Cognition

A fundamental question in visual perception is how the human visual system transforms the rich kinematic information present in observed actions into coherent social meaning. We addressed this by validating a 5-dimensional action space model - defined by Formidableness, Friendliness, Locomotion, Abduction, and Environmental Interaction - as a perceptual representation of avatar-conveyed actions. Using Representational Similarity Analysis, we first demonstrated strong topological correspondence between the models geometry and the structure of independent perceptual judgements, with cross-validated regression confirming the model as a generative framework that reliably predicts how observers evaluate novel actions. A morphing paradigm further revealed that perceptual ratings scaled approximately linearly with geometric distances along model dimensions, with each dimension selectively predicting its corresponding perceptual quality, satisfying the criteria for a valid psychological metric space. Critically, the 5D model showed substantially stronger alignment with semantic representations of actions than with their raw skeletal kinematics - an association robust to statistical control for kinematic similarity. This dissociation suggests that higher-order social-evaluative dimensions of action perception are largely invariant to low-level motion statistics, consistent with a hierarchical visual processing architecture in which kinematic input is progressively abstracted into a compact, semantically organised representational space optimised for social inference.

Michottes "launching displays" are animations of collision-like interactions between two objects that elicit a stable and robust impression that one object, the launcher, caused another object, the target, to move. Although it is well-known that unexpected disruptions of movement continuation between launcher and target decrease causal impressions in centre-to-centre collisions, the role of observers visual uncertainty around predicted moving trajectories remains relatively unexplored. In this work, we (1) assess observers uncertainty around post-collision moving angles in a trajectory prediction task and (2) collect their causal impression in a causality rating task. In the latter task, observers viewed centre-to-centre collisions with different levels of movement continuity between the launcher and the target disc. By presenting different launch orientations, we exploited the well-known oblique effect to vary trajectory prediction uncertainty within individuals. If observers rely on their trajectory predictions to rate the causality of the collision, we expect their accuracy in (1) to have a systematic influence on their causality rating in (2). We replicate previous findings that observers report stronger causal impressions in trials where the target and the launcher move in the same direction and weaker causal impressions for collisions where the target and the launcher moving trajectory deviated. Furthermore, causality ratings were on average higher for oblique compared to cardinal launch directions, implying that increased sensory uncertainty induces a stronger causal impression. We hope this work will inspire deeper empirical assessments and computational models describing the role of sensory uncertainty and predictive processes in shaping subjective impressions of causality.

Building upon foundational psychological theories of event segmentation, this study addresses the limitation of overreliance on temporal boundaries as the primary segmentation criterion. Drawing on two experiments of direct and indirect causation in Mandarin Chinese, this study demonstrates how cognitive segmentation granularity and semantic integration jointly shape syntactic encoding. Results reveal distinct event encoding patterns for direct and indirect causation: coarse-grained segmentation leads to compact syntactic structures (e.g., verb-resultatives), while fine-grained segmentation yields varied multi-clausal expressions. Chinese speakers update event models via prediction errors of intentionality and protagonists, and tend to establish event boundaries at goal-relevant action endpoints when construing causal chains. These conceptual dimensions exert a modulating influence on both event segmentation and semantic integration. We propose a triad model integrating event segmentation, semantic integration, and linguistic specificity, providing a unified framework for elucidating the mind-language interface in conceptual construction and event coding of causation.

Previous research has shown that the eyes pupils are larger when imaging dark as compared to bright objects or scenes. Based on this, it has been claimed that pupil size is a sensitive marker of mental-imagery vividness. We investigated this claim in three experiments, conducted in two countries (Norway and The Netherlands; Ntotal = 115), in which participants read, listened, or freely imagined stories that evoked a sense of darkness or brightness. In addition, participants rated their imagery vividness after each story, as a measure of moment-to-moment fluctuations in imagery; and their imagery vividness in general, as a measure of individual differences in imagery. Overall, we found that darkness-evoking stories induced larger pupils than brightness-evoking stories, although this effect was highly variable and only statistically reliable for longer (> 1 min) audio stories. Importantly, we consistently found that this pupil-size difference (dark - bright) was largest for vividly imagined stories. Finally, we did not find any relationship between this pupil-size difference and individual differences in general in imagery. We conclude that the strength of pupil-size changes in response to imagined darkness or brightness reflects moment-to-moment fluctuations in imagery vividness within an individual rather than individual differences in imagery vividness as a personal trait.

