Does precrastination explain why some observers are suboptimal in a visual search task?

How do we decide where to search for a target? Optimal search relies on first considering the relative informational value of different locations and then executing eye movements to the best options. However, many participants consistently move their eyes to locations that can be easily ascertained to neither contain the target nor provide new information about the target's location. Here, we asked whether this suboptimal search behaviour represents a specific example of a general tendency towards precrastination: starting sub-goals of a task before they are needed, and in so doing, spending longer time on doing the task than is necessary. To test this hypothesis, we asked 200 participants to do two tasks: retrieve two heavy buckets (one close and one far) and search for a line segment. Precrastination is defined as consistently picking up the closer bucket first, versus the more efficient strategy of picking up the farther bucket first. Search efficiency is the proportion of fixations directed to more cluttered regions of the search array. Based on the pilot data, we predicted an association of precrastination with inefficient search strategies. Personality inventories were also administered to identify stable characteristics associated with these strategies. In the final dataset, there was no clear association between search strategy and precrastination, nor did these correlate strongly with any of the personality measures collected. This article received in-principle acceptance (IPA) at Royal Society Open Science on 29 January 2020. The accepted Stage 1 version of the manuscript, not including results and discussion, may be found at https://osf.io/p2sjx. This preregistration was performed prior to data collection and analysis.

Variable search for orientation, uniformly optimal search for identity.

We compare eye movement strategies across a range of different stimulus sets to test the prediction that eye movements are guided by expected information gain. When searching for a simple target that has been defined based on orientation, interindividual variability is high, and a large proportion of eye movements are directed to locations where peripheral vision would have been sufficient to determine whether the target was present there or not. In contrast, when searching for a target defined based on identity, eye movements are similar across individuals and highly efficient, being directed almost exclusively to the locations where central vision is most needed. The results suggest that for most people, the way they search for a simple feature (orientation) is not directly representative of the way they search for objects based on their identity. More generally, the results highlight that because humans are adaptable, contradictory theories can be accurate descriptions of search in particular contexts and individuals. For a complete and accurate account of human search behavior to be achieved, the conditions that shift us from one mode of behavior to another need to be part of our models. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The role of framing, agency and uncertainty in a focus-divide dilemma.

How to prioritise multiple objectives is a common dilemma of daily life. A simple and effective decision rule is to focus resources when the tasks are difficult, and divide when tasks are easy. Nonetheless, in experimental paradigms of this dilemma, participants make highly variable and suboptimal strategic decisions when asked to allocate resources to two competing goals that vary in difficulty. We developed a new version in which participants had to choose where to park a fire truck between houses of varying distances apart. Unlike in the previous versions of the dilemma, participants approached the optimal strategy in this task. Three key differences between the fire truck version and previous versions of the task were investigated: (1) Framing (whether the objectives are familiar or abstract), by comparing a group who placed cartoon trucks between houses to a group performing the same task with abstract shapes; (2) Agency (how much of the task is under the participants' direct control), by comparing groups who controlled the movement of the truck to those who did not; (3) Uncertainty, by adding variability to the driving speed of the truck to make success or failure on a given trial more difficult to predict. Framing and agency did not influence strategic decisions. When adding variability to outcomes, however, decisions shifted away from optimal. The results suggest choices become more variable when the outcome is less certain, consistent with exploration of response alternatives triggered by an inability to predict success.

Correction: Foraging as sampling without replacement: A Bayesian statistical model for estimating biases in target selection.

[This corrects the article DOI: 10.1371/journal.pcbi.1009813.].

Six of one, half dozen of the other: Suboptimal prioritizing for equal and unequal alternatives.

It is possible to accomplish multiple goals when available resources are abundant, but when the tasks are difficult and resources are limited, it is better to focus on one task and complete it successfully than to divide your efforts and fail on both. Previous research has shown that people rarely apply this logic when faced with prioritizing dilemmas. The pairs of tasks in previous research had equal utility, which according to some models, can disrupt decision-making. We investigated whether the equivalence of two tasks contributes to suboptimal decisions about how to prioritize them. If so, removing or manipulating the arbitrary nature of the decision between options should facilitate optimal decisions about whether to focus effort on one goal or divide effort over two. Across all three experiments, however, participants did not appropriately adjust their decisions with task difficulty. The only condition in which participants adopted a strategy that approached optimal was when they had voluntarily placed more reward on one task over the other. For the task that was more rewarded, choices were modified more effectively with task difficulty. However, participants were more likely to choose to distribute rewards equally than unequally. The results demonstrate that situations involving choices between options with equal utility are not avoided and are even slightly preferred over unequal options, despite unequal options having larger potential gains and leading to more effective prioritizing strategies.

