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

Abstract

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

Safety in Numbers for walkers and bicyclists: exploring the mechanisms

“…Driving requires continual and rapid decision-making and makes significant cognitive demands of the motorist, who must detect, recognise, predict, and respond to a variety of stationary and moving objects, in a range of sizes, in a highly dynamic environment. Furthermore, drivers must not just select targets for their attention; they must continuously identify the most important target for their driving task 20. In short, driving demands a tremendous amount of visual and cognitive processing.…”

Modeling Lag‐2 Revisits to Understand Trade‐Offs in Mixed Control of Fixation Termination During Visual Search

“…Second, our results can also help to offer new insights into how participants fail to detect targets in visual search. It has been noted that targets are often missed as a consequence of failures of perceptual identification (Cain et al., ; Schwark et al., )—that is, even after fixating the target object, the target is still missed by participants (Engel, ; Godwin et al., ,a,b; Godwin et al., ; Gould & Cairn, ; Hooge & Erkelens, ; Hout, Walenchok, Goldinger, & Wolfe, ; Nodine & Kundel, ). These failures have important societal consequences, such as in radiographic image screening, where tumors can go undetected and missed by searchers.…”

“…The existence of perceptual identification errors has been used as evidence against strict direct‐control accounts, with such occurrences being regarded as a natural by‐product of the fact that fixations can be terminated by an indirect mechanism (e.g., an autonomous timer) that drives fixations to new locations irrespective of whether or not the processing of an object at a given fixation location has been completed. However, more recent studies (Godwin, Menneer, Riggs, Cave, & Donnelly, ; Godwin et al., ; Hout et al., ) have found that perceptual identification errors are more likely to occur when the target is presented on a small proportion of trials (5% of trials) compared with a higher proportion of trials (45%), perhaps because of priming from target repetition and/or expectations about the likelihood of a target being presented (Godwin et al., ,b). This finding suggests that failures to detect the target upon fixating it may reflect object identification failures rather than being a consequence of some indirect mechanism, as predicted by indirect‐control accounts.…”

“…Importantly, we wanted to test whether a global parameter was required to simulate the fixation behavior, and if so, what form this parameter takes. That is, if lag‐2 revisits are a form of trade‐off between the overall rate of search and the accuracy in target detection on the first fixation, then participants should be less likely to make lag‐2 revisits when the objects being fixated are more likely to be a target (Godwin et al., ,b; Hout et al., in press). If so, then this would provide evidence of a new, previously unknown global parameter (the value of which is affected by the probability of any fixated object being the target) influencing the push‐pull relationship between online cognitive processing and the drive to program and initiate new saccades in order to proceed with search.…”

The influence of experience upon information-sampling and decision-making behaviour during risk assessment in military personnel

“…Both information-sampling and decision-making are vital components in the detection of visual targets. When information-sampling fails to guide the eyes to targets, those targets are often missed (Chapman & Underwood, 1998;Godwin, Menneer, Riggs, Cave, & Donnelly, 2015;Kundel & Nodine, 1975;Nodine & Mello-Thoms, 2000). When the targets are examined, decision-making can also fail to detect the targets once fixed, causing the targets to again be missed (Cain, Adamo, & Mitroff, 2013;Godwin et al, 2015;Nodine & Kundel, 1987;Schwark, MacDonald, Sandry, & Dolgov, 2013).…”