Low target prevalence is a stubborn source of errors in visual search tasks

Greater benefits of deep learning-based computer-aided detection systems for finding small signals in 3D volumetric medical images

Purpose

Radiologists are tasked with visually scrutinizing large amounts of data produced by 3D volumetric imaging modalities. Small signals can go unnoticed during the 3D search because they are hard to detect in the visual periphery. Recent advances in machine learning and computer vision have led to effective computer-aided detection (CADe) support systems with the potential to mitigate perceptual errors.

Approach

Sixteen nonexpert observers searched through digital breast tomosynthesis (DBT) phantoms and single cross-sectional slices of the DBT phantoms. The 3D/2D searches occurred with and without a convolutional neural network (CNN)-based CADe support system. The model provided observers with bounding boxes superimposed on the image stimuli while they looked for a small microcalcification signal and a large mass signal. Eye gaze positions were recorded and correlated with changes in the area under the ROC curve (AUC).

Results

The CNN-CADe improved the 3D search for the small microcalcification signal ( Δ   AUC = 0.098 , p = 0.0002 ) and the 2D search for the large mass signal ( Δ   AUC = 0.076 , p = 0.002 ). The CNN-CADe benefit in 3D for the small signal was markedly greater than in 2D ( Δ Δ   AUC = 0.066 , p = 0.035 ). Analysis of individual differences suggests that those who explored the least with eye movements benefited the most from the CNN-CADe ( r = - 0.528 , p = 0.036 ). However, for the large signal, the 2D benefit was not significantly greater than the 3D benefit ( Δ Δ   AUC = 0.033 , p = 0.133 ).

Conclusion

The CNN-CADe brings unique performance benefits to the 3D (versus 2D) search of small signals by reducing errors caused by the underexploration of the volumetric data.

Individual differences in visual search: A systematic review of the link between visual search performance and traits or abilities

Visual search (VS) comprises a class of tasks that we typically perform several times during a day and requires intentionally scanning (with or without moving the eyes) the environment for a specific target (be it an object or a feature) among distractor stimuli. Experimental research in lab-based or real-world settings has offered insight into its underlying neurocognitive mechanisms from a nomothetic point of view. A lesser-known but rapidly growing body of quasi-experimental and correlational research has explored the link between individual differences and VS performance. This combines different research traditions and covers a wide range of individual differences in studies deploying a vast array of VS tasks. As such, it is a challenge to determine whether any associations highlighted in single studies are robust when considering the wider literature. However, clarifying such relationships systematically and comprehensively would help build more accurate models of VS, and it would highlight promising directions for future research. This systematic review provides an up to date and comprehensive synthesis of the existing literature investigating associations between common indices of performance in VS tasks and measures of individual differences mapped onto four categories of cognitive abilities (short-term working memory, fluid reasoning, visual processing and processing speed) and seven categories of traits (Big Five traits, trait anxiety and autistic traits). Consistent associations for both traits (in particular, conscientiousness, autistic traits and trait anxiety - the latter limited to emotional stimuli) and cognitive abilities (particularly visual processing) were identified. Overall, however, informativeness of future studies would benefit from checking and reporting the reliability of all measurement tools, applying multiplicity correction, using complementary techniques, study preregistration and testing why, rather than only if, a robust relation between certain individual differences and VS performance exists.

Inattentional blindness in medicine

People often fail to notice unexpected stimuli when their attention is directed elsewhere. Most studies of this "inattentional blindness" have been conducted using laboratory tasks with little connection to real-world performance. Medical case reports document examples of missed findings in radiographs and CT images, unintentionally retained guidewires following surgery, and additional conditions being overlooked after making initial diagnoses. These cases suggest that inattentional blindness might contribute to medical errors, but relatively few studies have directly examined inattentional blindness in realistic medical contexts. We review the existing literature, much of which focuses on the use of augmented reality aids or inspection of medical images. Although these studies suggest a role for inattentional blindness in errors, most of the studies do not provide clear evidence that these errors result from inattentional blindness as opposed to other mechanisms. We discuss the design, analysis, and reporting practices that can make the contributions of inattentional blindness unclear, and we describe guidelines for future research in medicine and similar contexts that could provide clearer evidence for the role of inattentional blindness.

Errors in visual search: Are they stochastic or deterministic?

In any visual search task in the lab or in the world, observers will make errors. Those errors can be categorized as "deterministic": If you miss this target in this display once, you will definitely miss it again. Alternatively, errors can be "stochastic", occurring randomly with some probability from trial to trial. Researchers and practitioners have sought to reduce errors in visual search, but different types of errors might require different techniques for mitigation. To empirically categorize errors in a simple search task, our observers searched for the letter "T" among "L" distractors, with each display presented twice. When the letters were clearly visible (white letters on a gray background), the errors were almost completely stochastic (Exp 1). An error made on the first appearance of a display did not predict that an error would be made on the second appearance. When the visibility of the letters was manipulated (letters of different gray levels on a noisy background), the errors became a mix of stochastic and deterministic. Unsurprisingly, lower contrast targets produced more deterministic errors. (Exp 2). Using the stimuli of Exp 2, we tested whether errors could be reduced using cues that guided attention around the display but knew nothing about the content of that display (Exp3a, b). This had no effect, but cueing all item locations did succeed in reducing deterministic errors (Exp3c).

Fatigue and vigilance in medical experts detecting breast cancer

An abundance of laboratory-based experiments has described a vigilance decrement of reducing accuracy to detect targets with time on task, but there are few real-world studies, none of which have previously controlled the environment to control for bias. We describe accuracy in clinical practice for 360 experts who examined >1 million women's mammograms for signs of cancer, whilst controlling for potential biases. The vigilance decrement pattern was not observed. Instead, test accuracy improved over time, through a reduction in false alarms and an increase in speed, with no significant change in sensitivity. The multiple-decision model explains why experts miss targets in low prevalence settings through a change in decision threshold and search quit threshold and propose it should be adapted to explain these observed patterns of accuracy with time on task. What is typically thought of as standard and robust research findings in controlled laboratory settings may not directly apply to real-world environments and instead large, controlled studies in relevant environments are needed.