A Bayesian Statistical Model Is Able to Predict Target-by-Target Selection Behaviour in a Human Foraging Task.

Foraging refers to search involving multiple targets or multiple types of targets, and as a model task has a long history in animal behaviour and human cognition research. Foraging behaviour is usually operationalized using summary statistics, such as average distance covered during target collection (the path length) and the frequency of switching between target types. We recently introduced an alternative approach, which is to model each instance of target selection as random selection without replacement. Our model produces estimates of a set of foraging biases, such as a bias to select closer targets or targets of a particular category. Here we apply this model to predict individual target selection events. We add a new start position bias to the model, and generate foraging paths using the parameters estimated from individual participants' pre-existing data. The model predicts which target the participant will select next with a range of accuracy from 43% to 69% across participants (chance is 11%). The model therefore explains a substantial proportion of foraging behaviour in this paradigm. The situations where the model makes errors reveal useful information to guide future research on those aspects of foraging that we have not yet explained.

Visual search habits and the spatial structure of scenes.

Some spatial layouts may suit our visual search habits better than others. We compared eye movements during search across three spatial configurations. Participants searched for a line segment oriented 45∘ to the right. Variation in the orientation of distractor line segments determines the extent to which this target would be visible in peripheral vision: a target among homogeneous distractors is highly visible, while a target among heterogeneous distractors requires central vision. When the search array is split into homogeneous and heterogeneous left and right halves, a large proportion of fixations are "wasted" on the homogeneous half, leading to slower search times. We compared this pattern to two new configurations. In the first, the array was split into upper and lower halves. During a passive viewing baseline condition, we observed biases to look both at the top half and also at the hetergeneous region first. Both of these biases were weaker during active search, despite the fact that the heterogeneous bias would have led to improvements in efficiency if it had been retained. In the second experiment, patches of more or less heterogeneous line segments were scattered across the search space. This configuration allows for more natural, spatially distributed scanpaths. Participants were more efficient and less variable relative to the left/right configuration. The results are consistent with the idea that visual search is associated with a distributed sequence of fixations, guided only loosely by the potential visibility of the target in different regions of the scene.

Foraging as sampling without replacement: A Bayesian statistical model for estimating biases in target selection.

Foraging entails finding multiple targets sequentially. In humans and other animals, a key observation has been a tendency to forage in 'runs' of the same target type. This tendency is context-sensitive, and in humans, it is strongest when the targets are difficult to distinguish from the distractors. Many important questions have yet to be addressed about this and other tendencies in human foraging, and a key limitation is a lack of precise measures of foraging behaviour. The standard measures tend to be run statistics, such as the maximum run length and the number of runs. But these measures are not only interdependent, they are also constrained by the number and distribution of targets, making it difficult to make inferences about the effects of these aspects of the environment on foraging. Moreover, run statistics are underspecified about the underlying cognitive processes determining foraging behaviour. We present an alternative approach: modelling foraging as a procedure of generative sampling without replacement, implemented in a Bayesian multilevel model. This allows us to break behaviour down into a number of biases that influence target selection, such as the proximity of targets and a bias for selecting targets in runs, in a way that is not dependent on the number of targets present. Our method thereby facilitates direct comparison of specific foraging tendencies between search environments that differ in theoretically important dimensions. We demonstrate the use of our model with simulation examples and re-analysis of existing data. We believe our model will provide deeper insights into visual foraging and provide a foundation for further modelling work in this area.

Stable individual differences in strategies within, but not between, visual search tasks.

