Search

Abstract Irrelevant salient distractors can trigger early quitting in visual search, causing observers to miss targets they might otherwise find. Here, we asked whether task-relevant salient cues can produce a similar early quitting effect on the subset of trials where those cues fail to highlight the target. We presented participants with a difficult visual search task and used two cueing conditions. In the high-predictive condition, a salient cue in the form of a red circle highlighted the target most of the time a target was present. In the low-predictive condition, the cue was far less accurate and did not reliably predict the target (i.e., the cue was often a false positive). These were contrasted against a control condition in which no cues were presented. In the high-predictive condition, we found clear evidence of early quitting on trials where the cue was a false positive, as evidenced by both increased miss errors and shorter response times on target absent trials. No such effects were observed with low-predictive cues. Together, these results suggest that salient cues which are false positives can trigger early quitting, though perhaps only when the cues have a high-predictive value. These results have implications for real-world searches, such as medical image screening, where salient cues (referred to as computer-aided detection or CAD) may be used to highlight potentially relevant areas of images but are sometimes inaccurate.

Retrospectively obvious events are frequently missed when attention is engaged in another task-a phenomenon known as inattentional blindness. Although the task characteristics that predict inattentional blindness rates are relatively well understood, the observer characteristics that predict inattentional blindness rates are largely unknown. Previously, expert radiologists showed a surprising rate of inattentional blindness to a gorilla photoshopped into a CT scan during lung-cancer screening. However, inattentional blindness rates were higher for a group of naïve observers performing the same task, suggesting that perceptual expertise may provide protection against inattentional blindness. Here, we tested whether expertise in radiology predicts inattentional blindness rates for unexpected abnormalities that were clinically relevant. Fifty radiologists evaluated CT scans for lung cancer. The final case contained a large (9.1 cm) breast mass and lymphadenopathy. When their attention was focused on searching for lung nodules, 66% of radiologists did not detect breast cancer and 30% did not detect lymphadenopathy. In contrast, only 3% and 10% of radiologists (N = 30), respectively, missed these abnormalities in a follow-up study when searching for a broader range of abnormalities. Neither experience, primary task performance, nor search behavior predicted which radiologists missed the unexpected abnormalities. These findings suggest perceptual expertise does not protect against inattentional blindness, even for unexpected stimuli that are within the domain of expertise.

Expert radiologists can quickly extract a basic gist understanding of a medical image following less than a second exposure, leading to above-chance diagnostic classification of images. Most of this work has focused on radiology tasks (such as screening mammography), and it is currently unclear whether this pattern of results and the nature of visual expertise underlying this ability are applicable to pathology, another medical imaging domain demanding visual diagnostic interpretation. To further characterize the detection, localization, and diagnosis of medical images, this study examined eye movements and diagnostic decision-making when pathologists were briefly exposed to digital whole slide images of melanocytic skin biopsies. Twelve resident (N = 5), fellow (N = 5), and attending pathologists (N = 2) with experience interpreting dermatopathology briefly viewed 48 cases presented for 500 ms each, and we tracked their eye movements towards histological abnormalities, their ability to classify images as containing or not containing invasive melanoma, and their ability to localize critical image regions. Results demonstrated rapid shifts of the eyes towards critical abnormalities during image viewing, high diagnostic sensitivity and specificity, and a surprisingly accurate ability to localize critical diagnostic image regions. Furthermore, when pathologists fixated critical regions with their eyes, they were subsequently much more likely to successfully localize that region on an outline of the image. Results are discussed relative to models of medical image interpretation and innovative methods for monitoring and assessing expertise development during medical education and training.

Inspecting digital imaging for primary diagnosis introduces perceptual and cognitive demands for physicians tasked with interpreting visual medical information and arriving at appropriate diagnoses and treatment decisions. The process of medical interpretation and diagnosis involves a complex interplay between visual perception and multiple cognitive processes, including memory retrieval, problem-solving, and decision-making. Eye-tracking technologies are becoming increasingly available in the consumer and research markets and provide novel opportunities to learn more about the interpretive process, including differences between novices and experts, how heuristics and biases shape visual perception and decision-making, and the mechanisms underlying misinterpretation and misdiagnosis. The present review provides an overview of eye-tracking technology, the perceptual and cognitive processes involved in medical interpretation, how eye tracking has been employed to understand medical interpretation and promote medical education and training, and some of the promises and challenges for future applications of this technology.