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.

Recent approaches conceptualize mental imagery as a simulatory mode of perceptual experience, which relies on the voluntary engagement of the same top-down prediction processes that shape our perception of the external world. If so, then imagery should induce similar predictive biases as those that are known to govern the perceptual representation of others behaviour. In four experiments, participants saw object-directed approach and avoidance actions and reported the hands last seen location after their sudden disappearance. All revealed robust predictive biases, showing that perceptual judgments are illusorily distorted towards the implied goals of the actions and away from obstacles. Importantly, the experiments also showed that prior action imagery suffices to induce similar biases, so that perceptual judgments become distorted not only towards the actions expected next steps but also the imagined ones. These imagery-induced biases were robust across stimulus sets and measurement methods. They reflect prior knowledge of how people move and can be induced not only through imagery of the actions itself, but also through imagery of situations in which the actions are merely expected. These data show that imagery induces similar perceptual expectations as other prediction processes, in line with the proposal that imagery reflects the voluntary control of predictive pathways that govern an events perceptual representation. Moreover, imagery can drive prediction processes, inducing expectations about events likely to occur in the imagined (not observed) realities, suggesting shared pathways through which imagery and prediction may support mental simulation and counterfactual reasoning. Public Significance StatementThis study uses the perception of other peoples behaviour as a testing bed to advance the hypothesis that imagery can be understood as predicted perception: that, when people imagine, they make voluntary use of the same prediction mechanisms that otherwise allow them to anticipate - and visualise - how a situation will develop further. In four experiments, the study shows (1) that imagining anothers behaviour induces the expectation that their actions will develop in the imagined manner, (2) that imagining situations elicits expectations about how people will behave within them, (3) that these imagery-induced expectations are integrated with other expectations people have about others behaviour and (4) subtly distort how these behaviours are visuospatially represented. The findings demonstrate a link between imagery and predictive perceptual abilities and reveal how imagery can act as a key tool in peoples ability to anticipate relevant futures and explore counterfactual realities.

Perceptual confidence reflects the ability to evaluate the evidence that supports perceptual decisions. It is thought to play a critical role in guiding decision-making, but only a few empirical studies have actually investigated the function of confidence. To address this issue, we designed a perceptual task in which participants provided a confidence judgment on the accuracy of their perceptual decision. Then, they viewed the response of a machine or human partner, and they were instructed to decide whether to keep or change their initial response. We observed that confidence predicted participants decision to keep or change their initial responses more than task difficulty and perceptual accuracy. This suggests that confidence, as a subjective evaluation of uncertainty, enables us to weigh our decisions, driving the interaction with a partner. Furthermore, confidence judgments could be predicted by pre-response pupil dynamics, suggesting that arousal changes are linked to confidence computations. This study contributes to our understanding of the function of confidence in decision-making and highlights the possibility of using pupil dynamics as a proxy of confidence.

