Low Target Prevalence Research Articles

No evidence of attentional prioritization for threatening targets in visual search

Throughout human evolutionary history, snakes have been associated with danger and threat. Research has shown that snakes are prioritized by our attentional system, despite many of us rarely encountering them in our daily lives. We conducted two high-powered, pre-registered experiments (total N = 224) manipulating target prevalence to understand this heightened prioritization of threatening targets. Target prevalence refers to the proportion of trials wherein a target is presented; reductions in prevalence consistently reduce the likelihood that targets will be found. We reasoned that snake targets in visual search should experience weaker effects of low target prevalence compared to non-threatening targets (rabbits) because they should be prioritized by searchers despite appearing rarely. In both experiments, we found evidence of classic prevalence effects but (contrasting prior work) we also found that search for threatening targets was slower and less accurate than for nonthreatening targets. This surprising result is possibly due to methodological issues common in prior studies, including comparatively smaller sample sizes, fewer trials, and a tendency to exclusively examine conditions of relatively high prevalence. Our findings call into question accounts of threat prioritization and suggest that prior attention findings may be constrained to a narrow range of circumstances.

Reduced low-prevalence visual search detriment with increasing age: Implications for cognitive theories of aging and real-world search tasks

When performing multiple successive visual searches, low-prevalence targets are at elevated risk of being missed. This has important implications for real-world visual search tasks, such as diagnostic medical imaging (e.g., searching for a cancer) and airport baggage security screening (e.g., searching for a weapon), which are characterized by low-prevalence targets and potentially dire consequences of target misses. Previous work on low-prevalence visual search indicates that individuals who spontaneously respond more slowly miss fewer targets, which has been attributed to higher quitting thresholds predicting better performance. Previous aging research indicates that older adults typically respond more slowly across multiple task contexts. This has been attributed to both intrinsic limitations in processing speed and a strategic trade-off to prioritize accuracy with increasing age. Synthesizing these two separate lines of research, here we tested whether older adults had a higher quitting threshold and/or slower processing speed in low-prevalence visual search, and the consequences of these for the magnitude of the low-prevalence visual search detriment. We recruited a large sample (N = 380) across a range of ages (20–80 years) and had them search for targets under low- and high-prevalence conditions. Older adults had both slower processing speed and higher quitting thresholds. Older adults were moderately less susceptible to the low-prevalence detriment, and this relationship was mediated by countervailing effects: slower processing speed exacerbated older adults’ low-prevalence detriment, whereas elevated quitting threshold mitigated it. Theoretical implications for cognitive aging and practical implications for professional visual search tasks are discussed.

Eyes of the machine: AI-assisted satellite archaeological survey in the Andes

Archaeological surveys conducted through the inspection of high-resolution satellite imagery promise to transform how archaeologists conduct large-scale regional and supra-regional research. However, conducting manual surveys of satellite imagery is labour- and time-intensive, and low target prevalence substantially increases the likelihood of miss-errors (false negatives). In this article, the authors compare the results of an imagery survey conducted using artificial intelligence computer vision techniques (Convolutional Neural Networks) to a survey conducted manually by a team of experts through the Geo-PACHA platform (for further details of the project, see Wernke et al. 2023). Results suggest that future surveys may benefit from a hybrid approach—combining manual and automated methods—to conduct an AI-assisted survey and improve data completeness and robustness.

The Influence of Clutter on Target Prevalence and Decision Making

The current study aimed to identify how set size and clutter influence the target prevalence effect and participants’ decision-making during visual search. Low target prevalence leads to shorter search times and an increased miss rate, with the opposite being true for high target prevalence. Both increased set size and clutter should require more attention shifts between items (attention for recognition) leading to longer search times. However, if spacing between items is held constant as set size increases, only increased clutter should affect attention needed to inhibit the information crowding items (attention against competition) leading to longer target decisions in response to increased clutter. Participants in Experiment 1 viewed a display of either a small (10 items) or large (40 items) set size composed of rotated and offset Ls. On each trial, participants had to determine whether a rotated target T was present or absent. In Experiment 2, participants searched for a single bump elevation marker within either a low or high cluttered map. In both experiments, a target appeared on 10% of trials for low target prevalence and 90% for high target prevalence. In Experiment 1, attention for recognition altered the target prevalence effect by making participants search longer in response to more attention shifts (large set size). In Experiment 2, clutter altered the target prevalence effect, making participants search longer in response to high clutter (attention for recognition) and getting rid of the target prevalence effect for the false alarm rate and in response to low clutter for the miss rate (attention against competition). Our results suggest that attention for recognition and attention against competition impact the target prevalence effect by altering participants’ decision making, and this pattern of results can be explained using the Multiple-Decision Model (MDM) of visual search.

