Cognition

Bayesian decision theory proposes that people make statistically rational decisions by combining prior knowledge with sensory information (likelihoods). This framework successfully explains many aspects of human behaviour. However, debate persists over whether people perform precise Bayesian computations (i.e., explicit Bayesian strategy) or rely on less demanding strategies - such as approximations or heuristics - that produce Bayesian-like behaviour (i.e., implicit Bayesian strategy). To address this, we examined people's sensitivity to metamers: different prior-likelihood combinations yielding identical optimal policies. An explicit Bayesian observer would show a temporary performance drop immediately after a switch of prior-likelihood combination, followed by recovery, reflecting prior updating. In two studies, we trained participants to estimate hidden target locations drawn from a Gaussian prior. On each trial, scattered dots provided likelihood information. Over time, participants learned the prior and combined it with likelihood information to infer target locations. We then covertly introduced an untrained prior-likelihood metamer. Unlike explicit Bayesian observers, participants' performance declined after the switch and persisted throughout the untrained pair presentation. This finding challenges strict Bayesian interpretations of task performance and suggests that participants rely instead on likelihood-sensitive strategy that is neither explicit Bayesian nor does it not fully integrate prior information. Our study demonstrates how metamer manipulations can distinguish behaviour that merely appears Bayesian, from behaviour genuinely produced by Bayesian computations, and calls for the use of metamers for ruling out alternative explanations of Bayesian-like behaviours.

The Sense of Agency (SoA), the experience of being in control of ones own actions, is thought to emerge from the comparison of internal sensorimotor predictions with afferent feedback. Classical comparator models treat SoA as arising from a prediction-feedback comparison. Volitional action likely engages multiple forward models that predict distinct features of an outcome, such as its timing and spatial trajectory. Whether prediction errors arising from these distinct forward models are integrated into a domain-general representation of agency, and if so by what computational logic, remains unresolved. We addressed this question using a Virtual Reality reaching task. Participants observed a virtual hand replicating their movements while we independently manipulated two sensorimotor domains: temporal delay and spatial angle deviation, in isolation and in factorial combinations. After each trial, participants made an SoA judgment. We examined whether SoA responses show computational hallmarks of integration between different features of sensorimotor prediction. Specifically, we pre-registered three computational models (Multiplicative, Minimum, and Mean) and compared their fit to per-trial responses. Across an exploratory sample (N = 16) and a pre-registered replication (N = 38), SoA declined monotonically with conflict magnitude in both domains. Critically, a Multiplicative integration rule consistently outperformed the Minimum and Mean rules. These results provide direct evidence for domain-general integration between prediction errors in SoA, governed by a multiplicative computational logic.

Why does an angry face feel uncomfortable? The answer is that it signals a threat. However, a face is only part of an encounter, and distance, facial stimulus type, and gaze may shape discomfort regardless of perceived anger. To separate these cues, we conducted three within-subjects virtual reality experiments. In each experiment, 24 adults viewed avatars at intimate, personal, and social distances (30, 100, and 300 cm, respectively) and rated the faces perceived anger and their own discomfort; head movement was recorded in Experiments 2 and 3. In Experiment 1, the expression (angry, neutral) and facial color (natural, red) were crossed with distance; in Experiment 2, a featureless mannequin served as a nonface comparison; and in Experiment 3, the gaze direction (direct, averted) was manipulated. Expression primarily determined perceived anger, whereas distance predominantly determined discomfort: A nearby neutral face was uncomfortable despite low perceived anger (Experiment 1). A neutral human face was more uncomfortable than a mannequin, although both received similarly low perceived-anger ratings (Experiment 2). Direct gaze increased the discomfort without changing perceived anger (Experiment 3). Backward head movement exhibited a similar pattern, with participants leaning back more from human faces than from the mannequin. These results indicate that the discomfort associated with an angry face is not merely explained by perceived anger. Instead, social discomfort was differentially associated with interpersonal distance and gaze direction and differed between the human-face and mannequin conditions.