A key challenge in todays fast-paced digital world is to integrate information from various sources, which differ in their reliability. Yet, little is known about how explicit probabilistic information about the likelihood that a source provides correct information is used in decision-making. Here, we investigated how such explicit reliability markers are integrated and the extent to which individuals have metacognitive insight into this process. We developed a novel paradigm where participants viewed opinions from sources of varying reliability to make a choice between two options. After each decision, they rated how much they felt a given source influenced their choice. Using computational modelling, we estimated the effective reliability that participants assigned to each source and how leaky their decision process was. Overall, we found that participants acted as if sources were more informative than they actually were, inflating the reliability they were communicated. Interestingly, we show that even though sources were explicitly labelled as unreliable, these sources biased choices, as if these were treated as moderately reliable. Additionally, the presence of sources known to be lying, reliably voting for the incorrect answer, impaired performance by increasing decision leakiness. Despite these biases, participants showed some metacognitive awareness of what influenced their choices: they were generally accurate in reporting the degree to which a source influenced them and were aware of the impact unreliable sources had on their decisions. These results suggest that people make suboptimal use of explicit source reliability, but have some awareness of their suboptimal choices. Author summaryIn everyday life, we constantly draw on information from multiple sources that differ in how much they can be trusted. When scrolling through social media or online platforms, for instance, we know some sources are reliable, others dubious, and some clearly misleading. In this study, we created a simple task mirroring this everyday challenge to examine how people form beliefs using information from sources of known, varying reliability. Using a computational model, we uncovered two systematic ways in which decisions fell short of optimal. First, sources that were clearly identified as unreliable still influenced the opinions and final choice of individuals. Second, peoples choices were often swayed by the last piece of information they saw, especially in a context where misleading sources were present. Surprisingly, participants were aware of some of these biases and could report which sources had shaped their choices, suggesting that awareness of bias is not necessarily sufficient to overcome it.

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.

Autonomous systems have pervaded many aspects of human activities. However, research suggest that the interaction with those machines may influence human decision-making processes. These effects raise ethical concerns in moral situations. We created an ad hoc setup to investigate the effects of system autonomy on moral decision-making and human agency in a trolley-like dilemma. In a battlefield simulation, participants had to decide whether to initiate an attack depending on conflicting moral values. Our results suggest that our paradigm is suitable for future research aimed at understanding the effects of system autonomy on moral decision -making and human agency.

The transformative effects of interpersonal synchrony on reshaping the relationship between the self and the group by fostering self-other blurring are well-documented. However, these findings largely rely on self-reported measures, leaving aspects of the self inaccessible to explicit measures unexplored. We combined the Implicit Association Task (IAT) with conventional explicit evaluations of self-other blurring to examine how experiences of synchronous movement may also swiftly shape implicit measures indicative of self-other blurring. In three online experiments participants experienced synchronous movement as opposed to no movement (Experiment 1) or unpredictable movement (Experiment 2) or asynchronous movement (Experiment 3) with virtually presented agents. Our data indicate that synchronous movement led to higher levels of self-other blurring on the Inclusion of Other in Self (IOS) scale and implicit self-concept evaluations on the IAT. Participants demonstrated a preference for associating self-related words with images of the synchronous group, while associating other-related words with images from the no-movement, unpredictable, and asynchronous movement groups. This suggests that experiencing synchronous movement with a group influences implicit semantic self-associations. These findings suggest that interpersonal synchrony may alter self-concept at both an embodied and semantic level, extending beyond conscious affiliation. Our combined methodology offers a deeper insight into the impact of synchronous experiences on self-constructs and social relationships.

Tonal languages differ from other languages in their use of pitch (tones) to distinguish words. Lifelong experience speaking and hearing tonal languages has been argued to shape auditory processing in ways that generalize beyond the perception of linguistic pitch to the perception of pitch in other domains like music. To examine this, we first conducted a meta-analysis, finding moderate evidence for this idea, but in studies strongly limited by mostly small sample sizes in only a few tonal languages and countries. This makes it challenging to disentangle the effects of linguistic experience from variability in music training experience, cultural differences, and other potential confounds. To address these issues, we used web-based citizen science to test this question on a global scale. We assessed music perception skill in n = 34, 034 native speakers of 19 tonal languages (e.g., Mandarin, Yoruba) and compared their performance to n = 459, 066 native speakers of other languages, including 6 pitch-accented (e.g., Japanese) and 29 non-tonal languages (e.g., Hungarian). Whether or not participants had taken music lessons, native speakers of all 19 tonal languages had an improved ability to discriminate musical melodies. But this improvement came with a trade-off: relative to speakers of pitch-accented or non-tonal languages, tonal language speakers were also worse at processing the musical beat. These results, which held across tonal languages from a variety of geographic regions and were robust to geographic and demographic variation, demonstrate that linguistic experience shapes music perception ability, with implications for relations between music, language, and culture in the human mind.

