Accounting for attention in sequential sampling models of decision making

Attention biases the process of risky decision-making: Evidence from eye-tracking

Attention determines what kind of option information is processed during risky choices owing to the limitation of visual attention. This paper reviews research on the relationship between higher-complexity risky decision-making and attention as illustrated by eye-tracking to explain the process of risky decision-making by the effect of attention. We demonstrate this process from three stages: the pre-phase guidance of options on attention, the process of attention being biased, and the impact of attention on final risk preference. We conclude that exogenous information can capture attention directly to salient options, thereby altering evidence accumulation. In particular, for multi-attribute risky decision-making, attentional advantages increase the weight of specific attributes, thus biasing risk preference in different directions. We highlight the significance of understanding how people use available information to weigh risks from an information-processing perspective via process data.

Effects of outcome revaluation on attentional prioritisation of reward-related stimuli

Stimuli associated with rewards can acquire the ability to capture our attention independently of our goals and intentions. Here, we examined whether attentional prioritisation of reward-related cues is sensitive to changes in the value of the reward itself. To this end, we incorporated an instructed outcome devaluation (Experiment 1a), "super-valuation" (Experiment 1b), or value switch (Experiment 2) into a visual search task, using eye-tracking to examine attentional prioritisation of stimuli signalling high- and low-value rewards. In Experiments 1a and 1b, we found that prioritisation of high- and low-value stimuli was insensitive to devaluation of a previously high-value outcome, and super-valuation of a previously low-value outcome, even when participants were provided with further experience of receiving that outcome. In Experiment 2, following a value-switch manipulation, we found that prioritisation of a high-value stimulus could not be overcome with knowledge of the new values of outcomes alone. Only when provided with further experience of receiving the outcomes did patterns of attentional prioritisation of high- and low-value stimuli switch, in line with the updated values of the outcomes they signalled. To reconcile these findings, we suggest that participants were motivated to engage in effortful updating of attentional control settings when there was a relative difference between reward values at test (Experiment 2) but that previous settings were allowed to persist when both outcomes had the same value at test (Experiments 1a and 1b). These findings provide a novel framework to further understand the role of cognitive control in driving reward-modulated attention and behaviour.

Attention to novelty interferes with toddlers' emerging memory decision-making

Memory decision-making in 26- to 32-month-olds was investigated using visual-paired comparison paradigms, requiring toddlers to select familiar stimuli (Active condition) or view familiar and novel stimuli (Passive condition). In Experiment 1 (N = 108, 54.6% female, 62% White; replication N = 98), toddlers with higher accuracy in the Active condition showed reduced novelty preference in that condition, but not in the Passive condition (d = -.11). In Experiment 2 (N = 78; 52.6% female; 70.5% White), a brief 5% increase in target size boosted gaze transitions across conditions (d = .50) and accuracy in the Active condition (d = .53). Overall, evidence suggests that better attentional distribution can support decision-making. Research was conducted between 2014 and 2020 in Northern California.

Learning about me and you: Only deterministic stimulus associations elicit self-prioritization

Self-relevant material has been shown to be prioritized over stimuli relating to others (e.g., friend, stranger), generating benefits in attention, memory, and decision-making. What is not yet understood, however, is whether the conditions under which self-related knowledge is acquired impacts the emergence of self-bias. To address this matter, here we used an associative-learning paradigm in combination with a stimulus-classification task to explore the effects of different learning experiences (i.e., deterministic vs. probabilistic) on self-prioritization. The results revealed an effect of prior learning on task performance, with self-prioritization only emerging when participants acquired target-related associations (i.e., self vs. friend) under conditions of certainty (vs. uncertainty). A further computational (i.e., drift diffusion model) analysis indicated that differences in the efficiency of stimulus processing (i.e., rate of information uptake) underpinned this self-prioritization effect. The implications of these findings for accounts of self-function are considered.

Modelling decision-making biases

Biases are a fundamental aspect of everyday life decision-making. A variety of modelling approaches have been suggested to capture decision-making biases. Statistical models are a means to describe the data, but the results are usually interpreted according to a verbal theory. This can lead to an ambiguous interpretation of the data. Mathematical cognitive models of decision-making outline the structure of the decision process with formal assumptions, providing advantages in terms of prediction, simulation, and interpretability compared to statistical models. We compare studies that used both signal detection theory and evidence accumulation models as models of decision-making biases, concluding that the latter provides a more comprehensive account of the decision-making phenomena by including response time behavior. We conclude by reviewing recent studies investigating attention and expectation biases with evidence accumulation models. Previous findings, reporting an exclusive influence of attention on the speed of evidence accumulation and prior probability on starting point, are challenged by novel results suggesting an additional effect of attention on non-decision time and prior probability on drift rate.