This study characterizes how people combine visual and tactile directional cues while acting in a fully immersive 360{degrees} virtual environment. Participants used a vibrotactile belt and VR headset to localize targets while we manipulated visual reliability and the spatial discrepancy between visual and tactile signals. Behaviorally, degraded visual input made visual responses slower, less precise, and more susceptible to tactile pull, whereas tactile-guided responses remained comparatively stable. We then asked whether these behavioral changes reflected a change in multisensory binding or a change in sensory uncertainty. A Bayesian Causal Inference (BCI) framework captured the structure of behavior under high visual reliability and continued to track individual differences under low visual reliability, even though its absolute goodness-of-fit decreased. Under extreme visual noise, Bayesian Information Criterion sometimes favored a simpler Maximum Likelihood Estimation (MLE) model, but MLE showed poor absolute fit and did not capture meaningful behavioral variability. This dissociation shows that statistical parsimony and explanatory validity can diverge when behavior becomes highly variable. BCI-derived parameters further indicated that degraded vision increased visual uncertainty, while the prior tendency to bind visual and tactile cues remained stable. Kinematic analyses added a complementary insight: early movement trajectories were strongly shaped by tactile signals, even when final localization was visually guided. Together, these findings suggest that visual-tactile integration in 360{degrees} environments depends on sensory reliability and task demands, with tactile cues providing fast body-centered guidance when visual information is limited.

How conceptual knowledge is organized in the mind remains difficult to observe directly in natural behavior. Here we show that explaining knowledge to others brings out spatially structured representations of conceptual memory in naturalistic speech. Participants with varying schizotypy traits learned associations between two conceptual dimensions through either image-based or language-based input, and subsequently described their memory strategies or explained how they would teach the information to others. Spatial structure was more likely to emerge during teaching than reflection, particularly following image-based learning. As predicted by prior evidence that visual input requires the active construction of internal relational scaffolding, cognitive disorganization selectively attenuated spatial expression after image-based, but not language-based, learning. These findings establish naturalistic speech as a behavioral readout of conceptual map structure, and suggest that a common mechanism links map construction and cognitive disorganization across task performance and verbal communication.

Spontaneous thought changes over time, yet the moment-to-moment factors shaping these changes remain poorly understood. We examined whether heartbeat-related bodily processing, operating largely outside explicit awareness, is associated with the organization of ongoing thought. Forty adults performed an auditory attention task with intermittent thought probes in which auditory events were scheduled either 200 ms after each detected R peak (synch condition) or independently of ongoing cardiac timing (asynch condition), with occasional omissions in both conditions. Heartbeat-synchronous omissions in this paradigm have been shown to induce cardiac deceleration and modulate heartbeat-evoked potentials (HEPs). The score of the heartbeat counting task (HCT) served as a behavioral index related to cardiac interoceptive accuracy. The results showed that higher HCT score was associated with a stronger synch-asynch shift toward more self-related and less task/self-unrelated thought. HEPs showed a synch-related negative shift across several thought groups, although the magnitude of this condition effect did not reliably differ among thought groups. Overall thought-group distributions were similar across conditions, while transition analyses suggested a tendency in the synch condition toward more frequent transitions linking predominantly interoceptive stimulus-dependent thought with both on-task and self-related thought. Together, these findings suggest that heartbeat-related bodily processing may influence the organization of spontaneous thought, particularly in individuals with greater cardiac interoceptive accuracy. Bodily signals may therefore act as an automatic constraint on the ongoing stream of thought, biasing which thought contents and transitions become more likely over time.

