Categorical search involves looking for objects based on category information from long-term memory. Previous research has shown that search efficiency in categorical search is influenced by target/distractor similarity and category variability (i.e., heterogeneity). However, the interaction between these factors and their impact on different subprocesses of search remains unclear. This study examined the effects of target/distractor similarity and category variability on processes of categorical search. Using multidimensional scaling, we manipulated target/distractor similarity and measured category variability for target categories that participants searched for. Eye-tracking data were collected to examine attentional guidance and target verification. The results demonstrated that the effect of category variability on response times (RTs) was dependent on the level of target/distractor similarity. Specifically, when distractors were highly similar to target categories, there was a negative relation between RTs and variability, with low variability categories producing longer RTs than higher variability categories. Surprisingly, this trend was only present in the eye-tracking measures of target verification but not attentional guidance. Our results suggest that searchers more effectively guide attention to low-variability categories compared to high-variability categories, regardless of the degree of similarity between targets and distractors. However, low category variability interferes with target match decisions when distractors are highly similar to the category, thus the advantage that low category variability provides to searchers is not equal across processes of search.

Categorical search has been heavily investigated over the past decade, mostly using natural categories that leave the underlying category mental representation unknown. The categorization literature offers several theoretical accounts of category mental representations. One prominent account is that separate learning systems account for classification: an explicit learning system that relies on easily verbalized rules and an implicit learning system that relies on an associatively learned (nonverbalizable) information integration strategy. The current study assessed the contributions of these separate category learning systems in the context of categorical search using simple stimuli. Participants learned to classify sinusoidal grating stimuli according to explicit or implicit categorization strategies, followed by a categorical search task using these same stimulus categories. Computational modeling determined which participants used the appropriate classification strategy during training and search, and eye movements collected during categorical search were assessed. We found that the trained categorization strategies overwhelmingly transferred to the verification (classification response) phase of search. Implicit category learning led to faster search response and shorter target dwell times relative to explicit category learning, consistent with the notion that explicit rule classification relies on a more deliberative response strategy. Participants who transferred the correct category learning strategy to the search guidance phase produced stronger search guidance (defined as the proportion of trials on which the target was the first item fixated) with evidence of greater guidance in implicit-strategy learners. This demonstrates that both implicit and explicit categorization systems contribute to categorical search and produce dissociable patterns of data.

The paper addresses the capabilities and limitations of extrafoveal processing during a categorical visual search. Previous research has established that a target could be identified from the very first or without any saccade, suggesting that extrafoveal perception is necessarily involved. However, the limits in complexity defining the processed information are still not clear. We performed four experiments with a gradual increase of stimuli complexity to determine the role of extrafoveal processing in searching for the categorically defined geometric shape. The series of experiments demonstrated a significant role of extrafoveal processing while searching for simple two-dimensional shapes and its gradual decrease in a condition with more complicated three-dimensional shapes. The factors of objects\' spatial orientation and distractor homogeneity significantly influenced both reaction time and the number of saccades required to identify a categorically defined target. An analysis of the individual p-value distributions revealed pronounced individual differences in using extrafoveal analysis and allowed examination of the performance of each particular participant. The condition with the forced prohibition of eye movements enabled us to investigate the efficacy of covert attention in the condition with complicated shapes. Our results indicate that both foveal and extrafoveal processing are simultaneously involved during a categorical search, and the specificity of their interaction is determined by the spatial orientation of objects, type of distractors, the prohibition to use overt attention, and individual characteristics of the participants.

The degree to which an item is rated as being a typical member of its category influences an observer\'s ability to find that item during word-cued search. However, there are conflicting accounts as to whether or not typicality affects attentional guidance to categorical items, or whether it affects some other aspect of the search process. In this study, we employed word-cued search and eye tracking to disentangle typicality effects on attentional guidance and target verification across differing category cue specificities (i.e., superordinate or basic-level cues), while also varying the degree of similarity between targets and non-targets. We found that typicality influenced attentional guidance when searchers were cued at the superordinate level (e.g., clothing). When cues were provided at the basic level (e.g., pants), typicality did not influence attentional guidance, and only affected target verification when there was featural similarity between targets and non-targets. When a searcher uses a target template comprising features cued at the basic level, therefore, target/non-target similarity produces interference that affects attentional guidance, but we did not find evidence that it also affects target verification.

