Multialternative drift-diffusion model predicts the relationship between visual fixations and choice in value-based decisions

The dynamics of explore-exploit decisions reveal a signal-to-noise mechanism for random exploration

Growing evidence suggests that behavioral variability plays a critical role in how humans manage the tradeoff between exploration and exploitation. In these decisions a little variability can help us to overcome the desire to exploit known rewards by encouraging us to randomly explore something else. Here we investigate how such 'random exploration' could be controlled using a drift-diffusion model of the explore-exploit choice. In this model, variability is controlled by either the signal-to-noise ratio with which reward is encoded (the 'drift rate'), or the amount of information required before a decision is made (the 'threshold'). By fitting this model to behavior, we find that while, statistically, both drift and threshold change when people randomly explore, numerically, the change in drift rate has by far the largest effect. This suggests that random exploration is primarily driven by changes in the signal-to-noise ratio with which reward information is represented in the brain.

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.

A pupillary index of susceptibility to decision biases

The demonstration that human decision-making can systematically violate the laws of rationality has had a wide impact on behavioural sciences. In this study, we use a pupillary index to adjudicate between two existing hypotheses about how irrational biases emerge: the hypothesis that biases result from fast, effortless processing and the hypothesis that biases result from more extensive integration. While effortless processing is associated with smaller pupillary responses, more extensive integration is associated with larger pupillary responses. Thus, we tested the relationship between pupil response and choice behaviour on six different foundational decision-making tasks that are classically used to demonstrate irrational biases. Participants demonstrated the expected systematic biases and their pupillary measurements satisfied pre-specified quality checks. Planned analyses returned inconclusive results, but exploratory examination of the data revealed an association between high pupillary responses and biased decisions. The findings provide preliminary support for the hypothesis that biases arise from gradual information integration. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 19 December 2018. The protocol, as accepted by the journal, can be found at https://doi.org/10.6084/m9.figshare.c.4368452.v1 .

Attentional shifts and preference reversals: An eye-tracking study

The classic preference reversal phenomenon, where monetary evaluations contradict risky choices, has been argued to arise due to a focus on outcomes during the evaluation of alternatives, leading to overpricing of long-shot options. Such an explanation makes the implicit assumption that attentional shifts drive the phenomenon. We conducted an eye-tracking study to causally test this hypothesis by comparing a treatment based on cardinal, monetary evaluations with a different treatment avoiding a monetary frame. We find a significant treatment effect in the form of a shift in attention toward outcomes (relative to probabilities) when evaluations are monetary. Our evidence suggests that attentional shifts resulting from the monetary frame of evaluations are a driver of preference reversals.

A comparative analysis of neuromarketing methods for brand purchasing predictions among young adults

Until now, neuromarketing studies have usually been aimed at assessing the predictive value of psychophysiological measures gathered while watching a marketing message related to a particular product. This study is the first attempt to verify the possibility of predicting familiar and unfamiliar brand purchases based on psychophysiological reactions to a retailer television advertisement measured by EEG, EDA and eye-tracking. The number of private label products chosen later served to assess the binary dependent variable. A logistic regression model (with a prediction rate of 61.2%) was applied to determine which psychophysiological variables explained the largest part of the variance of a final purchase decision. The results show that among various measures, only the electrodermal peaks per second were significant in predicting further purchase decisions. The decision to buy was also influenced by brand familiarity. The article concludes that EDA is an unobtrusive measure of emotion-related anticipation of significant outcomes, particularly for dynamic stimuli, as related to decision-making.

Testing the drift-diffusion model

The drift-diffusion model (DDM) is a model of sequential sampling with diffusion signals, where the decision maker accumulates evidence until the process hits either an upper or lower stopping boundary and then stops and chooses the alternative that corresponds to that boundary. In perceptual tasks, the drift of the process is related to which choice is objectively correct, whereas in consumption tasks, the drift is related to the relative appeal of the alternatives. The simplest version of the DDM assumes that the stopping boundaries are constant over time. More recently, a number of papers have used nonconstant boundaries to better fit the data. This paper provides a statistical test for DDMs with general, nonconstant boundaries. As a by-product, we show that the drift and the boundary are uniquely identified. We use our condition to nonparametrically estimate the drift and the boundary and construct a test statistic based on finite samples.

Confidence in subjective pain is predicted by reaction time during decision making

Self-report is the gold standard for measuring pain. However, decisions about pain can vary substantially within and between individuals. We measured whether self-reported pain is accompanied by metacognition and variations in confidence, similar to perceptual decision-making in other modalities. Eighty healthy volunteers underwent acute thermal pain and provided pain ratings followed by confidence judgments on continuous visual analogue scales. We investigated whether eye fixations and reaction time during pain rating might serve as implicit markers of confidence. Confidence varied across trials and increased confidence was associated with faster pain rating reaction times. The association between confidence and fixations varied across individuals as a function of the reliability of individuals’ association between temperature and pain. Taken together, this work indicates that individuals can provide metacognitive judgments of pain and extends research on confidence in perceptual decision-making to pain.

