Journal of Experimental Psychology: General

We study how confidence in perceptual decisions depends on whether it is communicated verbally (e.g., "very likely") or numerically (e.g., "80% certainty"). We find that verbal expressions more reliably distinguish correct from incorrect choices than numerical reports, challenging the common assumption that numerical probabilities provide more precise representations of uncertainty. Additionally, in a dyadic decision-making task in which participants can revise their initial reports based on a partners choice and expressed confidence, verbal and numerical reports are equally effective in supporting accurate revisions of initial judgments. Together, these results underscore the effectiveness of verbal expressions as a means of conveying decision confidence.

The willingness to exert cognitive effort is essential but is constrained by the subjective cost of effort. Although effortful tasks are often avoided, positive bias about ones own performance may help sustain engagement with cognitive demands. Here, participants completed an effort-based decision-making task and reported trial-by-trial predictions of their own performance, allowing us to quantify performance prediction error (PPE) as the discrepancy between subjective and objective accuracy. The results showed that PPE was predominantly positive and increased with effort level, indicating greater overestimation under higher cognitive demands. Using a computational model, we show that choices were best explained by a learning model in which rewarded trials accompanied by positive PPE decreased subsequent sensitivity to effort. A confidence-based control model did not provide a better account of choices, suggesting that this effect was better captured by positive performance bias than by confidence alone. Our findings provide a computational account of how biased self-evaluation may attenuate the subjective cost of cognitive effort and extend the positive bias literature to the task need for cognitive effort.

Human decision-making behavior varies widely across individuals and task conditions. This variability is often interpreted in terms of different suboptimal decision strategies, but the principles that govern these suboptimalities remain poorly understood. We propose that some of these suboptimalities can be understood in terms of limited-capacity, but information-efficient, inference processes that inform decision-making. We developed and used new theoretical and empirical approaches to compare the amount of information used (capacity) to the effectiveness with which it was used (accuracy) by individual participants performing simple inference tasks. Variable, suboptimal performance was explained largely by inference that had variable, limited information capacity. Across these capacity limits, and regardless of whether the inference strategy was based on optimal or heuristic principles, the information was used effectively to maximize accuracy for a given capacity. This form of flexible and efficient information bottleneck reflects fundamental capacity-accuracy tradeoffs that structure individual variability.

Visual working memory (vWM) is often linked to conscious experience and visual imagery, but it is typically described as a system that stores separate, independent items. These assumptions are difficult to reconcile, given the unified nature of conscious experience. Here, we test the hypothesis that vWM relies on at least two distinct representations: an underlying, unconscious memory trace and a consciously accessible, integrated representation. A total of 216 participants performed a change-detection task, in which they rated their perceptual awareness of the memory display during the maintenance interval. Critically, we manipulated the statistical properties of the displays (average item size and size variability) to probe sensitivity to unified ensemble-level structure. Results revealed a dissociation between subjective and objective measures. Perceptual awareness increased for displays with larger, more variable items, whereas objective performance improved for displays with smaller, less variable items. Despite this difference, subjective awareness still predicted performance, and even incorrect responses showed consistent biases rather than random guesses. Importantly, individual differences in imagery vividness (VVIQ) were selectively associated with subjective awareness and estimation bias, but not with objective correctness. These precision biases were further shaped by display statistics, suggesting that multiple representations can guide behavior. Together, our findings support a reinterpretation of vWM performance in which task responses can draw on both unconscious and consciously accessible representations. One possible explanation for these behavioral patterns is that subjective experience reflects integrated, ensemble-like representations, while objective performance depends more strongly on item-specific information. Public significance statementsWorking memory allows us to temporarily hold and use information, and differences in this ability are closely linked to broader cognitive skills such as intelligence. This study shows that these differences may not depend only on how much information people can store, but also on how they experience it: some individuals appear to rely more on consciously accessible, image-like representations, especially when memory is uncertain or prone to error. By demonstrating that subjective experience and the vividness of imagery can shape behavior independently of objective accuracy, these findings suggest that how we use memory may be as important as how much we can store, with implications for understanding individual differences in cognition.