Museum visits typically follow curator-defined routes that constrain how visitors shape their own experience, yet choice is widely held to heighten engagement, autonomy, and enjoyment. Virtual reality (VR) offers a setting in which to study these processes because it combines ecological immersion with precise, continuous behavioral measurement. We investigated (i) whether VR- derived behavioral signals are associated with self-reported enjoyment during a virtual museum tour, and (ii) whether the level of agency afforded to visitors influences enjoyment. Forty-eight adults completed a room-scale, life-size VR tour (8 * 4 m) of seven paintings from the Tel Aviv Museum of Art, each accompanied by a synchronized audio guide. Synchronized gaze and head- position streams were logged continuously (50 Hz) and segmented into painting-level viewing episodes using a trial-and-tile pipeline that intersects each painting's trial interval with an empirically defined spatial window in front of the canvas. Participants were randomly assigned to one of three agency conditions, Active (choice before every artwork), Semi-Active (choice for the first three), or Passive (fixed route),while the artwork sequence was held identical. Self- reported enjoyment at the tour and painting levels did not differ reliably across agency conditions. Among VR-derived measures, gaze engagement during the audio guide showed the clearest (though modest) association with painting-level liking, whereas locomotion and pacing measures were weak and inconsistent predictors. Agency nonetheless reliably modulated several gaze- and time-based viewing measures. The findings reveal a dissociation between subjective enjoyment and the micro-structure of viewing, and establish a reusable framework for full-tour, painting-level behavioral analysis in immersive settings.

Spatial-numerical association reflects an internal "mental number line" where numerosities are mapped from left to right in space. While evidence from 8- to 9-month-old human infants suggests a privileged link between number and space, these findings do not definitively establish whether discrete numerosity or continuous quantity is the primary driver of spatialization due to the relatively extensive postnatal experience. Using domestic chicks (Gallus gallus), a model testable with minimal postnatal experience, we investigated precocial predispositions to map both discrete numerosities and continuous quantity (physical size) onto space. In Experiment 1, we replicated spatial-numerical association: chicks associated relatively smaller numerosities with the left hemispace and larger ones with the right hemispace. In Experiment 2, however, spatial-quantity association for physical size was asymmetric: chicks showed a rightward preference for smaller sizes and no congruent small-left/large-right mapping. Together with infant data, these findings indicate that a generalized and congruent spatial-magnitude association does not emerge at the earliest stages of development, and challenge accounts positing that spatial mappings for continuous magnitudes precede and underpin the spatial organization of number.

You are not not reading this sentence. True, because you are. It's the law of double negation, a logical rule that states that a statement that is not not true is itself true. The development of pure logic - the study of the properties of formal systems, irrespective of their content - represents one of the most abstract intellectual achievements of human culture. Yet its neural correlates remain vastly unexplored. Is pure logic represented in a linguistic format like natural language, in an abstract symbolic format like other formal systems such as mathematics, or as a fully distinct domain of knowledge? To address this question, we monitored the brain activity of professional logicians and matched controls while they evaluated the truth of spoken statements of pure logic, and compared these activations to those elicited by language and mental arithmetic. We show that pure logic recruits left-lateralized brain circuits that are completely distinct from those involved in language processing. Those circuits only partially overlap with those involved in mathematics. These findings highlight an independent neural pathway for abstract thought and indicate that the brain's capacity to process structured rules of formal systems is implemented beyond language and at the boundaries with mathematics.

Human language processing can be studied through both behavior and brain activity, yet it remains unclear whether these two data types reflect sensitivity to the same information. One influential view holds that both behavioral and neural responses are largely determined by processing effort, often estimated by word surprisal together with the context-independent properties of word frequency and length. At the same time, neural responses have been shown to encode richer aspects of linguistic content, including meaning. Here, we use neural network language models to operationalize these alternatives and systematically compare, within the same analytic computational framework, the predictive power of low-dimensional effort-based predictors and high-dimensional embedding representations that encode contextualized linguistic content, including meaning. Across 8 behavioral datasets and 5 neural datasets (4 fMRI and 1 ERP), we find that processing effort captures substantial variance in both behavioral and neural measures of language processing, in line with much previous work. However, for brain responses---but not for behavioral measures---embedding representations carry substantial predictive power beyond the estimates of processing effort. These results therefore suggest that neural data provide access to rich, high-dimensional dynamics of language comprehension, whereas behavioral data reflect a bottlenecking of these dynamics into a small set of theoretically motivated properties of contextualized linguistic input.

