Navigating complex social environments requires understanding how individuals are connected within social networks. People are highly efficient at integrating dyadic relationships into larger network structures. However, social networks are embedded within different types of groups (e.g., task groups vs. social categories), raising the question of how group typology shapes the learning and representation of social networks. Across four experiments, we demonstrate that group-related network schemas-specifically, expectations that task groups are more interconnected and centralized than social categories-systematically guide social network learning and representation. Participants exhibited prior expectations about the relational structure of different group types, and memory for social relationships was enhanced when the learned network structure aligned with these schematic expectations, producing a matching effect that was correlated with schema strength (Experiment 1). This effect was causally driven by schema strength: Weakening group-related schemas through explicit descriptions attenuated the matching effect (Experiment 2). Critically, the effect was domain specific: When social relationships were replaced with nonsocial connections (airport-flight networks), the matching effect disappeared despite comparable structural properties and task demands (Experiment 3). Computational modeling using the Successor Representation framework further revealed that schema-structure misalignment reduced multistep abstraction, reflected in lower successor discount parameters (γ), yielding less integrated global representations of social networks (Experiment 4). Together, these findings show that social network learning is guided by top-down group-related schemas. It advances our understanding of social network cognition by highlighting the importance of schema-driven abstraction and by bridging local learning mechanisms with global representational structure. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Anorexia nervosa (AN) is a deadly psychiatric disorder with relapse rates approaching 50% after weight restoration. Disrupted gastrointestinal interoception may underlie persistent symptoms and relapse vulnerability. To examine behavioral, computational, neural, and physiological markers of gastrointestinal interoception in weight-restored individuals with AN and test their association with relapse. This crossover trial was a single-blind, within-participant, randomized (block-order) trial conducted at the Laureate Institute for Brain Research between August 2021 and February 2025. Participants were females with weight-restored restrictive AN and age- and sex-matched healthy comparators (HCs). All participants ingested a vibrating capsule that delivered counterbalanced blocks of normal- and enhanced-intensity gut stimulation. Behavioral detection performance, electroencephalography, peripheral physiology, and computational modeling were used to assess interoception. Experimental-session measures included interoceptive accuracy, prior beliefs, interoceptive precision, learning rates, gastric-evoked potentials (GEPs), and hunger. Main clinical outcomes at 6 months included relapse status and symptom severity. The cohort included 62 female participants with weight-restored restrictive AN (mean [SD] age, 18.9 [4.5] years) and 57 age- and sex-matched healthy comparators (HCs; mean [SD] age, 20.7 [5.3] years). Six-month follow-up data were collected for 54 participants with AN. Compared with HCs, participants with AN showed lower perceptual accuracy (Cohen d = -0.98; 95% CI, -1.51 to -0.44; P = .001) and higher miss rates (Cohen d = 1.02; 95% CI, 0.55 to 1.48; P < .001). Computational modeling revealed in the AN group stronger prior expectations that capsule vibrations would not be present (Cohen d = -0.31; 95% CI, -0.67 to 0.05; P = .05), greater shifts in interoceptive precision between blocks (Cohen d = 0.38; 95% CI, 0.02 to 0.75; P = .01), and learning asymmetries (vibration: Cohen d = -0.40; 95% CI, -0.77 to -0.04; P = .007; no-vibration: Cohen d = 0.35; 95% CI, -0.02 to 0.71; P = .01). GEP amplitudes did not differ by group but were correlated with accuracy and learning in AN. Capsule stimulation induced greater hunger increases in AN (interaction: η2p = 0.04, P = .04; AN: Cohen d = 0.94; 95% CI, 0.57 to 1.30; HCs: Cohen d = 0.40; 95% CI, 0.03 to 0.77). At follow-up, relapse was predicted by initial priors (odds ratio [OR], 3.82; 95% CI, 1.02 to 15.91; P = .05), response bias (OR, 5.37; 95% CI, 1.15 to 32.04; P = .04), and stomach unpleasantness (OR, 5.73; 95% CI, 1.38 to 33.5; P = .03), while eating disorder symptom severity was predicted by miss rate (β = 1.05; R2 = 0.08; P = .05), difference in interoceptive precision (β = 5.84; R2 = 0.16; P = .004), and initial priors (β = -2.99; R2 = 0.09; P = .05). In this study of weight-restored females with AN, gastrointestinal interoception was disrupted across multiple domains, including reduced accuracy detecting gut signals, maladaptive priors, rigid learning, and abnormal hunger rating. Several interoceptive markers predicted relapse and symptom severity at follow-up. These findings support the use of ingestible mechanosensory probes and computational modeling as scalable tools to monitor treatment response and guide relapse prevention in eating disorders. ClinicalTrials.gov Identifier: NCT05111977.