Goal-directed behavior often requires sustained effort across a sequence of interdependent decisions, yet the determinants of persistence in such contexts remain poorly understood. Here, we investigated how individuals regulate persistence in a novel sequential effort-based task in which they controlled an avatar through successive checkpoints to reach a final goal and could make repeated attempts following failure. At each attempt, participants could choose either to persist in the same task or to disengage toward an easier but less rewarding alternative. We found that decisions to persist or disengage were jointly shaped by multiple interacting factors. Disengagement increased with task difficulty and lower skill level. It also increased with repeated attempts and time-on-task, indexing fatigue, and with accumulated errors, indexing lack of progress. Conversely, proximity to the goal promoted persistence and shaped decision dynamics by reducing choice conflict during persistence decisions and increasing hesitation during disengagement near the goal. Notably, clearing the first checkpoint produced a sharp increase in persistence, suggesting that early success plays a pivotal role. Furthermore, persistence reflected both retrospective and prospective evaluations of effort, with prior investment promoting commitment and anticipated effort reducing it. Finally, disengagement was preceded by short-term performance decline but not by gradual increases in decision conflict, suggesting relatively abrupt strategy shifts following repeated failures. Together, these findings provide a comprehensive account of persistence in sequential effortful tasks, showing that decisions to persist or disengage are jointly shaped by multiple factors related to fatigue, (lack of) progress, goal proximity, and early success.

Saccades made during memory maintenance prioritize memory for the saccade target, but it is unclear if this benefit is specific to a location or extends across memorized objects. In three experiments, we examined whether saccadic selection spreads to other locations within the same object. In Experiment 1, we asked observers to remember three oriented Gabors presented either within contour-defined objects or without object structure. A subsequent movement cue prompted observers to move their eyes to the indicated location. We then probed memory for stimuli at locations equidistant from the saccade target, in either the same or a different object. Memory was best for stimuli at locations congruent with the saccade target, and consistently weaker for other stimuli presented in the same or a different object than the saccade target. In Experiment 2, we created more complex objects by adding more object features to the stimulus. Again, memory performance was best for stimuli congruent with the saccade target location, whereas memory in incongruent trials was worse and similar for stimuli in the same and different object as the saccade target. In Experiment 3, we tested if saccadic selection is present and propagates within the object in a change detection task. Again, memory performance (i.e., change detection) was best at the saccade target location. However, this memory benefit also spread to other locations within the same object. Our results imply that saccadic selection in visual working memory is primarily space-based but can also spread towards locations within the object where a saccade was directed.

Attentional control balances proactive suppression of predictable distractors with reactive suppression of unexpected ones. Yet, how internal states such as alertness shape this balance is unclear. Using pupillometry and eye tracking across two probability-cueing experiments (conducted in 2024) with varying distractor prevalence, we distinguished tonic (baseline pupil size across blocks) from trial-level pupil size fluctuations (trial-by-trial residual variability in pre-stimulus pupil size). With moderate prevalence, suppression of frequent-region distractors developed gradually, whereas high prevalence induced near-immediate suppression. Behavioral measures (e.g., reaction times) were closely linked to tonic and trial-level pupil size fluctuations. Critically, both alertness components jointly influenced control: during early learning, heightened trial-level pupil size increased distractor capture and reduced target fixations, whereas later on, suppression shifted to a proactive mode resilient to trial-level fluctuations. Under high prevalence, this shift occurred faster. Notably, higher trial-level pupil size generally accelerated first target selection. These findings show that tonic alertness and trial-level alertness fluctuations dynamically regulate reactive and proactive control during statistical learning. Impact StatementThis study shows that people become better at ignoring predictable distractions over time, but that this improvement depends not only on what they have learned about the task environment, but also on their current level of alertness. By combining eye tracking and pupil measures, we found that temporary increases in alertness can sometimes help people orient more quickly to relevant information, yet during earlier stages of learning they can also make attention more vulnerable to distracting events. These findings suggest that successful focus in complex environments depends on a dynamic interplay between learned expectations and moment-to-moment fluctuations in mental state, with implications for understanding sustained attention in settings such as monitoring, driving, and other tasks that require people to stay engaged while resisting distraction.