A striking range of individual differences has recently been reported in three different visual search tasks. These differences in performance can be attributed to strategy, that is, the efficiency with which participants control their search to complete the task quickly and accurately. Here, we ask whether an individual's strategy and performance in one search task is correlated with how they perform in the other two. We tested 64 observers and found that even though the test-retest reliability of the tasks was high, an observer's performance and strategy in one task was not predictive of their behaviour in the other two. These results suggest search strategies are stable over time, but context-specific. To understand visual search, we therefore need to account not only for differences between individuals but also how individuals interact with the search task and context.

Search strategies improve with practice, but not with time pressure or financial incentives.

When searching for an object, do we minimize the number of eye movements we need to make? Under most circumstances, the cost of saccadic parsimony likely outweighs the benefit, given the cost is extensive computation and the benefit is a few hundred milliseconds of time saved. Previous research has measured the proportion of eye movements directed to locations where the target would have been visible in the periphery as a way of quantifying the proportion of superfluous fixations. A surprisingly large range of individual differences has emerged from these studies, suggesting some people are highly efficient and others much less so. Our question in the current study is whether these individual differences can be explained by differences in motivation. In two experiments, we demonstrate that neither time pressure nor financial incentive led to improvements of visual search strategies; the majority of participants continued to make many superfluous fixations in both experiments. The wide range of individual differences in efficiency observed previously was replicated here. We observed small but consistent improvements in strategy over the course of the experiment (regardless of reward or time pressure) suggesting practice, not motivation, makes participants more efficient. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Decision making in slow and rapid reaching: Sacrificing success to minimize effort.

Current studies on visuomotor decision making come to inconsistent conclusions regarding the optimality with which these decisions are made. When executing rapid reaching movements under uncertainty, humans tend to automatically select optimal movement paths that take into account the position of all potential targets (spatial averaging). In contrast, humans rarely employ optimal strategies when making decisions on whether to pursue two action goals simultaneously or prioritise one goal over another. Here, we manipulated whether spatial averaging or pre-selection of a single target would provide the optimal strategy by varying the spatial separation between two potential movement targets as well as the time available for movement execution. In Experiment 1, we aimed to determine the time needed to reach for targets with small and large separation between them and to measure baseline strategies under low time pressure. Given generous time limits, participants did not employ a pure averaging approach but instead tended to pre-select the target that was easiest to reach and corrected their movement path in-flight if required. In Experiment 2, a strict time limit was set such that the optimal strategy to reach the correct target depended on the separation between the potential targets: for small separations, there was enough time to employ averaging strategies, but higher success for larger separations required pre-selecting the final target instead. While participants varied in the strategies they preferred, none of them flexibly adjusted their movement strategies depending on the spatial separation of the targets. In Experiment 3, we confirm the bias toward targets that are easiest to reach and show that this comes at the expense of overall task success. The results suggest a strong tendency for humans to minimize immediate movement effort and a general failure to adapt movement strategies flexibly with changes in the task parameters.

The eye that binds: Feature integration is not disrupted by saccadic eye movements.

Feature integration theory proposes that visual features, such as shape and color, can only be combined into a unified object when spatial attention is directed to their location in retinotopic maps. Eye movements cause dramatic changes on our retinae, and are associated with obligatory shifts in spatial attention. In two experiments, we measured the prevalence of conjunction errors (that is, reporting an object as having an attribute that belonged to another object), for brief stimulus presentation before, during, and after a saccade. Planning and executing a saccade did not itself disrupt feature integration. Motion did disrupt feature integration, leading to an increase in conjunction errors. However, retinal motion of an equal extent but caused by saccadic eye movements is spared this disruption, and showed similar rates of conjunction errors as a condition with static stimuli presented to a static eye. The results suggest that extra-retinal signals are able to compensate for the motion caused by saccadic eye movements, thereby preserving the integrity of objects across saccades and preventing their features from mixing or mis-binding.

Shared attention for action selection and action monitoring in goal-directed reaching.

