Serial vs. parallel models of attention in visual search: accounting for benchmark RT-distributions

ATLAS: Mapping ATtention's Location And Size to probe five modes of serial and parallel search

Conventional visual search tasks do not address attention directly and their core manipulation of 'set size' - the number of displayed items - introduces stimulus confounds that hinder interpretation. However, alternative approaches have not been widely adopted, perhaps reflecting their complexity, assumptions, or indirect attention-sampling. Here, a new procedure, the ATtention Location And Size ('ATLAS') task used probe displays to track attention's location, breadth, and guidance during search. Though most probe displays comprised six items, participants reported only the single item they judged themselves to have perceived most clearly - indexing the attention 'peak'. By sampling peaks across variable 'choice sets', the size and position of the attention window during search was profiled. These indices appeared to distinguish narrow- from broad attention, signalled attention to pairs of items where it arose and tracked evolving attention-guidance over time. ATLAS is designed to discriminate five key search modes: serial-unguided, sequential-guided, unguided attention to 'clumps' with local guidance, and broad parallel-attention with or without guidance. This initial investigation used only an example set of highly regular stimuli, but its broader potential should be investigated.

Contextual facilitation: Separable roles of contextual guidance and context suppression in visual search

Visual search is facilitated when targets are repeatedly encountered at a fixed position relative to an invariant distractor layout, compared to random distractor arrangements. However, standard investigations of this contextual-facilitation effect employ fixed distractor layouts that predict a constant target location, which does not always reflect real-world situations where the target location may vary relative to an invariant distractor arrangement. To explore the mechanisms involved in contextual learning, we employed a training-test procedure, introducing not only the standard full-repeated displays with fixed target-distractor locations but also distractor-repeated displays in which the distractor arrangement remained unchanged but the target locations varied. During the training phase, participants encountered three types of display: full-repeated, distractor-repeated, and random arrangements. The results revealed full-repeated displays to engender larger performance gains than distractor-repeated displays, relative to the random-display baseline. In the test phase, the gains were substantially reduced when full-repeated displays changed into distractor-repeated displays, while the transition from distractor-repeated to full-repeated displays failed to yield additional gains. We take this pattern to indicate that contextual learning can improve performance with both predictive and non-predictive (repeated) contexts, employing distinct mechanisms: contextual guidance and context suppression, respectively. We consider how these mechanisms might be implemented (neuro-)computationally.

Bayesian multi-level modelling for predicting single and double feature visual search

Performance in visual search tasks is frequently summarised by "search slopes" - the additional cost in reaction time for each additional distractor. While search tasks with a shallow search slopes are termed efficient (pop-out, parallel, feature), there is no clear dichotomy between efficient and inefficient (serial, conjunction) search. Indeed, a range of search slopes are observed in empirical data. The Target Contrast Signal (TCS) Theory is a rare example of quantitative model that attempts to predict search slopes for efficient visual search. One study using the TCS framework has shown that the search slope in a double-feature search (where the target differs in both colour and shape from the distractors) can be estimated from the slopes of the associated single-feature searches. This estimation is done using a contrast combination model, and a collinear contrast integration model was shown to outperform other options. In our work, we extend TCS to a Bayesian multi-level framework. We investigate modelling using normal and shifted-lognormal distributions, and show that the latter allows for a better fit to previously published data. We run a new fully within-subjects experiment to attempt to replicate the key original findings, and show that overall, TCS does a good job of predicting the data. However, we do not replicate the finding that the collinear combination model outperforms the other contrast combination models, instead finding that it may be difficult to conclusively distinguish between them.

Contextual cueing of visual search reflects the acquisition of an optimal, one-for-all oculomotor scanning strategy

Visual search improves when a target is encountered repeatedly at a fixed location within a stable distractor arrangement (spatial context), compared to non-repeated contexts. The standard account attributes this contextual-cueing effect to the acquisition of display-specific long-term memories, which, when activated by the current display, cue attention to the target location. Here we present an alternative, procedural-optimization account, according to which contextual facilitation arises from the acquisition of generic oculomotor scanning strategies, optimized with respect to the entire set of displays, with frequently searched displays accruing greater weight in the optimization process. To decide between these alternatives, we examined measures of the similarity, across time-on-task, of the spatio-temporal sequences of fixations through repeated and non-repeated displays. We found scanpath similarity to increase generally with learning, but more for repeated versus non-repeated displays. This pattern contradicts display-specific guidance, but supports one-for-all scanpath optimization.

