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.].

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.

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.

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.

The mental health crisis of expectant women in the UK: effects of the COVID-19 pandemic on prenatal mental health, antenatal attachment and social support.

BACKGROUND: Pregnancy has been shown to be times in a woman's life particularly prone to mental health issues, however a substantial percentage of mothers report subclinical perinatal mental health symptoms that go undetected. Experiences of prenatal trauma, such as the COVID-19 pandemic, may exacerbate vulnerability to negative health outcomes for pregnant women and their infants. We aimed to examine the role of: 1) anxiety, depression, and stress related to COVID-19 in predicting the quality of antenatal attachment; 2) perceived social support and COVID-19 appraisal in predicting maternal anxiety and depression. METHODS: A sample of 150 UK expectant women were surveyed during the COVID-19 pandemic. Questions included demographics, pregnancy details, and COVID-19 appraisal. Validated measures were used to collect self-reported maternal antenatal attachment (MAAS), symptoms of anxiety (STAI), depression (BDI-II), and stress related to the psychological impact of COVID-19 (IES-r). RESULTS: We found that the pandemic has affected UK expectant mothers' mental health by increasing prevalence of depression (47%), anxiety (60%) and stress related to the psychological impact of COVID-19 (40%). Women for whom COVID-19 had a higher psychological impact were more likely to suffer from depressive (95% HDPI = [0.04, 0.39]) and anxiety symptoms (95% HPDI = [0.40, 0.69]). High depressive symptoms were associated with reduced attachment to the unborn baby (95% HPDI [-0.46, -0.1]). Whilst women who appraised the impact of COVID-19 to be more negative showed higher levels of anxiety (HPDI = [0.15, 0.46]), higher social support acted as a protective factor and was associated with lower anxiety (95% HPDI = [-0.52, -0.21]). CONCLUSIONS: The current findings demonstrate that direct experience of prenatal trauma, such as the one experienced during the COVID-19 pandemic, significantly amplifies mothers' vulnerability to mental health symptoms and impairs the formation of a positive relationship with their unborn baby. Health services should prioritise interventions strategies aimed at fostering support for pregnant women.

The human visual system preserves the hierarchy of two-dimensional pattern regularity.

Symmetries are present at many scales in natural scenes. Humans and other animals are highly sensitive to visual symmetry, and symmetry contributes to numerous domains of visual perception. The four fundamental symmetries-reflection, rotation, translation and glide reflection-can be combined into exactly 17 distinct regular textures. These wallpaper groups represent the complete set of symmetries in two-dimensional images. The current study seeks to provide a more comprehensive description of responses to symmetry in the human visual system, by collecting both brain imaging (steady-state visual evoked potentials measured using high-density EEG) and behavioural (symmetry detection thresholds) data using the entire set of wallpaper groups. This allows us to probe the hierarchy of complexity among wallpaper groups, in which simpler groups are subgroups of more complex ones. We find that both behaviour and brain activity preserve the hierarchy almost perfectly: subgroups consistently produce lower-amplitude symmetry-specific responses in visual cortex and require longer presentation durations to be reliably detected. These findings expand our understanding of symmetry perception by showing that the human brain encodes symmetries with a high level of precision and detail. This opens new avenues for research on how fine-grained representations of regular textures contribute to natural vision.

Characterizing the in-out asymmetry in visual crowding.

An object's processing is impaired by the presence of nearby clutter. Several distinct mechanisms, such as masking and visual crowding, are thought to contribute to such flanker-induced interference. It is therefore important to determine which mechanism is operational in any given situation. Previous studies have proposed that the in-out asymmetry (IOA), where a peripheral flanker interferes with the target more than a foveal flanker, is diagnostic of crowding. However, several studies have documented inconsistencies in the occurrence of this asymmetry, particularly at locations beyond the horizontal meridian, casting doubt on its ability to delineate crowding. In this study, to determine if IOA is diagnostic of crowding, we extensively charted its properties. We asked a relatively large set of participants (n = 38) to identify a briefly presented peripheral letter flanked by a single inward or outward letter at one of four locations. We also manipulated target location uncertainty and attentional allocation by blocking, randomizing or pre-cueing the target location. Using multilevel Bayesian regression analysis, we found robust IOA at all locations, although its strength was modulated by target location, location uncertainty, and attentional allocation. Our findings suggest that IOA can be an excellent marker of crowding, to the extent that it is not observed in other flanker-interference mechanisms, such as masking.