Using dynamic monitoring of choices to predict and understand risk preferences

Navigating conflict is integral to decision-making, serving a central role both in the subjective experience of choice as well as contemporary theories of how we choose. However, the lack of a sensitive, accessible, and interpretable metric of conflict has led researchers to focus on choice itself rather than how individuals arrive at that choice. Using mouse-tracking-continuously sampling computer mouse location as participants decide-we demonstrate the theoretical and practical uses of dynamic assessments of choice from decision onset through conclusion. Specifically, we use mouse tracking to index conflict, quantified by the relative directness to the chosen option, in a domain for which conflict is integral: decisions involving risk. In deciding whether to accept risk, decision makers must integrate gains, losses, status quos, and outcome probabilities, a process that inevitably involves conflict. Across three preregistered studies, we tracked participants' motor movements while they decided whether to accept or reject gambles. Our results show that 1) mouse-tracking metrics of conflict sensitively detect differences in the subjective value of risky versus certain options; 2) these metrics of conflict strongly predict participants' risk preferences (loss aversion and decreasing marginal utility), even on a single-trial level; 3) these mouse-tracking metrics outperform participants' reaction times in predicting risk preferences; and 4) manipulating risk preferences via a broad versus narrow bracketing manipulation influences conflict as indexed by mouse tracking. Together, these results highlight the importance of measuring conflict during risky choice and demonstrate the usefulness of mouse tracking as a tool to do so.

Visual attention modulates the integration of goal-relevant evidence and not value

When choosing between options, such as food items presented in plain view, people tend to choose the option they spend longer looking at. The prevailing interpretation is that visual attention increases value. However, in previous studies, 'value' was coupled to a behavioural goal, since subjects had to choose the item they preferred. This makes it impossible to discern if visual attention has an effect on value, or, instead, if attention modulates the information most relevant for the goal of the decision-maker. Here, we present the results of two independent studies-a perceptual and a value-based task-that allow us to decouple value from goal-relevant information using specific task-framing. Combining psychophysics with computational modelling, we show that, contrary to the current interpretation, attention does not boost value, but instead it modulates goal-relevant information. This work provides a novel and more general mechanism by which attention interacts with choice.

Slow Drift of Neural Activity as a Signature of Impulsivity in Macaque Visual and Prefrontal Cortex

An animal's decision depends not only on incoming sensory evidence but also on its fluctuating internal state. This state embodies multiple cognitive factors, such as arousal and fatigue, but it is unclear how these factors influence the neural processes that encode sensory stimuli and form a decision. We discovered that, unprompted by task conditions, animals slowly shifted their likelihood of detecting stimulus changes over the timescale of tens of minutes. Neural population activity from visual area V4, as well as from prefrontal cortex, slowly drifted together with these behavioral fluctuations. We found that this slow drift, rather than altering the encoding of the sensory stimulus, acted as an impulsivity signal, overriding sensory evidence to dictate the final decision. Overall, this work uncovers an internal state embedded in population activity across multiple brain areas and sheds further light on how internal states contribute to the decision-making process.

Eye Gaze Patterns of Decision Process in Prosocial Behavior

Understanding human behavior remains a grand challenge across disciplines. We used eye tracking to investigate how visual perception is associated with a strategic behavior in the decision process. Gaze activity and eye movement patterns were measured in 14 human participants with different decision strategies. We also employed a social domain to force strategic behavior. We find that social interaction significantly improves the level of cooperation, prosocial decisions, and overall cooperative strategy in experiment participants. Gaze behavior in individuals with a cooperative strategy is characterized by a greater number of fixations and frequent gaze returns to the scanned areas. On the contrary, individuals with a non-cooperative strategy approach decision-making task stimuli in a distinct way with long-duration fixations and a low number of gaze returns to the areas already scanned. Social domain, which enhances cooperation and prosocial behavior, makes participants more attentive to the task stimuli in our experiments. Moreover, prolonged gaze at the area of cooperative choice testifies in favor of the cooperative decision.

An Empirical Test of the Role of Value Certainty in Decision Making

Most contemporary models of value-based decisions are built on value estimates that are typically self-reported by the decision maker. Such models have been successful in accounting for choice accuracy and response time, and more recently choice confidence. The fundamental driver of such models is choice difficulty, which is almost always defined as the absolute value difference between the subjective value ratings of the options in a choice set. Yet a decision maker is not necessarily able to provide a value estimate with the same degree of certainty for each option that he encounters. We propose that choice difficulty is determined not only by absolute value distance of choice options, but also by their value certainty. In this study, we first demonstrate the reliability of the concept of an option-specific value certainty using three different experimental measures. We then demonstrate the influence that value certainty has on choice, including accuracy (consistency), choice confidence, response time, and choice-induced preference change (i.e., the degree to which value estimates change from pre- to post-choice evaluation). We conclude with a suggestion of how popular contemporary models of choice (e.g., race model, drift-diffusion model) could be improved by including option-specific value certainty as one of their inputs.