Choice reaction time in pigeons fails to increase as predicted by Hick's law

Being able to correctly identify a target when presented with multiple possible alternatives, or increasing uncertainty, is highly beneficial in a wide variety of situations. This has been intensely investigated with human participants and results consistently demonstrated that participant reaction time (RT) increases linearly with the number of response alternatives, described as Hick's Law. Yet, the strength of this relationship is impacted by a variety of parameters, including stimulus-response compatibility, stimulus intensity, and practice. Different theories attempt to explain why these parameters affect the time to detect the target, but thus far these theories almost exclusively rely on human and nonhuman primate research. Therefore, it is unclear if these theories are universal or unique to primates, due to the scarcity of other animal models. A previous investigation showed that pigeon RT will increase in accordance with Hick's Law though not as steeply as human RT, potentially due to differences in the procedure used on pigeons. To better understand pigeon RT under uncertainty and facilitate cross species comparisons, these experiments used a procedure that was more similar to what has been given to humans. Surprisingly, pigeon RT did not follow Hick's Law as predicted. In Experiment 1, subjects showed an 'anti-Hick's' effect due to an artefact of stimulus location on the monitor. Subsequent experiments controlled for location, still RT did not increase with the number of choices as predicted by Hick's Law. Procedural changes that may have been responsible for this difference and the role of stimulus-response compatibility are discussed.

Could simplified stimuli change how the brain performs visual search tasks? A deep neural network study

Visual search is a complex behavior influenced by many factors. To control for these factors, many studies use highly simplified stimuli. However, the statistics of these stimuli are very different from the statistics of the natural images that the human visual system is optimized by evolution and experience to perceive. Could this difference change search behavior? If so, simplified stimuli may contribute to effects typically attributed to cognitive processes, such as selective attention. Here we use deep neural networks to test how optimizing models for the statistics of one distribution of images constrains performance on a task using images from a different distribution. We train four deep neural network architectures on one of three source datasets-natural images, faces, and x-ray images-and then adapt them to a visual search task using simplified stimuli. This adaptation produces models that exhibit performance limitations similar to humans, whereas models trained on the search task alone exhibit no such limitations. However, we also find that deep neural networks trained to classify natural images exhibit similar limitations when adapted to a search task that uses a different set of natural images. Therefore, the distribution of data alone cannot explain this effect. We discuss how future work might integrate an optimization-based approach into existing models of visual search behavior.

Dynamics of attentional and oculomotor orienting in visual foraging tasks

A vast amount of research has been carried out to understand how humans visually search for targets in their environment. However, this research has typically involved search for one unique target among several distractors. Although this line of research has yielded important insights into the basic characteristics of how humans explore their visual environment, this may not be a very realistic model for everyday visual orientation. Recently, researchers have used multi-target displays to assess orienting in the visual field. Eye movements in such tasks are, however, less well understood. Here, we investigated oculomotor dynamics during four visual foraging tasks differing in target crypticity (feature-based foraging vs. conjunction-based foraging) and the effector type being used for target selection (mouse foraging vs. gaze foraging). Our results show that both target crypticity and effector type affect foraging strategies. These changes are reflected in oculomotor dynamics, feature foraging being associated with focal exploration (long fixations and short-amplitude saccades), and conjunction foraging with ambient exploration (short fixations and high-amplitude saccades). These results provide important new information for existing accounts of visual attention and oculomotor control and emphasise the usefulness of foraging tasks for a better understanding of how humans orient in the visual environment.

L-DOPA administration shifts the stability-flexibility balance towards attentional capture by distractors during a visual search task

RATIONALE

The cognitive control dilemma describes the necessity to balance two antagonistic modes of attention: stability and flexibility. Stability refers to goal-directed thought, feeling, or action and flexibility refers to the complementary ability to adapt to an ever-changing environment. Their balance is thought to be maintained by neurotransmitters such as dopamine, most likely in a U-shaped rather than linear manner. However, in humans, studies on the stability-flexibility balance using a dopaminergic agent and/or measurement of brain dopamine are scarce.