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. The search target is visible in the periphery on the homogeneous array, but requires central vision to be detected on the heterogeneous array. For a compound search array that is heterogeneous on one side and homogeneous on the other, eye movements should be directed only to the heterogeneous side. Instead, participants made many fixations on the homogeneous side. By comparing search of compound arrays to an estimate of search performance based on uniform arrays, we isolate two contributions to search inefficiency. First, participants make superfluous fixations, sacrificing speed for a perceived (but not actual) gain in response certainty. Second, participants fixate the homogeneous side even more frequently than predicted by inefficient search of uniform arrays, suggesting they also fail to direct fixations to locations that yield the most new information.

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.

Failure of Intuition When Choosing Whether to Invest in a Single Goal or Split Resources Between Two Goals.

In a series of related experiments, we asked people to choose whether to split their attention between two equally likely potential tasks or to prioritize one task at the expense of the other. In such a choice, when the tasks are easy, the best strategy is to prepare for both of them. As difficulty increases beyond the point at which people can perform both tasks accurately, they should switch strategy and focus on one task at the expense of the other. Across three very different tasks (target detection, throwing, and memory), none of the participants switched their strategy at the correct point. Moreover, the majority consistently failed to modify their strategy in response to changes in task difficulty. This failure may have been related to uncertainty about their own ability, because in a version of the experiment in which there was no uncertainty, participants uniformly switched at an optimal point.

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. If the model does not detect the target, then it selects the next saccade by randomly sampling from the distribution of saccades that human observers made. We find that a memoryless stochastic model matches human performance in this task. Furthermore, we find that the similarity in the distribution of fixation locations between human observers and the ideal observer does not replicate: Rather than making the signature doughnut-shaped distribution predicted by the ideal search strategy, the fixations made by observers are best described by a central bias. We conclude that, when searching for a target in noise, humans use an essentially random strategy, which achieves near optimal behavior due to biases in the distributions of saccades we have a tendency to make. The findings reconcile the existence of highly efficient human search performance with recent studies demonstrating clear failures of optimality in single and multiple saccade tasks.

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.

Corrigendum: Where's Wally: the influence of visual salience on referring expression generation.

[This corrects the article DOI: 10.3389/fpsyg.2013.00329.].

Corrigendum: Giving good directions: order of mention reflects visual salience.

[This corrects the article DOI: 10.3389/fpsyg.2015.01793.].

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).

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.

The effects of display time and eccentricity on the detection of amplitude and phase degradations in textured stimuli.

The amplitude and phase spectra of an image contain important information for perception, and a large body of work has investigated the effects of manipulating these spectra on the recognition or classification of image content. Here, we use a novel means of investigating sensitivity to amplitude and phase spectra properties, testing the ability of observers to detect degradations of the spectral content of synthetic images of textured surfaces that are broadband in the frequency domain. The effects of display time and retinal eccentricity on sensitivity to these two manipulations are compared using stimuli matched for difficulty of detection. We find no difference between the time courses for the detection of degradation in the two spectra; in both cases, accuracy rises above chance when display times are greater than 80 ms. Increasing retinal eccentricity to 8.7°, however, has a significantly stronger effect on the accuracy of detecting degradations of the amplitude spectrum than of the phase spectrum. Further, sensitivity to phase randomization that is restricted to low spatial frequencies is greater in the periphery (at 8.7° eccentricity) than in the fovea. These last two results imply that the fovea and periphery are specialized for the processing of phase spectrum information in distinct spatial frequency bands.

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.

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.

Age differences in COVID-19 risk-taking, and the relationship with risk attitude and numerical ability.

This study aimed to investigate age differences in risk-taking concerning the coronavirus pandemic, while disentangling the contribution of risk attitude, objective risk and numeracy. We tested (i) whether older and younger adults differed in taking coronavirus-related health risks, (ii) whether there are age differences in coronavirus risk, risk attitude and numerical ability and (iii) whether these age differences in coronavirus risk, attitude and numerical ability are related to coronavirus risk-taking. The study was observational, with measures presented to all participants in random order. A sample of 469 participants reported their coronavirus-related risk-taking behaviour, objective risk, risk attitude towards health and safety risks, numerical ability and risk perception. Our findings show that age was significantly related to coronavirus risk-taking, with younger adults taking more risk, and that this was partially mediated by higher numeracy, but not objective risk or risk attitude. Exploratory analyses suggest that risk perception for self and others partially mediated age differences in coronavirus risk-taking. The findings of this study may better our understanding of why age groups differ in their adoption of protective behaviours during a pandemic and contribute to the debate whether age differences in risk-taking occur due to decline in abilities or changes in risk attitude.