Predicting patterns of behavioural coordination that emerge in small interacting groups is challenging because goal-directed social action is shaped by complex reciprocal and compensatory dynamics. In this study, we examined whether formal symmetry principles derived from group theory could explain coordination patterns among children performing a triadic jumping task. We investigated how geometric symmetries of the task environment and dispositional (a)symmetries associated with leader-follower tendencies jointly constrain collective behaviour. Forty-seven children were classified into symmetric or asymmetric triads based on teacher evaluations of leadership dispositions. Each triad completed multiple trials of a synchronized jumping game requiring movement between adjacent hoops arranged in triangular or square configurations. Results showed that temporal asymmetries in inter-child movement (first, second, or last to jump) were consistent with group-theoretic predictions. In triangular configurations, observed asymmetries corresponded to the highest-order subgroup defined by task and dispositional symmetries. These findings demonstrate that environmental symmetry exerts a hierarchically dominant constraint on collective coordination, within which actor dispositional (a)symmetries further modulate emerging patterns.

Previous work showed that observers integrate audiovisual duration cues optimally when cue-conflict is small. Does causal inference lead to a breakdown of audiovisual integration when duration conflicts are large? We addressed this by testing a wide range of duration cue-conflicts. Participants compared the auditory durations of a test and a standard stimulus. Audiovisual durations were consistent in the test stimulus, but differed by seven conflict durations (up to 250 ms) in the standard. Two levels of auditory noise were tested. Auditory duration percepts shifted systematically toward the visual duration, especially with high auditory noise. The shift was proportional to cue-conflict magnitude, inconsistent with causal inference. We compared several models. A heuristic model in which the observer probabilistically switches between the visual and auditory cues was preferred for most participants, although performance differences across models were small. Within the tested conflict range, the forced fusion, causal inference, and probabilistic cue switching models produced overlapping, near-linear shifts as a function of cue-conflict. Model simulations further revealed that given the measured sensory noise, forced fusion and causal inference can be discriminated only with unreasonably large conflicts. Together, while our results suggest that observers do not rely on causal inference when judging auditory durations under our conditions, high sensory encoding noise in auditory duration limits the discriminability of competing computational models.

Adults who stutter can speak fluently when speech is not addressed to another person, but stuttering emerges when they aim to convey information to a listener. The value of the information being conveyed to the listener also affects the likelihood of stuttering. Why should the mere absence of a listener neutralise a profound motor deficit, and why does a word's predictability affect whether it is spoken fluently? To resolve this socio-motor paradox, we develop a computational model of stuttering within an active inference architecture. The model represents the communicative context, including whether a listener is present and whether the agent is speaking or listening. It was designed around two candidate mechanisms for stuttering, a prior for silence and rigid phoneme sequencing precision. Using both, the model produced fluent private speech and more stuttering-like events during social speech. In the same parameter regime, the model also showed more stuttering-like events on words with higher information value, and produced a word-length effect, in which disfluency increased with longer words. To our knowledge, this is the first model of stuttering to generate both the private speech and the information-value effect from inferred communicative context. By representing the listener as a hidden state that makes the sensory consequences of resuming speech ambiguous, the model offers a computational link between social cognition and speech-motor instability, and suggests that speech fluency depends on whether the speaker believes anyone is present. Clinically, it may offer testable hypotheses and a route to personalising treatment, since the same overt severity can arise from different combinations of parameters.

Adaptive behaviour often requires deciding when to act in the absence of an explicit sensory cue. While temporal expectations are known to optimize behaviour when anticipated events trigger responses, it remains unclear how learned temporal regularities are transformed into internally generated decisions. Here, we developed the Temporal Inference Task, a novel virtual reality paradigm designed to isolate this transformation. Participants repeatedly observed an identical visual sequence in which a virtual object approached their hand. On most trials, a brief tactile No-Go signal instructed them to withhold their response, whereas on the remaining trials its omission required them to respond. Because Go trials were never accompanied by an explicit cue, participants had to infer when the expected No-Go signal could no longer occur before initiating a response. Across blocks, the timing of the No-Go signal was systematically varied, allowing participants to learn distinct temporal regularities while Go trials remained physically identical. Participants systematically shifted their response timing according to the learned temporal regularities. This behavioural adaptation was accompanied by corresponding shifts in parietal alpha- and beta-band desynchronization, with steeper pre-response desynchronization consistently preceding faster responses. Together, these findings identify a candidate neural mechanism through which learned temporal regularities are transformed into internally generated decisions about when to act.