Attraction comes from many sources: Attentional and comparative processes in decoy effects

The attraction effect emerges when adding a seemingly irrelevant option (decoy) to a binary choice shifts preference towards a target option. This suggests that choice behaviour is dynamic, i.e., choice values are developed during deliberation, rather than manifesting some pre-existing preference set. Whereas several models of multialternative and multiattribute decision making consider dynamic choice processes as crucial to explain the attraction effect, empirically investigating the exact nature of such processes requires complementing choice output with other data. In this study, we focused on asymmetrically dominated decoys (i.e., decoys that are clearly dominated only by the target option) to examine the attentional and comparative processes responsible for the attraction effect. Through an eye-tracker paradigm, we showed that the decoy option can affect subjects’ preferences in two different and not mutually exclusive ways: by focusing the attention on the salient option and the dominance attribute, and by increasing comparisons with the choice dominant pattern. Although conceptually and procedurally distinct, both pathways for decoy effects produce an increase in preferences for the target option, in line with attentional and dynamic models of decision making. Eye-tracking data provide further details to the verification of such models, by highlighting the context-dependent nature of attention and the development of similarity-driven competitive decisional processes.

Spatial encoding in dorsomedial prefrontal cortex and hippocampus is related during deliberation

Deliberation is thought to involve the internal simulation of the outcomes of candidate actions, the valuation of those outcomes, and the selection of the actions with the highest expected value. While it is known that deliberation involves prefrontal cortical areas, specifically the dorsomedial prefrontal cortex (dmPFC), as well as the hippocampus (HPC) and other brain regions, how these areas process prospective information and select actions is not well understood. We recorded simultaneously from ensembles in dmPFC and CA1 of dorsal HPC in rats during performance of a spatial contingency switching task, and examined the relationships between spatial and reward encoding in these two areas during deliberation at the choice point. We found that CA1 and dmPFC represented either goal locations or the current position simultaneously, but that when goal locations were encoded, HPC and dmPFC did not always represent the same goal location. Ensemble activity in dmPFC predicted when HPC would represent goal locations, but on a broad timescale on the order of seconds. Also, reward encoding in dmPFC increased during hippocampal theta cycles where CA1 ensembles represented the goal location. These results suggest that dmPFC and HPC share prospective information during deliberation, that dmPFC may influence whether HPC represents prospective information, and that information recalled about goal locations by HPC may be integrated into dmPFC reward representations on fast timescales.

To covet what we see: Autistic traits modulate the relationship between looking and choosing

Behavioral studies indicate that autistic traits predict reduced gaze toward social stimuli. Moreover, experiments that require participants to make an explicit choice between stimuli indicate reduced preferences for social stimuli in individuals with high autistic traits. These observations, in combination, fit with the idea that gaze is actively involved in the formation of choices-gaze toward a stimulus increases the likelihood of its subsequent selection. Although these aspects of gaze and choice behavior have been well characterized separately, it remains unclear how autistic traits affect the relationship between gaze and socially relevant choices. In a choice-based eye-tracking paradigm, we observed that autistic traits predict less frequent and delayed selection of social stimuli. Critically, eye tracking revealed novel phenomena underlying these choice behaviors: first, the relationship between gaze and choice behavior was weaker in individuals with high autistic traits-an increase in gaze to a stimulus was associated with a smaller increase in choice probability. Second, time-series analyses revealed that gaze became predictive of choice behaviors at longer latencies in observers with high autistic traits. This dissociation between gaze and choice in individuals with high autistic traits may reflect wider atypicalities in value coding. Such atypicalities may predict the development of atypical social behaviors associated with the autism phenotype. LAY SUMMARY: When presented with multiple stimuli to choose from, we tend to look more toward the stimuli we later choose. Here, we found that this relationship between looking and choosing was reduced in individuals with high autistic traits. These data indicate that autistic traits may be associated with atypical processing of value, which may contribute to the reduced preferences for social stimuli exhibited by individuals with autism.

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.

Wise or mad crowds? The cognitive mechanisms underlying information cascades

Whether getting vaccinated, buying stocks, or crossing streets, people rarely make decisions alone. Rather, multiple people decide sequentially, setting the stage for information cascades whereby early-deciding individuals can influence others' choices. To understand how information cascades through social systems, it is essential to capture the dynamics of the decision-making process. We introduce the social drift-diffusion model to capture these dynamics. We tested our model using a sequential choice task. The model was able to recover the dynamics of the social decision-making process, accurately capturing how individuals integrate personal and social information dynamically over time and when their decisions were timed. Our results show the importance of the interrelationships between accuracy, confidence, and response time in shaping the quality of information cascades. The model reveals the importance of capturing the dynamics of decision processes to understand how information cascades in social systems, paving the way for applications in other social systems.