OBJECTIVE

The study aimed to investigate the causal involvement of dopamine in the stability-flexibility balance and the nature of this relationship in humans.

METHODS

Distractibility was assessed as the difference in reaction time (RT) between distractor and non-distractor trials in a visual search task. In a randomized, placebo-controlled, double-blind, crossover study, 65 healthy participants performed the task under placebo and a dopamine precursor (L-DOPA). Using ¹⁸F-DOPA-PET, dopamine availability in the striatum was examined at baseline to investigate its relationship to the RT distractor effect and to the L-DOPA-induced change of the RT distractor effect.

RESULTS

There was a pronounced RT distractor effect in the placebo session that increased under L-DOPA. Neither the RT distractor effect in the placebo session nor the magnitude of its L-DOPA-induced increase were related to baseline striatal dopamine.

CONCLUSIONS

L-DOPA administration shifted the stability-flexibility balance towards attentional capture by distractors, suggesting causal involvement of dopamine. This finding is consistent with current theories of prefrontal cortex dopamine function. Current data can neither confirm nor falsify the inverted U-shaped function hypothesis with regard to cognitive control.

Visual search in virtual 3D space: the relation of multiple targets and distractors

Visual search and attentional alignment in 3D space are potentially modulated by information in unattended depth planes. The number of relevant and irrelevant items as well as their spatial relations may be regarded as factors which contribute to such effects. On a behavioral level, it might be different whether multiple distractors are presented in front of or behind target items. However, several studies revealed that attention cannot be restricted to a single depth plane. To further investigate this issue, two experiments were conducted. In the first experiment, participants searched for (multiple) targets in one depth plane, while non-target items (distractors) were simultaneously presented in this or another depth plane. In the second experiment, an additional spatial cue was presented with different validities to highlight the target position. Search durations were generally shorter when the search array contained two additional targets and were markedly longer when three distractors were displayed. The latter effect was most pronounced when a single target and three distractors coincided in the same depth plane and this effect persisted even when the target position was validly cued. The study reveals that the depth relation of target and distractor stimuli was more important than the absolute distance between these objects. Furthermore, the present findings suggest that within an attended depth plane, irrelevant information elicits strong interference. In sum, this study provides further evidence that allocation of attention is a flexible process which may be modulated by a variety of perceptual and cognitive factors.

Guided Search 6.0: An updated model of visual search

This paper describes Guided Search 6.0 (GS6), a revised model of visual search. When we encounter a scene, we can see something everywhere. However, we cannot recognize more than a few items at a time. Attention is used to select items so that their features can be "bound" into recognizable objects. Attention is "guided" so that items can be processed in an intelligent order. In GS6, this guidance comes from five sources of preattentive information: (1) top-down and (2) bottom-up feature guidance, (3) prior history (e.g., priming), (4) reward, and (5) scene syntax and semantics. These sources are combined into a spatial "priority map," a dynamic attentional landscape that evolves over the course of search. Selective attention is guided to the most active location in the priority map approximately 20 times per second. Guidance will not be uniform across the visual field. It will favor items near the point of fixation. Three types of functional visual field (FVFs) describe the nature of these foveal biases. There is a resolution FVF, an FVF governing exploratory eye movements, and an FVF governing covert deployments of attention. To be identified as targets or rejected as distractors, items must be compared to target templates held in memory. The binding and recognition of an attended object is modeled as a diffusion process taking > 150 ms/item. Since selection occurs more frequently than that, it follows that multiple items are undergoing recognition at the same time, though asynchronously, making GS6 a hybrid of serial and parallel processes. In GS6, if a target is not found, search terminates when an accumulating quitting signal reaches a threshold. Setting of that threshold is adaptive, allowing feedback about performance to shape subsequent searches. Simulation shows that the combination of asynchronous diffusion and a quitting signal can produce the basic patterns of response time and error data from a range of search experiments.