Language production requires the coordination of multiple cognitive processes. The ability to anticipate and override a habitual response in favor of a contextually-appropriate response are key subprocesses of cognitive control which enable speakers to communicate effectively. Word retrieval involves the co-activation of semantically related alternatives from which the speaker must select the appropriate target representation. Although cognitive control mechanisms have been proposed to contribute to resolving semantic interference during language production, the nature of these control processes remain unclear. Studies investigating the temporal dynamics of cognitive control during decision making tasks have led to a distinction between two operating processes: proactive control, initiated prior to the occurrence of conflict, and reactive control recruited after conflict is detected. We investigated the roles of proactive and reactive control in resolving interference between competing linguistic representations during word retrieval. We analyzed congruency sequence effects combined with delta-plot distributional analyses to dissociate potential adjustments in proactive versus reactive cognitive control in a picture-naming task manipulating semantic context compared to a minimally-linguistic Stroop-like paradigm. Reaction time distributional properties following semantically related trials revealed the engagement of proactive control in semantic interference resolution during word retrieval in the PWI task. In contrast, reactive inhibitory control was engaged in resolving semantic interference following low conflict trials. This distinction was not present in the minimally-linguistic task, which did not appear to engage adaptive control to the same extent. These findings demonstrate that both proactive and reactive cognitive control mechanisms contribute to language production, and are engaged dynamically, adjusting trial-by-trial to resolve semantic interference during word retrieval. In addition, our study provides important insight into the comparison of language with other cognitive domains and positions linguistic paradigms as being instrumental in the study of cognitive control dynamics.

The ability to mentally rotate objects is a fundamental feature of human cognition, and humans can use this ability to make choices about objects based on their geometry. However, remarkably little is known about how such choices are reached, and what sort of visual information might facilitate them. We devised an experiment where participants had to mentally simulate an object's rotation to choose which of two objects was better for a subsequent task based on its shape alone. We also tracked their gaze while they made their choice, to see which visual information they were using to facilitate this mental simulation. We found that participants were consistently able to choose the most suitable object for the task, and, remarkably, the visual information they sampled was directly linked to their choices. Put simply, participants made better choices when they looked at more informative regions of the objects, and participants who sampled regions that were better for facilitating mental simulation made better choices overall. These findings reveal a direct link between fixations, simulation, and decision-making, suggesting that to perform any fine-grained mental simulation people need to direct their gaze at specific, informative points of an object to simulate its two-dimensional proximal image displacement.

Humans have been shown to use an internalized representation or prior of Earth gravity to predict object motion. Often, this is shown using the fact that humans tend to neglect an objects acceleration when predicting its motion. This bias tends to be ameliorated when the acceleration acting on the object is Earth gravity. It is currently unclear whether this prior can also be used when assessing ones self-motion. We immersed two cohorts of 20 seated participants in a virtual environment of a street scene. They experienced simulated self-motion consistent with either flying straight upwards towards the ceiling (ANTI-GRAVITY) or falling downwards towards the ground (GRAVITY). After 0.8 s to 1.4 s of motion, the screen turned blank, and participants pressed a button to indicate when they thought they reached the surface they were moving towards. In Experiment 1, they were instructed to use their eye level as the reference (i.e., when they imagined the floor or ceiling to be aligned with their eyes). In Experiment 2, they used their feet or the top of theirs heads to judge when they had reached the ceiling or floor, respectively. In Experiment 1, no differences between the GRAVITY and ANTI-GRAVITY conditions were found in terms of accuracy or precision, contrary to our hypotheses. In Experiment 2 participants pressed the button significantly later in the ANTI-GRAVITY condition than in the GRAVITY condition, in line with the predictions of the use of a gravity prior, while precision remained unaffected. Speculatively, the instructions in Experiment 1 may have made the experience less ecologically valid and immersive, thus preventing participants from activating the strong gravity prior. Experiment 2 (head/feet as reference), on the other hand, provides convincing evidence for an involvement of this prior in the prediction of self-motion. In sum, the study provides evidence that humans can rely on an internalized representation of Earth gravity when predicting self-motion, at least under ecologically valid task conditions. The absence of effects in Experiment 1 and their presence in Experiment 2 suggest that activation of this gravity prior depends on the framing of the task.

Interception of moving objects requires the nervous system to compensate for sensory delays and uncertainty, yet how behavior is controlled remains debated. Key questions concern whether predictive processes play any role at all and, if so, whether they rely on simple motion extrapolation or incorporate internalized physical priors, such as gravity. Another open question is whether observers adopt a single control strategy or flexibly switch between predictive and reactive control - or between different predictive strategies - depending on task demands. To address these questions, we developed a virtual interception task in which participants intercepted moving targets under systematically varied conditions. We manipulated gravity (1g vs. 0g), visual availability (occluded vs. non-occluded), target velocity, and the initial spatial configuration of the ball and paddle (same vs. opposite side). Results indicate that interception is supported by predictive mechanisms across conditions. Behavioral patterns during occluded 0g trials suggest that participants extrapolate target motion using expectations consistent with gravity. Target velocity, visual occlusion, and task geometry modulated movement strategies, indicating that predictive control is flexibly adapted to task demands. These findings support the view that interception relies on predictive internal models incorporating structured physical priors while revealing flexible, context-dependent adaptations to sensory and task constraints.