Reward delays quitting in visual search

Reward motivates goal-directed behaviors, leading to faster reaction time (RT) and lower error rate in searching for a target in the reward condition than in the no-reward condition in target-discrimination tasks. However, it is unclear how reward influences target detection in which participants are required to judge whether a predesignated target is present or absent. Here, we asked participants to complete a target-detection search task in which the color of the search array indicated the reward availability of the current trial. Correct and faster (than a baseline) responses would be rewarded if the search array had the reward-related color. In Experiments 1A and 1B, the target was presented in 50% of the trials. Experiment 1B had the same design as Experiment 1A, except that different baselines were set for the target-present and target-absent conditions. In Experiment 2, the proportion of target presence was manipulated to be high (80%), moderate (50%), or low (20%) in different blocks of stimuli. Results showed that, across all the experiments, participants responded faster and made fewer errors in the reward than in the no-reward condition when the target was present. However, this facilitatory effect was reversed when the target was absent, showcasing a reward-induced interference. The signal detection analysis suggested that reward biased the report criterion to the "yes" response. These findings demonstrate that the impact of reward on goal-directed behavior can be detrimental and reward prolongs the search process by rendering participants reluctant to say "no" in visual search termination.

Determinants of Face Recognition: The Role of Target Prevalence and Similarity

Studies of facial identity processing typically assess perception (via matching) and/or memory (via recognition), with experimental designs differing with respect to one important aspect: Target Prevalence. Some designs include "target absent" (TA) among "target present" (TP) trials. In visual search tasks, TA trials shift an observer's decisional criterion towards a stricter one, increasing misses. However, decisional biases will differ between individuals and across an individual's decisions as well. In this way, excluding TA trials ensures comparable levels of expectation and thus a more controlled decisional bias both within and between observers by not considering correct rejections and false alarms. However, TA trials may occur, e.g., in police line-ups, where it is important to consider observers' face recognition ability net of the potential biases introduced by TA and TP trials. And, while these have been investigated in numerous other stimulus domains, their effects have not yet been extended to face recognition. We therefore sought to fill this void by testing different versions of the previously established Models Memory Test, which measures old/new recognition of experimentally learned facial identities. Our study found significant expectation effects, driven by target prevalence that persist even given prevalence changes. This implies that face recognition - even measured with naturalistic changes - is influenced by prior perceptual decisions.

Highly dangerous road hazards are not immune from the low prevalence effect

The low prevalence effect (LPE) is a cognitive limitation commonly found in visual search tasks, in which observers miss rare targets. Drivers looking for road hazards are also subject to the LPE. However, not all road hazards are equal; a paper bag floating down the road is much less dangerous than a rampaging moose. Here, we asked whether perceived hazardousness modulated the LPE. To examine this, we took a dataset in which 48 raters assessed the perceived dangerousness of hazards in recorded road videos (Song et al. in Behav Res Methods, 2023. https://doi.org/10.3758/s13428-023-02299-8 ) and correlated the ratings with data from a hazard detection task using the same stimuli with varying hazard prevalence rates (Kosovicheva et al. in Psychon Bull Rev 30(1):212-223, 2023. https://doi.org/10.3758/s13423-022-02159-0 ). We found that while hazard detectability increased monotonically with hazardousness ratings, the LPE was comparable across perceived hazardousness levels. Our findings are consistent with the decision criterion account of the LPE, in which target rarity induces a conservative shift in criterion. Importantly, feedback was necessary for a large and consistent LPE; when participants were not given feedback about their accuracy, the most dangerous hazards showed a non-significant LPE. However, eliminating feedback was not enough to induce the opposite of the LPE-prevalence induced concept change (Levari et al. in Science 360(6396):1465-1467, 2018. https://doi.org/10.1126/science.aap8731 ), in which participants adopt a more liberal criterion when instances of a category become rare. Our results suggest that the road hazard LPE may be somewhat affected by the inherent variability of driving situations, but is still observed for highly dangerous hazards.

High target prevalence may reduce the spread of attention during search tasks

Target prevalence influences many cognitive processes during visual search, including target detection, search efficiency, and item processing. The present research investigated whether target prevalence may also impact the spread of attention during search. Relative to low-prevalence searches, high-prevalence searches typically yield higher fixation counts, particularly during target-absent trials. This may emerge because the attention spread around each fixation may be smaller for high than low prevalence searches. To test this, observers searched for targets within object arrays in Experiments 1 (free-viewing) and 2 (gaze-contingent viewing). In Experiment 3, observers searched for targets in a Rapid Serial Visual Presentation (RSVP) stream at the center of the display while simultaneously processing occasional peripheral objects. Experiment 1 used fixation patterns to estimate attentional spread, and revealed that attention was narrowed during high, relative to low, prevalence searches. This effect was weakened during gaze-contingent search (Experiment 2) but emerged again when eye movements were unnecessary in RSVP search (Experiment 3). These results suggest that, although task demands impact how attention is allocated across displays, attention may also narrow when searching for frequent targets.

The attentional boost effect reflects both enhanced memory for target-paired objects and impaired memory for distractor-paired objects

Throughout prolonged tasks, visual attention fluctuates temporally in response to the present stimuli, task demands, and changes in available attentional resources. This temporal fluctuation has downstream effects on memory for stimuli presented during the task. Researchers have established that detection of a target (e.g., a square of a color to which participants are instructed to respond with a button press) within a rapid serial visual presentation (RSVP) stream leads to better memory for concurrently presented stimuli than for stimuli presented along with an RSVP distractor (e.g., a square of a color to which participants are instructed to withhold response). Although debates have arisen regarding whether this memory difference, termed the attentional boost effect, results from target-induced enhancement, distractor-induced impairment, or a combination of the two, researchers have largely come to focus on explanations that consider only target-induced memory enhancement. In the present study, we show across three large-sampled experiments a consistent appearance of both target-induced memory enhancement and distractor-induced memory impairment relative to a baseline. In each experiment, participants responded with a spacebar press to squares of one color in an RSVP stream while withholding response to squares of another color and trials with no square (baseline trials). They simultaneously memorized concurrently presented objects. The presence of both enhancement and impairment in these experiments invites the development of new dual-task research that considers distractor-induced memory impairment and the control of temporal selection across tasks. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Emphasizing responder speed or accuracy modulates but does not abolish the distractor-induced quitting effect in visual search

When a highly salient distractor is present in a search array, it speeds target absent visual search and increases errors during target present visual search, suggesting lowered quitting thresholds (Moher in Psychol Sci 31(1):31-42, 2020). Missing a critical target in the presence of a highly salient distractor can have dire consequences in real-world search tasks where accurate target detection is crucial, such as baggage screening. As such, the current study examined whether emphasizing either accuracy or speed would eliminate the distractor-generated quitting threshold effect (QTE). Three blocks of a target detection search task which included a highly salient distractor on half of all trials were used. In one block, participants received no instructions or feedback regarding performance. In the remaining two blocks, they received instructions and trial-by-trial feedback that either emphasized response speed or response accuracy. Overall, the distractor lowered quitting thresholds, regardless of whether response speed or response accuracy was emphasized in a block of trials. However, the effect of the distractor on target misses was smaller when accuracy was emphasized. It, therefore, appears that while the distractor QTE is not easily eradicated by explicit instructions and feedback, it can be shifted. As such, future research should examine the applicability of these and similar strategies in real-world search scenarios.