Abstract Prior research has shown that interruptions lead to a variety of performance costs. However, these costs are heterogenous and poorly understood. Under some circumstances, interruptions lead to large decreases in accuracy on the primary task, whereas in others task duration increases, but task accuracy is unaffected. Presently, the underlying cause of these costs is unclear. The Memory for Goals model suggests that interruptions interfere with the ability to represent the current goal of the primary task. Here, we test the idea that working memory (WM) may play a critical role in representing the current goal and thus may underlie the observed costs associated with interruption. In two experiments, we utilized laboratory-based visual search tasks, which differed in their WM demands, in order to assess how this difference influenced the observed interruption costs. Interruptions led to more severe performance costs when the target of the search changed on each trial. When the search target was consistent across trials, the cost of interruption was greatly reduced. This suggests that the WM demands associated with the primary task play an important role in determining the performance costs of interruption. Our findings suggest that it is important for research to consider the cognitive processes a task engages in order to predict the nature of the adverse effects of interruption in applied settings such as radiology.

Abstract Interpretation of volumetric medical images represents a rapidly growing proportion of the workload in radiology. However, relatively little is known about the strategies that best guide search behavior when looking for abnormalities in volumetric images. Although there is extensive literature on two-dimensional medical image perception, it is an open question whether the conclusions drawn from these images can be generalized to volumetric images. Importantly, volumetric images have distinct characteristics (e.g., scrolling through depth, smooth-pursuit eye-movements, motion onset cues, etc.) that should be considered in future research. In this manuscript, we will review the literature on medical image perception and discuss relevant findings from basic science that can be used to generate predictions about expertise in volumetric image interpretation. By better understanding search through volumetric images, we may be able to identify common sources of error, characterize the optimal strategies for searching through depth, or develop new training and assessment techniques for radiology residents.

Abstract Inspecting digital imaging for primary diagnosis introduces perceptual and cognitive demands for physicians tasked with interpreting visual medical information and arriving at appropriate diagnoses and treatment decisions. The process of medical interpretation and diagnosis involves a complex interplay between visual perception and multiple cognitive processes, including memory retrieval, problem-solving, and decision-making. Eye-tracking technologies are becoming increasingly available in the consumer and research markets and provide novel opportunities to learn more about the interpretive process, including differences between novices and experts, how heuristics and biases shape visual perception and decision-making, and the mechanisms underlying misinterpretation and misdiagnosis. The present review provides an overview of eye-tracking technology, the perceptual and cognitive processes involved in medical interpretation, how eye tracking has been employed to understand medical interpretation and promote medical education and training, and some of the promises and challenges for future applications of this technology.

Abstract Searching for targets in the visual world, or visual search, is something we all do every day. We frequently make ‘false-negative’ errors, wherein we erroneously conclude a target was absent when one was, in fact, present. These sorts of errors can have tremendous costs, as when signs of cancers are missed in diagnostic radiology. Prior research has characterized the cause of many of these errors as being due to failure to completely search the area where targets may be present; indeed, roughly one-third of chest nodules missed in lung cancer screening are never fixated (Drew, Võ, Olwal, Jacobson, Seltzer and Wolfe, Journal of Vision 13:3, 2013). This suggests that observers do not have a good representation of what areas have and have not been searched prior to declaring an area target free. Therefore, in six experiments, we sought to examine the utility of reducing the uncertainty with respect to what areas had been examined via online eye-tracking feedback. We hypothesized that providing information about what areas had or had not been examined would lead to lower rates of false negatives or more efficient search, namely faster response times with no cost on target detection accuracy. Neither of these predictions held true. Over six experiments, online eye-tracking feedback did not yield any reliable performance benefits.

Recent evidence has suggested that visual working memory (VWM) plays an important role in representing the target prior to initiating a visual search. The more familiar we are with the search target, the more refined the representation of the target (or “target template”) becomes. This sharpening of the target template is thought to underlie the reduced response time (RT) and increased accuracy associated with repeatedly searching for the same target. Perhaps target representations transition from limited-capacity VWM to Long-Term Memory (LTM) as targets repeat. In prior work, amplitude of an event-related potential (ERP) component associated with VWM representation decreased with target repetition, broadly supporting this notion. However, previous research has focused on artificial stimuli (Landolt Cs) that are far removed from search targets in the real world. The current study extends this work by directly comparing target representations for artificial stimuli and common object images. We found VWM representation follows the same pattern for real and artificial stimuli. However, the initial selection of the real world objects follows a much different pattern than more typical artificial stimuli. Further, the morphology of nonlateralized waveforms was substantially different for the two stimulus categories. This suggests that the two types of stimuli were processed in fundamentally different ways. We conclude that object type strongly influences how we deploy attentional and mnemonic resources prior to search. Early attentional selection of familiar objects may facilitate additional LTM processes that lead to behavioral benefits not seen with more simplistic stimuli.