Internal forward models predict the sensory consequences of motor commands; however, whether the anticipated availability of post-action feedback contributes to the precision of the action itself remains unknown. We manipulated the predictability of post-release visual occlusion in skilled basketball players. Participants performed three-point shots while wearing liquid-crystal shutter goggles. The study tested three conditions: a no-occlusion baseline, certain-occlusion condition in which players knew that their vision would be occluded at ball release in every trial, and random-occlusion condition in which they could not predict whether an occlusion would occur. Shooting accuracy declined in the certain-occlusion condition relative to the no-occlusion condition (49.2% vs 41.7%). The random-occlusion condition did not differ from the baseline (46.1%). Within the random condition, the accuracy in occluded trials were virtually identical to that in non-occluded trials (46.6% vs 46.2%), even though the immediate visual occlusion was the same as in the certain-occlusion condition. These results demonstrate that it is not the absence of post-action information per se that disrupts motor execution, but the prior certainty that action consequences will be unavailable. We interpret this finding as a prospective influence of anticipated consequence loss, whereby motor execution depends on whether the prediction-outcome loop remains closable.

Perception is typically biased towards prior expectations. In some cases, however, it seems repelled away from expectations, such that percepts appear less like what is expected. Even more intriguingly, separate studies have recently reported that predictions derived from gravity may shape perception in opposing ways. Specifically, gravity causes unsupported objects to accelerate downwards, leading to two predictions; that objects will move downwards (location prior) and at an increasing speed (acceleration prior). There is evidence that perceptual judgements are attracted towards location priors yet repelled from acceleration ones. Here we examine these effects in the same paradigm to determine whether they result from different types of stimuli and judgement, or more interestingly, might result from opposite influences of common predictive mechanisms influencing perception. We first replicate previous reports of a systematic bias to report upward moving objects as more accelerating than downward moving objects: effectively a repulsion from acceleration priors. We then show that the effect applies both at the level of retinal space and due to contextual cues concerning gravitational direction. Finally, we find that participants errors in a location reproduction task are similarly consistent with a repulsion from acceleration priors and, simultaneously, with an attraction towards location priors. We conclude by considering the ways in which these concurrent attractive and repulsive biases may reflect mechanisms optimising fast, accurate, and informative experiences in our ever-changing sensory world, therefore optimising the interface between perception and learning. Public Significance StatementIn a series of behavioural experiments, we show that expectations about how objects move due to gravity concurrently attract perception towards the prediction that objects move downwards, and repel perception away from the prediction that they do so at an increasing rate. These opposing influences inform current theories of perceptual processing, which explain how expectations may generate percepts that are fast, veridical, and informative.

Confirmation bias impacts judgments and decisions across a range of domains including finance, policy and science. Here we examine whether explicitly labelling information as true or false disrupts a core underlying computational mechanism that can generate this pervasive bias - asymmetric learning. Human participants (Study 1: N=47; Study 2: N=57) completed a 2 alternative forced choice (2AFC) task previously used to test for the presence of confirmation bias. Participants made choices between pairs of options that could win or lose money and received either factual or counterfactual feedback after each choice. We introduced a key novel feature into the task - providing explicit cues that signalled to participants whether feedback they had seen was true (verified) or false (debunked). Learning in response to feedback was attenuated under false compared to true labels but was present under both. Fitting participants choices to computational models enabled us to examine how sensitivity to the feedback varied as a function of both the label (true/false) and confirmation (confirmatory/disconfirmatory). This revealed a distinct pattern of learning rates typical of confirmation bias (enhanced learning from positive prediction errors for chosen options and from negative prediction errors for unchosen options) in response to both true and false labels. The findings highlight how confirmation bias plays an important role in the effectiveness of interventions designed to verify true and/or debunk false claims. Verification is less likely to succeed when information disconfirms prior beliefs. Conversely, debunking false claims is unlikely to succeed when the information confirms ones prior beliefs.