Graded prioritisation of targets in search: reward diminishes the low prevalence effect

In many real-life contexts, observers are required to search for targets that are rarely present (e.g. tumours in X-rays; dangerous items in airport security screenings). Despite the rarity of these items, they are of enormous importance for the health and safety of the public, yet they are easily missed during visual search. This is referred to as the prevalence effect. In the current series of experiments, we investigate whether unequal reward can modulate the prevalence effect, in a multiple target search task. Having first established the impact of prevalence (Experiment 1) and reward (Experiment 2) on how efficiently participants can find one of several targets in the current paradigm, we then combined the two forms of priority to investigate their interaction. An unequal reward distribution (where lower prevalence items are more rewarded; Experiment 3) was found to diminish the effect of prevalence, compared to an equal reward distribution (Experiment 4) as indicated by faster response times and fewer misses. These findings suggest that when combined with an unequal reward distribution, the low prevalence effect can be diminished.

Serial dependence in perception across naturalistic generative adversarial network-generated mammogram

Purpose

Human perception and decisions are biased toward previously seen stimuli. This phenomenon is known as serial dependence and has been extensively studied for the last decade. Recent evidence suggests that clinicians' judgments of mammograms might also be impacted by serial dependence. However, the stimuli used in previous psychophysical experiments on this question, consisting of artificial geometric shapes and healthy tissue backgrounds, were unrealistic. We utilized realistic and controlled generative adversarial network (GAN)-generated radiographs to mimic images that clinicians typically encounter.

Approach

Mammograms from the digital database for screening mammography (DDSM) were utilized to train a GAN. This pretrained GAN was then adopted to generate a large set of authentic-looking simulated mammograms: 20 circular morph continuums, each with 147 images, for a total of 2940 images. Using these stimuli in a standard serial dependence experiment, participants viewed a random GAN-generated mammogram on each trial and subsequently matched the GAN-generated mammogram encountered using a continuous report. The characteristics of serial dependence from each continuum were analyzed.

Results

We found that serial dependence affected the perception of all naturalistic GAN-generated mammogram morph continuums. In all cases, the perceptual judgments of GAN-generated mammograms were biased toward previously encountered GAN-generated mammograms. On average, perceptual decisions had 7% categorization errors that were pulled in the direction of serial dependence.

Conclusions

Serial dependence was found even in the perception of naturalistic GAN-generated mammograms created by a GAN. This supports the idea that serial dependence could, in principle, contribute to decision errors in medical image perception tasks.

Performance-linked visual feedback slows response times during a sustained attention task

In the present study, we tested a visual feedback triggering system based on real-time tracking of response time (RT) in a sustained attention task. In our task, at certain points, brief visual feedback epochs were presented without interrupting the task itself. When these feedback epochs were performance-linked-meaning that they were triggered because participants were responding more quickly than usual-RTs were slowed after the presentation of feedback. However, visual feedback epochs displayed at predetermined times that were independent of participants' performance did not slow RTs. Results from a second experiment support the idea that this is not simply a return to baseline that would have occurred had the feedback not been presented, but instead suggest that the feedback itself was effective in altering participants' responses. In a third experiment, we replicated this result across with both written word feedback and visual symbolic feedback, as well as in cases where the participant was explicitly told that the feedback was linked to their performance. All together, these data provide insight into potential mechanisms for detecting and disrupting lapses in sustained attention without interrupting a continuous task.

Framing the fallibility of Computer-Aided Detection aids cancer detection

Computer-Aided Detection (CAD) has been proposed to help operators search for cancers in mammograms. Previous studies have found that although accurate CAD leads to an improvement in cancer detection, inaccurate CAD leads to an increase in both missed cancers and false alarms. This is known as the over-reliance effect. We investigated whether providing framing statements of CAD fallibility could keep the benefits of CAD while reducing over-reliance. In Experiment 1, participants were told about the benefits or costs of CAD, prior to the experiment. Experiment 2 was similar, except that participants were given a stronger warning and instruction set in relation to the costs of CAD. The results showed that although there was no effect of framing in Experiment 1, a stronger message in Experiment 2 led to a reduction in the over-reliance effect. A similar result was found in Experiment 3 where the target had a lower prevalence. The results show that although the presence of CAD can result in over-reliance on the technology, these effects can be mitigated by framing and instruction sets in relation to CAD fallibility.

Time on task and task load in visual inspection: A four-month field study with X-ray baggage screeners

Previous studies suggest that performance in visual inspection and typical vigilance tasks depend on time on task and task load. European regulation mandates that security officers (screeners) take a break or change tasks after 20 min of X-ray baggage screening. However, longer screening durations could reduce staffing challenges. We investigated the effects of time on task and task load on visual inspection performance in a four-month field study with screeners. At an international airport, 22 screeners inspected X-ray images of cabin baggage for up to 60 min, while a control group (N = 19) screened for 20 min. Hit rate remained stable for low and average task loads. However, when the task load was high, the screeners compensated by speeding up X-ray image inspection at the expense of the hit rate over time on task. Our results support the dynamic-allocation resource theory. Moreover, extending the permitted screening duration to 30 or 40 min should be considered.

Improving forensic perpetrator identification with Super-Recognizers

About a decade ago, Super-Recognizers (SRs) were first described as individuals with exceptional face identity processing abilities. Since then, various tests have been developed or adapted to assess individuals' abilities and identify SRs. The extant literature suggests that SRs may be beneficial in police tasks requiring individual identification. However, in reality, the performance of SRs has never been examined using authentic forensic material. This not only limits the external validity of test procedures used to identify SRs, but also claims concerning their deployment in policing. Here, we report the first-ever investigation of SRs' ability to identify perpetrators using authentic case material. We report the data of 73 SRs and 45 control participants. These include (a) performance on three challenging tests of face identity processing recommended by Ramon (2021) for SR identification; (b) performance for perpetrator identification using four CCTV sequences depicting five perpetrators and police line-ups created for criminal investigation purposes. Our findings demonstrate that the face identity processing tests used here are valid in measuring such abilities and identifying SRs. Moreover, SRs excel at perpetrator identification relative to control participants, with more correct perpetrator identifications, the better their performance across lab tests. These results provide external validity for the recently proposed diagnostic framework and its tests used for SR identification (Ramon, 2021). This study provides the first empirical evidence that SRs identified using these measures can be beneficial for forensic perpetrator identification. We discuss theoretical and practical implications for law enforcement, whose procedures can be improved via a human-centric approach centered around individuals with superior abilities.