Duration reproduction under memory pressure: Modeling the roles of visual memory set size in duration encoding and reproduction.

Seamless visual perception is achieved through the balance between recent perceptual history and ongoing sensory evidence. This balance has been examined under the framework of perceptual hysteresis, in which the visual system either favors perceptual history to maintain stability (positive hysteresis) or favors current sensory input to accommodate important changes in the environment (negative hysteresis). However, it remains unclear which direction of hysteresis prevails when recognizing semantic categories in changing scenes. Here, we investigate hysteresis using smoothly transitioning scene-image sequences generated by a generative adversarial network. Each sequence was presented in two opposite directions between two scene categories (e.g., bedroom vs. living room), and participants indicated the frame at which they perceived the category change in each direction. Compared with the estimated true category boundary, responses were systematically delayed, indicating that perceived boundaries were biased toward the recently perceived category. This positive hysteresis effect was robust across transition directions, even after accounting for motor response time (Experiment 1) and manipulating prior expectations of upcoming categories (Experiment 2). Together, these findings extend evidence for positive hysteresis to complex, naturalistic scenes, highlighting its role as a stability-promoting process that supports coherent interpretation in continuous vision. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Humans possess the metacognitive ability to estimate the likely accuracy of their own decisions through confidence judgments. Yet, whether prior information shapes confidence and the neural mechanisms mediating such influence, remain to be determined. Here, two complementary studies identify parietal alpha modulation as an oscillatory mechanism linking prior expectations to selective shifts in metacognitive bias. In Study 1, 75 participants performed a visual detection task with symbolic cues signaling target probability. Within the Type II Signal Detection Theory framework, probabilistic cues induce a congruence-dependent metacognitive bias: confidence increases when perceptual responses align with expectations and decreases when they diverge. Importantly, metacognitive sensitivity is unaffected. Critically, electroencephalography shows that cue-induced right-parietal alpha modulation predicts interindividual differences in the magnitude of this bias. In Study 2 (N = 88), right-parietal continuous Theta-Burst Stimulation (cTBS) disrupts cue-induced alpha modulation, relative to sham stimulation. This oscillatory change, in turn, drives the selective reduction in metacognitive bias. Together, these findings demonstrate that parietal alpha modulation causally and selectively shapes metacognitive bias, revealing an oscillatory mechanism for predictive metacognition.

Perception is an active process guided by prior knowledge and expectations, allowing the brain to optimize sensory processing and reduce uncertainty. Although modulations in alpha (7-13 Hz) and beta (15-25 Hz) frequencies have been linked to perceptual and top-down processing, their distinct roles within the predictive coding framework remain elusive. Here, we recorded electroencephalographic activity in 60 participants before (at rest) and during a representational momentum task, where prior information of motion typically biases subsequent perceptual judgments. Within participants, instantaneous frequency modulations occurred throughout the trial. Beta-band modulations tracked the inducer's speed and participant's perceptual choices, consistent with a role in encoding predictive information about stimulus dynamics. In contrast, alpha-band frequency modulations were selectively related to perceptual outcomes in trials that elicited representational momentum, with faster instantaneous alpha frequencies associated with the absence of predictive motion extrapolation. This pattern extends previous findings suggesting that alpha frequency dynamics bias the balance between temporal integration and segregation in the context of motion extrapolation, such that faster alpha rhythms favor veridical segmentation of sensory input, whereas slower alpha rhythms promote predictive integration over time. In contrast to ongoing oscillatory activity, resting-state individual alpha and beta frequencies were not associated with the representational momentum phenomenon, indicating that dynamic, task-related frequency modulations, rather than trait-like oscillatory fingerprints, are critical for understanding predictive perceptual biases in highly dynamic contexts.

The effects and interactions of top-down influences on word recognition.

Older adults' perceptions and previous expectations about retirement and its causes: a qualitative study.

Human movement is variable even when the latent intention is identical, which complicates action prediction from kinematics. Although perceptual expertise often improves anticipation, it remains unclear how this benefit is modulated by intrinsic trial-to-trial fluctuations in kinematic structure. We introduce kinematic observability, operationalized as the distance of a movement instance from the optimal decision boundary in kinematic feature space. In a table-tennis action prediction task with an expert-novice paradigm, we sampled trials based on objective evidence strength rather than masking body parts. Experts outperformed novices on high-observability trials and showed readout weights more closely aligned with the optimal encoding direction. However, under low observability, the expert advantage was attenuated, accompanied by a criterion shift reflecting increased reliance on prior expectations. These results indicate that expertise improves anticipatory readout when observability is high but yields smaller benefits when trial-wise kinematic evidence is weak; under low observability, experts also shift decision criterion in a manner consistent with increased reliance on prior expectations.