Psychological value theory: A computational cognitive model of charitable giving

Charitable giving involves a complex economic and social decision because the giver expends resources for goods or services they will never receive. Although psychologists have identified numerous factors that influence charitable giving, there currently exists no unifying computational model of charitable choice. Here, we submit one such model, based within the strictures of Psychological Value Theory (PVT). In four experiments, we assess whether charitable giving is driven by the perceived Psychological Value of the recipient. Across all four experiments, we simultaneously predict response choice and response time with high accuracy. In a fifth experiment, we show that PVT predicts charitable giving more accurately than an account based on competence and warmth. PVT accurately predicts which charity a respondent will choose to donate to and separately, whether a respondent will choose to donate at all. PVT models the cognitive processes underlying charitable donations and it provides a computational framework for integrating known influences on charitable giving. For example, we show that in-group preference influences charitable giving by changing the Psychological Values of the options, rather than by bringing about a response bias toward the in-group.

The role of attention in status quo bias

In many decision-making contexts, people often persist with their previous selections. This predisposition to choose to maintain a current (or previous) choice is referred to as the status quo bias (SQB). In this work, we propose that increased attention towards the status quo option-enabled by its visual salience-is a previously underappreciated driver of SQB. We base this hypothesis on three propositions: (1) the status quo bias option is often more visually salient relative to the non-status quo options on offer, (2) greater visual salience of an option biases attention towards that option, and (3) increased attention towards an option leads to that option being selected at greater rates. We examined the attention hypothesis among 6,854 participants in four studies. Studies 1 and 2 showed that increasing the visual salience of a non-status quo option (i.e., the type of visual salience often garnered by the status quo option) increased the selection rate of that option. Study 3 directly tested the hypothesis by lessening the visual salience of the status quo option. Doing so eliminated SQB. Study 4 replicated and extended the findings of Study 3 in a real-world decision context. Collectively, these studies suggest that the selection of the status quo may often be related to its salience relative to other available options.

Gaze differences in configural and elemental evaluation during multi-attribute decision-making

Introduction

While many everyday choices are between multi-attribute options, how attribute values are integrated to allow such choices remains unclear. Recent findings suggest a distinction between elemental (attribute-by-attribute) and configural (holistic) evaluation of multi-attribute options, with different neural substrates. Here, we asked if there are behavioral or gaze pattern differences between these putatively distinct modes of multi-attribute decision-making.

Methods

Thirty-nine healthy men and women learned the monetary values of novel multi-attribute pseudo-objects (fribbles) and then made choices between pairs of these objects while eye movements were tracked. Value was associated with individual attributes in the elemental condition, and with unique combinations of attributes in the configural condition. Choice, reaction time, gaze fixation time on options and individual attributes, and within- and between-option gaze transitions were recorded.

Results

There were systematic behavioral differences between elemental and configural conditions. Elemental trials had longer reaction times and more between-option transitions, while configural trials had more within-option transitions. The effect of last fixation on choice was more pronounced in the configural condition.

Discussion

We observed differences in gaze patterns and the influence of last fixation location on choice in multi-attribute value-based choices depending on how value is associated with those attributes. This adds support for the claim that multi-attribute option values may emerge either elementally or holistically, reminiscent of similar distinctions in multi-attribute object recognition. This may be important to consider in neuroeconomics research that involve visually-presented complex objects.

Monkeys exhibit human-like gaze biases in economic decisions

In economic decision-making individuals choose between items based on their perceived value. For both humans and nonhuman primates, these decisions are often carried out while shifting gaze between the available options. Recent studies in humans suggest that these shifts in gaze actively influence choice, manifesting as a bias in favor of the items that are viewed first, viewed last, or viewed for the overall longest duration in a given trial. This suggests a mechanism that links gaze behavior to the neural computations underlying value-based choices. In order to identify this mechanism, it is first necessary to develop and validate a suitable animal model of this behavior. To this end, we have created a novel value-based choice task for macaque monkeys that captures the essential features of the human paradigms in which gaze biases have been observed. Using this task, we identified gaze biases in the monkeys that were both qualitatively and quantitatively similar to those in humans. In addition, the monkeys' gaze biases were well-explained using a sequential sampling model framework previously used to describe gaze biases in humans-the first time this framework has been used to assess value-based decision mechanisms in nonhuman primates. Together, these findings suggest a common mechanism that can explain gaze-related choice biases across species, and open the way for mechanistic studies to identify the neural origins of this behavior.