The power of last fixation: Biasing simple choices by gaze-contingent manipulation

Among the established findings in eye movement during decision-making, decision-makers are likely to choose the last fixated option, and this phenomenon has proven robust. However, the causal link between last fixation and choices requires further examination. In Study 1 (N = 40), a gaze-contingent manipulation paradigm was developed by controlling the timing of decision prompts to manipulate the last fixation. The results showed that participants' value-based choices were biased toward the last fixated option. However, the manipulation in Study 1 may disturb their decision process, leading to an unnatural decision environment. In Study 2 (N = 40), the gaze-contingent paradigm was further developed to manipulate the last fixation by directing an additional fixation on the target option after the participants' decision prompts. The results showed that participants' choices were also biased in the uninterrupted decisions. Our findings suggest a causal link between last fixation and value-based choices.

Altering the availability of products within physical micro-environments: a conceptual framework

Altering the availability of products (e.g. food, alcohol or tobacco products) is one potential intervention to change behaviours to help reduce preventable premature deaths worldwide. However, research on these interventions lacks consistent conceptualisation, hindering clear reporting and cumulative synthesis. This paper proposes a conceptual framework – categorising intervention types and summarising constituent components – with which interventions can be reliably described and evidence synthesised. Three principal distinctions are proposed: interventions altering: (i) Absolute Availability (changing the overall number of options, while keeping the proportions comprised by any subsets of options constant); (ii) Relative Availability (changing the proportion comprised by a subset of options, yet keeping the overall number of options constant); (iii) Absolute and Relative Availability (changing both the overall number of options and the proportions comprised by subsets of options). These are subdivided into those targeting (a) a product or (b) a category of products. Mechanisms that might underlie each of these intervention types are discussed, and implications for future research highlighted. The proposed framework aims to facilitate study of a set of interventions that could contribute significantly to healthier behaviour across populations.

Value-based attention but not divisive normalization influences decisions with multiple alternatives

Violations of economic rationality principles in choices between three or more options are critical for understanding the neural and cognitive mechanisms of decision-making. A recent study reported that the relative choice accuracy between two options decreases as the value of a third (distractor) option increases and attributed this effect to divisive normalization of neural value representations. In two preregistered experiments, a direct replication and an eye-tracking experiment, we assessed the replicability of this effect and tested an alternative account that assumes value-based attention to mediate the distractor effect. Surprisingly, we could not replicate the distractor effect in our experiments. However, we found a dynamic influence of distractor value on fixations to distractors as predicted by the value-based attention theory. Computationally, we show that extending an established sequential sampling decision-making model by a value-based attention mechanism offers a comprehensive account of the interplay between value, attention, response times and decisions.

A distributional and dynamic theory of pricing and preference

Theories that describe how people assign prices and make choices are typically based on the idea that both of these responses are derived from a common static, deterministic function used to assign utilities to options. However, preference reversals-where prices assigned to gambles conflict with preference orders elicited through binary choices-indicate that the response processes underlying these different methods of evaluation are more intricate. We address this issue by formulating a new computational model that assumes an initial bias or anchor that depends on type of price task (buying, selling, or certainty equivalents) and a stochastic evaluation accumulation process that depends on gamble attributes. To test this new model, we investigated choices and prices for a wide range of gambles and price tasks, including pricing under time pressure. In line with model predictions, we found that price distributions possessed stark skew that depended on the type of price and the attributes of gambles being considered. Prices were also sensitive to time pressure, indicating a dynamic evaluation process underlying price generation. The model out-performed prospect theory in predicting prices and additionally predicted the response times associated with these prices, which no prior model has accomplished. Finally, we show that the model successfully predicts out-of-sample choices and that its parameters allow us to fit choice response times as well. This price accumulation model therefore provides a superior account of the distributional and dynamic properties of price, leveraging process-level mechanisms to provide a more complete account of the valuation processes common across multiple methods of eliciting preference. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Representation of probabilistic outcomes during risky decision-making

Goal-directed behaviour requires prospectively retrieving and evaluating multiple possible action outcomes. While a plethora of studies suggested sequential retrieval for deterministic choice outcomes, it remains unclear whether this is also the case when integrating multiple probabilistic outcomes of the same action. We address this question by capitalising on magnetoencephalography (MEG) in humans who made choices in a risky foraging task. We train classifiers to distinguish MEG field patterns during presentation of two probabilistic outcomes (reward, loss), and then apply these to decode such patterns during deliberation. First, decoded outcome representations have a temporal structure, suggesting alternating retrieval of the outcomes. Moreover, the probability that one or the other outcome is being represented depends on loss magnitude, but not on loss probability, and it predicts the chosen action. In summary, we demonstrate decodable outcome representations during probabilistic decision-making, which are sequentially structured, depend on task features, and predict subsequent action.