Exposure to environmental regularities allows individuals to build internal models, supporting the integration of prior expectations with sensory input in social contexts. However, how social prediction models develop across age and experience remains unclear. To address this, we investigated whether the formation of social predictive models varies across age and experiences in neurotypical individuals (early adolescents, young adults, and adults). Participants completed, in counterbalanced order, two scenarios of an immersive virtual reality (IVR) task that facilitates the creation of top-down predictions during action perception, requiring the participants to implicitly associate the hand movement of four avatars toward one preferred object among three. Self-report questionnaires and standard social cognition tests were used to assess embodiment, presence, usability in the IVR setting, and the direct association between the novel IVR task and social-cognitive tests. Results showed significant performance improvement from the first to the second scenario in all groups, indicating learning and refinement of predictive models. Early adolescents performed significantly worse and showed a lower learning rate than adult groups, who did not differ from each other, suggesting slower formation of social prior expectations in early adolescents. The IVR paradigm was feasible across all age groups and proved valid for assessing social processing. These findings support a developmental trajectory in which the creation of predictive internal models improves with age and experience.

Emotion dysregulation is a common issue across childhood and adolescence, including in autism and attention-deficit/hyperactivity disorder (ADHD). Yet most accounts remain descriptive-focusing on irritability, rapid escalation, slow return to baseline-without specifying the computational processes that stabilize emotions in context. We propose a predictive-coding account in which emotion regulation depends on how the brain predicts bodily and environmental signals, detects mismatches, between expectation and sensation, and determines how much confidence to assign those mismatches. Within this framework, dysregulation can arise when prediction errors are assigned excessive precision (i.e., incoming signals are overweighted relative to prior expectations, making them feel "too loud"), amplifying emotional reactivity or when prior expectations update too slowly (feelings get "stuck"), prolonging emotional states beyond contextual demands. We hypothesize that autism may involve heightened confidence assigned to surprising inputs together with sluggish updating of expectations, a combination that can produce both reactivity and emotional inertia. ADHD, by contrast, may be characterized by weaker expectations and unstable gain control, meaning the system's amplification of incoming signals fluctuates from moment to moment, contributing to rapid, reactive swings in affect. We outline candidate physiological correlates-including heart-rate variability dynamics, pupillary variability, mismatch negativity, and neural indices of interoceptive precision-that could evaluate these hypotheses. Framing intervention around restoring flexible inference rather than suppressing emotion offers a mechanistic direction for developmental research. These predictions await empirical validation in developmental samples.

Abstract Research shows that voters use coalition decisions as a heuristic to infer party positions, but little work has studied whether coalition decisions have long-term effects. I argue that voters have longer-lasting impressions of coalition relationships that affect their perceptions of parties after any given coalition ends. Voters keep a running tally of which parties have governed together and update their perceptions of current coalitions based on these prior expectations. Using data from ParlGov and CSES, I analyze coalition relationships across European countries to model the inter-dependencies between party dyads. The results of this analysis show that voters view parties that have previously coalesced as closer together when neither party is in government, as long as they do not change partners, and voters have the strongest reactions to unprecedented and exclusive coalition partnerships.

The perception of the external world relies on integrating information from multiple sensory modalities. To do this effectively, the brain must determine whether sensory signals come from a common source and, if so, combine them to reduce perceptual uncertainty. While Bayesian observer models have been successful in accounting for multisensory causal inference decisions by humans, they typically rely on simplifying assumptions that may not reflect the true complexity of human perception. In this study, we challenge two assumptions common in Bayesian multisensory perception models: homoskedastic (constant across space) sensory noise and Gaussian priors. We collected an auditory-visual perceptual dataset featuring both unisensory and bisensory tasks, where participants must either provide stimulus location estimates or same-different source judgments. Subsequently, we developed a flexible semiparametric approach that allowed us to infer the sensory noise and prior shapes from participants' data, and subsequently 'distill' them into new model classes through visual inspection of the semiparametrically fitted function shapes. We find that human multisensory perception is best described by an eccentricity-dependent sensory noise that plateaus in the periphery and a prior distribution with a narrow central peak and smoother tails. We also found evidence for auditory range recalibration and increased sensory noise in multisensory conditions, suggesting complex interactions between sensory modalities. These findings deviate substantially from traditional modeling assumptions and highlight the value of data-driven rather than theory-driven modeling assumptions. Overall, our study demonstrates the value of systematically exploring model assumptions in multisensory research and provides a new set of modeling tools for perceptual causal inference.

