AbstractHumans are remarkably efficient at learning new tasks, in large part by relying on the integration of previously learned knowledge. However, research on task learning typically focuses on the learning of abstract task rules on minimalist stimuli, to study behavior independent of the learning history that humans come equipped with (i.e., semantic knowledge). In contrast, several theories suggest that the use of semantic knowledge and labels may help the learning of new task information. Here, we tested whether providing existing, semantically rich task embeddings and response labels allowed for more robust task rule encoding and less (catastrophic) forgetting and interference. Our results show that providing semantically rich task settings and response labels resulted in less task forgetting (Experiment 1), both when using pictorial symbols or words as labels (Experiment 2), or when contrasted with visually matched shape labels without inherent meaning (Experiment 4). Using a subsequent value-based decision-making task and reinforcement learning modeling (Experiment 3), we demonstrate how the learned embedding of novel stimuli in semantically rich, representations, further allowed for a more efficient, feature-specific processing when learning new task information. Finally, using artificial recurrent neural networks fitted to our participants’ task performance, we found that task separation during learning was more predictive of learning and task performance in the semantically rich conditions. Together, our findings show the benefit of using semantically rich task rules and response labels during novel task learning, thereby offering important insights into why humans excel in continual learning and are less susceptible to catastrophic forgetting compared to most artificial agents.

AbstractDespite cross-linguistic diversity in how kin relations map to terminology, there are constraints on which kin may be categorised together. But what are the constraints on kin term variation, and where do they come from? One proposed constraint is internal co-selection—an evolutionary process where terminological changes in one generation of kin co-occur with parallel changes in other generations. This results in kin categories which are predictable on the basis of other kin categories, a property we call predictive structure. To determine the strength of this constraint, we measured the predictive structure of kinship terminology systems from 731 languages. We found that kinship terminologies exhibit a significant degree of predictive structure, and we argue that its prevalence reflects a cognitive pressure for simplicity imposed during the generalisation of known kin categories to new referent types. We tested this claim using an artificial kin term generalisation task. Our results suggest that people do favour predictive structure when generalising from known kin categories to new referents, but that this preference faces interference from other pressures to distinguish kin by features like gender.

AbstractNavigating the social world is guided by remembering which people know each other. Yet, different factors might influence how social relationships are remembered, where people’s shared attributes could distort a social network’s mnemonic representation. Here, we study whether dyadically shared contexts and personality traits impact how people remember relationships in social networks. Through varying levels of network topological complexity, we find the contexts where people know each other are most memorable and that better contextual retrieval predicts relationship recall. In contrast, shared personality traits affect relationship recall differently depending on social network complexity, where shared negatively valenced traits relate to worse relationship recall in the simple network. Subsequent modeling revealed that as networks become more complex, relationships between more centrally positioned individuals that share negatively valenced traits are better recalled compared to less well-connected individuals. These results suggest contextual memory can serve as a scaffold for remembering relationships in a social network, while affective traits’ impact on social network retrievability depends on emotional valence and the individuals involved. More generally, our findings give insight into how the same social network can be represented differently based on one’s past experience.

AbstractWhen people see an agent perform a task, do they care if the underlying algorithm driving it is ‘intelligent’ or not? More generally, when people intuitively evaluate the performance of others, do they value external performance metrics (intuitive behaviorism) or do they also take into account the underlying algorithm driving the agent’s behavior (intuitive cognitivism)? We propose 3 dimensions for examining this distinction: Action Efficiency, Representation Efficiency, and Generalization. Across 3 tasks (N = 598), we showed people pairs of maze-solving agents, together with the programs driving the agents’ behavior. Participants were asked to pick the ‘better’ of the two programs, based on a single example of the two programs, evaluated on the same maze. Each pair of programs varied along one of our 3 proposed dimensions. Our framework predicts people’s choice of program across the tasks, and the results support the idea that people are intuitive cognitivists.