Taking prevalence effects on the road: Rare hazards are often missed

Previous work has shown that, in many visual search and detection tasks, observers frequently miss rare but important targets, like weapons in bags or abnormalities in radiological images. These prior studies of the low-prevalence effect (LPE) use static stimuli and typically permitted observers to search at will. In contrast, many real-world tasks, like looking for dangerous behavior on the road, only afford observers a brief glimpse of a complex, changing scene before they must make a decision. Can the LPE be a factor in in dynamic, time-limited moments of real driving? To test this, we developed a novel hazard-detection task that preserves much of the perceptual richness and complexity of hazard detection in the real world, while allowing for experimental control over event prevalence. Observers viewed brief video clips of road scenes recorded from dashboard cameras and reported whether they saw a hazardous event. In separate sessions, the prevalence of these events was either high (50% of videos) or low (4%). Under low prevalence, observers missed hazards at more than twice the rate observed in the high-prevalence condition. Follow-up experiments demonstrate that this elevation of miss rate at low prevalence persists when participants were allowed to correct their responses, increases as hazards become increasingly rare (down to 1% prevalence) and is resistant to simple cognitive intervention (participant prebriefing). Together, our results demonstrate that the LPE generalizes to complex perceptual decisions in dynamic natural scenes, such as driving, where observers must monitor and respond to rare hazards.

Hip fracture or not? The reversed prevalence effect among non-experts' diagnosis

Despite numerous investigations of the prevalence effect on medical image perception, little research has been done to examine the effect of expertise, and its possible interaction with prevalence. In this study, medical practitioners were instructed to detect the presence of hip fracture in 50 X-ray images with either high prevalence (N_signal = 40) or low prevalence (N_signal = 10). Results showed that compared to novices (e.g., pediatricians, dentists, neurologists), the manipulation of prevalence shifted participant's criteria in a different direction for experts who perform hip fracture diagnosis on a daily basis. That is, when prevalence rate is low (p_{fracture-present} = 0.2), experts held more conservative criteria in answering "fracture-present," whereas novices were more likely to believe there was fracture. Importantly, participants' detection discriminability did not vary by the prevalence condition. In addition, all participants were more conservative with "fracture-present" responses when task difficulty increased. We suspect the apparent opposite criteria shift between experts and novices may have come from medical training that made novices to believe that a miss would result in larger cost compared to false positive, or because they failed to update their prior belief about the signal prevalence in the task, both would suggest that novices and experts may have different beliefs in placing the optimal strategy in the hip fracture diagnosis. Our work can contribute to medical education training as well as other applied clinical diagnosis that aims to mitigate the prevalence effect.

Enhanced threat detection in three dimensions: An image-matched comparison of computed tomography and dual-view X-ray baggage screening

Computed Tomography (CT) is increasingly used in screening of cabin baggage in airports. The current study aimed to establish whether screening with CT confers a detection advantage over dual-view (DV) X-ray when resolution is controlled. We also evaluated whether a 'targetless' search strategy - in which screeners identify and reject safe items - improved detection relative to target-based methods. In an online study, 104 novice screeners were trained with either CT or DV, and either a targetless or a target-based search strategy. Screeners were then tested in a simulated cabin baggage screening task. CT screeners performed with greater sensitivity than DV screeners. Search strategy did not affect sensitivity, although the target-based strategy resulted in a more liberal criterion. We conclude that CT imaging confers a benefit to screening performance over DV when image resolution is controlled. This is likely due to the ability to rotate the image to resolve occlusions.

The influence of category representativeness on the low prevalence effect in visual search

Visual search is greatly affected by the appearance rate of given target types, such that low-prevalence items are harder to detect, which has consequences for real-world search tasks where target frequency cannot be balanced. However, targets that are highly representative of a categorically defined task set are also easier to find. We hypothesized that targets that are highly representative are less vulnerable to low-prevalence effects because an observer's attentional set prioritizes guidance toward them even when they are rare. We assessed this hypothesis by first determining the categorical structure of "prohibited carry-ons" via an exemplar-naming task, and used this structure to assess how category representativeness interacted with prevalence. Specifically, from the exemplar-naming task we selected a commonly named (knives) and rarely named (gas cans) target for a search task in which one of the targets was shown infrequently. As predicted, highly representative targets were found more easily than their less representative counterparts, but they also were less affected by prevalence manipulations. Experiment 1b replicated the results with targets matched for emotional valence (water bottles and fireworks). These findings demonstrate the powerful explanatory power of theories of attentional guidance that incorporate the dynamic influence of recent experience with the knowledge that comes from life experience to better predict behavioral outcomes associated with high-stakes search environments.

Normal blindness: when we Look But Fail To See

Humans routinely miss important information that is 'right in front of our eyes', from overlooking typos in a paper to failing to see a cyclist in an intersection. Recent studies on these 'Looked But Failed To See' (LBFTS) errors point to a common mechanism underlying these failures, whether the missed item was an unexpected gorilla, the clearly defined target of a visual search, or that simple typo. We argue that normal blindness is the by-product of the limited-capacity prediction engine that is our visual system. The processes that evolved to allow us to move through the world with ease are virtually guaranteed to cause us to miss some significant stimuli, especially in important tasks like driving and medical image perception.

Measuring the Efficiency of Automation-Aided Performance in a Simulated Baggage Screening Task

OBJECTIVE

The present study replicated and extended prior findings of suboptimal automation use in a signal detection task, benchmarking automation-aided performance to the predictions of several statistical models of collaborative decision making.

BACKGROUND

Though automated decision aids can assist human operators to perform complex tasks, operators often use the aids suboptimally, achieving performance lower than statistically ideal.

METHOD

Participants performed a simulated security screening task requiring them to judge whether a target (a knife) was present or absent in a series of colored X-ray images of passenger baggage. They completed the task both with and without assistance from a 93%-reliable automated decision aid that provided a binary text diagnosis. A series of three experiments varied task characteristics including the timing of the aid's judgment relative to the raw stimuli, target certainty, and target prevalence.

RESULTS AND CONCLUSION

Automation-aided performance fell closest to the predictions of the most suboptimal model under consideration, one which assumes the participant defers to the aid's diagnosis with a probability of 50%. Performance was similar across experiments.

APPLICATION

Results suggest that human operators' performance when undertaking a naturalistic search task falls far short of optimal and far lower than prior findings using an abstract signal detection task.

