Psychological Science

How children come to evaluate social-affective cues is shaped within the family, yet the neural expression of this process and its dependence on family relationships remain unclear. We tested whether parent-child similarity in the neural coding of affective judgment varies with family environment, and whether it relates to youth affective distress. Twenty-five parent-child dyads (youth, mean age 11.8; parents mean age 42 years) judged faces morphed along an angry-to-happy continuum as positive or negative during fMRI. For each participant, we defined an evaluative choice axis distinguishing faces judged positive from negative, independent of expression intensity. Using searchlight-based parent-child cross-decoding, we tested whether one dyad member's evaluative coding predicted the other member's judgments, indexing shared evaluative coding rather than shared sensitivity to expression intensity. Inference focused a priori on medial prefrontal cortex. There was no reliable average parent-child neural similarity across the sample. Instead, higher family conflict was associated with lower parent-child neural similarity in ventromedial prefrontal cortex (vmPFC). Demonstrating specificity to negative relational strain, this effect was not observed for complementary dimensions of family cohesion or identity. Moreover, the effect was specific to true dyads rather than random pairings and to vmPFC rather than a face-selective network or other medial prefrontal regions. Lower vmPFC similarity showed a preliminary association with higher youth affective distress. These findings indicate that affective valuation, rather than sensory encoding, may be a representational level at which perceived family conflict is reflected in parent-child neural similarity.

Empathy has been linked to facial emotion recognition, but whether empathy is associated with the structural representation of facial affect (how observers position different affects relative to one another in face-shape space) remains largely unexplored. 53 adults completed a genetic-algorithm face task that generated prototypes for 13 affects using the Basel Face Model, and completed the 60-item Empathy Quotient (EQ). The genetic-algorithm task produced structurally distinct prototypes for all 13 affects (all paired tests p < .001 Bonferroni-corrected; Cohens dz 1.74-3.13), confirming that participants generated reliable, affect-specific face representations. A 13 x 13 between-affect distance matrix was then compared between higher-EQ (n = 30) and lower-EQ (n = 23) groups. 1 pair survived full correction across all 156 off-diagonal cells: Amusement x Contempt (Cohens d = -1.31), with higher-empathy participants representing these two affects as structurally closer to each other. Both amusement and contempt are social-evaluative affects that share overlapping facial action components, and this convergence may reflect heightened sensitivity to shared expressive structure among higher-empathy observers. In exploratory analyses, permutation testing and continuous-EQ correlations pointed to a broader pattern centered on social-evaluative affects (Amusement, Awe, Contempt, Fear, Happiness, Pride, Sadness, Interest). Individual differences in empathy appear most prominently associated with how social-evaluative affects are structurally positioned in face-shape space, suggesting that empathy modulates not just emotion recognition accuracy but the representational geometry of facial affect itself.

Eye contact is one of the most potent social signals, but it remains unclear how little visual input is sufficient to register direct gaze, and whether such registration requires conscious awareness. Here, we used a custom tachistoscope to present faces for only 1-5 ms, asking whether gaze direction can shape perception at the very limits of vision. Direct-gaze faces required less visual input to localise than averted-gaze faces and produced higher localisation sensitivity from 3 ms onwards. Crucially, this advantage emerged before participants could explicitly categorise gaze direction, and before perceptual awareness ratings showed metacognitive access to the information driving localisation, both of which appeared only at 4-5 ms. Information-theoretic analyses confirmed that localisation responses carried stimulus-location information before explicit reports and awareness ratings became informative. A second experiment showed that the earliest eye-contact advantage depended mainly on low spatial frequencies, indicating a role for coarse visual information. Finally, autistic traits were associated with a reduced localisation advantage for direct gaze. These findings show that eye contact can influence perceptual processing within just a few milliseconds, with less visual stimulation than is required for conscious access to gaze direction.