How do we measure attention? Using factor analysis to establish construct validity of neuropsychological tests

We investigated whether standardized neuropsychological tests and experimental cognitive paradigms measure the same cognitive faculties. Specifically, do neuropsychological tests commonly used to assess attention measure the same construct as attention paradigms used in cognitive psychology and neuroscience? We built on the “general attention factor”, comprising several widely used experimental paradigms (Huang et al., 2012). Participants (n = 636) completed an on-line battery (TestMyBrain.org) of six experimental tests [Multiple Object Tracking, Flanker Interference, Visual Working Memory, Approximate Number Sense, Spatial Configuration Visual Search, and Gradual Onset Continuous Performance Task (Grad CPT)] and eight neuropsychological tests [Trail Making Test versions A & B (TMT-A, TMT-B), Digit Symbol Coding, Forward and Backward Digit Span, Letter Cancellation, Spatial Span, and Arithmetic]. Exploratory factor analysis in a subset of 357 participants identified a five-factor structure: (1) attentional capacity (Multiple Object Tracking, Visual Working Memory, Digit Symbol Coding, Spatial Span), (2) search (Visual Search, TMT-A, TMT-B, Letter Cancellation); (3) Digit Span; (4) Arithmetic; and (5) Sustained Attention (GradCPT). Confirmatory analysis in 279 held-out participants showed that this model fit better than competing models. A hierarchical model where a general cognitive factor was imposed above the five specific factors fit as well as the model without the general factor. We conclude that Digit Span and Arithmetic tests should not be classified as attention tests. Digit Symbol Coding and Spatial Span tap attentional capacity, while TMT-A, TMT-B, and Letter Cancellation tap search (or attention-shifting) ability. These five tests can be classified as attention tests.

Serial, self-terminating search can be distinguished from others: Evidence from multi-target search data

How do people find a target among multiple stimuli? The process of searching for a target among distractors has been a fundamental issue in human perception and cognition, evoking raging debates. Some researchers argued that search should be carried out by serially allocating focal attention to each item until the target is found. Others claimed that multiple stimuli, sharing a finite amount of processing resource, could be processed in parallel. This strict serial/parallel dichotomy in visual search has been challenged and many recent theories suggest that visual search tasks involve both serial and parallel processes. However, some search tasks should primarily depend on serial processing, while others would rely upon parallel processing to a greater extent. Here, by simple innovation of an experimental paradigm, we were able to identify a specific behavioral pattern associated with serial, self-terminating search and clarified which tasks depend on serial processing to a greater extent than others. Using this paradigm, we provide insights regarding under which condition the search becomes more serial or parallel. We also discuss several recent models of visual search that are capable of accommodating these findings and reconciling the extant controversy.

Massive Effects of Saliency on Information Processing in Visual Working Memory

Limitations in the ability to temporarily represent information in visual working memory (VWM) are crucial for visual cognition. Whether VWM processing is dependent on an object’s saliency (i.e., how much it stands out) has been neglected in VWM research. Therefore, we developed a novel VWM task that allows direct control over saliency. In three experiments with this task (on 10, 31, and 60 adults, respectively), we consistently found that VWM performance is strongly and parametrically influenced by saliency and that both an object’s relative saliency (compared with concurrently presented objects) and absolute saliency influence VWM processing. We also demonstrated that this effect is indeed due to bottom-up saliency rather than differential fit between each object and the top-down attentional template. A simple computational model assuming that VWM performance is determined by the weighted sum of absolute and relative saliency accounts well for the observed data patterns.

Assessing visual search performance using a novel dynamic naturalistic scene

Daily activities require the constant searching and tracking of visual targets in dynamic and complex scenes. Classic work assessing visual search performance has been dominated by the use of simple geometric shapes, patterns, and static backgrounds. Recently, there has been a shift toward investigating visual search in more naturalistic dynamic scenes using virtual reality (VR)-based paradigms. In this direction, we have developed a first-person perspective VR environment combined with eye tracking for the capture of a variety of objective measures. Participants were instructed to search for a preselected human target walking in a crowded hallway setting. Performance was quantified based on saccade and smooth pursuit ocular motor behavior. To assess the effect of task difficulty, we manipulated factors of the visual scene, including crowd density (i.e., number of surrounding distractors) and the presence of environmental clutter. In general, results showed a pattern of worsening performance with increasing crowd density. In contrast, the presence of visual clutter had no effect. These results demonstrate how visual search performance can be investigated using VR-based naturalistic dynamic scenes and with high behavioral relevance. This engaging platform may also have utility in assessing visual search in a variety of clinical populations of interest.