Good-enough attentional guidance

Theories of attention posit that attentional guidance operates on information held in a target template within memory. The template is often thought to contain veridical target features, akin to a photograph, and to guide attention to objects that match the exact target features. However, recent evidence suggests that attentional guidance is highly flexible and often guided by non-veridical features, a subset of features, or only associated features. We integrate these findings and propose that attentional guidance maximizes search efficiency based on a 'good-enough' principle to rapidly localize candidate target objects. Candidates are then serially interrogated to make target-match decisions using more precise information. We suggest that good-enough guidance optimizes the speed-accuracy-effort trade-offs inherent in each stage of visual search.

Self-judgment dissected: A computational modeling analysis of self-referential processing and its relationship to trait mindfulness facets and depression symptoms

Cognitive theories of depression, and mindfulness theories of well-being, converge on the notion that self-judgment plays a critical role in mental health. However, these theories have rarely been tested via tasks and computational modeling analyses that can disentangle the information processes operative in self-judgments. We applied a drift-diffusion computational model to the self-referential encoding task (SRET) collected before and after an 8-week mindfulness intervention (n = 96). A drift-rate regression parameter representing positive-relative to negative-self-referential judgment strength positively related to mindful awareness and inversely related to depression, both at baseline and over time; however, this parameter did not significantly relate to the interaction between mindful awareness and nonjudgmentalness. At the level of individual depression symptoms, at baseline, a spectrum of symptoms (inversely) correlated with the drift-rate regression parameter, suggesting that many distinct depression symptoms relate to valenced self-judgment between subjects. By contrast, over the intervention, changes in only a smaller subset of anhedonia-related depression symptoms showed substantial relationships with this parameter. Both behavioral and model-derived measures showed modest split-half and test-retest correlations. Results support cognitive theories that implicate self-judgment in depression and mindfulness theories, which imply that mindful awareness should lead to more positive self-views.

Facilitating animacy perception by manipulating stimuli exposure time

Animacy perception-discriminating between animate and inanimate visual stimuli-is the basis for engaging in social cognition and for our survival (e.g., avoiding potential danger). Previous studies indicate that factors in a target, such as the features or motion of a target, enhance animacy perception. However, factors in a perceiver, such as the visual attention of a perceiver to a target, have received little attention from researchers. Research on judgment, decision-making, and neuroeconomics indicates the active role of visual attention in constructing decisions. This study examined the role of visual attention in the perception of animacy by manipulating the exposure time of targets. Among Studies 1a to 1c conducted in this study, participants saw two face illustrations alternately; one of the faces was shown to be longer than the other. The participants chose the face that they considered more animated and rounder. Consequently, longer exposure time toward targets facilitated animacy perception and preference rather than the perception of roundness. Furthermore, preregistered Study 2 examined the underlying mechanisms. The results suggest that mere exposure, rather than orienting behavior, might play a vital role in the perception of animacy. Thus, in the reverse relationship between visual attention and animacy perception, animate objects capture attention-attention results in the perception of animacy.

A unified neural account of contextual and individual differences in altruism

Altruism is critical for cooperation and productivity in human societies but is known to vary strongly across contexts and individuals. The origin of these differences is largely unknown, but may in principle reflect variations in different neurocognitive processes that temporally unfold during altruistic decision making (ranging from initial perceptual processing via value computations to final integrative choice mechanisms). Here, we elucidate the neural origins of individual and contextual differences in altruism by examining altruistic choices in different inequality contexts with computational modeling and electroencephalography (EEG). Our results show that across all contexts and individuals, wealth distribution choices recruit a similar late decision process evident in model-predicted evidence accumulation signals over parietal regions. Contextual and individual differences in behavior related instead to initial processing of stimulus-locked inequality-related value information in centroparietal and centrofrontal sensors, as well as to gamma-band synchronization of these value-related signals with parietal response-locked evidence-accumulation signals. Our findings suggest separable biological bases for individual and contextual differences in altruism that relate to differences in the initial processing of choice-relevant information.

