Psychological Science

Large-scale genomic studies have identified biomarkers of adult cognitive functioning and educational attainment, yet the developmental pathways connecting these biomarkers to adult outcomes remain unclear. Drawing on four cohorts, we examined the developmental correlates of an epigenetic index of adult cognitive function ( Epigenetic-g) alongside polygenic indices of cognition and education. Epigenetic-g and polygenic indices were uncorrelated and captured distinct variation in childrens cognitive and academic performance. Longitudinal analyses revealed that Epigenetic-g is plastic in early childhood, reaching moderate stability by adolescence, and, unlike polygenic indices, is not related to longitudinal cognitive growth. Twin models indicated that Epigenetic-g captures genetic and unique environmental variation relevant to cognitive and academic achievement that is not identified by current polygenic indices. Epigenetic indices relevant to psychological development can be generated from DNA methylation studies of adults, with most variation in these indices emerging early in life.

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.

Human cognitive abilities are considerably diverse from basic perceptions to complex social behaviors. All human cognitive functions are principally categorized into a two-order hierarchy. Almost all of the first-order cognitive abilities investigated in behavioral genetics have been found to be dominantly heritable. However, the origins of the human second-order cognitive abilities in metacognition and mentalizing so far remain unclear. We here systematically compared the origins of the first-order and second-order cognitive abilities involved in the metacognition and mentalizing tasks using the classical twin paradigm on human adults. Our results demonstrated a double dissociation of the genetic and environmental contributions to the first-order and second-order cognitive abilities. All the first-order cognitive abilities involved in the metacognition and mentalizing tasks were dominantly heritable. In contrast, the shared environmental effects, rather than the genetic effects, had dominant contributions to the second-order cognitive abilities of metacognition and mentalizing in human adults. Hence, our findings suggest that human adults monitoring sensitivities in metacognition and mentalizing are profoundly sculpted by their social or cultural experiences, but less preconditioned by their biological nature.

When individuals view the same visual input, they often differ in their aesthetic appeal judgments, yet why people differ remains largely unclear. Here, we tested whether individual differences in aesthetic experience are linked to differences in visual exploration. In two experiments, participants watched the documentary "Home" while their eye movements were recorded. In Experiment 1, participants continuously rated aesthetic experience throughout the movie, whereas in Experiment 2, they watched the first half without a task and rated aesthetic experience only during the second half. Inter-individual similarity in gaze patterns, assessed using fixation heatmaps across time, predicted similarity in aesthetic appeal judgments in both experiments. Notably, in Experiment 2, gaze similarity during free viewing in the first half of the movie predicted similarity in aesthetic ratings during the second half, indicating that incidental eye movement patterns predict aesthetic experiences. Together, these results show that shared gaze patterns are linked to shared aesthetic experiences under naturalistic, dynamic viewing conditions.

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)).

Imagine you are asked to draw a typical bedroom, what would you put on paper? Your choice of objects is likely to depend on visual occurrence statistics (i.e., the objects present in previously encountered bedrooms) and semantic relations between objects and scenes (i.e., the semantic relationship between the bedroom and its constituent objects). To investigate how these two factors contribute to the composition of typical scene drawings, we analyzed 1,192 drawings of six indoor scene categories, obtained from 303 participants. For each object featured in the drawings, we estimated its visual occurrence frequency from the ADE20K dataset of annotated scene images, and its semantic relatedness to the scene concept from a word2vec language processing model. Across all scenes of a given category, generalized linear models revealed that visual and conceptual factors both predicted the likelihood of an object featuring in the scene drawings, with a combined model outperforming both single-factor models. We further computed the visual and semantic specificity of objects for a given scene, that is, how diagnostic an object is for the scene. Object specificity offered only weak predictive power when predicting the selection of objects, yet even infrequently drawn objects remained diagnostic of their scenes. Taken together, we show that visual and conceptual factors jointly shape the composition of typical scene drawings. By releasing a large dataset of typical scene drawings alongside this work, we further provide a starting point for future studies exploring other critical properties of human drawings.

Memorability, or the likelihood that an image is later remembered, is an intrinsic stimulus property that is remarkably consistent across viewers. Despite this consistency in what people remember and forget, previous findings suggest a lack of consistency in what individuals subjectively believe to be memorable and forgettable. We aimed to improve the ability of participants to judge memorability using a feedback-based training paradigm containing face images (Experiment 1) or scene images (Experiment 2 and its replication and control experiments). Overall, participants were fairly accurate at categorizing the memorability of images. In response to the training, participants were able to improve their memorability judgments of scenes, but not faces. Those who used certain strategies to perform the task, namely relying on characteristic features of the scenes, showed greater learning. Although participants improved slightly over time, they never reached the level of ResMem, the leading DNN for estimating image memorability. These results suggest that with training, human participants can better their understanding of image memorability, but may be unable to access its full variance.