AbstractJudgment is often described in terms of an intuitive (System 1) versus deliberative (System 2) dichotomy, yet sound deliberation itself can take more than one form. Building on philosophical traditions and distinctions in treatment of sound judgment in economics and law, we propose that lay conceptions revolve around two distinct types of deliberate judgment: rational, emphasizing rule-based and utility-focused reasoning for well-defined problems, and reasonable, prioritizing context-sensitive and socially conscious reasoning for ill-defined problems. Across four studies in English-speaking Western samples (Studies 1–4; N = 2,130) and a Mandarin-speaking Chinese sample (Study 4; N = 697), participants described their notions of “sound” and “good” judgment, evaluated social scenarios, chose between candidates with distinct judgmental profiles, and categorized non-social objects. Results consistently showed that people view both rationality and reasonableness as common forms of deliberate sound judgment, while treating them as distinct. Participants preferred rational deliberation for algorithmic social roles linked to well-defined tasks and reasonable deliberation for interpretive roles linked to ill-defined tasks. Moreover, framing decisions as rational vs. reasonable influenced whether participants relied on rule-based vs. overall-similarity strategies in classification tasks. These findings suggest that lay understanding of sound judgment does not rely on a single standard of judgmental competence. Instead, people recognize that both rationality and reasonableness are critical for competent deliberation on different types of problems in life.

AbstractConspiracy theories have pervaded human thought across time and cultures, often emerging during crises such as the COVID-19 pandemic, where they influenced public behaviors and attitudes, notably in vaccine hesitancy. This research explores the metacognitive foundations of conspiracy beliefs, particularly focusing on how individuals monitor and assess their problem-solving processes. We propose that conspiracy beliefs are linked to high propositional confidence—often unsupported by accurate reasoning. Two studies were conducted to investigate the potential relationship between meta-reasoning inaccuracies (i.e., prospective confidence judgments and commission errors) during problem solving and conspiracy beliefs. Across two studies, we examine metacognitive markers of this overconfidence. Study 1 analyzes archival data from George and Mielicki’s (2023) to investigate how COVID-19 conspiracy beliefs are associated with initial judgments of solvability in solvable and unsolvable Compound Remote Associate (CRA) tasks. Study 2 examines the relationship between commission errors on Rebus puzzles and conspiracy beliefs, while also assessing Socio-Cognitive Polarization (SCP)—a construct encompassing ideological rigidity, intolerance of ambiguity, and xenophobia. Results show that SCP amplified the effects of commission errors on conspiracy beliefs, situating these cognitive patterns within socio-political contexts. These findings offer novel evidence that conspiracy beliefs are not merely a product of what people think, but how they think—underscoring the intertwined roles of flawed meta-reasoning and socio-political attitudes in sustaining conspiratorial worldviews.

AbstractUsing our hands to move a stick along a path differs in systematic ways from using our hands to communicate about moving the stick. Kinematic signatures (e.g., enlarged moving trajectories) have been found to mark a movement as communicative, relative to its non-communicative counterpart. But communicative movements are frequently embedded within an expressive system and might differ as a function of that system. For example, deaf signers move their hands when they communicate with sign language, which is a linguistic system. Hearing speakers also move their hands—they gesture along with speech—but those gestures do not form a linguistic system unto themselves. Do the communicative movements signers and speakers use to describe the same event differ as a function of the expressive systems within which they are embedded? Because some signs are highly iconic, researchers often assume that movements in these signs have the same properties as speakers’ gestures. To test this assumption, we compared spontaneous hand gestures produced by hearing speakers when they talk (co-speech gesture) to productive iconic hand signs produced by deaf signers when the signs superficially resemble co-speech gestures (classifier signs). We used motion tracking and kinematic analyses to disentangle the spatial and temporal kinematic patterns of communicative movements in 33 English-speakers and 10 American Sign Language (ASL) signers, using each group’s non-communicative movements as a control. Participants copied a movement on an object performed by a model (non-communicative movement) and then described what they did with the object (communicative movement). We found no differences between groups in how non-communicative movements related to communicative movements for spatial kinematics. However, for temporal kinematics, speakers’ co-speech movements were less rhythmic and jerkier than their non-communicative movements, but signers’ communicative movements were more rhythmic and smoother than their non-communicative movements. We thus found differences in the temporal aspects of co-speech gestures vs. classifier signs, leading to 3 conclusions: (i) Communicative movements do not always have the same kinematic signatures but depend on the expressive system within which they are embedded. (ii) Since signers’ and speakers’ communicative movements have different kinematic features, even highly iconic signed movements cannot be considered entirely gestural. (iii) We need fine-grained techniques to measure communicative movements, particularly when trying to identify the gestural aspects of sign. Communicative movements, even when superficially similar, differ as a function of the system they are part of.