Cognitive and neural principles of a memory bias on preferential choices

Value-based decisions depend on different forms of memory. However, the respective roles of memory and valuation processes that give rise to these decisions are often vaguely described and have rarely been investigated jointly. In this review article, we address the problem of memory-based decision making from a neuroeconomic perspective. We first describe the neural and cognitive processes involved in decisions requiring memory processes, with a focus on episodic memory. Based on the results of a systematic research program, we then spotlight the phenomenon of the memory bias, a general preference for choice options that can be retrieved from episodic memory more successfully. Our findings indicate that failed memory recall biases neural valuation processes as indicated by altered effective connectivity between the hippocampus and ventromedial prefrontal cortex. This bias can be attributed to meta-cognitive beliefs about the relationship between subjective value and memory as well as to uncertainty aversion. After summarizing the findings, we outline potential future research endeavors to integrate the two research traditions of memory and decision making.

High-throughput automated methods for classical and operant conditioning of Drosophila larvae

Learning which stimuli (classical conditioning) or which actions (operant conditioning) predict rewards or punishments can improve chances of survival. However, the circuit mechanisms that underlie distinct types of associative learning are still not fully understood. Automated, high-throughput paradigms for studying different types of associative learning, combined with manipulation of specific neurons in freely behaving animals, can help advance this field. The Drosophila melanogaster larva is a tractable model system for studying the circuit basis of behaviour, but many forms of associative learning have not yet been demonstrated in this animal. Here, we developed a high-throughput (i.e. multi-larva) training system that combines real-time behaviour detection of freely moving larvae with targeted opto- and thermogenetic stimulation of tracked animals. Both stimuli are controlled in either open- or closed-loop, and delivered with high temporal and spatial precision. Using this tracker, we show for the first time that Drosophila larvae can perform classical conditioning with no overlap between sensory stimuli (i.e. trace conditioning). We also demonstrate that larvae are capable of operant conditioning by inducing a bend direction preference through optogenetic activation of reward-encoding serotonergic neurons. Our results extend the known associative learning capacities of Drosophila larvae. Our automated training rig will facilitate the study of many different forms of associative learning and the identification of the neural circuits that underpin them.

A Computational View on the Nature of Reward and Value in Anhedonia

Anhedonia - a common feature of depression and other neuropsychiatric disorders - encompasses a reduction in the subjective experience and anticipation of rewarding events, and a reduction in the motivation to seek out such events. The presence of anhedonia often predicts or accompanies treatment resistance, and as such better interventions and treatments are important. Yet the mechanisms giving rise to anhedonia are not well understood. In this chapter, we briefly review existing computational conceptualisations of anhedonia. We argue that they are mostly descriptive and fail to provide an explanatory account of why anhedonia may occur. Working within the framework of reinforcement learning, we examine two potential computational mechanisms that could give rise to anhedonic phenomena. First, we show how anhedonia can arise in multi-dimensional drive-reduction settings through a trade-off between different rewards or needs. We then generalise this in terms of model-based value inference and identify a key role for associational belief structure. We close with a brief discussion of treatment implications of both of these conceptualisations. In summary, computational accounts of anhedonia have provided a useful descriptive framework. Recent advances in reinforcement learning suggest promising avenues by which the mechanisms underlying anhedonia may be teased apart, potentially motivating novel approaches to treatment.

A causal role for the right frontal eye fields in value comparison

Recent studies have suggested close functional links between overt visual attention and decision making. This suggests that the corresponding mechanisms may interface in brain regions known to be crucial for guiding visual attention - such as the frontal eye field (FEF). Here, we combined brain stimulation, eye tracking, and computational approaches to explore this possibility. We show that inhibitory transcranial magnetic stimulation (TMS) over the right FEF has a causal impact on decision making, reducing the effect of gaze dwell time on choice while also increasing reaction times. We computationally characterize this putative mechanism by using the attentional drift diffusion model (aDDM), which reveals that FEF inhibition reduces the relative discounting of the non-fixated option in the comparison process. Our findings establish an important causal role of the right FEF in choice, elucidate the underlying mechanism, and provide support for one of the key causal hypotheses associated with the aDDM.

Webcam-based online eye-tracking for behavioral research

Experiments are increasingly moving online. This poses a major challenge for researchers who rely on in-lab techniques such as eye-tracking. Researchers in computer science have developed web-based eye-tracking applications (WebGazer; Papoutsaki et al., 2016) but they have yet to see them used in behavioral research. This is likely due to the extensive calibration and validation procedure, inconsistent temporal resolution (Semmelmann & Weigelt, 2018), and the challenge of integrating it into experimental software. Here, we incorporate WebGazer into a JavaScript library widely used by behavioral researchers (jsPsych) and adjust the procedure and code to reduce calibration/validation and improve the temporal resolution (from 100–1000 ms to 20–30 ms). We test this procedure with a decision-making study on Amazon MTurk, replicating previous in-lab findings on the relationship between gaze and choice, with little degradation in spatial or temporal resolution. This provides evidence that online web-based eye-tracking is feasible in behavioral research.