The drift diffusion model as the choice rule in inter-temporal and risky choice: A case study in medial orbitofrontal cortex lesion patients and controls

Sequential sampling models such as the drift diffusion model (DDM) have a long tradition in research on perceptual decision-making, but mounting evidence suggests that these models can account for response time (RT) distributions that arise during reinforcement learning and value-based decision-making. Building on this previous work, we implemented the DDM as the choice rule in inter-temporal choice (temporal discounting) and risky choice (probability discounting) using hierarchical Bayesian parameter estimation. We validated our approach in data from nine patients with focal lesions to the ventromedial prefrontal cortex / medial orbitofrontal cortex (vmPFC/mOFC) and nineteen age- and education-matched controls. Model comparison revealed that, for both tasks, the data were best accounted for by a variant of the drift diffusion model including a non-linear mapping from value-differences to trial-wise drift rates. Posterior predictive checks confirmed that this model provided a superior account of the relationship between value and RT. We then applied this modeling framework and 1) reproduced our previous results regarding temporal discounting in vmPFC/mOFC patients and 2) showed in a previously unpublished data set on risky choice that vmPFC/mOFC patients exhibit increased risk-taking relative to controls. Analyses of DDM parameters revealed that patients showed substantially increased non-decision times and reduced response caution during risky choice. In contrast, vmPFC/mOFC damage abolished neither scaling nor asymptote of the drift rate. Relatively intact value processing was also confirmed using DDM mixture models, which revealed that in both groups >98% of trials were better accounted for by a DDM with value modulation than by a null model without value modulation. Our results highlight that novel insights can be gained from applying sequential sampling models in studies of inter-temporal and risky decision-making in cognitive neuroscience.

The gaze bias effect in toddlers: Preliminary evidence for the developmental study of visual decision-making

Several studies have investigated the interactive relationship between attention and decision‐making, which is known as the gaze bias effect. Although the generalizability of the gaze bias effect has recently been observed among young and older adults, it remains unknown in which developmental period individuals start to exhibit this relationship. This question was addressed in the current study by recruiting 58 toddlers aged 2–4 years. Participants were asked to do a two‐alternative forced‐choice task in which they chose one of two soft toys they preferred while their eye movements were recorded. Results demonstrated that toddlers exhibited gaze bias regardless of age. We also found that the number of gaze shifts during the task increased according to age. These results suggest that the interactive relationship between attention and decision is acquired by the age of two. The implications of the increased number of gaze shifts for visual decision‐making are discussed.

Journey of neuroscience: marketing management to organizational behavior

Purpose

The purpose of this paper is to provide an overview of the advancement of neuroscience research works in the domains of marketing management and organizational behavior and its future scope for expansion in the area of organizational behavior.

Design/methodology/approach

A total of 77 neuroscience research articles in the area of marketing management and organizational behavior published between 2004 and 2017 were reviewed, and a possible future direction for neuroscience research in the area of organizational behavior was identified in this article.

Findings

Findings from neuroscience research works suggest that tools and techniques that are useful in the neuroscience domain are also quite powerful and reliable in the context of organizational behavior research. Here, it should be noted that not all of these are independently powerful. Therefore, in certain cases, it is desirable to use neuroscience techniques in association with existing methods.

Originality/value

Neuroscientific research works in the context of the marketing domain were started with the motivation to identify the neural signaling in association with different marketing initiatives. However, the research works have proceeded much deeper and entered into the field of consumer psychology. Further research shows that neuroscience techniques are quite useful in the understanding of consumer behavior and can be extended in the field of organizational behavior. In this study, the authors have provided the future direction of neuroscience research works in the area of organizational behavior.

Training choices toward low value options

Food decisions are driven by differences in value of choice alternatives such that high value items are preferred over low value items. However, recent research has demonstrated that by implementing the Cue-Approach Training (CAT) the odds of choosing low value items over high value items can be increased. This effect was explained by increased attention to the low value items induced by CAT. Our goal was to replicate the original findings and to address the question of the underlying mechanism by employing eye-tracking during participants’ choice making. During CAT participants were presented with images of food items and were instructed to quickly respond to some of them when an auditory cue was presented (cued items), and not without this cue (uncued items). Next, participants made choices between two food items that differed on whether they were cued during CAT (cued versus uncued) and in pre-training value (high versus low). As predicted, results showed participants were more likely to select a low value food item over a high value food item for consumption when the low value food item had been cued compared to when the low value item had not been cued. Important, and against our hypothesis, there was no significant increase in gaze time for low value cued items compared to low value uncued items. Participants did spend more time fixating on the chosen item compared to the unchosen alternative, thus replicating previous work in this domain. The present research thus establishes the robustness of CAT as means of facilitating choices for low value over high value food but could not demonstrate that this increased preference was due to increased attention for cued low value items. The present research thus raises the question how CAT may increase choices for low value options.