The low prevalence effect in fingerprint comparison amongst forensic science trainees and novices

The low prevalence effect is a phenomenon whereby target prevalence affects performance in visual search (e.g., baggage screening) and comparison (e.g., fingerprint examination) tasks, such that people more often fail to detect infrequent target stimuli. For example, when exposed to higher base-rates of 'matching' (i.e., from the same person) than 'non-matching' (i.e., from different people) fingerprint pairs, people more often misjudge 'non-matching' pairs as 'matches'-an error that can falsely implicate an innocent person for a crime they did not commit. In this paper, we investigated whether forensic science training may mitigate the low prevalence effect in fingerprint comparison. Forensic science trainees (n = 111) and untrained novices (n = 114) judged 100 fingerprint pairs as 'matches' or 'non-matches' where the matching pair occurrence was either high (90%) or equal (50%). Some participants were also asked to use a novel feature-comparison strategy as a potential attenuation technique for the low prevalence effect. Regardless of strategy, both trainees and novices were susceptible to the effect, such that they more often misjudged non-matching pairs as matches when non-matches were rare. These results support the robust nature of the low prevalence effect in visual comparison and have important applied implications for forensic decision-making in the criminal justice system.

Mandating Limits on Workload, Duty, and Speed in Radiology

Research has not yet quantified the effects of workload or duty hours on the accuracy of radiologists. With the exception of a brief reduction in imaging studies during the 2020 peak of the COVID-19 pandemic, the workload of radiologists in the United States has seen relentless growth in recent years. One concern is that this increased demand could lead to reduced accuracy. Behavioral studies in species ranging from insects to humans have shown that decision speed is inversely correlated to decision accuracy. A potential solution is to institute workload and duty limits to optimize radiologist performance and patient safety. The concern, however, is that any prescribed mandated limits would be arbitrary and thus no more advantageous than allowing radiologists to self-regulate. Specific studies have been proposed to determine whether limits reduce error, and if so, to provide a principled basis for such limits. This could determine the precise susceptibility of individual radiologists to medical error as a function of speed during image viewing, the maximum number of studies that could be read during a work shift, and the appropriate shift duration as a function of time of day. Before principled recommendations for restrictions are made, however, it is important to understand how radiologists function both optimally and at the margins of adequate performance. This study examines the relationship between interpretation speed and error rates in radiology, the potential influence of artificial intelligence on reading speed and error rates, and the possible outcomes of imposed limits on both caseload and duty hours. This review concludes that the scientific evidence needed to make meaningful rules is lacking and notes that regulating workloads without scientific principles can be more harmful than not regulating at all.

Target-rate effect in continuous visual search

From infrared body temperature surveillance to lifeguarding, real-life visual search is usually continuous and comes with rare targets. Previous research has examined realistic search tasks involving separate slides (such as baggage screening and radiography), but search tasks that require continuous monitoring have generally received less attention. In this study, we investigated whether continuous visual search would display a target-rate effect similar to the low-prevalence effect (LPE) in regular visual search. We designed a continuous detection task for a target feature (e.g., a green color) among items of continuously and gradually changing features (e.g., other colors). In four experiments, we demonstrated target-rate effects in terms of slower hit response times (RTs) and higher miss rates when targets were rare. Similar to regular search, target-rate effects were also observed for relative frequencies across two target features. Taken together, these results suggest a target-rate effect in continuous visual search, and its behavioral characteristics are generally similar to those of the LPE in regular visual search.

Prior experience with target encounter affects attention allocation and prospective memory performance

We examined how prior experience encountering targets affected attention allocation and event-based prospective memory. Participants performed four color match task blocks with a difficult, but specified prospective memory task (Experiment 1) or an easier, but unspecified prospective memory task (Experiment 2). Participants were instructed to search for targets on each block. Participants in the prior experience condition saw targets on each block, participants in the no prior experience condition only saw targets on the fourth block, and, in Experiment 2, participants in the mixed prior experience condition encountered some of the targets on the first three blocks, and saw all the targets on the fourth block. In Experiment 1, participants in the no prior experience condition were less accurate at recognizing targets and quicker to respond on ongoing task trials than participants in the prior experience condition. In Experiment 2, we replicated the effect of prior experience on target accuracy, but there was no effect on ongoing trial response time. The mixed experience condition did not vary from the other conditions on either dependent variable, but their target accuracy varied in accordance with their experience. These findings demonstrate that prospective memory performance is influenced by experience with related tasks, thus extending our understanding of the dynamic nature of search efforts across related prospective memory tasks. This research has implications for understanding prospective memory in applied settings where targets do not reliably occur such as baggage screenings and missing person searches.

Eliminating the Low-Prevalence Effect in Visual Search With a Remarkably Simple Strategy

The low-prevalence effect in visual search occurs when rare targets are missed at a disproportionately high rate. This effect has enormous significance for health and public safety and has proven resistant to intervention. In three experiments (Ns = 41, 40, and 44 adults), we documented a dramatic reduction of the effect using a simple cognitive strategy requiring no training. Instead of asking participants to search for the presence or absence of a target, as is typically done in visual search tasks, we asked participants to engage in "similarity search"-to identify the display element most similar to a target on every trial, regardless of whether a target was present. When participants received normal search instructions, we observed strong low-prevalence effects. When participants used similarity search, we failed to detect the low-prevalence effect under identical visual conditions across three experiments.

The presence of a distractor matching the content of working memory induces delayed quitting in visual search

Previous research has shown that the presence of a distractor object matching the current content of working memory interacts with visual search. Because finding a target and quitting a search without finding a target may be implemented by qualitatively different processes, it is possible that the effects of a memory-matching distractor on target-present trials and on target-absent trials reveal different mechanisms by which the memory-matching distractor interacts with visual search. Although previous studies have well established the effect of attentional capture by a memory-matching distractor when the target object is found in the search display, there remains an open question about whether the presence of a memory-matching distractor can affect the process of search termination when no target is found. In the present study, we showed that search termination times on target-absent trials were delayed by the presence of a distractor matching the content of visual working memory. This delayed quitting effect cannot be conceived of as a more general influence of visual short-term memory, because the presence of a distractor matching the content of passive visual short-term memory (i.e., visual priming) did not influence quitting behavior in visual search. These findings offer a novel perspective that distractors matching the information maintained in visual working memory can cause observers to delay search termination when no target has been found.