AbstractMany advances in NLP, starting with distributional semantics, are founded on the insight that the semantics of words can be revealed by their co-occurrences (the frequency for two words to be present in the same sentence). And the most sophisticated modern machines are built to reproduce the statistics of even larger sets of words. Yet, these systems do not provide a transparent description of these statistics. We reveal a second-order Zipf’s law: the frequencies of co-occurrences follow an inverse power law in all 17 languages we tested. To assess this, we use the most conservative methods to detect a power law (and even develop its extension in the natural case of a finite vocabulary, which reveals new insights). We show that this second-order Zipf’s law is not a consequence of random processes, it is not a consequence of the usual Zipf’s law on word frequencies (it is less robust in a shuffled corpus), and it is not a consequence of syntactic constraints (it is less robust in a shuffled corpus that respects syntactic categories). The second-order Zipf’s law may therefore be more foundational than Zipf’s original law, and able to provide (transparent) information about semantic aspects of language.

AbstractTo maintain and develop close relationships, people need to accurately represent the minds of their social partners. Although studies have characterized many aspects of children’s intuitive theory of the mind and children’s intuitive theory of relationships, it is largely unknown whether and how children think about mental state reasoning within relationships. In three experiments, we asked whether children think accurate mental state reasoning is a cue to social closeness. In Experiment 1 (n = 145), we found that 5- to 9-year-old children, but not 4-year-old children, inferred that characters who engage in affective touch (making physical contact, as though nuzzling, while moving together in synchrony) are socially closer and know about each other’s goals and desires. In Experiment 2 (n = 137), we found that 6- to 9-year-old children, but not younger children, inferred that characters who are correct about each other’s minds are socially close. Children did not think that being correct about external states of the world was evidence that a character was close to another. In Experiment 3 (n = 79), we conceptually replicated the main findings from Experiments 1 and 2, and we found that 6- to 9-year-old children did not form the same inferences concerning knowledge about observable features of individuals (e.g., an individual’s outfit); children’s inferences were specific to unobservable mental content. Thus, by 6 years of age, children integrate their intuitive theories of the mind and relationships to make sense of whether and how people are connected to each other, as well as the strength and nature of those connections.

AbstractEmerging single-process propositional perspectives in psychology and philosophy have introduced the key idea that, much like their explicit (deliberately retrieved) counterparts, implicit (automatically retrieved) attitudes should be sensitive to logical operations such as negation. In the present project, we subject this idea to a particularly stringent test by probing not only whether the formation of implicit attitudes is sensitive to negation but also whether such sensitivity additionally reflects the distinction between easy-to-negate bipolar adjectives (those with clear antonyms, e.g., strong) and difficult-to-negate unipolar adjectives (those without clear antonyms, e.g., unique). Across four experiments (three preregistered; total N = 6,707), we found (a) no significant difference in the formation of implicit attitudes in response to affirmed bipolar versus affirmed unipolar adjectives (β = 0.07); (b) modulation of the formation of implicit attitudes by whether adjectives were affirmed or negated (β = 0.67); and, critically, (c) stronger modulation of the formation of implicit attitudes by the negation of bipolar relative to unipolar adjectives (β = 0.23). These results generalized across three sets of adjectives, two implicit attitude measures (the Implicit Association Test and the Affect Misattribution Procedure), and two novel targets (social and nonsocial). Together, these data provide strong evidence to suggest that the formation of implicit attitudes is sensitive to logical operations, including not only whether an adjective is affirmed or negated but even whether adjectives are relatively easy or difficult to negate. We discuss theoretical implications for single-process and dual-process accounts of attitude formation and higher-order human cognition.