The ability to orient or attend to sensory events is generally greater in response to visual and auditory cues occurring together than in response to single-modality cues occurring alone. In such cases the perceptual fusion of cross-modal stimuli (multisensory integration) depends on low-level features (e.g., location, intensity) and follows well established principles. However, less is known about multisensory integration mechanisms when behavioral responses are less direct and require top-down control. Here we investigate this in human participants using an urgent multisensory choice task that effectively dissociates stimulus-driven and goal-driven contributions to performance based on their distinct temporal signatures. Task conditions varied the modality of the cues (auditory, visual, or both), their location (left or right), and the rule defining the correct choice (look toward or away from a given cue). When spatially coincident cues were associated with the same response rule ("look away"), we observed multisensory enhancement and performance remained close to a statistical expectation as the choice process unfolded. However, when spatially disparate cues were associated with different rules but the same target, one cue dominated performance and the other produced crossmodal capture, i.e., low-level competition. The results indicate that the efficacy of multisensory integration is dictated by the stimulus-and goal-driven signals produced by each cue, with all four factors rapidly interacting in accordance to the dynamics of spatial attention. Significance StatementAuditory and visual stimuli located near each other in space and time are typically bound into a single sensory percept that draws attention most effectively. However, it is unclear whether such "multisensory integration" occurs during behaviors that go beyond directly attending or orienting to cue stimuli and require top-down control. We investigated this using a novel task design with which stimulus-driven and goal-driven contributions to performance can be accurately identified. We found that multisensory enhancement depends not so much on the complexity of the requested cue-response associations, but rather on the timing and alignment of the stimulus-and goal-driven signals derived from each cue (auditory and visual) -- similar to the way that such signals dictate the allocation of spatial attention.

Humans rely on multiple sensory modalities, such as vision, audition, and touch, to perceive materials in everyday life. Previous research shows that multisensory perception leads to facilitation, yet the mechanisms responsible for this facilitation remain poorly understood. One potential mechanism is crossmodal prediction, whereby input from one modality generates predictions about another. While substantial research on multisensory facilitation has focused on bottom-up processes, such as spatial, temporal, and semantic congruency, the role of crossmodal predictions, particularly in material perception, has received little attention. To address this gap, we conducted two experiments, a reaction time task and a material rating task, in which participants viewed computer-generated animations of familiar objects being dropped to the ground. The paradigm exploited the natural temporal structure of impact events: pre-impact visual appearance provides information about an objects material and therefore can generate expectations about the forthcoming impact sound. Critically, participants saw the event only until before the impact, after which the video was masked. Thus, vision and audition were temporally aligned but not presented concurrently, allowing us to isolate the influence of visually driven expectations on the incoming auditory information without a bottom-up conflict. In some trials, the sound matched the expected material, but in a subset, it was incongruent, violating expectations elicited by the preceding visual information. Across both experiments, participants took longer to respond on incongruent than congruent trials, suggesting increased processing demands. In the rating task, incongruent trials also shifted material judgments, such that ratings reflected a weighted combination of incoming auditory information and visually driven predictions, with large individual differences in relative cue weighting. These findings suggest that priors on material properties from one modality, specifically vision, not only establish high-level expectations within the modality about an objects future state, but also extend across modalities.

Action selection involves two systems: a model-free reinforcement learning strategy, which relies on experience with action-outcome pairs, and a model-based reinforcement learning strategy, which enables more flexible behavior via inference using a model of the invariant environmental structure. Although environmental change requires more flexible behavior, the ability of volatility, a higher-order statistic that captures how rapidly or frequently the environment changes, to systematically modulate these strategies remains unclear. We examined the effects of reward volatility on arbitration between model-free and model-based reinforcement learning strategies using two modified two-step decision tasks. In Experiment 1, participants performed tasks with different levels of reward volatility and time pressure. In Experiment 2, we systematically manipulated reward volatility across a broader range to assess the relationship between volatility and learning strategy. Behavioral data were analyzed using model-agnostic one-trial and multitrial back analyses, reinforcement learning simulations, and hierarchical Bayesian model fitting. Across experiments, reward volatility exerted an inverse U-shaped nonlinear effect on the arbitration between model-free and model-based reinforcement learning strategies, as the model-based learning strategy was strongly driven at intermediate levels of reward volatility. These modulation effects were observed only in individuals who had learned the transition structure in the task, whereas those who had not learned the transition structure relied on the model-free learning strategy regardless of reward volatility. Reinforcement learning simulations revealed that the relative advantage of the model-based learning strategy over the model-free learning strategy peaked at intermediate levels of reward volatility. Additionally, increased time pressure shifted behavior toward the model-free learning strategy. These results demonstrated that, humans do not always use the model-based reinforcement learning strategy in uncertain and dynamic environments, even when they are aware of the task structure, supporting cost-benefit optimization. Author SummaryThe ability to flexibly guide behavior by carefully considering future consequences is fundamental to a prominent property of human intelligence and rationality. However, what drives this deliberative system? In this study, we investigated the factors that promote deliberative versus habitual behavior using decision-making tasks with uncertain structures and changing rewards. We found that participants who spontaneously learned the hidden transition structure in the task used this knowledge to guide deliberative behavior. Conversely, participants who did not learn the structure relied primarily on habitual strategies, repeating actions that had previously been rewarded. Among participants who learned the structure, the degree of deliberative behavior changed nonlinearly with reward volatility, in which the speed at which rewards changed over time. We also observed that limiting the decision time reduced deliberative behavior and promoted habitual responding. These findings suggest that under uncertain and dynamic environments, deliberative control is adaptively regulated according to cost-benefit optimization. Our results contribute to understanding how humans flexibly adjust their behavioral control systems in response to environmental conditions.