LAG-1: A dynamic, integrative model of learning, attention, and gaze

It is clear that learning and attention interact, but it is an ongoing challenge to integrate their psychological and neurophysiological descriptions. Here we introduce LAG-1, a dynamic neural field model of learning, attention and gaze, that we fit to human learning and eye-movement data from two category learning experiments. LAG-1 comprises three control systems: one for visuospatial attention, one for saccadic timing and control, and one for category learning. The model is able to extract a kind of information gain from pairwise differences in simple associations between visual features and categories. Providing this gain as a reentrant signal with bottom-up visual information, and in top-down spatial priority, appropriately influences the initiation of saccades. LAG-1 provides a moment-by-moment simulation of the interactions of learning and gaze, and thus simultaneously produces phenomena on many timescales, from the duration of saccades and gaze fixations, to the response times for trials, to the slow optimization of attention toward task relevant information across a whole experiment. With only three free parameters (learning rate, trial impatience, and fixation impatience) LAG-1 produces qualitatively correct fits for learning, behavioural timing and eye movement measures, and also for previously unmodelled empirical phenomena (e.g., fixation orders showing stimulus-specific attention, and decreasing fixation counts during feedback). Because LAG-1 is built to capture attention and gaze generally, we demonstrate how it can be applied to other phenomena of visual cognition such as the free viewing of visual stimuli, visual search, and covert attention.

How Realistic Is Threat Image Projection for X-ray Baggage Screening?

At airports, security officers (screeners) inspect X-ray images of passenger baggage in order to prevent threat items (bombs, guns, knives, etc.) from being brought onto an aircraft. Because threat items rarely occur, many airports use a threat-image-projection (TIP) system, which projects pre-recorded X-ray images of threat items onto some of the X-ray baggage images in order to improve the threat detection of screeners. TIP is regulatorily mandated in many countries and is also used to identify officers with insufficient threat-detection performance. However, TIP images sometimes look unrealistic because of artifacts and unrealistic scenarios, which could reduce the efficacy of TIP. Screeners rated a representative sample of TIP images regarding artifacts identified in a pre-study. We also evaluated whether specific image characteristics affect the occurrence rate of artifacts. 24% of the TIP images were rated to display artifacts and 26% to depict unrealistic scenarios, with 34% showing at least one of the two. With two-thirds of the TIP images having been perceived as realistic, we argue that TIP still serves its purpose, but artifacts and unrealistic scenarios should be reduced. Recommendations on how to improve the efficacy of TIP by considering image characteristics are provided.

The elephant in the room: attention to salient scene features increases with comedic expertise

What differentiates the joke writing strategy employed by professional comedians from non-comedians? Previous MRI work found that professional comedians relied to a greater extent on "bottom-up processes," i.e., associations driven by the prompt stimuli themselves, while controls relied more on prefrontal lobe directed, "top-down" processes. In the present work, professional improv comedians and controls generated humorous captions to cartoons while their eye movements were tracked. Participants' visual fixation patterns were compared to predictions of the saliency model (Harel et al. in Adv Neural Inf Process Syst 19:545-552, 2007)-a computer model for identifying the most salient locations in an image based on visual features. Captions generated by the participants were rated for funniness by independent raters. Relative to controls, professional comedians' gaze was driven to a greater extent by the cartoons' salient visual features. For all participants, captions' funniness positively correlated with visual attention to salient cartoon features. Results suggest that comedic expertise is associated with increased reliance on bottom-up, stimulus-driven creativity, and that a bottom-up strategy results, on average, in funnier captions whether employed by comedians or controls. The cognitive processes underlying successful comedic creativity appear to adhere to the old comedians' adage "pay attention to the elephant in the room."

The optimal use of computer aided detection to find low prevalence cancers

People miss a high proportion of targets that only appear rarely. This low prevalence (LP) effect has implications for applied search tasks such as the clinical reading of mammograms. Computer aided detection (CAD) has been used to help radiologists search mammograms by highlighting areas likely to contain a cancer. Previous research has found a benefit in search when CAD cues were correct but a cost to search when CAD cues were incorrect. The current research investigated whether there is an optimal way to present CAD to ensure low error rates when CAD is both correct and incorrect. Experiment 1 compared an automatic condition, where CAD appeared simultaneously with the display to an interactive condition, where participants could choose to use CAD. Experiment 2 compared the automatic condition to a confirm condition, where participants searched the display first before being shown the CAD cues. The results showed that miss errors were reduced overall in the confirm condition, with no cost to false alarms. Furthermore, having CAD be interactive, resulted in a low uptake where it was only used in 34% of trials. The results showed that the presentation mode of CAD can affect decision-making in LP 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.

Advancing Research on Medical Image Perception by Strengthening Multidisciplinary Collaboration

Medical image interpretation is central to detecting, diagnosing, and staging cancer and many other disorders. At a time when medical imaging is being transformed by digital technologies and artificial intelligence, understanding the basic perceptual and cognitive processes underlying medical image interpretation is vital for increasing diagnosticians’ accuracy and performance, improving patient outcomes, and reducing diagnostician burn-out. Medical image perception remains substantially understudied. In September of 2019, the National Cancer Institute convened a multidisciplinary panel of radiologists and pathologists together with researchers working in medical image perception and adjacent fields of cognition and perception for the “Cognition and Medical Image Perception Think Tank.” The Think Tank’s key objectives were: to identify critical unsolved problems related to visual perception in pathology and radiology from the perspective of diagnosticians; to discuss how these clinically relevant questions could be addressed through cognitive and perception research; to identify barriers and solutions for transdisciplinary collaborations; to define ways to elevate the profile of cognition and perception research within the medical image community; to determine the greatest needs to advance medical image perception; and to outline future goals and strategies to evaluate progress. The Think Tank emphasized diagnosticians’ perspectives as the crucial starting point for medical image perception research, with diagnosticians describing their interpretation process and identifying perceptual and cognitive problems that arise. This paper reports the deliberations of the Think Tank participants to address these objectives and highlight opportunities to expand research on medical image perception.

Serial dependence in the perceptual judgments of radiologists

In radiological screening, clinicians scan myriads of radiographs with the intent of recognizing and differentiating lesions. Even though they are trained experts, radiologists’ human search engines are not perfect: average daily error rates are estimated around 3–5%. A main underlying assumption in radiological screening is that visual search on a current radiograph occurs independently of previously seen radiographs. However, recent studies have shown that human perception is biased by previously seen stimuli; the bias in our visual system to misperceive current stimuli towards previous stimuli is called serial dependence. Here, we tested whether serial dependence impacts radiologists’ recognition of simulated lesions embedded in actual radiographs. We found that serial dependence affected radiologists’ recognition of simulated lesions; perception on an average trial was pulled 13% toward the 1-back stimulus. Simulated lesions were perceived as biased towards the those seen in the previous 1 or 2 radiographs. Similar results were found when testing lesion recognition in a group of untrained observers. Taken together, these results suggest that perceptual judgements of radiologists are affected by previous visual experience, and thus some of the diagnostic errors exhibited by radiologists may be caused by serial dependence from previously seen radiographs.