A rational model of people's inferences about others' preferences based on response times

There's a difference between someone instantaneously saying "Yes!" when you ask them on a date compared to "…yes." Psychologists and economists have long studied how people can infer preferences from others' choices. However, these models have tended to focus on what people choose and not how long it takes them to make a choice. We present a rational model for inferring preferences from response times, using a drift diffusion model to characterize how preferences influence response time, and Bayesian inference to invert this relationship. We test our model's predictions for three experimental questions. Matching model predictions, participants inferred that a decision-maker preferred a chosen item more if the decision-maker spent less time deliberating (Experiment 1), participants predicted a decision-maker's choice in a novel comparison based on inferring the decision-maker's relative preferences from previous response times and choices (Experiment 2), and participants could incorporate information about a decision-maker's mental state of cautious or careless (Experiments 3, 4A, and 4B).

An uncertainty-based model of the effects of fixation on choice

When people view a consumable item for a longer amount of time, they choose it more frequently; this also seems to be the direction of causality. The leading model of this effect is a drift-diffusion model with a fixation-based attentional bias. Here, we propose an explicitly Bayesian account for the same data. This account is based on the notion that the brain builds a posterior belief over the value of an item in the same way it would over a sensory variable. As the agent gathers evidence about the item from sensory observations and from retrieved memories, the posterior distribution narrows. We further postulate that the utility of an item is a weighted sum of the posterior mean and the negative posterior standard deviation, with the latter accounting for risk aversion. Fixating for longer can increase or decrease the posterior mean, but will inevitably lower the posterior standard deviation. This model fits the data better than the original attentional drift-diffusion model but worse than a variant with a collapsing bound. We discuss the often overlooked technical challenges in fitting models simultaneously to choice and response time data in the absence of an analytical expression. Our results hopefully contribute to emerging accounts of valuation as an inference process.

When people look longer at a food item, they tend to like it more. We propose a new theory in which this occurs because looking gathers information that reduces uncertainty, and people are uncertainty averse. We turn the theory into a mathematical model and fit it to previously published data. It fits better than the leading model, although we also find that the leading model can be improved.

The influence of visual attention on memory-based preferential choice

Many decisions rely on past experiences. Recent research indicates that people's choices are biased towards choosing better-remembered options, even if these options are comparatively unattractive (i.e., a memory bias). In the current study, we used eye tracking to compare the influence of visual attention on preferential choice between memory-based and non-memory-based decisions. Participants completed the remember-and-decide task. In this task, they first learned associations between screen locations and snack items. Then, they made binary choices between snack items. These snacks were either hidden and required recall (memory-based decisions), or they were visible (non-memory-based decisions). Remarkably, choices were more strongly influenced by attention in memory-based compared to non-memory-based decisions. However, visual attention did not mediate the memory bias on preferential choices. Finally, we adopt and expand a recently proposed computational model to provide a comprehensive description of the role of attention in memory-based decisions. In sum, the present work elucidates how visual attention interacts with episodic memory and preference formation in memory-based decisions.

Eye-tracking research on sensory and consumer science: A review, pitfalls and future directions

Visual processing is a core cognitive element of sensory and consumer science. Consumers visually attend to food types, packaging, label design, advertisements, supermarket shelves, food menus, and other visible information. During the past decade, sensory and consumer science have used eye tracking to elucidate visual processing by consumers. This review paper summarizes earlier findings in terms of bottom-up (i.e., stimulus-driven) processing such as visual salience, size, and top-down (i.e., goal-driven) processing such as goals, task instructions, task complexity, and emotions. Downstream effects of gaze on choice are also reviewed. Pitfalls and future directions of eye-tracking research on sensory and consumer science are also discussed.