Forced-choice paradigms in facial emotion perception research require observers to commit to a single label and discard any simultaneous activation of related categories that participants might otherwise express. We introduce a multi-select rating paradigm in which 112 participants rated each of 52 facial-expression stimuli on 13 emotion categories using continuous 0-to-10 sliders, alongside a separate authenticity slider. Stimuli were generated using OpenAIs DALL-E 3 from an orthogonal four-factor design (emotion, race, gender, age), allowing demographic balance and compositional uniformity more readily than photograph-based stimulus sets permit. Linear mixed-effects models with participant random intercepts and logistic regression with cluster-robust standard errors were applied to 5,824 trials. Perceived authenticity reliably predicted agreement between the participants top-rated category and the AI-prompted target emotion (odds ratio 1.03 per +1 unit, p < .001), and a principal-components analysis of the 13-emotion rating matrix recovered three interpretable dimensions accounting for over half of trial-level variance, with the first two corresponding to the canonical valence and arousal axes. Hierarchical clustering exposed a tight cluster of self-conscious negative emotions (sadness, embarrassment, shame) that does not align with the canonical basic-versus-complex emotion distinction. Collapsing the participants top-rated emotion to its cluster raised the trial-level prompt-agreement rate from 43.1% to 86.9% ({Delta} = +43.8 percentage points), indicating that participants most common departures from the prompted target fell within rather than across clusters. Among Autism-Spectrum Quotient subscales, the Social-Skill subscale showed a robust interaction with contempt-target faces (p < .001), with higher Social-Skill scores predicting elevated contempt ratings of approximately 1.2 points on the 0-to-10 scale. Two further secondary patterns emerged in the AQ-subscale-by-emotion grid, including an opposing-direction effect of Imagination and Attention-to-Detail subscales on awe ratings. We acknowledge that some of the recovered structure may partly reflect statistical regularities of the AI-generation pipeline rather than human perceptual geometry alone, and we discuss this caveat at length below. Multi-select rating with hyper-realistic AI-generated stimuli produces a richer perceptual probe than the forced-choice paradigms that have dominated this literature, and reveals subscale-level autistic-trait associations that AQ-total analyses obscure.

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.

Over the past two decades, converging evidence from neuroscience and psychology has shown that predictions based on learnt statistical regularities exert a widespread influence on perception, action and cognition. Predictive processes in cognition and the brain are usually modelled as tracking objective event probabilities, deriving predictions and prediction errors from the statistical structure of the environment. However, our subjective models of our environments do not always align with these objective statistics. Currently we know little about how these subjective representations may determine the predictive functions. To separate subjective and objective contributions to prediction, we conducted three studies where cues (actions or tones) predicted visual outcomes (shapes or Gabors) with varying contingencies, and adult participants discriminated these outcomes. Uniquely to our paradigm, participants also reported their experiences of the statistical structure embedded in the task - the subjective probability (Experiment 1; N = 68), expectedness (Experiment 2; N = 35), or surprise (Experiment 3; N = 35) associated with the outcomes. When modelling subjective ratings alongside objective structure, the speed of perceptual decisions was best explained by independent, additive contributions of both. The decision itself was usually only explained by the subjective ratings, with little additional variance explained by objective statistical structure. These findings suggest that subjective experience may play a key, overlooked role in predictive processes, and open a host of interesting questions about the relative objective and subjective contributions to prediction, perception, and learning.