The Transition from Evaluation to Selection Involves Neural Subspace Reorganization in Core Reward Regions

Economic choice proceeds from evaluation, in which we contemplate options, to selection, in which we weigh options and choose one. These stages must be differentiated so that decision makers do not proceed to selection before evaluation is complete. We examined responses of neurons in two core reward regions, orbitofrontal (OFC) and ventromedial prefrontal cortex (vmPFC), during two-option choice with asynchronous offer presentation. Our data suggest that neurons selective during the first (presumed evaluation) and second (presumed comparison and selection) offer epochs come from a single pool. Stage transition is accompanied by a shift toward orthogonality in the low-dimensional population response manifold. Nonetheless, the relative position of each option in driving responses in the population subspace is preserved. The orthogonalization we observe supports the hypothesis that the transition from evaluation to selection leads to reorganization of response subspace and suggests a mechanism by which value-related signals are prevented from prematurely driving choice.

Incentive motivation improves numerosity discrimination: Insights from pupillometry combined with drift-diffusion modelling

Recent studies show that training the approximate number system (ANS) holds promise for improving symbolic math abilities. Extending this line of research, the present study aims to shed light on incentive motivation of numerosity discrimination and the underlying mechanisms. Thirty-two young adults performed a novel incentivized dot comparison task, that we developed, to discern the larger of two numerosities. An EZ-diffusion model was applied to decompose motivational effects on component processes of perceptual decision-making. Furthermore, phasic pupil dilation served as an indicator of the involvement of the salience network. The results of improved accuracy and a higher information accumulation rate under the reward condition suggest that incentive motivation boosts the precision of the ANS. These novel findings extend earlier evidence on reward-related enhancements of perceptual discrimination to the domain of numerosity perception. In light of the Adaptive Gain Theory, we interpret the results in terms of two processes of gain modulation driven by the locus coeruleus-norepinephrine system. Specifically, the reward-induced increase in pupil dilation may reflect incentive modulation of (i) salience attention during reward anticipation towards incentivized stimuli to upregulate stimulus processing that results in a larger drift rate; and (ii) response caution that leads to an increased decision threshold.

The Art of Influencing Consumer Choices: A Reflection on Recent Advances in Decision Neuroscience

In recent years, our knowledge concerning the neurobiology of choice has increased tremendously. Research in the field of decision-making has identified important brain mechanisms by which a representation of the subjective value of an option is built based on previous experience, retrieved and compared to that of other available options in order to make a choice. One body of research, in particular, has focused on simple value-based choices (e.g., choices between two types of fruits) to study situations very similar to our daily life decisions as consumers. The use of neuroimaging techniques has deepened and refined our knowledge of decision processes. Additionally, computational approaches have helped identifying and describing the mechanisms underlying newly found components of the decisional process. They provide mechanistic explanations for diverse biases that can drive decision makers away from their own preferences or from rational choices. It is now clear that both attentional and affective factors can exert robust effects on an individual's decisions. Because these factors can be manipulated externally, academic research and theories are of great interest to the marketing industry. This approach is becoming increasingly effective in manipulating consumer behavior and has the potential to become even more effective in the future. Another line of research has revealed differences in the decision-making neural circuitry that underlie sub-optimal choice behavior, rendering some individuals particularly vulnerable to marketing strategies. As neuroscientists, we wonder whether relevant institutions should direct their efforts toward raising citizens' awareness, demanding more transparency on marketing applications and regulate the most pervasive communication techniques in marketing, in view of their current use and of recent research progress.

Perceptual salience influences food choices independently of health and taste preferences

Background

Making decisions about food is a critical part of everyday life and a principal concern for a number of public health issues. Yet, the mechanisms involved in how people decide what to eat are not yet fully understood. Here, we examined the role of visual attention in healthy eating intentions and choices. We conducted two-alternative forced choice tests of competing food stimuli that paired healthy and unhealthy foods that varied in taste preference. We manipulated their perceptual salience such that, in some cases, one food item was more perceptually salient than the other. In addition, we manipulated the cognitive load and time pressure to test the generalizability of the salience effect.

Results

Manipulating salience had a powerful effect on choice in all situations; even when an unhealthy but tastier food was presented as an alternative, healthy food options were selected more often when they were perceptually salient. Moreover, in a second experiment, food choices on one trial impacted food choices on subsequent trials; when a participant chose the healthy option, they were more likely to choose a healthy option again on the next trial. Furthermore, robust effects of salience on food choice were observed across situations of high cognitive load and time pressure.

Conclusions

These results have implications both for understanding the mechanisms of food-related decision-making and for implementing interventions that might make it easier for people to make healthy eating choices.