Numerosity adaptation (the underestimation of number after exposure to a numerous adaptor) is reduced when adaptor and test differ in color, suggesting that the numerosity system parses items into color-defined categories. Here we ask whether this chromatic selectivity is organized into multiple narrowly tuned chromatic channels, and whether its expression depends on individual chromatic sensitivity. Twenty observers (aged 22-61) completed two psychophysical tasks. First, chromatic discrimination was measured for five hues spaced in 5{degrees} CIE L*a*b* steps ({Delta}H = 0{degrees}, 5{degrees}, 10{degrees}, 15{degrees}, 20{degrees}) from a red reference (LCh: 54, 118, 38), yielding an individual just-noticeable difference (JND). Second, numerosity adaptation was measured across the same five chromatic distances between a 48-dot adaptor and the test. Observers with superior discrimination (JND < 2.5{degrees}) showed robust chromatic tuning, adaptation declining as the test moved away from the adaptor hue, whereas poorer discriminators showed none. Using an interindividual-covariance / factor-analytic approach, we found that adaptation strengths at neighboring chromatic distances were highly correlated and fell off with chromatic separation. Principal component analysis extracted two factors, one loading on the larger chromatic distances and one on the smaller; under oblique (promax) rotation the two factors were substantially correlated (r = .66), implying at least two dissociable but overlapping chromatically tuned mechanisms. These results suggest that numerosity adaptation is mediated by multiple, comparatively narrow chromatic channels, resembling the higher-order color mechanisms inferred from color scaling, SSVEP, and fMRI, rather than the two early cardinal axes (L-M, S-(L+M)).

Social media users often feel that time vanishes while scrolling, but real feeds confound novelty, rewards, social signals, and self-paced control, leaving the driver of this distortion unclear. We tested whether self-paced visual exploration is sufficient to compress subjective time by comparing active scrolling with passive, yoked viewing and a static baseline. Twenty-three adults viewed sequences of natural images under three within-subject conditions: Scrolling (self-paced mouse clicks), Watching (a passive, yoked replay of their own scrolling sequence), and a Baseline (a static image). Participants estimated the elapsed duration of each block. Subjective duration was most compressed under Scrolling (48% of elapsed time), followed by Watching (51%) and Baseline (65%). Two sources separated these effects. Adding back the empty inter-image fixations brought the image-rich conditions to within seconds of the Baseline, showing that observers barely counted the blank gaps; the Scrolling--Watching difference, by contrast, was independent of these shared gaps, isolating self-paced control as a second source of compression. Electrophysiology linked that control to anticipatory neural states and the timing of early visual responses, with no amplified encoding of individual images. The results favor an attention-weighted account of timing, on which subjective duration tracks how much attention reaches the clock, a resource that a self-paced stream and its uncounted gaps both draw away.

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.

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.

Formal writing is evolutionarily recent, yet the brains of literate adults contain regions - the OTS-words subregions - that respond more strongly to written text than other stimuli. We tested a novel solution to this multi-disciplinary paradox: Does symbolic language processing, which emerged early in human history, lay the neural foundation for reading? In a longitudinal fMRI study, we followed 17 children through their first year of literacy training and related neural responses to text, symbolic language processing, and emerging reading skills over time. We found that middle OTS-words is engaged in symbolic language processing before children learn to read, and that this early engagement predicts later text selectivity and reading ability. These findings suggest that literacy builds on a pre-existing neural scaffold linking vision and language.

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.

Autistic people can find social interactions difficult to navigate, traditionally attributed to difficulties in taking others perspectives. However, we have a limited understanding of how autistic people integrate self and other information efficiently during social decision-making. We conducted four highly powered experiments (total N = 1,621) to determine whether autistic traits affect two aspects of self-other integration during social decision making: self-bias and social basis function use. Using Bayesian analyses, we found strong support for the absence of a relationship between autistic traits and either aspect of social decision making, even after controlling for potential confounds (BF01 = 32.13 for self-bias, BF01 = 7.04 for social basis function use). Our results indicate that variations along autistic traits do not impact how people prioritise self-relevant information (self-bias) or utilize compressed social patterns of interaction (social basis function use) to guide their decisions about oneself and other people. These findings nuance the conceptualisation of social-cognitive processes across autistic traits while highlighting the need for large samples to validate null effects.