Many forms of memory are thought to rely on visual imagery, but individuals who report lacking visual imagery (aphantasia) can still perform various memory tasks. There is, however, evidence that aphantasia may lead to less detailed autobiographical memories, suggesting there may be deficits in the underlying cognitive processes that support personal memories. One such process is associative memory, which requires binding of different types of information. Here, we tested whether associative visual memory is intact in aphantasia. We assessed 72 self-identified individuals with aphantasia and 77 controls who reported having visual imagery. Participants completed an associative memory task which involved memorising displays where a unique object in a specific location was associated with a particular colour fixation point. Individuals with aphantasia performed equivalently to controls for object locations and outperformed controls on the associated object-identity. In addition, whereas controls were significantly worse at remembering associated object-identity than object-location, individuals with aphantasia showed no such difference. Both groups showed good metacognitive performance evidenced by a positive correlation between confidence and accuracy; there were no significant differences in confidence between the groups. Reported strategies varied between groups: a large proportion of control participants reported using visual imagery and self-reported use of imagery positively correlated with performance. Conversely, individuals with aphantasia mostly reported using nonvisual strategies to remember the associations. Overall, the findings suggest that individuals with aphantasia can form associative memories using nonvisual strategies. Thus, difficulties with autobiographical memory in aphantasia seem unlikely to be due to fundamental issues with associative memory.

Facial features are known to play a key role in how we judge a persons traits. However, in many scenarios people do not evaluate a person in isolation but are required to compare and choose between multiple candidates. Yet, the principles that govern these decisions remain unknown. In economic literature, decisions are known to be influenced by the context of available options, but it is unclear to what extent these principles apply to social decisions about naturalistic stimuli such as human faces. Here, we bridged between these two fields of research - face evaluations and economic decisions - to investigate whether facial preferences can be systematically shifted by context, exhibiting a well-known choice context effect, the "decoy effect". We asked participants to choose the person they think is more trustworthy from either a set of two ("target" and "competitor") or three faces (including a "decoy"). Based on economic theory, we carefully selected face sets using their trustworthiness rankings and perceptual similarity, and tested them across several exploratory samples (n=100-400) and one large, preregistered experiment (n=1099). We found that adding a decoy face to the choice set increased participants choices of the target option by up to 7%, while the decoy face was rarely selected, consistent with a typical decoy effect. These results provide direct evidence that social judgements are affected by the same context-dependent principles known from economic choices, and that the decoy effect can be generalized to complex naturalistic stimuli such as human faces, relevant to various real-world applications.

Social decision-making depends on inferring others hidden preferences from observable behavior. Yet it remains unclear how humans combine choices with process cues such as response times and gaze when learning about others in real-time interaction. Here we combine a novel multi-attribute bargaining task with eye-tracking and show that multiple decision-process cues support preference inference. Across 75 buyer-seller dyads, buyers acceptance rates tracked offer utility, rejection speed reflected decision confidence, and first fixations preferentially targeted the highest-weighted attribute. Sellers adapted subsequent offers using choices, response times, and, when available, gaze cues. A hierarchical inference and choice model suggested that sellers balanced expected utility with expected information gain and updated their beliefs in a Bayesian manner. Although gaze access did not improve overall performance, it changed how sellers used attentional information. These findings shed light on how humans infer others hidden preferences from decision dynamics in real-time social interaction.