AbstractIn classic research, Hamlin et al. (2007) found that infants preferentially reach to agents who help others over agents who hinder others. These early findings provided evidence that infants may engage in social evaluation. There have now been multiple failures to replicate the original findings, and these failed replication attempts have called into question whether infants engage in social evaluation. In the present paper, we contextualize these failed replication attempts in the broader literature. We review evidence that infants and toddlers evaluate a range of social behaviors, including acts of physical harm, resource distribution, comforting, imitation, and dominance. We also review evidence that infants and toddlers have demonstrated other behaviors, beyond preferential reaching, that suggest that they engage in social evaluation. The larger body of evidence therefore supports the possibility that early social evaluation is a real phenomenon. We discuss how cognitive scientists can better study early social evaluation moving forward.

Abstract‘Why are we curious?’ has been among the central puzzles of neuroscience and psychology in the past decades. A popular hypothesis is that curiosity is driven by intrinsically generated reward signals, which have evolved to support survival in complex environments. To formalize and test this hypothesis, we need to understand the enigmatic relationship between (i) intrinsic rewards (as drives of curiosity), (ii) optimality conditions (as objectives of curiosity), and (iii) environment structures. Here, we demystify this relationship through a systematic simulation study. First, we propose an algorithm to generate environments that capture key abstract features of different real-world situations. Then, we simulate artificial agents that explore these environments by seeking one of six representative intrinsic rewards: novelty, surprise, information gain, empowerment, maximum occupancy principle, and successor-predecessor intrinsic exploration. We evaluate the exploration performance of these simulated agents regarding three potential objectives of curiosity: state discovery, model accuracy, and uniform state visitation. Our results show that the comparative performance of each intrinsic reward is highly dependent on the environmental features and the curiosity objective; this indicates that ‘optimality’ in top-down theories of curiosity needs a precise formulation of assumptions. Nevertheless, we found that agents seeking a combination of novelty and information gain always achieve a close-to-optimal performance on objectives of curiosity as well as in collecting extrinsic rewards. This suggests that novelty and information gain are two principal axes of curiosity-driven behavior. These results pave the way for the further development of computational models of curiosity and the design of theory-informed experimental paradigms.

AbstractConditional statements often have two interpretations. For instance, the statement, “If you mow the lawn, you will receive $5”, might be understood to mean that mowing the lawn is just one possible way to earn $5 or, more strongly, that mowing the lawn is the only way one can receive $5 – an interpretation sometimes called Conditional Perfection. We investigated how people arrive at “perfected” interpretations of conditional statements: whether they initially consider a statement's literal meaning and then perfect it or begin with a perfected interpretation and revert to the weaker meaning only when necessary. Reaction time data from Experiment 1 supports the latter sequence, as evidenced by the longer time required to arrive at literal interpretations than perfected ones. Additionally, in Experiment 2, we found that participants under cognitive load were more likely to perfect conditional statements relative to participants not under load, again suggesting that people begin with a perfected meaning that is optionally canceled with effort.

AbstractIn the field of affective neuroscience, the “Reading the Mind in the Eyes Test” (RMET) is regarded as the gold standard for assessing Theory of Mind (ToM) in general and clinical populations. Despite its widespread use and acceptance, there has been no comprehensive evaluation of the psychometric properties of the Spanish version of the test, particularly concerning its internal structure and dimensionality, especially with regard to the application of Item Response Theory (IRT). Therefore, the aim of this study is to examine the items of the Argentine version of the RMET through an IRT approach to explore its effectiveness in measuring ToM in neurotypical adult populations within Argentina. A sample of 899 adults from Buenos Aires, Argentina (34.3% men, 65.7% women) aged between 18 and 82 (M = 32.95, SD = 13.35) completed a sociodemographic questionnaire and the RMET. Based on a preliminary assessment of the data’s suitability for factor analysis, including inspection of item-level sampling adequacy, we analysed a reduced 13-item version of the test. While these items were consistent with a unidimensional structure, the main factor explained only 21.2% of the variance, and the factor loadings were relatively low. The analysis revealed weak and questionable evidence for the dimensionality of the construct, with retained items showing medium-low difficulty and moderate discrimination. Additionally, the overall reliability estimates were insufficient. Therefore, the results of this study do not support the psychometric properties of the argentine version of RMET and contribute to increasing awareness of the critical need to thoroughly evaluate its validity and reliability.