How one block of trials influences the next: persistent effects of disease prevalence and feedback on decisions about images of skin lesions in a large online study

Using an online, medical image labeling app, 803 individuals rated images of skin lesions as either "melanoma" (skin cancer) or "nevus" (a skin mole). Each block consisted of 80 images. Blocks could have high (50%) or low (20%) target prevalence and could provide full, accurate feedback or no feedback. As in prior work, with feedback, decision criteria were more conservative at low prevalence than at high prevalence and resulted in more miss errors. Without feedback, this low prevalence effect was reversed (albeit, not significantly). Participants could participate in up to four different conditions a day on each of 6 days. Our main interest was in the effect of Block N on Block N + 1. Low prevalence with feedback made participants more conservative on a subsequent block. High prevalence with feedback made participants more liberal on a subsequent block. Conditions with no feedback had no significant impact on the subsequent block. The delay between Blocks 1 and 2 had no significant effect. The effect on the second half of Block 2 was just as large as on the first half. Medical expertise (over the range available in the study) had no impact on these effects, though medical students were better at the task than other groups. Overall, these seem to be robust effects where feedback may be 'teaching' participants how to respond in the future. This might have application in, for example, training or re-training situations.

Target Detection Vulnerability to Low Target Prevalence Across Display Type and Speed

Target Detection Vulnerability to Low Target Prevalence Across Display Type and Speed

Visual Perception: How Better Imaging Can Make Things Worse

Summary Visual search is critical to daily life and to socially important tasks — from cancer screening to airport security. New research shows how a technological advancement can interact with the human visual system to improve search for one type of target while making matters worse for another. Part of the problem is that we are surprisingly bad at knowing where we have looked.

Meeting Proceedings of the “Phase I: Where Science Becomes Medicine” Conference, Manchester, UK

Meeting Proceedings of the “Phase I: Where Science Becomes Medicine” Conference, Manchester, UK

Spotting rare items makes the brain "blink" harder: Evidence from pupillometry.

In many visual search tasks (e.g., cancer screening, airport baggage inspections), the most serious search targets occur infrequently. As an ironic side effect, when observers finally encounter important objects (e.g., a weapon in baggage), they often fail to notice them, a phenomenon known as the low-prevalence effect (LPE). Although many studies have investigated LPE search errors, we investigated the attentional consequences of successful rare target detection. Using an attentional blink paradigm, we manipulated how often observers encountered the first serial target (T1), then measured its effects on their ability to detect a following target (T2). Across two experiments, we show that the LPE is more than just an inflated miss rate: When observers successfully detected rare targets, they were less likely to spot subsequent targets. Using pupillometry to index locus-coeruleus (LC) mediated attentional engagement, Experiment 2 confirmed that an LC refractory period mediates the attentional blink (`Nieuwenhuis, Gilzenrat, Holmes, & Cohen, 2005, Journal of Experimental Psychology: General, 134[3], 291-307), and that these effects emerge relatively quickly following T1 onset. Moreover, in both behavioral and pupil analyses, we found that detecting low-prevalence targets exacerbates the LC refractory period. Consequences for theories of the LPE are discussed.

Learning in the Target Prevalence Effect

Rare or low prevalence targets are detected less well than counterparts that occur with higher probability. It stands to reason, though, that before such a deficit is apparent, information about a given target's probability of occurrence must be apprehended. In this study, we investigated how much target experience is necessary for target probabilities to be fully acquired and established within mental task representations. A central finding was that different target probability values required approximately the same amount of target sampling to learn. This was true whether learning about target probabilities from a naive start-point (Experiment 1) or when recalibrating from one probability value to another (Experiment 2). We discuss these findings in relation to how mental task representations are modified when new task-relevant information is received and the attentional consequences of such changes.

Can Radiologists Learn From Airport Baggage Screening?: A Survey About Using Fictional Patients for Quality Assurance

For both airport baggage screeners and radiologists, low target prevalence is associated with low detection rate, a phenomenon known as "prevalence effect." In airport baggage screening, the target prevalence is artificially increased with fictional weapons that are digitally superimposed on real baggage. This strategy improves the detection rate of real weapons and also allows airport supervisors to monitor screener performance. A similar strategy using fictional patients could be applied in radiology. The purpose of this study was twofold: (1) to review the psychophysics literature regarding low target prevalence and (2) to survey radiologists' attitudes toward using fictional patients as a quality assurance tool. We reviewed the psychophysics literature on low target prevalence and airport x-ray baggage screeners. An online survey was e-mailed to all members of the Association of University Radiologists to determine their attitudes toward using fictional patients in radiology. Of the 1503 Association of University Radiologists member recipients, there were 153 respondents (10% response rate). When asked whether the use of fictional patients was a good idea, the responses were as follows: disagree (44%), neutral (25%), and agree (31%). The most frequent concern was the time taken away from doing clinical work (89% of the respondents). The psychophysics literature supports the use of fictional targets to mitigate the prevalence effect. However, the use of fictional patients is not a popular idea among academic radiologists.