How do we make sense of something weve never seen before? Classifying objects into superordinate classes like animal is a key step in interpreting novel experiences, but is challenging because radically different items (e.g., octopus, rabbit) must somehow be grouped together. In general, no single feature is shared by all members. We reasoned that to classify or imagine novel items from outside the distribution of previous experiences, observers parse objects into meaningful component features that they can mentally recombine ( compositionality). To test this, we asked participants to draw familiar and novel members of nine superordinate object classes. We then asked other participants to classify the drawings, and mark and label their defining parts. We find that human classification performance is well predicted by a Bayesian classifier that optimally combines the part labels, suggesting humans can create and classify out-of-distribution experiences through a compositional generative representation of object features.

Recent work, including the third visual stream hypothesis, frames social perception as a largely automatic visual process. Simple animations of shapes engaged in "social" behaviors such as chasing have long been used to study social perception; however, both behavioral and neural responses are typically modeled against discrete, experimenter-assigned stimulus labels. This approach is insufficient, given that perceptions of such stimuli vary not only between people but also across trials. Here, we directly compared the neural responses to objective (stimulus-based) and subjective (response-based) socialness in an fMRI study in which the degree of chase between two agents was varied algorithmically. Participants (n=24) rated their perception of a chase on a continuous scale. Subjective ratings better predicted activity in visuo-social brain regions, predominantly in area MT, even after controlling for optic flow. Our findings underscore the visual nature of social cognition and highlight the importance of analyses sensitive to idiosyncrasies in perception.

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.

Background: Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD) exhibit high clinical overlap, but categorical diagnostic boundaries obscure their shared, dynamic physiological vulnerabilities during real-world sensory processing. Methods: We analyzed multimodal eye-tracking synchrony in a large transdiagnostic pediatric cohort (N = 2,026) during naturalistic viewing of four distinct media paradigms. A novel 2D complex correlation framework captured gaze inter-subject correlation (ISC) magnitude and spatiotemporal phase divergence, while 1D pupil ISC measured autonomic arousal synchrony. Linear models evaluated dimensional (RDoC) and categorical (2x2 ANCOVA) diagnostic frameworks alongside rigorous medication and severity controls. Results: Dimensional models revealed a domain-general vulnerability: autistic traits independently predicted widespread reductions across gaze synchrony in all media contexts, and pupillary synchrony in narrative-driven contexts, whereas continuous ADHD traits showed minimal independent effects. In contrast, severe spatiotemporal misalignment (phase divergence) did not scale dimensionally but emerged strictly at clinical boundaries, reflecting highly idiosyncratic spatial locking in isolated ASD. Furthermore, categorical models demonstrated a robust, non-additive interaction: the clinical co-occurrence of ADHD paradoxically buffered against this severe spatiotemporal decoupling. Crucially, this protective phenotype was localized strictly to character-driven social narratives and remained highly significant after rigorously adjusting for daily stimulant medication, outlier instability, and baseline autism trait severity. Conclusions: These findings validate model-free physiological synchrony as a candidate transdiagnostic biomarker. Rather than compounding impairment, comorbid ASD and ADHD reflect competing, non-additive neurocognitive strategies that yield distinct, context-dependent visual phenotypes.

Depression is associated with biased facial emotion processing, yet existing paradigms measure only the recognition of pre-selected stimuli, conflating the process of forming an internal representation with its endpoint product. Here, we used a genetic-algorithm (GA) face synthesis task to disentangle these components. Fifty-seven undergraduates (40 Low Risk, 17 At Risk by Beck Depression Inventory-II) iteratively evolved photorealistic 3D faces to match their internal representations of 13 emotions across seven generations in a 199-dimensional face shape space. We extracted five evolutionary metrics capturing how participants constructed their representations (convergence speed, velocity, stability, range) and the structure they ultimately produced (peak intensity). At Risk participants converged on embarrassment representations significantly faster than Low Risk participants (d = 0.88, p = .001, FDR-corrected, permutation-validated), reaching their template in roughly half the number of generations. Anger representations showed greater evolutionary instability in the At Risk group (d = -0.75, p = .029, permutation-validated). Critically, endpoint face intensities did not differ between groups for any emotion. These results suggest that depression severity is associated with rigid self-conscious emotion schemas and unstable anger representations during face generation, reflecting altered cognitive processes rather than distorted perceptual products. The findings extend cognitive schema theory to the domain of facial affect representation and highlight self-conscious emotions as an underexplored locus of depression-related perceptual bias.