Neural underpinnings of value-guided choice during auction tasks: An eye-fixation related potentials study

Values are attributed to goods during free viewing of objects which entails multi- and trans-saccadic cognitive processes. Using electroencephalographic eye-fixation related potentials, the present study investigated how neural signals related to value-guided choice evolved over time when viewing household and office products during an auction task. Participants completed a Becker-DeGroot-Marschak auction task whereby half of the stimuli were presented in either a free or forced bid protocol to obtain willingness-to-pay. Stimuli were assigned to three value categories of low, medium and high value based on subjective willingness-to-pay. Eye fixations were organised into five 800 ms time-bins spanning the objects total viewing time. Independent component analysis was applied to eye-fixation related potentials. One independent component (IC) was found to represent fixations for high value products with increased activation over the left parietal region of the scalp. An IC with a spatial maximum over a fronto-central region of the scalp coded the intermediate values. Finally, one IC displaying activity that extends over the right frontal scalp region responded to intermediate- and low-value items. Each of these components responded early on during viewing an object and remained active over the entire viewing period, both during free and forced bid trials. Results suggest that the subjective value of goods are encoded using sets of brain activation patterns which are tuned to respond uniquely to either low, medium, or high values. Data indicates that the right frontal region of the brain responds to low and the left frontal region to high values. Values of goods are determined at an early point in the decision making process and carried for the duration of the decision period via trans-saccadic processes.

Sensitivity of reaction time to the magnitude of rewards reveals the cost-structure of time

The Drift-Diffusion Model (DDM) is the prevalent computational model of the speed-accuracy trade-off in decision making. The DDM provides an explanation of behavior by optimally balancing reaction times and error rates. However, when applied to value-based decision making, the DDM makes the stark prediction that reaction times depend only on the relative utility difference between the options and not on absolute utility magnitudes. This prediction runs counter to evidence that reaction times decrease with higher utility magnitude. Here, we ask if and how it could be optimal for reaction times to show this observed pattern. We study an algorithmic framework that balances the cost of delaying rewards against the utility of obtained rewards. We find that the functional form of the cost of delay plays a key role, with the empirically observed pattern becoming optimal under multiplicative discounting. We add to the empirical literature by testing whether utility magnitude affects reaction times using a novel methodology that does not rely on functional form assumptions for the subjects’ utilities. Our results advance the understanding of how and why reaction times are sensitive to the magnitude of rewards.

GLAMbox: A Python toolbox for investigating the association between gaze allocation and decision behaviour

Recent empirical findings have indicated that gaze allocation plays a crucial role in simple decision behaviour. Many of these findings point towards an influence of gaze allocation onto the speed of evidence accumulation in an accumulation-to-bound decision process (resulting in generally higher choice probabilities for items that have been looked at longer). Further, researchers have shown that the strength of the association between gaze and choice behaviour is highly variable between individuals, encouraging future work to study this association on the individual level. However, few decision models exist that enable a straightforward characterization of the gaze-choice association at the individual level, due to the high cost of developing and implementing them. The model space is particularly scarce for choice sets with more than two choice alternatives. Here, we present GLAMbox, a Python-based toolbox that is built upon PyMC3 and allows the easy application of the gaze-weighted linear accumulator model (GLAM) to experimental choice data. The GLAM assumes gaze-dependent evidence accumulation in a linear stochastic race that extends to decision scenarios with many choice alternatives. GLAMbox enables Bayesian parameter estimation of the GLAM for individual, pooled or hierarchical models, provides an easy-to-use interface to predict choice behaviour and visualize choice data, and benefits from all of PyMC3's Bayesian statistical modeling functionality. Further documentation, resources and the toolbox itself are available at https://glambox.readthedocs.io.

What drives the (un)empathic bystander to intervene? Insights from eye tracking

Norm violations (e.g., unfair transgressions) are often met with punishment even by people who are not directly affected. However, punishing a transgressor is not the only option for a bystander to restore justice. Empathic concerns may dictate instead to give a helping hand to a victim. Using a pre-registered, fully incentivized eye-tracking study (N = 47), we investigated the cognitive mechanism linking bystanders' empathic concern and justice-restoring intervention behaviour. The results show that not only the decision to intervene (i.e., either costly compensating the victim or punishing the transgressor) but also the attention directed towards a victim's payoffs (i.e., measured by the proportion of fixations) during the decision-making period systematically varied with the individual level of empathic concern. Exploring this link further, we additionally instructed participants to focus on specific components of the norm violation, namely the (un)fair conduct of the offender or the victim's feelings. Surprisingly, highly empathic bystanders were more likely to punish the offender when the norm violation was highlighted. However, we did not observe the modulation of the instructed focus on the link between gaze-based measures and empathic concern. Overall, these results provide initial evidence about the interacting impact of empathic concern as well as the focus on specific components of the norm violation when bystanders respond to unfair transgressions.