Reinforcement learning (RL) models explain how people adapt behavior through incremental value updates but assume that individual experiences are not explicitly stored or retrieved. Across two experiments (N = 282 and N = 1,818), we tested whether people rely on such explicit memory representations during experience-based choice. Participants sampled outcomes from two lotteries and, in an "ignore" condition, were instructed to disregard specific outcomes before deciding. Ignoring these outcomes substantially altered preferences, suggesting that choices were guided by explicit episodic representations rather than cumulative reinforcement. Frequency judgments revealed generally accurate memory for experienced outcomes, but reduced precision for continuous compared with discrete outcome distributions. These findings challenge purely incremental RL accounts and support theories proposing that human choice integrates flexible episodic memory with reinforcement mechanisms, bridging models of learning, memory, and decision-making. Statement of RelevanceHow people learn from experience shapes decisions in many everyday situations, from choosing a stock to invest in to selecting a restaurant or deciding which route to take home. Our experiments show that people do not rely solely on incremental value updates but instead exploit memory representations of past outcomes to guide choices. When asked to ignore certain outcomes, participants adjusted their preferences in line with these representations. These findings reveal that human decision-making also engages flexible use of memory for past experiences, highlighting the importance of memory-based mechanisms in adaptive, real-world choice behaviour.

Light extramission is a popular yet erroneous model of human vision positing that light projects through the eyes over surrounding objects, allowing them to become visible. However, light extramission research has failed to distinguish between light and other types of emissions coming from the eyes, thereby discounting the possibility that extramission mechanisms might hold true for phenomena other than light. Here, we explored the thought extramission model, which is the notion that thoughts emanate from the eyes in the form of visualized representations. We show that the eyes project thoughts a short distance away in the form of high-resolution conceptual maps whose structure collapses at great distances. We also demonstrate that sensory filtering of thought projection by reducing light contrast lowers the resolution of conceptual maps. Our results highlight the supporting role of the visual system for thought processes relying on contrast, luminance, and perspective formation.

Theories of embodied language hold that word processing is automatically accompanied by sensory and motor simulations. For example, when you read the word sun, a sensory simulation of brightness as well as a motor simulation of pupil constriction would be automatically triggered. Consistent with this notion, Mathot, Grainger, and Strijkers (2017) found that the eyes pupil was slightly smaller after reading single words that were associated with brightness (e.g. sun) as compared to darkness (e.g. night); that is, the pupil light response was modulated by the semantic brightness of words. However, (other) key findings within the field of embodied language have proven difficult to replicate, and we therefore felt that it was crucial to replicate the effect of semantic brightness on pupil size. To this end, we conducted a close-but-non-identical replication of two key experiments from Mathot, Grainger, and Strijkers (2017): one experiment with visually presented words, and one experiment with spoken words. Both experiments were successfully replicated. We propose that cognitive modulations of the pupil light response reflect activity in visual brain areas; therefore, the effect of semantic brightness on pupil size can be used as a marker for the involvement of visual brain areas in language processing, and thus to address a wide variety of key questions within psycholinguistics.

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.

In our everyday lives, we continually need to commit to courses of future action even when direct feedback is not available. The expected reward of an action depends not only on a single decision but on a sequence of interdependent choices that will happen in the future. Admittedly, most decisions we make concern sequences of actions as opposed to single-step choices. To make these decisions, we rely on our ability to plan and forecast the potential outcomes of sequential decisions. However, how humans plan under novel real-world scenarios remains poorly understood. We developed a novel task to investigate how humans evaluate options and prioritize their decisions during planning in realistic situations. In each trial, a written planning scenario (for example, "plan your birthday party") was followed by 9 pictures divided into three categories (e.g., 3 birthday cakes, 3 party locations, and 3 decorations). Participants were asked to choose one option from each category to create the best possible plan - the one with the highest subjective value - while both their response and gaze were tracked. With each option possibly having a different subjective value according to the other selected options, the required planning process resembles the navigation of an internal decision tree, whose complexity grows exponentially with the number of choices and future outcomes considered. Our results show that participants gather information at all levels of the decision trees, as suggested by their gaze-switching behavior. In addition, based on their assessments of importance and difficulty, we find that participants generally choose first what they report to be the most important and easiest category and then the least important and most difficult one. Overall, our task provides a novel means to study planning behavior in realistic, multi-alternative situations, as participants can freely navigate through all levels of the decision tree by subjectively evaluating potential scenarios through internal sampling and imagination.