Ian Krajbich

Many global challenges require changing social norms to promote collective action. Interventions providing information about others' behavior can increase prosocial actions like charitable giving, but some people conform while others resist, and interventions are sometimes counterproductive. It remains unclear whether people fail to conform because of inattention to social information or strategic choices to ignore it. Here, we use eye-tracking in repeated dictator games with varying social information to show that resistance to social information reflects strategic attention allocation rather than ignorance. While 75% of participants conformed to some degree, most did so selfservingly: two-thirds conformed more to low norms than high norms or only conformed when already exceeding the norm. Critically, conformity was unrelated to overall attention-even non-conformers spent substantial time viewing others' decisions. Instead, attention patterns differed by social preference. Altruistic participants looked at and returned to high givers. In contrast, selfish participants only attended to high givers when giving was cheap, continued searching after encountering high givers, and increasingly disengaged from social information as the experiment progressed. These findings reveal that some people are aware of the norm but strategically seek information that justifies their preferences. Our results demonstrate that attention dynamics can identify underlying prosocial preferences and predict who will respond to norm-based interventions.

Subjective value ratings guide everyday choices, and value-based decision-making research collects them in many experiments. Yet the field has no common method for eliciting them. Studies use different response scales, instructions, and stimulus sets, and their ratings are rarely shared in a form that allows them to be used together. We present the Liking Initiative, a curated database of 759,399 individual ratings from 38 studies (59 datasets) covering 2,217 items, rated by 5,377 participants summed across datasets. Each rating is provided along with dataset-level metadata documenting the response scale, the question asked, and the source publication. The database is available through a web application, versioned releases on Zenodo, and R and Python packages. Because many items were rated in more than one dataset, item-level ratings can be compared across samples, response scales, and laboratories.

Randomness in choice can be attributed to many potential mechanisms, including shocks to utility and attention. In a gaze-contingent lottery experiment, we observe attention and choice jointly and provide reduced-form facts that discriminate between these mechanisms. We measure choice reversals and first-order stochastic dominance violations, as well as two margins of attention-extensive (whether an option is seen) and intensive (how long it is examined). Choice 'randomness' is a nearly deterministic function of attention: from the gaze record alone we predict the chosen option in 93% of within-person choice reversals (against a benchmark of 50%), and classify dominated from dominating choices in 95% of repetitions (against a benchmark of 85%). We further show that the extensive margin of attention accounts for well under half of each behavior; behaviors around choice reversals (but not around dominance violations) change at certain gaze thresholds (0.3 seconds, and 0.5 seconds); and attention does not reliably screen out dominated options Moreover, the relationships between attention and both reversals and dominance violations change depending on menu size, but controlling for extensive attention eliminates menu-size effects in reversals while only slightly attenuating them for FOSD violations.

When indicating a preference between two options, decision makers are thought to compare and accumulate evidence in an attention-guided process. Little is known about this process’s neural substrates or how visual attention affects the representations of accumulated evidence. We conducted a simultaneous eye-tracking and fMRI experiment in which human subjects gradually learnt about the value of two food-lotteries. With this design, we were able to extend decisions over a prolonged time-course, manipulate the temporal onset of evidence, and therefore, dissociate sampled and accumulated evidence. We observed inconsistent correlations of both sampled and accumulated evidence with activity in the ventromedial prefrontal cortex (vmPFC), the ventral striatum, and the intraparietal sulcus (IPS), and more consistent correlations of accumulated evidence with activity in the dorsolateral prefrontal cortex (dlPFC) and pre-supplementary motor area (pre-SMA). We also found that more gaze on an option increased its choice probability and that gaze consistently amplified accumulated-value signals above and beyond the non-gaze-modulated signals in the pre-SMA and partially in the dlPFC, providing novel evidence that visual attention has lasting effects on decision variables and suggesting that activity in the pre-SMA and dlPFC reflects gaze-weighted accumulated evidence. These results shed new light on the neural mechanisms underlying gaze-driven decision processes.

When indicating a preference between two options, decision makers are thought to compare and accumulate evidence in an attention-guided process. Little is known about this process’s neural substrates or how visual attention affects the representations of accumulated evidence. We conducted a simultaneous eye-tracking and fMRI experiment in which human subjects gradually learned about the value of two food-lotteries. With this design we were able to extend decisions over a prolonged time-course, manipulate the temporal onset of evidence, and therefore dissociate sampled and accumulated evidence. We observed inconsistent correlations of both sampled and accumulated evidence with activity in the ventromedial prefrontal cortex (vmPFC), the ventral striatum, and the intraparietal sulcus (IPS), and more consistent correlations of accumulated evidence with activity in the dorsolateral prefrontal cortex (dlPFC) and pre-supplementary motor area (pre-SMA). We also found that more gaze on an option increased its choice probability and that gaze consistently amplified accumulated-value signals above and beyond the non-gaze-modulated signals in the pre-SMA and partially in the dlPFC, providing novel evidence that visual attention has lasting effects on decision variables and suggesting that activity in the pre-SMA and dlPFC reflect gaze-weighted accumulated evidence. These results shed new light on the neural mechanisms underlying gaze-driven decision processes.

Attention plays a key role in decision-making by directing limited cognitive resources to relevant information. It has been proposed that attention also biases the decision process, due to a multiplicative interaction between attention and subjective value (e.g., Krajbich et al., 2010). We tested two predictions of models that posit a causal multiplicative effect of attention on decision formation: (i) the last fixation should be more informative about the choice when the overall value of the alternatives is high, and (ii) more attention should be directed to the chosen option when choices conflict with stated preferences than when they do not. Reanalyzing several datasets from a food-choice task, we found no evidence supporting these predictions. An alternative model where attention reflects choices after the decision has completed explains key observations, including the last-fixation bias, the gaze-cascade effect, and the effect of the overall value of the alternatives on response times. However, this model does not fully account for the association between dwell time and choice. We conclude that gaze behavior prior to the choice report likely reflects both decisional and post-decisional processes.

Attention plays a key role in decision-making by directing limited cognitive resources to relevant information. It has been proposed that attention also biases the decision process, due to a multiplicative interaction between attention and subjective value (e.g., Krajbich et al., 2010). We tested two predictions of models that posit a causal multiplicative effect of attention on decision formation: (i) the last fixation should be more informative about the choice when the overall value of the alternatives is high, and (ii) more attention should be directed to the chosen option when choices conflict with stated preferences than when they do not. Reanalyzing several datasets from a food-choice task, we found no evidence supporting these predictions. An alternative model where attention reflects choices after the decision has completed, explains key observations, including the last-fixation bias, the gaze-cascade effect and the effect of the overall value of the alternatives on response times. However, this model does not fully account for the association between dwell time and choice. We conclude that gaze behavior prior to the choice report likely reflects both decisional and post-decisional processes.