Studying the dynamics of visual search behavior using RT hazard and micro-level speed-accuracy tradeoff functions: A role for recurrent object recognition and cognitive control processes

Thanks to the work of Anne Treisman and many others, the visual search paradigm has become one of the most popular paradigms in the study of visual attention. However, statistics like mean correct response time (RT) and percent error do not usually suffice to decide between the different search models that have been developed. Recently, to move beyond mean performance measures in visual search, RT histograms have been plotted, theoretical waiting time distributions have been fitted, and whole RT and error distributions have been simulated. Here we promote and illustrate the general application of discrete-time hazard analysis to response times, and of micro-level speed-accuracy tradeoff analysis to timed response accuracies. An exploratory analysis of published benchmark search data from feature, conjunction, and spatial configuration search tasks reveals new features of visual search behavior, such as a relatively flat hazard function in the right tail of the RT distributions for all tasks, a clear effect of set size on the shape of the RT distribution for the feature search task, and individual differences in the presence of a systematic pattern of early errors. Our findings suggest that the temporal dynamics of visual search behavior results from a decision process that is temporally modulated by concurrently active recurrent object recognition, learning, and cognitive control processes, next to attentional selection processes.

Visual Search: How Do We Find What We Are Looking For?

In visual search tasks, observers look for targets among distractors. In the lab, this often takes the form of multiple searches for a simple shape that may or may not be present among other items scattered at random on a computer screen (e.g., Find a red T among other letters that are either black or red.). In the real world, observers may search for multiple classes of target in complex scenes that occur only once (e.g., As I emerge from the subway, can I find lunch, my friend, and a street sign in the scene before me?). This article reviews work on how search is guided intelligently. I ask how serial and parallel processes collaborate in visual search, describe the distinction between search templates in working memory and target templates in long-term memory, and consider how searches are terminated.

A diffusion model analysis of target detection in near-threshold visual search

When searching for a target briefly presented among distractors how do people combine information across display locations to make a decision and how does the quality of the evidence entering the decision process vary with the type of items in the display? Research on accuracy in near-threshold visual search has had difficulty in distinguishing between models that make similar predictions about accuracy but make different assumptions about the underlying psychological processes. We used the diffusion model to analyse response times and accuracy data from four near-threshold search tasks which showed striking asymmetries between response-time distributions on target-present and target-absent trials. We found that performance was better explained by a model in which evidence was accumulated in parallel about each stimulus separately than one in which the evidence was pooled into a single decision process. We found that as contrast increased, the quality of the evidence entering the decision process about targets was markedly stronger than the evidence about nontargets. The overall pattern of evidence strength for stimuli on target-present and target-absent trials was consistent with a fixed-capacity memory system in which early visual processes assigned resources preferentially to targets over nontargets. The asymmetry was somewhat reduced in a letter-digit discrimination task that used heterogeneous targets and distractors, likely because heterogeneity reduces the efficiency of the preattentive filtering processes.

Motor control drives visual bodily judgements

The 'embodied cognition' framework proposes that our motor repertoire shapes visual perception and cognition. But recent studies showing normal visual body representation in individuals born without hands challenges the contribution of motor control on visual body representation. Here, we studied hand laterality judgements in three groups with fundamentally different visual and motor hand experiences: two-handed controls, one-handers born without a hand (congenital one-handers) and one-handers with an acquired amputation (amputees). Congenital one-handers, lacking both motor and first-person visual information of their missing hand, diverged in their performance from the other groups, exhibiting more errors for their intact hand and slower reaction-times for challenging hand postures. Amputees, who have lingering non-visual motor control of their missing (phantom) hand, performed the task similarly to controls. Amputees' reaction-times for visual laterality judgements correlated positively with their phantom hand's motor control, such that deteriorated motor control associated with slower visual laterality judgements. Finally, we have implemented a computational simulation to describe how a mechanism that utilises a single hand representation in congenital one-handers as opposed to two in controls, could replicate our empirical results. Together, our findings demonstrate that motor control is a driver in making visual bodily judgments.