The relationship between the subjective experience of real-world cognitive failures and objective target-detection performance in visual search

Visual search is a common occurrence in everyday life, such as searching for the location of keys, identifying a friend in a crowd, or scanning an upcoming intersection for hazards while driving. Visual search is also used in professional contexts, such as medical diagnostic imaging and airport baggage screening. These contexts are often characterised by low-prevalence or rare targets. Here we tested whether individual differences in the detection of targets in visual search could be predicted from variables derived from the rich informational source of participants' subjective experience of their cognitive and attentional function in everyday life. We tested this in both low-prevalence (Experiment 1) and high-prevalence (Experiment 2) visual search conditions. In both experiments, participants completed a visual search with arrays containing multiple photorealistic objects, and their task was to detect the presence of a gun. Following this, they completed the Cognitive Failures Questionnaire (CFQ) and the Attentional Control Scale (ACS). In Experiment 1, the target was present on 2% of trials, while in Experiment 2, it was present on 50%. In both experiments, participants' scores on the False Triggering component of the CFQ were negatively associated with accuracy on target-present trials, while participants' scores on the Forgetfulness component of the CFQ were positively associated with target-present accuracy. These results show that objective performance in visual search can be predicted from subjective experiences of cognitive function. They also highlight that the CFQ is not monolithic. Instead, the CFQ subfactors can have qualitatively different relationships with performance. Theoretical and practical implications are discussed.

From "satisfaction of search" to "subsequent search misses": a review of multiple-target search errors across radiology and cognitive science

For over 50 years, the satisfaction of search effect has been studied within the field of radiology. Defined as a decrease in detection rates for a subsequent target when an initial target is found within the image, these multiple target errors are known to underlie errors of omission (e.g., a radiologist is more likely to miss an abnormality if another abnormality is identified). More recently, they have also been found to underlie lab-based search errors in cognitive science experiments (e.g., an observer is more likely to miss a target 'T' if a different target 'T' was detected). This phenomenon was renamed the subsequent search miss (SSM) effect in cognitive science. Here we review the SSM literature in both radiology and cognitive science and discuss: (1) the current SSM theories (i.e., satisfaction, perceptual set, and resource depletion theories), (2) the eye movement errors that underlie the SSM effect, (3) the existing efforts tested to alleviate SSM errors, and (4) the evolution of methodologies and analyses used when calculating the SSM effect. Finally, we present the attentional template theory, a novel mechanistic explanation for SSM errors, which ties together our current understanding of SSM errors and the attentional template literature.

Low prevalence match and mismatch detection in simultaneous face matching: Influence of face recognition ability and feature focus guidance

Simultaneous face matching to verify identity is key to security and policing. However, matching is error-prone, particularly when target-item prevalence is low. Two experiments examined whether superior face recognition ability and the use of internal or external facial feature guidance scales would reduce low prevalence effects. In Experiment 1, super-recognisers (n = 317) significantly outperformed typical-ability controls (n = 452), while internal feature guidance enhanced accuracy across all prevalence conditions. However, an unexpected effect in controls revealed higher accuracy in low prevalence conditions, probably because no low-match or low-mismatch prevalence information was provided. In Experiment 2, top-end-of-typical range ability participants (n = 841) were informed of their low prevalence condition and demonstrated the expected low-prevalence effects. Findings and implications are discussed.

Perceptual and response factors in the gradual onset continuous performance tasks

Using a novel gradual onset continuous performance task (gradCPT), recent research has uncovered a brain network of the sustained attention ability, demonstrating marked individual differences. Yet much about the cognitive processes that support performance on the gradCPT remains unknown. Here, we tested the importance of response inhibition and perceptual discrimination in the gradCPT. Participants monitored a continuous stream of natural scenes from two categories-cities and mountains-with a 9:1 ratio. In separate task blocks, they responded either to the frequent or the rare, yielding a response rate of either 90% or 10%. Performance was much worse, and declined more significantly over time, when the required response rate was higher. To test the role of stimulus onset, separate task blocks presented the scenes either gradually, with adjacent scenes blending into each other (gradCPT), or abruptly, with a single scene visible at a time (abruptCPT). Despite its increased complexity, the gradCPT yielded better performance than the abruptCPT, contradicting the perceptual complexity hypothesis and suggesting a detrimental role of the automaticity of responses to rhythmic stimuli in sustained attention. Further bolstering the role of response inhibition in the gradCPT, participants with superior inhibitory function, as assessed by the "stop-signal" task, did better on the gradCPT. These findings show that response inhibition contributes to the ability to sustain attention, especially in tasks that require frequent and repetitive responses as in assembly-line jobs.

What do experts look at and what do experts find when reading mammograms?

Purpose: Radiologists sometimes fail to report clearly visible, clinically significant findings. Eye tracking can provide insight into the causes of such errors. Approach: We tracked eye movements of 17 radiologists, searching for masses in 80 mammograms (60 with masses). Results: Errors were classified using the Kundel et al. (1978) taxonomy: search errors (target never fixated), recognition errors (fixated < 500    ms ), or decision errors (fixated > 500    ms ). Error proportions replicated Krupinski (1996): search 25%, recognition 25%, and decision 50%. Interestingly, we found few differences between experts and residents in accuracy or eye movement metrics. Error categorization depends on the definition of the useful field of view (UFOV) around fixation. We explored different UFOV definitions, based on targeting saccades and search saccades. Targeting saccades averaged slightly longer than search saccades. Of most interest, we found that the probability that the eyes would move to the target on the next saccade or even on one of the next three saccades was strikingly low ( ∼ 33 % , even when the eyes were < 2    deg from the target). This makes it clear that observers do not fully process everything within a UFOV. Using a probabilistic UFOV, we find, unsurprisingly, that observers cover more of the image when no target is present than when it is found. Interestingly, we do not find evidence that observers cover too little of the image on trials when they miss the target. Conclusions: These results indicate that many errors in mammography reflect failed deployment of attention; not failure to fixate clinically significant locations.