Attentional capture by emotionally salient stimuli is adaptive, permitting identification of possible threats; however, an excessive bias towards emotional stimuli can interrupt goal-directed behavior. This is especially relevant in psychiatric disease, where severe emotional distress can interfere with daily function. As such, understanding the mechanisms by which emotional stimuli compete for attentional resources is a critical area of investigation. Previous studies using rapid serial visual presentation (RSVP) paradigms observe that emotional distractors disrupt the detection of subsequent stimuli, referred to as emotion-induced blindness (EIB). Our study expands upon this work, characterizing how temporal and perceptual factors shape the emergence and intensity of EIB. Contrary to previous assumptions regarding temporal dynamics of EIB, we found that effects of emotional distractors persisted across prolonged image presentation durations. Further, we investigated the extent to which the depth of distractor processing influences EIB using a distractor recall task. While recall was predictive of EIB magnitude, a significant effect of emotional distractors on target detection was nonetheless present even without conscious recall of the distractor. These findings demonstrate the robustness of the EIB effect in RSVP in the context of temporal and perceptual manipulations.

Human observers prioritise the left visual field in perceptual judgements, a phenomenon widely attributed to cerebral asymmetries in vision. How stable are these mechanisms across differences in reading direction? We show that the classic left-side bias for faces is correlated with reading direction and tightly linked to gaze. Observers with varying proficiency in reading English (left-to-right) and Arabic (right-to-left) performed a chimeric face matching task (N = 271), with eye movements recorded in a subset (N = 115). The left-side bias scaled linearly with reading direction: strongest in English readers, reduced in bidirectional readers, and absent in Arabic readers. Reading direction also shifted gaze: English readers fixated further left on target faces and preferentially inspected faces in the left hemifield, and these gaze patterns predicted trial-by-trial perceptual judgements. These results suggest that cerebral asymmetries in face perception are flexible, coupled to gaze, and modified by reading direction.

Humans can extract regularities from their environment, enabling them to recognize and predict sequences of events. The process of regularity extraction is called statistical learning and is generally thought to occur rapidly and automatically; that is, regularities are extracted from repeated stimulus presentations, without intent or awareness, as long as the stimuli are attended. We hypothesized that visual statistical learning is not entirely automatic, even when stimuli are attended, and that the learning depends on the extent to which viewers process the relationships between stimuli. To test this, we measured statistical learning performance across seven conditions in which participants (N=774) viewed image sequences. As task instructions across conditions increasingly required participants to attend to relationships between stimuli, their learning performance increased from chance to robust levels. We conclude that the learning observed in visual statistical learning paradigms is, for the most part, not automatic and requires more than passively attending to stimuli.

Each individual person looks at natural scenes in their own unique way, resulting in a distinct perceptual experience of the world. However, little is known about why such differences in gaze emerge. Here, we test the hypothesis that idiosyncrasies in gaze behavior are predicted by inter-subject variations in internal models--expectations about how scenes typically look. In two experiments, we first characterized participants personal internal models by asking them to draw typical bathroom and kitchen scenes. Individual differences in these drawings were quantified using an objective deep learning pipeline and, in turn, related to individual differences in gaze behavior. In Experiment 1, where participants freely viewed a set of kitchen and bathroom photographs, inter-subject similarities in internal models did not predict inter-subject similarities in gaze. In Experiment 2, we encouraged strategic exploration through gaze-contingent viewing and a memory task. Here, inter-subject similarities in internal models predicted similarities in fixation frequency and the sequence in which different object categories were inspected. These findings suggest that the influence of internal models on visual exploration is stronger under increased sensory uncertainty and when expectation-guided sampling of the environment is encouraged. Together, our results provide new insights into how individual expectations shape gaze behavior and help explain why people differ in how they explore the visual world.

Some images are consistently remembered better than others, suggesting that memorability reflects intrinsic image properties. We tested whether within-category distinctiveness underlies this effect. Across three experiments (N = 477), participants categorized indoor scenes previously rated for subjective typicality and then completed recognition memory tests. Typical scenes were categorized faster and more accurately, but were remembered worse and showed a more liberal response bias than atypical scenes. These opposing effects were robust across categories. To link subjective typicality to visual representations, we quantified image distinctiveness using a convolutional neural network (CNN). Across layers, CNN-derived distinctiveness closely tracked human typicality judgments and predicted both categorization speed and memorability, with strongest effects in higher, semantic layers. Critically, the memory advantage for atypical scenes persisted even when most images were atypical, ruling out rarity within the experimental context. Together, the results show that intrinsic scene memorability reflects an images position within a category-specific representational space.