Trusting selectively is a crucial ability in successfully navigating social environments: trusting a trustworthy partner maximizes mutual benefits; withholding trust from an untrustworthy partner minimizes chances of being exploited. Here, we ask how children's trust expectations and experienced trustworthiness inform their own trust decisions. Using a child-friendly repeated Trust Game, we employ a computational modeling approach to examine how children learn about the trustworthiness of others through experience and adjust their own trust behaviors. We tested N = 96 children ages 6-11 years who played 40 trials of the game as trustors with a trustworthy and an untrustworthy trustee. Regression analyses showed that overall, children shared more with trustworthy than untrustworthy partners and older children shared overall more than younger children. Computational models provided a more fine-grained analysis of the learning pattern: a reinforcement learning model that included parameters for individual variation in prior trust expectations and a parameter quantifying the behavioral adjustment over time provided the best fit for the data. Using this computational approach, we could ascertain that children's behavioral adjustments became less responsive over time, suggesting a shift toward more stable patterns of trust once initial impressions were formed. Together, these findings shed light on the development of children's trust interaction with novel partners and highlight the opportunity that computational modeling provides in capturing developmental differences in trust behaviors. SUMMARY: Children aged 6-11 used experience to distinguish trustworthy from untrustworthy partners in a repeated Trust Game, sharing more with the trustworthy than the untrustworthy partner. Older children shared more than younger children, although they were not significantly differentiating between the trustworthy than the untrustworthy partner. Reinforcement learning modeling suggested that children updated trust expectations from experience, with age-related differences in the efficiency of impression updating. These findings highlight both children's capacity in flexibly adjusting their economic trust behaviors and the value of computational modeling in studying economic trust development.

Functional neurological disorders (FNDs) are common, disabling conditions that are genuinely experienced and arise from functional rather than structural abnormalities. Although theoretical frameworks implicate aberrant integration of prior expectations and sensory input, empirical evidence is limited, and it remains unclear whether such alterations reflect symptom-specific deficits or broader trait characteristics. To determine whether individuals with functional tremor exhibit altered integration of prior expectations and sensory input, by comparing their rate of adaptation to a split-belt gait perturbation with that of healthy controls. We examined split-belt treadmill adaptation-a paradigm inducing mismatch between predicted and actual sensory feedback-in patients with functional upper-limb tremor and age-matched healthy control subjects. Fifteen patients and 15 control subjects were recruited; three patients were excluded postenrolment because of the presence of functional gait features resulting in an inability to walk unsupported. Participants completed fast and slow tied-belt baseline walking, 7 minutes of split-belt adaptation, and 4 minutes of washout (ie, slow tied-belt walking). Adaptation and washout of step length asymmetry were quantified using single-exponential fits. Baseline spatiotemporal gait parameters did not differ between groups. Patients with functional tremor adapted step length asymmetry significantly faster than control subjects (26.7 ± 24.9 seconds vs. 100.6 ± 82.2 seconds; P = 0.006) and showed faster adaptation when returning to tied-belt modus (4.1 ± 5.9 seconds vs. 12.2 ± 11.3 seconds; P = 0.033). These findings indicate that individuals with functional tremor exhibit enhanced adaptation to novel sensorimotor contexts, contrasting with slowed adaptation reported in other neurological populations such as Parkinson's disease. Because this study included people with upper-limb functional tremor, accelerated adaptation may reflect a predisposing trait of FND rather than a symptom-specific or task-dependent phenomenon. © 2026 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

People who hear voices may have strong prior expectations of speech, so that noisy auditory signals are resolved as speech. Data in non-clinical voice hearers suggest that voice hearing may involve sensitivity to speech in degraded stimuli. This has yet to be examined in people with schizophrenia (SZ). In this case-control study, we presented sine-wave-speech (SWS; made by replacing the formants in speech with pure tone whistles) to people with SZ (n = 63) and healthy controls (HC; n = 27). SWS is typically unintelligible on first exposure. However, once the listener knows that it is potentially intelligible as speech (by exposure to the unaltered speech template, which thus serves as a prior expectation), relatively high levels of comprehension are achieved. Our participants first listened to intelligible and unintelligible SWS and reported whether they heard speech. They were then exposed to the speech templates, and then the first phase was repeated. Compared to HC, people with SZ reported hearing more speech before template exposure. The Reveal increased both groups' false alarms and reporting of speech, but there was no interaction with group. Change in hit rates after the Reveal correlated with hallucinations, which is consistent with a greater influence of the priors enhancement in SZ patients who hear voices. These findings suggest that people with SZ have stronger expectations of speech. This task has validity for hallucinatory voice hearing. It is also simple and convenient to administer, and may prove useful in detecting prodromal risk, as well as acute exacerbation in voice hearing.