Low target prevalence exacerbates problems with Computer-Aided Detection (CAD) during visual search

Low target prevalence exacerbates problems with Computer-Aided Detection (CAD) during visual search

Target-present guessing as a function of target prevalence and accumulated information in visual search.

Target prevalence influences visual search behavior. At low target prevalence, miss rates are high and false alarms are low, while the opposite is true at high prevalence. Several models of search aim to describe search behavior, one of which has been specifically intended to model search at varying prevalence levels. The multiple decision model (Wolfe & Van Wert, Current Biology, 20(2), 121--124, 2010) posits that all searches that end before the observer detects a target result in a target-absent response. However, researchers have found very high false alarms in high-prevalence searches, suggesting that prevalence rates may be used as a source of information to make "educated guesses" after search termination. Here, we further examine the ability for prevalence level and knowledge gained during visual search to influence guessing rates. We manipulate target prevalence and the amount of information that an observer accumulates about a search display prior to making a response to test if these sources of evidence are used to inform target present guess rates. We find that observers use both information about target prevalence rates and information about the proportion of the array inspected prior to making a response allowing them to make an informed and statistically driven guess about the target's presence.

Individual differences predict low prevalence visual search performance

Critical real-world visual search tasks such as radiology and baggage screening rely on the detection of rare targets. When targets are rare, observers search for a relatively short amount of time and have a high miss rate, a pattern of results known as the low prevalence effect. Attempts to improve the search for rare targets have been unsuccessful or resulted in an increase in detections at the price of more false alarms. As an alternative to improving visual search performance through experimental manipulations, an individual differences approach found that those with higher working memory capacity were better at finding rare targets. We build on the individual differences approach and assess 141 observers’ visual working memory capacity (vWMC), vigilance, attentional control, big five personality traits, and performance in both high and low prevalence search tasks. vWMC, vigilance, attentional control, high prevalence visual search performance, and level of introversion were all significant predictors of low prevalence search accuracy, and together account for more than 50% of the variance in search performance. With the exception of vigilance, these factors are also significant predictors of reaction time; better performance was associated with longer reaction times, suggesting these factors identify observers who maintain relatively high quitting thresholds, even with low target prevalence. Our results suggest that a quick and easy-to-administer battery of tasks can identify observers who are likely to perform well in low prevalence search tasks, and these predictor variables are associated with higher quitting thresholds, leading to higher accuracy.

Analog Computer-Aided Detection (CAD) information can be more effective than binary marks.

In socially important visual search tasks, such as baggage screening and diagnostic radiology, experts miss more targets than is desirable. Computer-aided detection (CAD) programs have been developed specifically to improve performance in these professional search tasks. For example, in breast cancer screening, many CAD systems are capable of detecting approximately 90% of breast cancer, with approximately 0.5 false-positive detections per image. Nevertheless, benefits of CAD in clinical settings tend to be small (Birdwell, 2009) or even absent (Meziane et al., 2011; Philpotts, 2009). The marks made by a CAD system can be "binary," giving the same signal to any location where the signal is above some threshold. Alternatively, a CAD system presents an analog signal that reflects strength of the signal at a location. In the experiments reported, we compare analog and binary CAD presentations using nonexpert observers and artificial stimuli defined by two noisy signals: a visible color signal and an "invisible" signal that informed our simulated CAD system. We found that analog CAD generally yielded better overall performance than binary CAD. The analog benefit is similar at high and low target prevalence. Our data suggest that the form of the CAD signal can directly influence performance. Analog CAD may allow the computer to be more helpful to the searcher.

Decision processes in visual search as a function of target prevalence.

The probability of missing a target increases in low target prevalence search tasks. Wolfe and Van Wert (2010) propose 2 causes of this effect: reducing the quitting threshold, and conservatively shifting the decision making criterion used to evaluate each item. Reducing the quitting threshold predicts that target absent responses will be made without fully inspecting the display, increasing misses due to never inspecting the target (selection errors). The shift in decision criterion increases the likelihood of failing to recognize an inspected target (identification errors). Though there is robust evidence that target prevalence rates shift quitting thresholds, the proposed shift in decision making criterion has little support. In Experiment 1 we eye-tracked participants during searches of high, medium, and low prevalence. Eye movements were used to classify misses as selection or identification errors. Identification errors increased as prevalence decreased, supporting the claim that decision criterion becomes more conservative as prevalence decreases. In addition, as prevalence decreased, the dwell time on targets increased while dwell times on distractors decreased. We propose that the effect of prevalence on decision making for individual items is best modeled as a shift in criterion in a drift diffusion model, rather than signal detection, as drift diffusion accounts for this pattern of decision times. In Experiment 2 we replicate these findings while presenting stimuli in an rapid serial visual presentation (RSVP) stream. Experiments 1 and 2 were consistent with the conclusion that prevalence rate influences the item-by-item decision criterion, and are consistent with a drift diffusion model of this decision process. (PsycINFO Database Record

Failures of perception in the low-prevalence effect: Evidence from active and passive visual search.