The attentional blink is a well-known phenomenon illustrating the limitations of human attention: When two visual targets are presented in rapid succession, identification of the second target is often impaired. While the attentional blink is known to attenuate when targets share perceptual features or category membership, real-world objects are also linked through contextual associations, shaped by objects typically occurring within the same environments. Here, we devised an attentional blink experiment in which we orthogonally manipulated contextual and categorical relationships between the two targets while controlling for their perceptual similarity. As the key result, contextual associations facilitated identification of the second target but impaired identification of the first target. These findings suggest that contextual associations yield distinct benefits and costs for visual cognition, where enhanced attentional access to subsequent targets is traded off against increased interference between targets.

Theories of predictive coding propose that perception is the process of inferring the causes of our sensory input by comparing that input with predictions derived from our internal models of the world. Such predictive processes are thought to play a central role in language comprehension, however, robust neurophysiological evidence for such processes, particularly during natural speech perception, remains limited. Previous work has suggested that the early auditory encoding of words in natural speech is influenced by their preceding linguistic context. However, it remains unclear whether this effect is driven by prediction per se or dynamic modulations of attention based on contextual uncertainty. To distinguish between these alternatives, we recorded electroencephalography from 17 healthy adults while they listened to slightly changed audiobook. Specifically, we identified and replaced several unsurprising content words with more surprising words. We quantified the early auditory encoding of words using speech-envelope reconstruction accuracy within 100-ms time window after word onset and examined its relationship to word surprisal and contextual uncertainty. We found that more surprising words showed enhanced early auditory encoding despite matched contextual constraint. Moreover, the temporal profile of this enhancement depended on when the incoming speech signal diverged from the predicted phonological sequence, consistent with the emergence of prediction-error responses. Linear mixed-effects modeling further revealed that word surprisal had a substantially stronger influence on early auditory encoding than contextual uncertainty. Together, these findings indicate that the early auditory encoding of words during naturalistic speech perception is more strongly associated with predictive computations than with uncertainty-driven attentional gain. Significance StatementDuring natural speech comprehension, contextual information influences how the brain processes incoming sensory input. However, whether this context-dependent modulation of the early auditory encoding of words reflects predictive computations or dynamic changes in attentional gain has remained unresolved. By combining a naturalistic speech paradigm with a stimulus manipulation that varies word surprisal while controlling contextual uncertainty, we show that the early auditory encoding of words is driven by word surprisal under matched contextual constraint. Moreover, the temporal dynamics of this modulation closely follow the point at which the incoming speech signal departs from the predicted phonological sequence. These findings provide neurophysiological evidence that predictive computations contribute to the context- dependent modulation of early auditory processing during natural speech comprehension.

Wayfinding in hospitals is often hindered by ineffective signage; however, the cognitive mechanisms of healthcare wayfinding symbols comprehension remain under-researched. This study utilized eye-tracking and spatial gaze mapping to examine how visual complexity, abstraction, and human figuration modulate perception in 40 healthy adults viewing 24 hospital-related healthcare wayfinding symbols. Results indicate that pupil size is a sensitive physiological marker of cognitive load, significantly influenced by visual complexity ({chi}2 = 11.32, p = .022) and abstraction ({chi}2 = 7.49, p = .027). Human figuration reduced fixation duration and increased saccade amplitude, facilitating efficient semantic integration. Furthermore, human-centric healthcare wayfinding symbols elicited streamlined gaze trajectories, whereas abstract/complex designs induced chaotic scanpaths. These findings suggest that human figuration acts as a cognitive scaffold, reducing mental effort. We provide evidence-based guidelines for optimizing healthcare wayfinding symbols by prioritizing human body representations and balancing abstraction levels. HighlightO_LIPupil size indexes cognitive load during symbol comprehension. C_LIO_LIHuman figuration cuts fixation duration, boosting wayfinding efficiency. C_LIO_LIAbstract symbols increase pupil dilation, raising cognitive load. C_LI