According to predictive processing models, hallucinations can arise from over-weighting of prior expectations relative to sensory input. Individuals who hallucinate may misattribute internally-generated experiences to external sources. Combining these mechanisms, we hypothesized that hallucination-proneness in a non-clinical sample is associated with a greater reliance on internally-generated priors compared to externally-provided priors during degraded speech perception. Two online experiments were conducted with healthy adult participants. Experiment 1 (n = 92) targeted lower-level perceptual processes by assessing sensitivity and bias in distinguishing regular vocoded speech from unintelligible, spectrally-rotated vocoded stimuli at varying levels of sensory clarity. Experiment 2 (n = 100) compared the influence of internally-generated versus externally-provided priors on perception of vocoded speech content. Internal- and external-priors were matched in reliability to test if hallucination-proneness was linked to differential influences of internally-generated priors on speech perception. Experiment 1 confirmed that participants who are more hallucination-prone showed a reduced ability to distinguish potentially intelligible speech from unintelligible speech, and a higher bias toward indicating that speech was present in unintelligible stimuli. Experiment 2 confirmed differential effects of internal priors, showing that hallucination-proneness scores were linked to a greater influence on internally-generated priors on perceptual report when these were incorrect, and a lower reliance on externally-provided priors when these were correct. These findings suggest that hallucination-proneness is linked to an increased influence of internally-generated compared to externally-provided predictions on perception, suggesting an additional element of predictive processing theories of hallucinations.

We reexamined hydrated electron motifs in water cluster anions using photoelectron and electronic absorption spectroscopies under identical ion source conditions. The structural motifs, previously characterized as four, are now established as five in the present work, thereby refining the framework of hydrated electron isomers. Time-resolved photoelectron spectroscopy revealed motif-dependent relaxation dynamics, with certain surface-bound species undergoing more efficient excited-state autodetachment than others. Extending the temporal probing window uncovered long-lived vibrationally excited ground-state anions (τ ∼ 340 ps), far exceeding prior expectations, while increasing cluster size enhanced internal conversion efficiency. These results closely align with theoretical predictions. More broadly, they demonstrate that excited-state dynamics are highly sensitive to local structure, giving rise to distinct relaxation pathways under different hydration environments. The structure–dynamics relationships established here provide a foundation for extending such studies to other hydrated species, advancing fundamental insight into electron solvation and relaxation in aqueous systems.

Acute postoperative pain remains a major clinical challenge, affecting both recovery and resource utilisation. Beyond nociceptive input, pain is shaped by cognitive and emotional factors, including patient expectations. This narrative review examines the role of expectations in perioperative pain modulation, framed within predictive coding and Bayesian inference models. These models conceptualise pain as a probabilistic process that integrates sensory input with prior expectations, weighted by precision. In theory, positive expectations may enhance analgesic efficacy, whereas negative expectations may amplify pain via nocebo mechanisms. Control modifies expectations and may reduce perceived pain, while uncertainty diminishes these benefits. Evidence from observational studies links preoperative pain self-efficacy and anticipated pain scores to postoperative outcomes, yet interventional trials remain scarce. In this narrative review, we propose that expectation-sensitive strategies, including structured communication and computational modelling, may inform individualised anaesthesia and analgesia. Future research should validate these frameworks in clinical trials, optimise preoperative expectation management, and explore synergistic approaches that combine pharmacology with cognitive modulation. Understanding and leveraging expectations may offer a promising conceptual direction for more individualised perioperative care, although this approach remains hypothesis-generating at present.

This study applies the Expectation-Disconfirmation Theory (EDT) to analyze participant satisfaction with the “Rapid Integrated Planning” system in Seoul. Using Structural Equation Modeling (SEM) based on a survey of 516 landowners and experts, the study examines the relationships among prior expectations, perceived performance, and policy satisfaction. The results reveal that high prior expectations for administrative speed negatively impact perceived speed performance, leading to negative disconfirmation. Conversely, the perceived professionalism and rationality of the plan are the most significant positive drivers of satisfaction. Notably, perceived communication showed a negative effect on satisfaction, suggesting that the substantive quality of planning outcomes outweighs the mere frequency of communication. Furthermore, perceived performance was found to mediate the relationship between expectations and satisfaction. These findings imply that the success of the system depends not only on shortening timelines but also on managing stakeholder expectations and prioritizing the qualitative rationality of the plan.