Rare, but obviously there: effects of target frequency and salience on visual search accuracy

Determining the efficacy of visual inspections at detecting non-biosecurity-compliant goods

Examination of imported commodities by trained inspectors searching for pest organisms is a common practice that phytosanitary regulatory agencies use to mitigate biosecurity risks along trade pathways. To investigate the effects of target size and color on the efficacy of these visual assessments, we affixed square decals to polystyrene models of mandarins. Sample units of 100 model fruit containing up to 10 marked models were examined by inspectors. Six sizes in six shades of brown were tested across two prevalence levels. The experiment consisted of five inspection rounds where 11 inspectors examined 77 sample units within an allocated time. The probability that decals were detected increased with mark size and color contrast. Smaller, low-contrast marks were mainly missed. The prevalence rate did not affect the detectability. Through the experiment, the false-positive rate dropped from 6% to 3%, whereas false-negative rates were constant throughout. Large, dark targets were readily found with a mean recall of >90%, whereas small, pale marks had a mean recall of 9%. Increased experience made inspectors more competent at recognizing decals, reducing the false positive rate. However, constant false-negative rates indicate that experience did not prevent inspectors from overlooking targets they could not perceive.

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.

Searching for meaning: Local scene semantics guide attention during natural visual search in scenes

Models of visual search in scenes include image salience as a source of attentional guidance. However, because scene meaning is correlated with image salience, it could be that the salience predictor in these models is driven by meaning. To test this proposal, we generated meaning maps that represented the spatial distribution of semantic informativeness in scenes, and salience maps which represented the spatial distribution of conspicuous image features and tested their influence on fixation densities from two object search tasks in real-world scenes. The results showed that meaning accounted for significantly greater variance in fixation densities than image salience, both overall and in early attention across both studies. Here, meaning explained 58% and 63% of the theoretical ceiling of variance in attention across both studies, respectively. Furthermore, both studies demonstrated that fast initial saccades were not more likely to be directed to higher salience regions than slower initial saccades, and initial saccades of all latencies were directed to regions containing higher meaning than salience. Together, these results demonstrated that even though meaning was task-neutral, the visual system still selected meaningful over salient scene regions for attention during search.

Driver mileage and accident involvement: A synthesis of evidence

The relationship between driver mileage and accident involvement has been a controversial topic for at least 20 years. The key issue is whether driver accident involvement rate increases in proportion to miles driven or has a non-linear relationship to miles driven. This paper presents a synthesis of evidence from studies of how the number of accidents per driver per unit of time relates to distance driven in the same period. Most studies of this relationship are methodologically weak and their results highly inconsistent and potentially misleading. Unreliable data and poor control for confounding factors characterise most studies. Only a few studies based on multivariate statistical models control for at least some of the confounding factors that may influence the relationship between distance driven and accident involvement. These studies consistently show that the number of accidents per driver per year increases less than in proportion to distance driven. A good approximation is that the number of accidents per driver per unit of time is proportional to the square root of distance driven. Potential methodological and substantive explanations of this finding are discussed.

Automated pose estimation in primates

Understanding the behavior of primates is important for primatology, for psychology, and for biology more broadly. It is also important for biomedicine, where primates are an important model organism, and whose behavior is often an important variable of interest. Our ability to rigorously quantify behavior has, however, long been limited. On one hand, we can rigorously quantify low-information measures like preference, looking time, and reaction time; on the other, we can use more gestalt measures like behavioral categories tracked via ethogram, but at high cost and with high variability. Recent technological advances have led to a major revolution in behavioral measurement that offers affordable and scalable rigor. Specifically, digital video cameras and automated pose tracking software can provide measures of full-body position (i.e., pose) of primates over time (i.e., behavior) with high spatial and temporal resolution. Pose-tracking technology in turn can be used to infer behavioral states, such as eating, sleeping, and mating. We call this technological approach behavioral imaging. In this review, we situate the behavioral imaging revolution in the history of the study of behavior, argue for investment in and development of analytical and research techniques that can profit from the advent of the era of big behavior, and propose that primate centers and zoos will take on a more central role in relevant fields of research than they have in the past.

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.

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.

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.

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.

Predicting Airport Screening Officers' Visual Search Competency With a Rapid Assessment

Objective The study's objective was to assess a new personnel selection and assessment tool for aviation security screeners. A mobile app was modified to create a tool, and the question was whether it could predict professional screeners' on-job performance. Background A variety of professions (airport security, radiology, the military, etc.) rely on visual search performance-being able to detect targets. Given the importance of such professions, it is necessary to maximize performance, and one means to do so is to select individuals who excel at visual search. A critical question is whether it is possible to predict search competency within a professional search environment. Method Professional searchers from the USA Transportation Security Administration (TSA) completed a rapid assessment on a tablet-based X-ray simulator (XRAY Screener, derived from the mobile technology app Airport Scanner; Kedlin Company). The assessment contained 72 trials that were simulated X-ray images of bags. Participants searched for prohibited items and tapped on them with their finger. Results Performance on the assessment significantly related to on-job performance measures for the TSA officers such that those who were better XRAY Screener performers were both more accurate and faster at the actual airport checkpoint. Conclusion XRAY Screener successfully predicted on-job performance for professional aviation security officers. While questions remain about the underlying cognitive mechanisms, this quick assessment was found to significantly predict on-job success for a task that relies on visual search performance. Application It may be possible to quickly assess an individual's visual search competency, which could help organizations select new hires and assess their current workforce.

Getting satisfied with "satisfaction of search": How to measure errors during multiple-target visual search

Visual search studies are common in cognitive psychology, and the results generally focus upon accuracy, response times, or both. Most research has focused upon search scenarios where no more than 1 target will be present for any single trial. However, if multiple targets can be present on a single trial, it introduces an additional source of error because the found target can interfere with subsequent search performance. These errors have been studied thoroughly in radiology for decades, although their emphasis in cognitive psychology studies has been more recent. One particular issue with multiple-target search is that these subsequent search errors (i.e., specific errors which occur following a found target) are measured differently by different studies. There is currently no guidance as to which measurement method is best or what impact different measurement methods could have upon various results and conclusions. The current investigation provides two efforts to address these issues. First, the existing literature is reviewed to clarify the appropriate scenarios where subsequent search errors could be observed. Second, several different measurement methods are used with several existing datasets to contrast and compare how each method would have affected the results and conclusions of those studies. The evidence is then used to provide appropriate guidelines for measuring multiple-target search errors in future studies.

Visual Search: You Are Who You Are (+ A Learning Curve)

Not everyone is equally well suited for every endeavor-individuals differ in their strengths and weaknesses, which makes some people better at performing some tasks than others. As such, it might be possible to predict individuals' peak competence (i.e., ultimate level of success) on a given task based on their early performance in that task. The current study leveraged "big data" from the mobile game, Airport Scanner (Kedlin Company), to assess the possibility of predicting individuals' ultimate visual search competency using the minimum possible unit of data: response time on a single visual search trial. Those who started out poorly were likely to stay relatively poor and those who started out strong were likely to remain top performers. This effect was apparent at the level of a single trial (in fact, the first trial), making it possible to use raw response time to predict later levels of success.

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.