Search for Face Identity or Expression: Set Size Effects in Developmental Prosopagnosia

The set size effect during visual search indexes the effects of processing load and thus the efficiency of perceptual mechanisms. Our goal was to investigate whether individuals with developmental prosopagnosia show increased set size effects when searching faces for face identity and how this compares to search for face expression. We tested 29 healthy individuals and 13 individuals with developmental prosopagnosia. Participants were shown sets of three to seven faces to judge whether the identities or expressions of the faces were the same across all stimuli or if one differed. The set size effect was the slope of the linear regression between the number of faces in the array and the response time. Accuracy was similar in both controls and prosopagnosic participants. Developmental prosopagnosic participants displayed increased set size effects in face identity search but not in expression search. Single-participant analyses reveal that 11 developmental prosopagnosic participants showed a putative classical dissociation, with impairments in identity but not expression search. Signal detection theory analysis showed that identity set size effects were highly reliable in discriminating prosopagnosic participants from controls. Finally, the set size ratios of same to different trials were consistent with the predictions of self-terminated serial search models for control participants and prosopagnosic participants engaged in expression search but deviated from those predictions for identity search by the prosopagnosic cohort. We conclude that the face set size effect reveals a highly prevalent and selective perceptual inefficiency for processing face identity in developmental prosopagnosia.

Selective Influence and Sequential Operations: A Research Strategy for Visual Search

We discuss the problem of elucidating mechanisms of visual search. We begin by considering the history, logic, and methods of relating behavioral or cognitive processes with neural processes. We then survey briefly the cognitive neurophysiology of visual search and essential aspects of the neural circuitry supporting this capacity. We introduce conceptually and empirically a powerful but underutilized experimental approach to dissect the cognitive processes supporting performance of a visual search task with factorial manipulations of singleton-distractor identifiability and stimulus-response cue discriminability. We show that systems factorial technology can distinguish processing architectures from the performance of macaque monkeys. This demonstration offers new opportunities to distinguish neural mechanisms through selective manipulation of visual encoding, search selection, rule encoding, and stimulus-response mapping.

Visual search for complex objects: Set-size effects for faces, words and cars

To compare visual processing for different object types, we developed visual search tests that generated accuracy and response time parameters, including an object set-size effect that indexes perceptual processing load. Our goal was to compare visual search for two expert object types, faces and visual words, as well as a less expert type, cars. We first asked if faces and words showed greater inversion effects in search. Second, we determined whether search with upright stimuli correlated with other perceptual indices. Last we assessed for correlations between tests within a single orientation, and between orientations for a single object type. Object set-size effects were smaller for faces and words than cars. All accuracy and temporal measures showed an inversion effect for faces and words, but not cars. Face-search accuracy measures correlated with accuracy on the Cambridge Face Memory Test and word-search temporal measures correlated with single-word reading times, but car search did not correlate with semantic car knowledge. There were cross-orientation correlations for all object types, as well as cross-object correlations in the inverted orientation, while in the upright orientation face search did not correlate with word or car search. We conclude that object search shows effects of expertise. Compared to cars, words and faces showed smaller object set-size effects, greater inversion effects, and their search results correlated with other indices of perceptual expertise. The correlation analyses provide preliminary evidence supporting contributions from common processes in the case of inverted stimuli, object-specific processes that operate in both orientations, and distinct processing for upright faces.

Biasing Allocations of Attention via Selective Weighting of Saliency Signals: Behavioral and Neuroimaging Evidence for the Dimension-Weighting Account

Objects that stand out from the environment tend to be of behavioral relevance, and the visual system is tuned to preferably process these salient objects by allocating focused attention. However, attention is not just passively (bottom-up) driven by stimulus features, but previous experiences and task goals exert strong biases toward attending or actively ignoring salient objects. The core and eponymous assumption of the dimension-weighting account (DWA) is that these top-down biases are not as flexible as one would like them to be; rather, they are subject to dimensional constraints. In particular, DWA assumes that people can often not search for objects that have a particular feature but only for objects that stand out from the environment (i.e., that are salient) in a particular feature dimension. We review behavioral and neuroimaging evidence for such dimensional constraints in three areas: search history, voluntary target enhancement, and distractor handling. The first two have been the focus of research on DWA since its inception and the latter the subject of our more recent research. Additionally, we discuss various challenges to the DWA and its relation to other prominent theories on top-down influences in visual search.