Feedback moderates the effect of prevalence on perceptual decisions

How does the prevalence of a target influence how it is perceived and categorized? A substantial body of work, mostly in visual search, shows that a higher proportion of targets are missed when prevalence is low. This classic low prevalence effect (LPE) involves a shift to a more conservative decision criterion that makes it less likely that observers will call an ambiguous item a target. In contrast, Levari et al. (Science, 360[6396], 1465-1467, 2018) recently reported the opposite effect in a simple categorization task. In their hands, at low prevalence, observers adopted a more liberal criterion, making observers more likely to label ambiguous dots on a blue-purple continuum "blue." They called this "prevalence-induced concept change" (PICC). Here, we report that the presence or absence of feedback is critical. With feedback, observers become more conservative at low prevalence, as in the LPE. Without feedback, they become more liberal, identifying a wider range of stimuli as targets, as in Levari's PICC studies. Stimuli from a shape continuum ranging from rounded ("Bouba") to bumpy ("Kiki") shapes produced similar results. Other variables: response type (2AFC vs. go/no-go), color (blue-purple vs. red-green), and stimuli type (solid color vs. texture) did not influence the criterion shifts. Understanding these effects of prevalence and ways they can be controlled illuminates the context-specific nature of perceptual decisions and may be useful in socially important, low prevalence tasks like cancer screening, airport security, and disease diagnosis in pathology.

Avoiding potential pitfalls in visual search and eye-movement experiments: A tutorial review

Examining eye-movement behavior during visual search is an increasingly popular approach for gaining insights into the moment-to-moment processing that takes place when we look for targets in our environment. In this tutorial review, we describe a set of pitfalls and considerations that are important for researchers – both experienced and new to the field – when engaging in eye-movement and visual search experiments. We walk the reader through the research cycle of a visual search and eye-movement experiment, from choosing the right predictions, through to data collection, reporting of methodology, analytic approaches, the different dependent variables to analyze, and drawing conclusions from patterns of results. Overall, our hope is that this review can serve as a guide, a talking point, a reflection on the practices and potential problems with the current literature on this topic, and ultimately a first step towards standardizing research practices in the field.

Target value and prevalence influence visual foraging in younger and older age

The prevalence and reward-value of targets have an influence on visual search. The strength of the effect of an item's reward-value on attentional selection varies substantially between individuals and is potentially sensitive to aging. We investigated individual and age differences in a hybrid foraging task, in which the prevalence and value of multiple target types was varied. Using optimal foraging theory measures, foraging was more efficient overall in younger than older observers. However, the influence of prevalence and value on target selections was similar across age groups, suggesting that the underlying cognitive mechanisms are preserved in older age. When prevalence was varied but target value was balanced, younger and older observers preferably selected the most frequent target type and were biased to select another instance of the previously selected target type. When value was varied, younger and older observers showed a tendency to select high-value targets, but preferences were more diverse between individuals. When value and prevalence were inversely related, some observers showed particularly strong preferences for high-valued target types, while others showed a preference for high-prevalent, albeit low-value, target types. In younger adults, individual differences in the selection choices correlated with a personality index, suggesting that avoiding selections of low-value targets may be related to reward-seeking behaviour.

Improved X-ray baggage screening sensitivity with 'targetless' search training

When searching for a known target, mental representations of target features, or templates, guide attention towards matching objects and facilitate recognition. When only distractor features are known, distractor templates allow irrelevant objects to be recognised and attention to be shifted away. This is particularly true in X-ray baggage search, a challenging real-world visual search task with implications for public safety, where targets may be unknown, difficult to predict and concealed by an adversary, but distractors are typically benign and easier to identify. In the present study, we draw on basic principles of distractor suppression and rejection to investigate a counterintuitive ‘targetless’ approach to training baggage search. In a simulated X-ray baggage search task, we observed significant benefits to target detection sensitivity (d′) for targetless relative to target-based training, but no effects of performance-contingent rewards or the inclusion of superordinate semantic categories during training. The benefits of targetless search training were most apparent for stimuli involving less spatial overlap (occlusion), which likely represents the difficulty and greater individual variation involved in searching more visually complex images. Together, these results demonstrate the effectiveness of a counterintuitive targetless approach to training target detection in X-ray baggage search, based on basic principles of distractor suppression and rejection, with potential for use as a real-world training tool.

Neural signatures of vigilance decrements predict behavioural errors before they occur

There are many monitoring environments, such as railway control, in which lapses of attention can have tragic consequences. Problematically, sustained monitoring for rare targets is difficult, with more misses and longer reaction times over time. What changes in the brain underpin these 'vigilance decrements'? We designed a multiple-object monitoring (MOM) paradigm to examine how the neural representation of information varied with target frequency and time performing the task. Behavioural performance decreased over time for the rare target (monitoring) condition, but not for a frequent target (active) condition. This was mirrored in neural decoding using magnetoencephalography: coding of critical information declined more during monitoring versus active conditions along the experiment. We developed new analyses that can predict behavioural errors from the neural data more than a second before they occurred. This facilitates pre-empting behavioural errors due to lapses in attention and provides new insight into the neural correlates of vigilance decrements.

Disentangling prevalence induced biases in medical image decision-making

Many important real-world decision tasks involve the detection of rarely occurring targets (e.g., weapons in luggage, potentially cancerous abnormalities in radiographs). Over the past decade, it has been repeatedly demonstrated that extreme prevalence (both high and low) leads to an increase in errors. While this "prevalence effect" is well established, the cognitive and/or perceptual mechanisms responsible for it are not. One reason for this is that the most common tool for analyzing prevalence effects, Signal Detection Theory, cannot distinguish between different biases that might be present. Through an application to pathology image-based decision-making, we illustrate that an evidence accumulation modeling framework can be used to disentangle different types of biases. Importantly, our results show that prevalence influences both response expectancy and stimulus evaluation biases, with novices (students, N = 96) showing a more pronounced response expectancy bias and experts (medical laboratory professionals, N = 19) showing a more pronounced stimulus evaluation bias.

When experience does not promote expertise: security professionals fail to detect low prevalence fake IDs

Professional screeners frequently verify photograph IDs in such industries as professional security, bar tending, and sales of age-restricted materials. Moreover, security screening is a vital tool for law enforcement in the search for missing or wanted persons. Nevertheless, previous research demonstrates that novice participants fail to spot fake IDs when they are rare (i.e., the low prevalence effect; LPE). To address whether this phenomenon also occurs with professional screeners, we conducted three experiments. Experiment 1 compared security professional and non-professionals. Experiment 2 compared bar-security professionals, access-security professionals, and non-professionals. Finally, Experiment 3 added a newly created Professional Identity Training Questionnaire to determine whether and how aspects of professionals’ employment predict ID-matching accuracy. Across all three experiments, all participants were susceptible to the LPE regardless of professional status. Neither length/type of professional experience nor length/type of training experience affected ID verification performance. We discuss task performance and survey responses with aims to acknowledge and address this potential problem in real-world screening scenarios.