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.

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 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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).

Human visual search behaviour is far from ideal.

Evolutionary pressures have made foraging behaviours highly efficient in many species. Eye movements during search present a useful instance of foraging behaviour in humans. We tested the efficiency of eye movements during search using homogeneous and heterogeneous arrays of line segments.

Inefficient search strategies in simulated hemianopia.

We investigated whether healthy participants can spontaneously adopt effective eye movement strategies to compensate for information loss similar to that experienced by patients with damage to visual cortex (hemianopia). Visual information in 1 hemifield was removed or degraded while participants searched for an emotional face among neutral faces or a line tilted 45° to the right among lines of varying degree of tilt. A bias to direct saccades toward the sighted field was observed across all 4 experiments.

People are unable to recognize or report on their own eye movements.

Eye movements bring new information into our visual system. The selection of each fixation is the result of a complex interplay of image features, task goals, and biases in motor control and perception. To what extent are we aware of the selection of saccades and their consequences? Here we use a converging methods approach to answer this question in three diverse experiments.

The effect of visualization on visual search performance : Does visualization trump vision?

Striking results recently demonstrated that visualizing search for a target can facilitate visual search for that target on subsequent trials (Reinhart et al. 2015). This visualization benefit was even greater than the benefit of actually repeating search for the target.

Human search for a target on a textured background is consistent with a stochastic model.

Previous work has demonstrated that search for a target in noise is consistent with the predictions of the optimal search strategy, both in the spatial distribution of fixation locations and in the number of fixations observers require to find the target. In this study we describe a challenging visual-search task and compare the number of fixations required by human observers to find the target to predictions made by a stochastic search model. This model relies on a target-visibility map based on human performance in a separate detection task.