How did I miss that? Developing mixed hybrid visual search as a 'model system' for incidental finding errors in radiology

In a real world search, it can be important to keep ‘an eye out’ for items of interest that are not the primary subject of the search. For instance, you might look for the exit sign on the freeway, but you should also respond to the armadillo crossing the road. In medicine, these items are known as “incidental findings,” findings of possible clinical significance that were not the main object of search. These errors (e.g., missing a broken rib while looking for pneumonia) have medical consequences for the patient and potential legal consequences for the physician. Here we report three experiments intended to develop a ‘model system’ for incidental findings – a paradigm that could be used in the lab to develop strategies to reduce incidental finding errors in the clinic. All the experiments involve ‘hybrid’ visual search for any of several targets held in memory. In this ‘mixed hybrid search task,’ observers search for any of three specific targets (e.g., this rabbit, this truck, and this spoon) and three categorical targets (e.g., masks, furniture, and plants). The hypothesis is that the specific items are like the specific goals of a real world search and the categorical targets are like the less well-defined incidental findings that might be present and that should be reported. In all these experiments, varying target prevalence, number of targets, etc., the categorical targets are missed at a much higher rate than the specific targets. This paradigm shows promise as a model of the incidental finding problem.

An appeal against the item's death sentence: Accounting for diagnostic data patterns with an item-based model of visual search

We show that our item-based model, competitive guided search, accounts for the empirical patterns that Hulleman & Olivers (H&O) invoke against item-based models, and we highlight recently reported diagnostic data that challenge their approach. We advise against “forsaking the item” unless and until a full fixation-based model is shown to be superior to extant item-based models.

Parallel attentive processing and pre-attentive guidance

This commentary focuses on two related, open questions in Hulleman & Olivers' (H&O's) proposal: (1) the nature of the parallel attentive process that determines target presence within, and thus presumably the size of, the functional visual field, and (2) how the pre-attentive guidance mechanism must be conceived to also account for search performance in tasks that afford no reliable target-based guidance.

Five Factors that Guide Attention in Visual Search

How do we find what we are looking for? Fundamental limits on visual processing mean that even when the desired target is in our field of view, we often need to search, because it is impossible to recognize everything at once. Searching involves directing attention to objects that might be the target. This deployment of attention is not random. It is guided to the most promising items and locations by five factors discussed here: Bottom-up salience, top-down feature guidance, scene structure and meaning, the previous history of search over time scales from msec to years, and the relative value of the targets and distractors. Modern theories of search need to specify how all five factors combine to shape search behavior. An understanding of the rules of guidance can be used to improve the accuracy and efficiency of socially-important search tasks, from security screening to medical image perception.

Recollection is delayed under changed viewing conditions: A graded effect on the latency of the late posterior component

Object recognition is a central human ability. In everyday life, the conditions under which objects have to be recognized are usually not perfect. Often, viewing conditions change in between two encounters with an object; typical are changes in illumination or in the object-observer distance. With such changes, object recognition sometimes feels slightly delayed. We examined this phenomenon empirically by measuring the latency of the well-established electrophysiological correlate of recollection, the late posterior component (LPC), in an object-recognition task. Although the cognitive processes underlying successful recognition are well examined, thus far the consequences of changed viewing conditions on the timing of these processes have not been investigated. The ERP technique is well suited for investigating this question, because it allows differentiating between processes contributing to recognition times (in particular, recollection from familiarity as indexed by the FN400 component) and measuring their time course with high temporal precision. In the present study, participants' task was to differentiate previously studied (old) objects from a set of new objects. Viewing conditions for old objects changed slightly, changed strongly, or remained identical between learning and test. We found that the latency of the LPC in response to an old object was delayed whenever viewing conditions changed. Moreover, this delay in LPC latency scaled with the size of the change. These effects were absent for the FN400. This is the first examination of effects of changes in viewing conditions on the latency of recollection and the first dissociation of FN400 and LPC latencies.