Light is a fundamental regulator of human physiology and behaviour. Whether prior light exposure shapes subsequent higher-order cognition and mood beyond the period of exposure remains unknown. We tested this in a within-subject, randomised crossover experiment in which 24 healthy young adult males completed a multimodal cognitive battery following 2 x15 min of full-spectrum light (FL; median 1,029 melanopic equivalent daylight illuminance [mEDI]) or standard indoor light (SL; median 234 mEDI), with all testing conducted under identical dim illumination. FL improved Digit-Symbol Substitution Test accuracy and promoted digit-directed gaze reallocation, consistent with more efficient associative encoding. On the Balloon Analogue Risk Task, FL reduced reward-seeking behaviour and suppressed backward-referencing gaze transitions linking current and prior-trial reward information. Mood declined following SL but remained stable after FL. Sustained attention, vigilance, and subjective sleepiness were unaffected. Our findings identify pre-task FL exposure as a selective primer of higher-order cognition and mood, independent of alertness.

Early life adversity is associated with increased risk for psychopathology and shifts in life history (LH) strategies, but the psychological mechanisms underlying these associations remain unclear. Drawing on evolutionary-developmental theory, we examined whether short-term mindsets mediate associations between dimensions of childhood adversity and mental health and LH-related outcomes. In a UK-representative sample of 877 adults, we assessed threat, deprivation, and unpredictability, alongside internalizing and externalizing symptoms, borderline features, and a latent factor capturing reproductive versus somatic maintenance effort. Structural equation models showed that adversity predicted poorer mental health and faster LH strategies. Short-term mindsets, indexed by lower future orientation and higher affective impulsivity, mediated effects of adversity, particularly unpredictability. Further decomposition of unpredictability into short-timescale and long-timescale forms revealed dissociable effects, with short-timescale unpredictability primarily linked to psychopathology and long-timescale unpredictability to reproductive-oriented LH strategies.

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.

Humans comprehend language incrementally, updating the representation of sentence meaning with each incoming word. These updates are guided by the distance between each perceived word and prior expectations--the prediction error. The alignment between large language models (LLMs) and cortical activity inspires the hypothesis that the cortical computation of prediction error is Surface-based, driven by statistical patterns of word form co-occurrence. In contrast, psycholinguistic models propose that prediction error computation is Meaning-based, driven by word semantics. We used polysemic words with ambiguous semantics to distinguish these models: ambiguity would introduce uncertainty into meaning representations and hence the prediction error, if Meaning-based, but would not affect the prediction error, if Surface-based. We examined how ambiguity influenced prediction error signatures in self-paced reading times and magnetoencephalographic (MEG) neural responses during sentence processing. While an LLM-based proxy of prediction error robustly predicted reading times and neural responses to unambiguous words, it failed to predict either under ambiguity. That is, prediction error computation was altered by uncertainty in word meaning, which supports the Meaning-based model and corroborates the essential role of word meaning in predictive language processing. Our findings highlight an important limitation of LLMs as in silico models of the human language faculty.

Human perception is shaped by both sensory input and prior knowledge or expectations. But how does prior contextual information influence rapid visual processing? Here, we combined eye tracking with feature-based encoding models across two experiments to predict detection latencies in a core visual task: rapid face detection in natural scenes (N = 38 per experiment). In the first experiment, we manipulated the presence of faceless scene previews. In the second experiment, we additionally restricted peripheral visual input using a moving-window paradigm, thereby increasing reliance on prior information. Across both experiments, prior context facilitated face detection, particularly for challenging images. This facilitation was already evident in the very first eye movement, suggesting that previews shape perceptual strategies from the outset. To quantify what information guided behavior, we modeled detection latencies using a set of image-based predictors capturing (i) sensory information and (ii) a scene-derived spatial prior: the expected face location. Both predictor classes explained latency variation across images. Among sensory predictors, the difference in deep neural network responses induced by the presence of the face provided the strongest out-of-sample prediction of detection latency. Critically, when scene previews were available, the contribution of the spatial prior increased, while reliance on sensory-driven features was generally reduced. Together, these findings indicate that prior scene context shifts the balance of information used for rapid face detection from sensory-driven to expectation-based spatial guidance.