Spatial language difficulties reflect the structure of intact spatial representation: Evidence from high-functioning autism

Previous studies have shown that the basic properties of the visual representation of space are reflected in spatial language. This close relationship between linguistic and non-linguistic spatial systems has been observed both in typical development and in some developmental disorders. Here we provide novel evidence for structural parallels along with a degree of autonomy between these two systems among individuals with Autism Spectrum Disorder, a developmental disorder with uneven cognitive and linguistic profiles. In four experiments, we investigated language and memory for locations organized around an axis-based reference system. Crucially, we also recorded participants' eye movements during the tasks in order to provide new insights into the online processes underlying spatial thinking. Twenty-three intellectually high-functioning individuals with autism (HFA) and 23 typically developing controls (TD), all native speakers of Norwegian matched on chronological age and cognitive abilities, participated in the studies. The results revealed a well-preserved axial reference system in HFA and weakness in the representation of direction within the axis, which was especially evident in spatial language. Performance on the non-linguistic tasks did not differ between HFA and control participants, and we observed clear structural parallels between spatial language and spatial representation in both groups. However, there were some subtle differences in the use of spatial language in HFA compared to TD, suggesting that despite the structural parallels, some aspects of spatial language in HFA deviated from the typical pattern. These findings provide novel insights into the prominence of the axial reference systems in non-linguistic spatial representations and spatial language, as well as the possibility that the two systems are, to some degree, autonomous.

Enhanced striatal and prefrontal activity is associated with individual differences in nonreinforced preference change for faces

Developing effective preference modification paradigms is crucial to improve the quality of life in a wide range of behaviors. The cue‐approach training (CAT) paradigm has been introduced as an effective tool to modify preferences lasting months, without external reinforcements, using the mere association of images with a cue and a speeded button response. In the current work for the first time, we used fMRI with faces as stimuli in the CAT paradigm, focusing on face‐selective brain regions. We found a behavioral change effect of CAT with faces immediately and 1‐month after training, however face‐selective regions were not indicative of behavioral change and thus preference change is less likely to rely on face processing brain regions. Nevertheless, we found that during training, fMRI activations in the ventral striatum were correlated with individual preference change. We also found a correlation between preference change and activations in the ventromedial prefrontal cortex during the binary choice phase. Functional connectivity among striatum, prefrontal regions, and high‐level visual regions was also related to individual preference change. Our work sheds new light on the involvement of neural mechanisms in the process of valuation. This could lead to development of novel real‐world interventions.

Goal congruency dominates reward value in accounting for behavioral and neural correlates of value-based decision-making

When choosing between options, whether menu items or career paths, we can evaluate how rewarding each one will be, or how congruent it is with our current choice goal (e.g., to point out the best option or the worst one.). Past decision-making research interpreted findings through the former lens, but in these experiments the most rewarding option was always most congruent with the task goal (choosing the best option). It is therefore unclear to what extent expected reward vs. goal congruency can account for choice value findings. To deconfound these two variables, we performed three behavioral studies and an fMRI study in which the task goal varied between identifying the best vs. the worst option. Contrary to prevailing accounts, we find that goal congruency dominates choice behavior and neural activity. We separately identify dissociable signals of expected reward. Our findings call for a reinterpretation of previous research on value-based choice.

Decision-making research has confounded the reward value of options with their goal-congruency, as the task goal was always to pick the most rewarding option. Here, authors separately asked participants to select the least rewarding of a set of options, revealing a dominant role for goal congruency.

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.

Increased Preference and Value of Consumer Products by Attentional Selection

It is usually assumed that individuals base their preferences for products or other items on the utility or value associated with the items. However, there is evidence that the attentional selection of an item alone already modulates the preference for that item. This has been shown, for instance, in preference choice tasks with unknown consumer products. Products that served as targets in a preceding visual search task were preferred to former distractor products. However, it is unclear whether such effects can also be observed when individuals have pre-existing attitudes toward products and whether attentional selection can change the perceived value of products. Hence, the aim of the present research was to replicate the attentional-selection effect on choice with known products and examine whether selective attention affects the perceived value of products beyond choosing the items. In two experiments, we replicated the attentional-selection effect on item preference in a choice task. Items that had served as targets in the search task were preferred to previous distractors. Introducing a response deadline in the preference-choice task in Experiment 2 did not further increase this effect. However, the value of former targets was rated higher than that of former distractors. Hence, the present results indicate that attentional selection not only affects preference choices but can also increase the value of attended and selected items.

A computational account of threat-related attentional bias

Visual selective attention acts as a filter on perceptual information, facilitating learning and inference about important events in an agent's environment. A role for visual attention in reward-based decisions has previously been demonstrated, but it remains unclear how visual attention is recruited during aversive learning, particularly when learning about multiple stimuli concurrently. This question is of particular importance in psychopathology, where enhanced attention to threat is a putative feature of pathological anxiety. Using an aversive reversal learning task that required subjects to learn, and exploit, predictions about multiple stimuli, we show that the allocation of visual attention is influenced significantly by aversive value but not by uncertainty. Moreover, this relationship is bidirectional in that attention biases value updates for attended stimuli, resulting in heightened value estimates. Our findings have implications for understanding biased attention in psychopathology and support a role for learning in the expression of threat-related attentional biases in anxiety.