Dual-task studies have shown higher sensitivity for stimuli presented at the targets of upcoming actions. We examined whether attention is directed to action targets for the purpose of action selection, or if attention is directed to these locations because they are expected to provide feedback about movement outcomes. In our experiment, endpoint accuracy feedback was spatially separated from the action targets to determine whether attention would be allocated to (a) the action targets, (b) the expected source of feedback, or (c) to both locations. Participants reached towards a location indicated by an arrow while identifying a discrimination target that could appear in any one of eight possible locations. Discrimination target accuracy was used as a measure of attention allocation. Participants were unable to see their hand during reaching and were provided with a small monetary reward for each accurate movement. Discrimination target accuracy was best at action targets but was also enhanced at the spatially separated feedback locations. Separating feedback from the reaching targets did not diminish discrimination accuracy at the movement targets but did result in delayed movement initiation and reduced reaching accuracy, relative to when feedback was presented at the reaching target. The results suggest attention is required for both action planning and monitoring movement outcomes. Dividing attention between these functions negatively impacts action performance.

Seeing Beyond Salience and Guidance: The Role of Bias and Decision in Visual Search.

Visual search is a popular tool for studying a range of questions about perception and attention, thanks to the ease with which the basic paradigm can be controlled and manipulated. While often thought of as a sub-field of vision science, search tasks are significantly more complex than most other perceptual tasks, with strategy and decision playing an essential, but neglected, role. In this review, we briefly describe some of the important theoretical advances about perception and attention that have been gained from studying visual search within the signal detection and guided search frameworks. Under most circumstances, search also involves executing a series of eye movements. We argue that understanding the contribution of biases, routines and strategies to visual search performance over multiple fixations will lead to new insights about these decision-related processes and how they interact with perception and attention. We also highlight the neglected potential for variability, both within and between searchers, to contribute to our understanding of visual search. The exciting challenge will be to account for variations in search performance caused by these numerous factors and their interactions. We conclude the review with some recommendations for ways future research can tackle these challenges to move the field forward.

Inefficient Eye Movements: Gamification Improves Task Execution, But Not Fixation Strategy.

Decisions about where to fixate are highly variable and often inefficient. In the current study, we investigated whether such decisions would improve with increased motivation. Participants had to detect a discrimination target, which would appear in one of two boxes, but only after they chose a location to fixate. The distance between boxes determines which location to fixate to maximise the probability of being able to see the target: participants should fixate between the two boxes when they are close together, and on one of the two boxes when they are far apart. We "gamified" this task, giving participants easy-to-track rewards that were contingent on discrimination accuracy. Their decisions and performance were compared to previous results that were gathered in the absence of this additional motivation. We used a Bayesian beta regression model to estimate the size of the effect and associated variance. The results demonstrate that discrimination accuracy does indeed improve in the presence of performance-related rewards. However, there was no difference in eye movement strategy between the two groups, suggesting this improvement in accuracy was not due to the participants making more optimal eye movement decisions. Instead, the motivation encouraged participants to expend more effort on other aspects of the task, such as paying more attention to the boxes and making fewer response errors.

The Relationship Between Spatial Attention and Eye Movements.

The nature of the relationship between spatial attention and eye movements has been the subject of intense debate for more than 40 years. Two ideas have dominated this debate. First is the idea that spatial attention shares common neural mechanisms with eye movement programming, characterizing attention as an eye movement that has been prepared but not executed. Second, based on the observation that attention shifts to saccade targets, several theories have proposed that saccade programming necessarily recruits attentional resources. In this chapter, we review the evidence for each of these ideas and discuss some of the limitations and challenges in confirming their predictions. Although they are clearly dependent under some circumstances, dissociations between spatial attention and eye movements, and clear differences in their basic functions, point to the existence of two interconnected, but separate, systems.

Practice-related changes in eye movement strategy in healthy adults with simulated hemianopia.

The impact of visual field deficits such as hemianopia can be mitigated by eye movements that position the visual image within the intact visual field. Effective eye movement strategies are not observed in all patients, however, and it is not known whether persistent deficits are due to injury or to pre-existing individual differences. Here we examined whether repeated exposure to a search task with rewards for good performance would lead to better eye movement strategies in healthy individuals. Participants were exposed to simulated hemianopia during a search task in five testing sessions over five consecutive days and received monetary payment for improvements in search times. With practice, most participants made saccades that went further into the blind field earlier in search, specifically under conditions where little information about the target location would be gained by inspecting the sighted field. These changes in search strategy were correlated with reduced search times. This strategy improvement also generalised to a novel task, with better performance in naming objects in a photograph under conditions of simulated hemianopia after practice with visual search compared to a control group. However, even after five days, eye movements in most participants remained far from optimal. The results demonstrate the benefits, and limitations, of practice and reward in the development of effective coping strategies for visual field deficits.