A Preferential Role for Ventromedial Prefrontal Cortex in Assessing "the Value of the Whole" in Multiattribute Object Evaluation

Everyday decision-making commonly involves assigning values to complex objects with multiple value-relevant attributes. Drawing on object recognition theories, we hypothesized two routes to multiattribute evaluation: assessing the value of the whole object based on holistic attribute configuration or summing individual attribute values. In two samples of healthy human male and female participants undergoing eye tracking and functional magnetic resonance imaging (fMRI) while evaluating novel pseudo objects, we found evidence for both forms of evaluation. Fixations to and transitions between attributes differed systematically when the value of pseudo objects was associated with individual attributes or attribute configurations. Ventromedial prefrontal cortex (vmPFC) and perirhinal cortex were engaged when configural processing was required. These results converge with our recent findings that individuals with vmPFC lesions were impaired in decisions requiring configural evaluation but not when evaluating the sum of the parts. This suggests that multiattribute decision-making engages distinct evaluation mechanisms relying on partially dissociable neural substrates, depending on the relationship between attributes and value.SIGNIFICANCE STATEMENT Decision neuroscience has only recently begun to address how multiple choice-relevant attributes are brought together during evaluation and choice among complex options. Object recognition research makes a crucial distinction between individual attribute and holistic/configural object processing, but how the brain evaluates attributes and whole objects remains unclear. Using fMRI and eye tracking, we found that the vmPFC and the perirhinal cortex contribute to value estimation specifically when value was related to whole objects, that is, predicted by the unique configuration of attributes and not when value was predicted by the sum of individual attribute values. This perspective on the interactions between subjective value and object processing mechanisms provides a novel bridge between the study of object recognition and reward-guided decision-making.

Frontal circuit specialisations for decision making

There is widespread consensus that distributed circuits across prefrontal and anterior cingulate cortex (PFC/ACC) are critical for reward-based decision making. The circuit specialisations of these areas in primates were likely shaped by their foraging niche, in which decision making is typically sequential, attention-guided and temporally extended. Here, I argue that in humans and other primates, PFC/ACC circuits are functionally specialised in two ways. First, microcircuits found across PFC/ACC are highly recurrent in nature and have synaptic properties that support persistent activity across temporally extended cognitive tasks. These properties provide the basis of a computational account of time-varying neural activity within PFC/ACC as a decision is being made. Second, the macrocircuit connections (to other brain areas) differ between distinct PFC/ACC cytoarchitectonic subregions. This variation in macrocircuit connections explains why PFC/ACC subregions make unique contributions to reward-based decision tasks and how these contributions are shaped by attention. They predict dissociable neural representations to emerge in orbitofrontal, anterior cingulate and dorsolateral prefrontal cortex during sequential attention-guided choice, as recently confirmed in neurophysiological recordings.

How peer influence shapes value computation in moral decision-making

Moral behavior is susceptible to peer influence. How does information from peers influence moral preferences? We used drift-diffusion modeling to show that peer influence changes the value of moral behavior by prioritizing the choice attributes that align with peers' goals. Study 1 (N = 100; preregistered) showed that participants accurately inferred the goals of prosocial and antisocial peers when observing their moral decisions. In Study 2 (N = 68), participants made moral decisions before and after observing the decisions of a prosocial or antisocial peer. Peer observation caused participants' own preferences to resemble those of their peers. This peer influence effect on value computation manifested as an increased weight on choice attributes promoting the peers' goals that occurred independently from peer influence on initial choice bias. Participants' self-reported awareness of influence tracked more closely with computational measures of prosocial than antisocial influence. Our findings have implications for bolstering and blocking the effects of prosocial and antisocial influence on moral behavior.

Fixation patterns in simple choice reflect optimal information sampling

Simple choices (e.g., eating an apple vs. an orange) are made by integrating noisy evidence that is sampled over time and influenced by visual attention; as a result, fluctuations in visual attention can affect choices. But what determines what is fixated and when? To address this question, we model the decision process for simple choice as an information sampling problem, and approximate the optimal sampling policy. We find that it is optimal to sample from options whose value estimates are both high and uncertain. Furthermore, the optimal policy provides a reasonable account of fixations and choices in binary and trinary simple choice, as well as the differences between the two cases. Overall, the results show that the fixation process during simple choice is influenced dynamically by the value estimates computed during the decision process, in a manner consistent with optimal information sampling.

Decision-Making in the Human-Machine Interface

If our choices make us who we are, then what does that mean when these choices are made in the human-machine interface? Developing a clear understanding of how human decision making is influenced by automated systems in the environment is critical because, as human-machine interfaces and assistive robotics become even more ubiquitous in everyday life, many daily decisions will be an emergent result of the interactions between the human and the machine – not stemming solely from the human. For example, choices can be influenced by the relative locations and motor costs of the response options, as well as by the timing of the response prompts. In drift diffusion model simulations of response-prompt timing manipulations, we find that it is only relatively equibiased choices that will be successfully influenced by this kind of perturbation. However, with drift diffusion model simulations of motor cost manipulations, we find that even relatively biased choices can still show some influence of the perturbation. We report the results of a two-alternative forced-choice experiment with a computer mouse modified to have a subtle velocity bias in a pre-determined direction for each trial, inducing an increased motor cost to move the cursor away from the pre-designated target direction. With queries that have each been normed in advance to be equibiased in people’s preferences, the participant will often begin their mouse movement before their cognitive choice has been finalized, and the directional bias in the mouse velocity exerts a small but significant influence on their final choice. With queries that are not equibiased, a similar influence is observed. By exploring the synergies that are developed between humans and machines and tracking their temporal dynamics, this work aims to provide insight into our evolving decisions.