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.

Our ability to recognize facial expressions is crucial for understanding others emotions1 and facilitating smooth communication2. Numerous studies have explored how we perceive these cues, considering factors such as health3, social signals4 and personality traits5. However, most of this research involves observers facing a monitor and assessing facial stimuli presented directly in front of them. Real-life scenarios offer more diverse spatial dynamics, such as conversing with someone at a table or glancing back at a passerby. Thus, faces behind the observer might trigger heightened recognition, akin to reacting swiftly to a perceived threat. Herein, we demonstrate that facial expression recognition is influenced by spatial relationships, i.e., faces in front of versus behind the observer. Participants judged the expressions of faces appearing in front of or behind them in virtual space. The findings of three experiments reveal an enhanced level of recognition for faces behind the participant. Interestingly, this effect varies with emotional valence; anger is amplified merely by the presence of a face behind the observer, while happiness requires actively turning to the rear for enhancement to occur. These findings suggest a biological instinct for perceiving threats behind us, potentially influencing subsequent actions. Hence, spatial relationships may modulate facial expression recognition.

Multiple theories have proposed that increasing central arousal through the brains locus coeruleus - norepinephrine system may facilitate cognitive control and memory. However, for emotion research this hypothesis poses a puzzle, because conventionally, successful emotion regulation is associated with a decrease in arousal. Pupil diameter is a proxy to infer upon the central arousal state. We employed an emotion regulation paradigm with a combination of design features that allowed us to dissociate regulation- from stimulus-associated arousal in the pupil diameter time course of healthy adults. A pupil diameter increase during regulation predicted individual differences in emotion regulation success beyond task difficulty. Moreover, the extent of this individual arousal boost predicted performance in another self-control task, dietary health challenges. Participants who harnessed more regulation-associated arousal during emotion regulation were also more successful in choosing healthier foods. These results suggest that a common arousal-based facilitation mechanism may support an individuals self-control across domains.

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.

Understanding how individuals evaluate social content in affective scenes is crucial for research in emotion, social cognition, and decision-making. However, standardized image databases often lack fine-grained ratings of social dimensions beyond basic emotional content. We present a normative dataset of 296 affective scenes rated by 424 adult participants across six social-affective dimensions: social relevance, emotion sharing, action sharing, interpersonal equality, scene pleasantness, and participatory arousal. Each image was independently coded for objective features such as number of people, face visibility, and gaze direction. All rating dimensions showed excellent interrater reliability. Pleasantness ratings demonstrated strong convergent validity with established valence norms from the International Affective Picture System (IAPS), while arousal ratings differentiated between experienced and participatory arousal, suggesting that the latter captures a distinct affective component. Correlation analyses revealed that social relevance was strongly predicted by scene pleasantness and a composite "engagement" factor combining emotion sharing, action sharing, and equality. Notably, the association between pleasantness and social relevance was especially pronounced in scenes depicting single individuals. Linear mixed models further indicated that extraversion modestly amplified the relationship between engagement and social relevance, while other personality traits and empathy did not significantly affect ratings. This open-access dataset provides a reliable, multidimensional tool for selecting affective scenes based on both emotional and social-interpersonal features. It supports improved stimulus control and design in a wide range of behavioral and neurocognitive research. By systematically mapping social meaning in static affective scenes, our study advances existing methodological resources and offers empirical insight into the structure of social-affective appraisals. All image codes, mean ratings, and analysis scripts are publicly available via the Open Science Framework.

People are eager to know and recast the self in the eyes of others, even at a personal cost. However, it remains unknown what drives people to pursue costly evaluations of the self. Here, we propose that the evaluation of the self is valuable and that such subjective value placed on evaluation drives the costly-to-know behavior. By measuring the amount of money that individuals would forgo for the opportunity to know evaluations from other people (social evaluation) or a computer program (non-social evaluation), we quantified the subjective value individuals assigned to the evaluation on the self. The results from 5 studies (n = 375) lent cognitive and computational support for this hypothesis. Furthermore, the subjective value was modulated by the source and valence of the evaluation. Participants equally valued positive and negative non-social evaluations, characterized by a shared unknown aversion computation. However, individuals computed independent unknown aversion towards positive and negative social evaluations and placed a higher value on the opportunity to know another persons evaluation on positive than negative aspects. Such a valence-dependent valuation of the social evaluation was facilitated by oxytocin, a neuropeptide linked to linked to social feedback learning and valuation processes, which decreased the value ascribed to negative social evaluation. Taken together, the current study reveals the psychological and computational processes underlying self-image formation and updating and suggests a role of oxytocin in modulating the value of social evaluation.