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

When engaged in a visual search for two targets, participants are slower and less accurate in their responses, relative to their performance when searching for singular targets. Previous work on this “dual-target cost” has primarily focused on the breakdown of attention guidance when looking for two items. Here, we investigated how object identification processes are affected by dual-target search. Our goal was to chart the speed at which distractors could be rejected, in order to assess whether dual-target search impairs object identification. To do so, we examined the capacity coefficient, which measures the speed at which decisions can be made, and provides a baseline of parallel performance against which to compare. We found that participants could search at or above this baseline, suggesting that dual-target search does not impair object identification abilities. We also found substantial differences in performance when participants were asked to search for simple versus complex images. Somewhat paradoxically, participants were able to reject complex images more rapidly than simple images. We suggest that this reflects the greater number of features that can be used to identify complex images, a finding that has important consequences for understanding object identification in visual search more generally.

During visual search, people are distracted by objects that visually resemble search targets; search is impaired when targets and distractors share overlapping features. In this study, we examined whether a nonvisual form of similarity, overlapping object names, can also affect search performance. In three experiments, people searched for images of real-world objects (e.g., a beetle) among items whose names either all shared the same phonological onset (/bi/), or were phonologically varied. Participants either searched for one or three potential targets per trial, with search targets designated either visually or verbally. We examined standard visual search (Experiments 1 and 3) and a self-paced serial search task wherein participants manually rejected each distractor (Experiment 2). We hypothesized that people would maintain visual templates when searching for single targets, but would rely more on object names when searching for multiple items and when targets were verbally cued. This reliance on target names would make performance susceptible to interference from similar-sounding distractors. Experiments 1 and 2 showed the predicted interference effect in conditions with high memory load and verbal cues. In Experiment 3, eye-movement results showed that phonological interference resulted from small increases in dwell time to all distractors. The results suggest that distractor names are implicitly activated during search, slowing attention disengagement when targets and distractors share similar names.

Recent research has suggested that bilinguals show advantages over monolinguals in visual search tasks, although these findings have been derived from global behavioral measures of accuracy and response times. In the present study we sought to explore the bilingual advantage by using more sensitive eyetracking techniques across three visual search experiments. These spatially and temporally fine-grained measures allowed us to carefully investigate any nuanced attentional differences between bilinguals and monolinguals. Bilingual and monolingual participants completed visual search tasks that varied in difficulty. The experiments required participants to make careful discriminations in order to detect target Landolt Cs among similar distractors. In Experiment 1, participants performed both feature and conjunction search. In Experiments 2 and 3, participants performed visual search while making different types of speeded discriminations, after either locating the target or mentally updating a constantly changing target. The results across all experiments revealed that bilinguals and monolinguals were equally efficient at guiding attention and generating responses. These findings suggest that the bilingual advantage does not reflect a general benefit in attentional guidance, but could reflect more efficient guidance only under specific task demands.

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.