Does Attention Increase the Value of Choice Alternatives?

A growing recognition of the role of attention in decision-making has been driven by both the technology of eye tracking and the development of models that explicitly incorporate attention. One result of this convergence is the arresting claim that attention, by itself, can increase the perceived value of a decision alternative. In this review, we cover the origins of that claim, its empirical foundation, and the reasoning that supports it. The conclusion is that, to date, there is not sufficient evidence to support the claim. Alternative explanations for the extant evidentiary base are discussed, as is the balance between the bottom-up influence of empirical evidence and the top-down commitment to a conceptual framework.

Attentional priorities drive effects of time pressure on altruistic choice

Dual-process models of altruistic choice assume that automatic responses give way to deliberation over time, and are a popular way to conceptualize how people make generous choices and why those choices might change under time pressure. However, these models have led to conflicting interpretations of behaviour and underlying psychological dynamics. Here, we propose that flexible, goal-directed deployment of attention towards information priorities provides a more parsimonious account of altruistic choice dynamics. We demonstrate that time pressure tends to produce early gaze-biases towards a person’s own outcomes, and that individual differences in this bias explain how individuals’ generosity changes under time pressure. Our gaze-informed drift-diffusion model incorporating moment-to-moment eye-gaze further reveals that underlying social preferences both drive attention, and interact with it to shape generosity under time pressure. These findings help explain existing inconsistencies in the field by emphasizing the role of dynamic attention-allocation during altruistic choice.

Forcing people to choose quickly often changes pro-social behavior, but it is unclear why. Here, the authors show that under time pressure, people engage in incomplete information searches biased by concern (or lack thereof) for others, explaining effects often attributed to automatic processing.

Salient nutrition labels shift peoples' attention to healthy foods and exert more influence on their choices

Nutrition labels are the most commonly used tools to promote healthy choices. Research has shown that color-coded traffic light (TL) labels are more effective than purely numerical Guideline Daily Amount (GDA) labels at promoting healthy eating. While these effects of TL labels on food choice are hypothesized to rely on attention, how this occurs remains unknown. Based on previous eye-tracking research we hypothesized that TL labels compared to GDA labels will attract more attention, will induce shifts in attention allocation to healthy food items, and will increase the influence of attention to the labels on food choice. To test our hypotheses, we conducted an eye-tracking experiment where participants chose between healthy and unhealthy food items accompanied either by TL or GDA labels. We found that TL labels biased choices towards healthier items because their presence caused participants to allocate more attention to healthy items and less to unhealthy items. Moreover, our data indicated that TL labels were more likely to be looked at, and had a larger effect on choice, despite attracting less dwell time. These results reveal that TL labels increase healthy food choice, relative to GDA labels, by shifting attention and the effects of attention on choice.

What the Eyes Hear: An Eye-Tracking Study on Phonological Awareness in Emirati Arabic

Phonological awareness is the ability to perceive and manipulate the sounds of spoken words. It is considered a good predictor of reading and spelling abilities. In the current study, we used an eye-tracking procedure to measure fixation differences while adults completed three conditions of phonological awareness in Emirati Arabic (EA): (1) explicit instructions for onset consonant matching (OCM), (2) implicit instructions for segmentation of initial consonant (SIC), and (3) rhyme matching (RM). We hypothesized that fixation indices would vary according to the experimental conditions. We expected explicit instructions to facilitate task performance. Thus, eye movements should reflect more efficient fixation patterns in the explicit OCM condition in comparison to the implicit SIC condition. Moreover, since Arabic is consonant-based, we hypothesized that participants would perform better in the consonant conditions (i.e., OCM and SIC) than in the rhyme condition (i.e., RM). Finally, we expected that providing feedback during practice trials would facilitate participants’ performance overall. Response accuracy, expressed as a percentage of correct responses, was recorded alongside eye movement data. Results show that performance was significantly compromised in the RM condition, where targets received more fixations of longer average duration, and significantly longer gaze durations in comparison to the OCM and SIC conditions. Response accuracy was also significantly lower in the RM condition. Our results indicate that eye-tracking can be used as a tool to test phonological awareness skills and shows differences in performance between tasks containing a vowel or consonant manipulation.

