registered with the Open Science Framework in September 2024. CONCLUSIONS The main outcome of this study is identifying differences in attentional bias metrics toward familiar versus novel food stimuli at different presentation times. These findings will provide preliminary data on the application of an integrated approach for capturing attentional bias to food-based stimuli based on their familiarity or novelty, and how these biases may be linked to food choice behaviors. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/69541