AbstractVisual-world eye-tracking has long been a useful tool for measuring young children’s real-time interpretation of words and sentences. Recently, researchers have extended this method to virtual platforms to reduce equipment costs and recruit more diverse participants. However, there is currently limited guidance on best practices, which require individual researchers to invent their own methodologies and may prevent broader adoption. Here, we present three broad approaches for implementing nine remote visual-world eye-tracking studies, and show that this method is highly feasible for assessing fine-grained language processing across populations of varying ages, clinical statuses, and socioeconomic status backgrounds. We outline strategic methods for conducting this research effectively, including strategies for experimental design, data collection, and data analysis given the variable conditions outside of a lab setting. We adopt four criteria for evaluating success for this method: 1) Minimal subject attrition relative to in-person studies, 2) Minimal track loss relative to conventional eye-tracking, 3) Conceptual replication of previous findings, and 4) Evidence of broadening participation. These case studies provide a thorough guide to future researchers looking to conduct remote eye-tracking research with developmental populations. Ultimately, we conclude that visual-world eye-tracking using internet-based methods is feasible for research with young children and may provide a relatively inexpensive option that can reach a broader, more diverse set of participants.

AbstractForming memories requires a focus on the external world; retrieving memories requires attention to our internal world. Computational models propose that the hippocampus resolves the tension between encoding and retrieval by alternating between states that prioritize one over the other. We asked whether the success of a retrieval state affects the success of an encoding state, when both are measured in behavior. Across 3 Experiments (N = 197), we operationalized retrieval as the use of memories to make predictions about the future, and tested whether successful (vs. unsuccessful) prediction affected the likelihood of successful encoding. Participants viewed a series of scene categories that contained structure (e.g., beaches are followed by castles), which enabled memory retrieval to guide prediction. After structure learning, they completed a simultaneous prediction and encoding task. They were shown trial-unique category exemplars and made predictions about upcoming scene categories. Finally, participants completed a surprise memory test for the trial-unique images. Accurate (vs. inaccurate) predictions were associated with better encoding, and increasing prediction distance hurt both prediction and encoding. This association between encoding and prediction could not be explained by generic on- vs. off-task states. We propose that, in addition to stimulus and endogenous factors that modulate switches between encoding and retrieval, the success of one state can facilitate a switch to the other. Thus, although encoding and prediction depend on distinct and competitive computational mechanisms, the success of one in behavior can increase the likelihood of success for the other.

AbstractWe can use prior knowledge of temporal structure to make predictions about how an event will unfold, and this schematic knowledge has been shown to impact the way that event memories are encoded and later reconstructed. Existing paradigms for studying prediction, however, are largely unable to separate effects of prediction accuracy from effects of stimulus probability: likely outcomes are assumed to be predicted, while unlikely outcomes are assumed to cause prediction errors. Here we use a novel approach in which we can independently manipulate prediction success and stimulus probability, by using real-time eye-tracking when viewing moves in a board game. The moves can be consistent or inconsistent with a participant’s predictions (assessed via fixation patterns) and can be also be likely or unlikely to be played by a strategic player. By decorrelating these two measures, we found that both probability and prediction accuracy boost memory through two separate mechanisms, leading to different eye-movement strategies at retrieval. Accurate prediction improved encoding precision, allowing participants to directly retrieve these moves without the use of schematic knowledge. Probable moves, on the other hand, led to improved memory through a retrieval-time strategy in which schematic knowledge was used to generate candidate moves for recognition. These results shed new light on the specific role of predictions in enhancing event memories, and provide a more realistic paradigm for studying schemas, learning, and decision making.