The role of attention in eye-movement awareness.

People are unable to accurately report on their own eye movements most of the time. Can this be explained as a lack of attention to the objects we fixate? Here, we elicited eye-movement errors using the classic oculomotor capture paradigm, in which people tend to look at sudden onsets even when they are irrelevant. In the first experiment, participants were able to report their own errors on about a quarter of the trials on which they occurred. The aim of the second experiment was to assess what differentiates errors that are detected from those that are not. Specifically, we estimated the relative influence of two possible factors: how long the onset distractor was fixated (dwell time), and a measure of how much attention was allocated to the onset distractor. Longer dwell times were associated with awareness of the error, but the measure of attention was not. The effect of the distractor identity on target discrimination reaction time was similar whether or not the participant was aware they had fixated the distractor. The results suggest that both attentional and oculomotor capture can occur in the absence of awareness, and have important implications for our understanding of the relationship between attention, eye movements, and awareness.

A Generative Model of Cognitive State from Task and Eye Movements.

The early eye tracking studies of Yarbus provided descriptive evidence that an observer's task influences patterns of eye movements, leading to the tantalizing prospect that an observer's intentions could be inferred from their saccade behavior. We investigate the predictive value of task and eye movement properties by creating a computational cognitive model of saccade selection based on instructed task and internal cognitive state using a Dynamic Bayesian Network (DBN). Understanding how humans generate saccades under different conditions and cognitive sets links recent work on salience models of low-level vision with higher level cognitive goals. This model provides a Bayesian, cognitive approach to top-down transitions in attentional set in pre-frontal areas along with vector-based saccade generation from the superior colliculus. Our approach is to begin with eye movement data that has previously been shown to differ across task. We first present an analysis of the extent to which individual saccadic features are diagnostic of an observer's task. Second, we use those features to infer an underlying cognitive state that potentially differs from the instructed task. Finally, we demonstrate how changes of cognitive state over time can be incorporated into a generative model of eye movement vectors without resorting to an external decision homunculus. Internal cognitive state frees the model from the assumption that instructed task is the only factor influencing observers' saccadic behavior. While the inclusion of hidden temporal state does not improve the classification accuracy of the model, it does allow accurate prediction of saccadic sequence results observed in search paradigms. Given the generative nature of this model, it is capable of saccadic simulation in real time. We demonstrated that the properties from its generated saccadic vectors closely match those of human observers given a particular task and cognitive state. Many current models of vision focus entirely on bottom-up salience to produce estimates of spatial "areas of interest" within a visual scene. While a few recent models do add top-down knowledge and task information, we believe our contribution is important in three key ways. First, we incorporate task as learned attentional sets that are capable of self-transition given only information available to the visual system. This matches influential theories of bias signals by (Miller and Cohen Annu Rev Neurosci 24:167-202, 2001) and implements selection of state without simply shifting the decision to an external homunculus. Second, our model is generative and capable of predicting sequence artifacts in saccade generation like those found in visual search. Third, our model generates relative saccadic vector information as opposed to absolute spatial coordinates. This matches more closely the internal saccadic representations as they are generated in the superior colliculus.

The saccadic flow baseline: Accounting for image-independent biases in fixation behavior.

Much effort has been made to explain eye guidance during natural scene viewing. However, a substantial component of fixation placement appears to be a set of consistent biases in eye movement behavior. We introduce the concept of saccadic flow, a generalization of the central bias that describes the image-independent conditional probability of making a saccade to (xi+1, yi+1), given a fixation at (xi, yi). We suggest that saccadic flow can be a useful prior when carrying out analyses of fixation locations, and can be used as a submodule in models of eye movements during scene viewing. We demonstrate the utility of this idea by presenting bias-weighted gaze landscapes, and show that there is a link between the likelihood of a saccade under the flow model, and the salience of the following fixation. We also present a minor improvement to our central bias model (based on using a multivariate truncated Gaussian), and investigate the leftwards and coarse-to-fine biases in scene viewing.