Irony and sarcasm are complex forms of non-literal language that hinge on a misalignment between surface meaning and speaker intent, requiring listeners to integrate contextual, semantic, and prosodic cues. While prior neuroimaging studies have implicated a broad network--including the temporal cortex, the inferior frontal gyrus, and the medial prefrontal cortex--in the comprehension of ironic and sarcastic speech, the precise neural mechanisms underlying the integration of semantic and prosodic information remain unclear. In the present study, we addressed this gap by employing voxel-wise encoding models to systematically identify brain regions specifically involved in combining prosodic and semantic cues during non-literal language comprehension. Participants listened to naturalistic auditory dialogues in which both discourse context and target utterance semantics and prosody were systematically manipulated. We derived custom text embeddings using transformer-based models to capture context-sensitive semantic representations of ironic statements, alongside acoustic features characterizing affective prosody. Ridge regression models were fitted to predict BOLD responses at the voxel level using semantic, prosodic, and combined features, and we identified integration as voxels in which each modality contributed predictive information beyond the other, using a permutation-based conjunction test. The regions integrating prosody and semantics depended on whether discourse context was modeled: integration was confined to the bilateral temporal speech cortex when statements were encoded in isolation, but additionally engaged the left inferior frontal gyrus pars orbitalis (IFGorb) when each statement was weighted by its relevance to the preceding context. These findings indicate that the left IFGorb integrates prosody with context-dependent meaning, engaging beyond the temporal speech cortex specifically when comprehension requires combining semantic, prosodic, and contextual cues--as in irony and sarcasm.

Confidence evaluates the likely accuracy of a current decision. However, to be maximally informative about accuracy, confidence judgments should incorporate information about ones broader decision tendencies, such as their propensity to favor specific alternatives. We distinguish bias-aware confidence, which considers such tendencies, from bias-blind confidence, which relies only on evidence available on the current trial. To adjudicate between bias-aware and bias-blind confidence, we identified a signature of bias-aware confidence: the down-weighting of confidence for alternatives that a participant is biased toward. We then used a large dataset (N = 200) spanning 4- and 8-choice digit-classification tasks to show that humans reliably exhibit this signature of bias-aware confidence. This effect was reduced under speed pressure and could not be explained by guessing. In contrast to the human results, artificial neural networks (ANNs) trained for object recognition lacked this signature of bias- aware confidence. Importantly, augmenting ANNs with a metacognitive module that allows confidence to take the networks biases into account led to the emergence of human-like bias- aware confidence. These findings show that human confidence incorporates not only information from the current trial but also longer-term decision tendencies, and that this capacity - absent in standard ANNs - can be conferred through specialized metacognitive mechanisms.

Creative performance fluctuates from moment to moment, suggesting that it depends partly on transient internal states present before creative thinking begins. Although such fluctuations have been identified in central neural activity, it remains unclear whether they are also reflected in autonomic physiology. We examined whether cardiac and electrodermal activity during a brief pre-trial resting period was associated with subsequent creative performance. Photoplethysmography, electrocardiography, and electrodermal activity were recorded while 28 participants completed the Alternative Uses Test and Fusion Innovation Test, assessing divergent and convergent creative thinking, respectively. Data from 27 participants was included in the analyses. Heart rate, heart rate variability, tonic skin conductance level, and phasic skin conductance activity were extracted from observation windows ranging from 11 to 30 s within a 30-s pre-trial rest period. Trial-level creativity was evaluated using GPT-based ratings of novelty, feasibility, and goal attainment. Linear mixed-effects models showed that higher pre-trial tonic skin conductance level was consistently associated with better subsequent creative performance across tasks, with overall model fit peaking at a 21-s observation window. Permutation-based feature-importance analysis provided convergent support for the contribution of tonic skin conductance, whereas the cardiac and phasic electrodermal indicators showed no reliable independent associations. However, the model explained only a small proportion of behavioral variance. These findings suggest that tonic sympathetic arousal reflects a momentary physiological state associated with creativity potential, while autonomic signals alone remain insufficient for accurate individual-level prediction.