AbstractThere is consistent evidence for a positive association between education and a wide range of cognitive abilities. In particular, spatial abilities have been shown to be strongly related to academic achievement. However, studying this association is complex as both education and spatial abilities are modulated by multivariate sociodemographic factors, likely to vary across countries. Most previous studies relied on small sample sizes or were restricted to a limited number of countries, thus were unable to control for these covariates. To overcome these limitations, we used a spatial navigation task embedded in a mobile video game. We quantified the wayfinding ability of 397,162 people across 38 countries and showed that on average, education level was positively associated with wayfinding ability. This difference was stronger in older participants and increased with task difficulty. However, the effect of education was different across countries, from near-zero and non-significant in India (Bayes’ factor = 0.08, Hedge’s g = −0.03, 95% CI = [−0.15, 0.08]), to modest and significant in Romania (Bayes’ factor = 345.44, Hedge’s g = 0.15, 95% CI = [0.08, 0.22]). We did not find any relationship between the education effect size of countries and economic indicators such as GDP per capita. Using the 1972 reform increasing the minimum school leaving age in the UK as a natural experiment, we used a regression discontinuity design to show that education has a causal effect on wayfinding ability.

AbstractA comprehensive cognitive science requires broad sampling of human behavior to justify general inferences about the mind. For example, the field of psycholinguistics relies on a rich history of comparative study, with many available resources that systematically document many languages. Surprisingly, despite a longstanding interest in questions of universality and diversity, the psychology of music has few such resources. Here, we report the Expanded Natural History of Song Discography, an open-access corpus of vocal music (n = 1007 song excerpts), with accompanying metadata detailing each song’s region of origin, language (of 413 languages represented here), and one of 10 behavioral contexts (e.g., work, storytelling, mourning, lullaby, dance). The corpus is designed to sample both broadly, with a large cross-section of societies and languages; and deeply, with many songs representing three well-studied language families (Atlantic-Congo, Austronesian, and Indo-European). This design facilitates direct comparison of musical and vocal features across cultures, principled approaches to sampling stimuli for experiments, and evaluation of models of the cultural evolution of song. In this paper we describe the corpus and provide two proofs of concept, demonstrating its utility. We report (1) a conceptual replication of previous findings that the acoustical forms of songs are predictive of their behavioral contexts, including in previously unstudied contexts (e.g., children’s play songs); and (2) similarities in acoustic content of songs across cultures are predictable, in part, by the relatedness of those cultures.

AbstractHow do we learn who is good at what? Building on the idea that humans draw rich inferences from others’ emotional expressions, here we ask whether others’ surprised reactions to performance outcomes can elicit inferences about competence. Across three experiments, participants were asked to choose “who is better” in scenarios where two students performed identically on the same task but their teacher expressed surprise to only one of them. In Experiment 1 (n = 60, adults) and Experiment 2 (n = 90, 6- to 8-year-old children), participants’ responses were modulated by not only the students’ performance outcomes (success or failure) but also the teacher’s response to the outcomes (surprise or no surprise). Specifically, participants preferentially chose the student who did not elicit the teacher’s surprise as more competent when both students succeeded, but chose the student who elicited surprise when both failed. Experiment 3a (n = 150, 4- to 8-year-olds) replicated this pattern in 6- to 8-year-olds as a group—but not in 4- to 5-year-olds—with increasing robustness with age. Finally, this pattern was significantly reduced in Experiment 3b where the teacher’s surprise was directed at an irrelevant event rather than the student’s performance (n = 90, 6- to 8-year-olds). Taken together, these results suggest that even non-valenced emotional reactions to performance outcomes—being surprised at someone’s success or failure—can inform inferences about valenced qualities such as competence. More broadly, the current findings demonstrate that emotional expressions we observe in our daily lives can lead to nuanced yet consequential social judgments.