Paying attention to attention in depression

Attention is the gate through which sensory information enters our conscious experiences. Oftentimes, patients with major depressive disorder (MDD) complain of concentration difficulties that negatively impact their day-to-day function, and these attention problems are not alleviated by current first-line treatments. In spite of attention's influence on many aspects of cognitive and emotional functioning, and the inclusion of concentration difficulties in the diagnostic criteria for MDD, the focus of depression as a disease is typically on mood features, with attentional features considered less of an imperative for investigation. Here, we summarize the breadth and depth of findings from the cognitive neurosciences regarding the neural mechanisms supporting goal-directed attention in order to better understand how these might go awry in depression. First, we characterize behavioral impairments in selective, sustained, and divided attention in depressed individuals. We then discuss interactions between goal-directed attention and other aspects of cognition (cognitive control, perception, and decision-making) and emotional functioning (negative biases, internally-focused attention, and interactions of mood and attention). We then review evidence for neurobiological mechanisms supporting attention, including the organization of large-scale neural networks and electrophysiological synchrony. Finally, we discuss the failure of current first-line treatments to alleviate attention impairments in MDD and review evidence for more targeted pharmacological, brain stimulation, and behavioral interventions. By synthesizing findings across disciplines and delineating avenues for future research, we aim to provide a clearer outline of how attention impairments may arise in the context of MDD and how, mechanistically, they may negatively impact daily functioning across various domains.

Visual fixation patterns during economic choice reflect covert valuation processes that emerge with learning

Where we direct our gaze can have a big impact on what we choose. However, where we choose to gaze during the decision process is not well-characterized, despite the important role it plays. In our study, monkeys performed a simple decision-making experiment where they were free to look around a computer screen showing choice options. They then indicated their economic choice with a joystick movement. When choice options appeared, monkeys rapidly gazed toward more valuable and novel stimuli—suggesting there is a system that orients gaze toward important information. However, despite the gaze preference for novel stimuli, subjects did not prefer to choose them. This suggests the mechanisms governing value-guided attentional capture and value-guided choice are dissociable.

Visual fixations play a vital role in decision making. Recent studies have demonstrated that the longer subjects fixate an option, the more likely they are to choose it. However, the role of evaluating stimuli covertly (i.e., without fixating them), and how covert evaluations determine where to subsequently fixate, remains relatively unexplored. Here, we trained monkeys to perform a decision-making task where they made binary choices between reward-predictive stimuli which were well-learned (“overtrained”), recently learned (“novel”), or a combination of both (“mixed”). Subjects were free to saccade around the screen and make a choice (via joystick response) at any time. Subjects rarely fixated both options, yet choice behavior was better explained by assuming the values of both stimuli governed choices. The first fixation latency was fast (∼150 ms) but, surprisingly, its direction was value-driven. This suggests covert evaluation of stimulus values prior to first saccade. This was particularly evident for overtrained stimuli. For novel stimuli, first fixations became increasingly value-driven throughout a behavioral session. However, this improvement lagged behind learning of accurate economic choices, suggesting separate processes governed their learning. Finally, mixed trials revealed a strong bias toward fixating the novel stimulus first but no bias toward choosing it. Our results suggest that the primate brain contains fast covert evaluation mechanisms for guiding fixations toward highly valuable and novel information. By employing such covert mechanisms, fixation behavior becomes dissociable from the value comparison processes that drive final choice. This implies that primates use separable decision systems for value-guided fixations and value-guided choice.

Gaze bias differences capture individual choice behaviour

How do we make simple choices such as deciding between an apple and an orange? Recent empirical evidence suggests that choice behaviour and gaze allocation are closely linked at the group level, whereby items looked at longer during the decision-making process are more likely to be chosen. However, it is unclear how variable this gaze bias effect is between individuals. Here we investigate this question across four different simple choice experiments and using a computational model that can be easily applied to individuals. We show that an association between gaze and choice is present for most individuals, but differs considerably in strength. Generally, individuals with a strong association between gaze and choice behaviour are worse at choosing the best item from a choice set compared with individuals with a weak association. Accounting for individuals' variability in gaze bias in the model can explain and accurately predict individual differences in choice behaviour.