In visual search, rare targets are missed disproportionately often. This low-prevalence effect (LPE) is a robust problem with demonstrable societal consequences. What is the source of the LPE? Is it a perceptual bias against rare targets or a later process, such as premature search termination or motor response errors? In 4 experiments, we examined the LPE using standard visual search (with eye tracking) and 2 variants of rapid serial visual presentation (RSVP) in which observers made present/absent decisions after sequences ended. In all experiments, observers looked for 2 target categories (teddy bear and butterfly) simultaneously. To minimize simple motor errors, caused by repetitive absent responses, we held overall target prevalence at 50%, with 1 low-prevalence and 1 high-prevalence target type. Across conditions, observers either searched for targets among other real-world objects or searched for specific bears or butterflies among within-category distractors. We report 4 main results: (a) In standard search, high-prevalence targets were found more quickly and accurately than low-prevalence targets. (b) The LPE persisted in RSVP search, even though observers never terminated search on their own. (c) Eye-tracking analyses showed that high-prevalence targets elicited better attentional guidance and faster perceptual decisions. And (d) even when observers looked directly at low-prevalence targets, they often (12%-34% of trials) failed to detect them. These results strongly argue that low-prevalence misses represent failures of perception when early search termination or motor errors are controlled.

Effects of Target Prevalence and Speech Intelligibility on Visual Search Performance

Visual search is commonly performed in the control rooms of several industries such as nuclear power plants, flight control, security screening, and monitoring. In this study, the effects of target prevalence and speech intelligibility on visual search performance were investigated. A 2 (target prevalence: low versus high) × 3 (speech transmission index = 0 versus 0.51 versus 0.69) mixed design experiment was conducted. Target prevalence was a between-subject variable, whereas the speech transmission index was a within-subject variable. A total of 32 participants participated in simulated X-ray screening tasks in different speech intelligibility conditions. Results revealed that both the target prevalence and the speech transmission index level had significant effects on visual search performance. The reaction time was shorter and the miss error rate was higher under low target prevalence condition than in high target prevalence condition. Compared with no speech condition (speech transmission index = 0), the reaction time of the participants increased significantly with the presence of intelligible speech in an acoustic environment. Performance loss was greatest when the speech transmission index was 0.51. The interaction effect of target prevalence and speech transmission index level was also significant. Proper measures should be taken to reduce unfavorable effects of low target prevalence and intelligible speech in acoustic environment on visual search performance in control rooms.

Improving the Efficacy of Security Screening Tasks: A Review of Visual Search Challenges and Ways to Mitigate Their Adverse Effects

SummarySecurity checkpoints are used to keep potentially dangerous items and individuals out of secure areas. Although technological advances can enhance security efficacy through both accuracy and speed, ultimate success or failure is largely determined by human performance. As such, it is necessary to minimize any shortcomings that stem from the limits of human cognitive abilities. Cognitive performance can be influenced by numerous factors, including those imposed by the search task (e.g., the number of prohibited items) and the basic abilities of the searchers themselves (e.g., competency and experience). Here, we review and discuss four specific challenges of the task itself that can negatively affect the accuracy of a security screening: target visibility, an unknown target set, the possible presence of multiple targets, and low target prevalence. For each, we present the challenge faced and the potential significance of the challenge and then offer possible solutions on the basis of the existing literature. Copyright © 2014 John Wiley & Sons, Ltd.

Perceptual failures in the selection and identification of low-prevalence targets in relative prevalence visual search.

Previous research has shown that during visual search tasks target prevalence (the proportion of trials in which a target appears) influences both the probability that a target will be detected, and the speed at which participants will quit searching and provide an 'absent' response. When prevalence is low (e.g., target presented on 2 % of trials), participants are less likely to detect the target than when prevalence is higher (e.g., 50 % of trials). In the present set of experiments, we examined perceptual failures to detect low prevalence targets in visual search. We used a relative prevalence search task in order to be able to present an overall 50 % target prevalence and thereby prevent the results being accounted for by early quitting behavior. Participants searched for two targets, one of which appeared on 45 % of trials and another that appeared on 5 % of trials, leaving overall target prevalence at 50 %. In the first experiment, participants searched for two dissimilar targets; in the second experiment, participants searched for two similar targets. Overall, the results supported the notion that a reduction in prevalence primarily influenced perceptual failures of identification, rather than of selection. Together, these experiments add to a growing body of research exploring how and why observers fail to detect low prevalence targets, especially in real-world tasks in which some targets are more likely to appear than others.