AbstractWhen making decisions, we often have more information about some options than others. Previous work has shown that people are more likely to choose options that they look at more and those that they are more confident in. But should one always prefer options one knows more about? Intuition suggests not. Rather, how additional information impacts our preferences should depend critically on how valuable we expect the options to be. Here, we formalize this intuition in a Bayesian sequential sampling model where attention and confidence influence the precision of momentary evidence. Our model makes a key prediction: attention and confidence both increase choice probability for better-than-average options, and both decrease choice probability for worse-than-average options. We confirm this prediction in two experiments in which we independently manipulate value and attention. Our results offer a novel perspective on prior work on the role of attention and confidence in decision-making, showing that people rely on contextual knowledge and uncertainty estimates to adaptively learn about their options and make better decisions.

AbstractMoving through our environment generates multiple changes in my sensations. But I do not experience the environment as changing. My conscious perceptual experience is of a stable environment through which I move. This perception is created by intricate neural computations that automatically take account of my movements. The stable environment that I experience is independent of my actions. As a result, I experience it as objective: a set of facts about the world that constrain my movements. Because it is objective I expect that it will also constrain the movements of others in the same way, whether these are rocks rolling down a hill or animals foraging for food. This experience of objectivity creates a shared understanding of the world that enhances our interactions with others. Our perceptual experiences, while personal, are shaped by our model of the world, and since others are modelling the same world, their models will be very similar. Interactions with others will further increase this similarity. The models create a form of common knowledge. This common knowledge is an inherent feature of our basic conscious perception, even when we’re not actively reflecting on or deliberately sharing our experiences. The common knowledge created by our conscious perception of the world enables the coordination of behaviour which is a critical precursor for the evolution of cooperative behaviour.

AbstractIndividuals with hearing loss have a diverse spectrum of auditory experiences, shaped by the degree of hearing loss and interventions. The study of social cognition in deaf children and more generally, children with hearing loss, contributes to a nuanced understanding of how learning experiences influence social and cognitive development. Research suggests that limited access to language may influence conceptual development in theory of mind or the development of information processing skills required in mental state reasoning. In this article, we briefly review decades of research on social-cognitive development of children with hearing loss acquired in infancy, discuss how access to language-mediated communication contributes to the emergence and expression of understanding other minds and highlight some implications for effective interventions.

AbstractIn language, comprehenders often need to infer the temporal order of events to construct a mental model of a complex situation. Dynamicity differences are a key predictor of these inferences: Non-dynamic states are reliably inferred to precede dynamic events. In two studies, we test two theoretical explanations for this phenomenon through temporal order judgments for past-under-past and future-under-future relative clauses in English: According to a tense-mediated account of temporal anchoring, people rely on the conceptual distinction between a more salient reference time—often a dynamic event—and a less salient anchored situation—often a static state. The temporal relationship between the two is determined at the linguistic level by tense meaning: For the past tense, the relationship should be one of anteriority, and for the future tense, it should be one of posteriority. However, the future tense has often been placed closer to modals than to tenses, relegating the question of temporal order to other mechanisms. Alternatively, from a purely cognitive perspective, salience differences between states and events are sufficient to infer temporal order, with states acting as temporal backgrounds for more salient events, regardless of tense. Our results support such a cognitive mechanism: In both experiments, states are backgrounded relative to events. Differences between the experiments furthermore support modal accounts of the semantics of the future.

AbstractIntegral stimuli (e.g., colors varying in saturation and brightness) are classically considered to be processed holistically (i.e., as undifferentiated stimulus wholes); people analyze such stimuli into their consistent dimensions only with substantial time, effort, training, or instruction (Foard & Kemler, 1984). In contrast, Combination Theory (Wills et al., 2015) argues that the dimensions of integral stimuli are quickly combined. Through an investigation of the effects of stimulus presentation time, we support Combination Theory over the classical holistic-to-analytic account. Specifically, using colored squares varying in saturation and brightness, we demonstrate that the prevalence of single-dimension classification increases as stimulus presentation time is reduced. We conclude that integral stimuli are not slowly analyzed, they are quickly synthesized.