Unlike in laboratory visual search tasks-wherein participants are typically presented with a pictorial representation of the item they are asked to seek out-in real-world searches, the observer rarely has veridical knowledge of the visual features that define their target. During categorical search, observers look for any instance of a categorically defined target (e.g., helping a family member look for their mobile phone). In these circumstances, people may not have information about noncritical features (e.g., the phone\'s color), and must instead create a broad mental representation using the features that define (or are typical of) the category of objects they are seeking out (e.g., modern phones are typically rectangular and thin). In the current investigation (Experiment 1), using a categorical visual search task, we add to the body of evidence suggesting that categorical templates are effective enough to conduct efficient visual searches. When color information was available (Experiment 1a), attentional guidance, attention restriction, and object identification were enhanced when participants looked for categories with consistent features (e.g., ambulances) relative to categories with more variable features (e.g., sedans). When color information was removed (Experiment 1b), attention benefits disappeared, but object recognition was still better for feature-consistent target categories. In Experiment 2, we empirically validated the relative homogeneity of our societally important vehicle stimuli. Taken together, our results are in line with a category-consistent view of categorical target templates (Yu, Maxfield, & Zelinsky in, Psychological Science, 2016. doi: 10.1177/0956797616640237 ), and suggest that when features of a category are consistent and predictable, searchers can create mental representations that allow for the efficient guidance and restriction of attention as well as swift object identification.

This article introduces a generative model of category representation that uses computer vision methods to extract category-consistent features (CCFs) directly from images of category exemplars. The model was trained on 4,800 images of common objects, and CCFs were obtained for 68 categories spanning subordinate, basic, and superordinate levels in a category hierarchy. When participants searched for these same categories, targets cued at the subordinate level were preferentially fixated, but fixated targets were verified faster when they followed a basic-level cue. The subordinate-level advantage in guidance is explained by the number of target-category CCFs, a measure of category specificity that decreases with movement up the category hierarchy. The basic-level advantage in verification is explained by multiplying the number of CCFs by sibling distance, a measure of category distinctiveness. With this model, the visual representations of real-world object categories, each learned from the vast numbers of image exemplars accumulated throughout everyday experience, can finally be studied.

Is it possible to infer a person\'s goal by decoding their fixations on objects? Two groups of participants categorically searched for either a teddy bear or butterfly among random category distractors, each rated as high, medium, or low in similarity to the target classes. Target-similar objects were preferentially fixated in both search tasks, demonstrating information about target category in looking behavior. Different participants then viewed the searchers\' scanpaths, superimposed over the target-absent displays, and attempted to decode the target category (bear/butterfly). Bear searchers were classified perfectly; butterfly searchers were classified at 77%. Bear and butterfly Support Vector Machine (SVM) classifiers were also used to decode the same preferentially fixated objects and found to yield highly comparable classification rates. We conclude that information about a person\'s search goal exists in fixation behavior, and that this information can be behaviorally decoded to reveal a search target-essentially reading a person\'s mind by analyzing their fixations.

Does the same basic-level advantage commonly observed in the categorization literature also hold for targets in a search task? We answered this question by first conducting a category verification task to define a set of categories showing a standard basic-level advantage, which we then used as stimuli in a search experiment. Participants were cued with a picture preview of the target or its category name at either superordinate, basic, or subordinate levels, then shown a target-present/absent search display. Although search guidance and target verification was best using pictorial cues, the effectiveness of the categorical cues depended on the hierarchical level. Search guidance was best for the specific subordinate level cues, while target verification showed a standard basic-level advantage. These findings demonstrate different hierarchical advantages for guidance and verification in categorical search. We interpret these results as evidence for a common target representation underlying categorical search guidance and verification.