Project description:Across the lifespan, empathic and counter-empathic emotions are shaped by social relationships. Here we test the hypothesis that this connection is encoded in children's intuitive theory of psychology, allowing them to predict when others will feel empathy versus counter-empathy and to use vicarious emotion information to infer relationships. We asked 4- to 7-year-old children (N = 79) to make emotion predictions or relationship inferences in response to stories featuring two characters, an experiencer and an observer, and either a positive or negative outcome for the experiencer. In the context of positive outcomes, we found that children engaged in robust joint reasoning about relationships and vicarious emotions. When given information about the characters' relationship, children predicted empathy from a friendly observer and counter-empathy from a rival observer. When given information about the observer's response to the experiencer, children inferred positive and negative relationships from empathic and counter-empathic responses, respectively. In the context of negative outcomes, children predicted that both friendly and rival observers would feel empathy toward the experiencer, but they still used information about empathic versus counter-empathic responses to infer relationship status. Our results suggest that young children in the US have a blanket expectation of empathic concern in response to negative outcomes, but otherwise expect and infer that vicarious emotions are connected to social relationships. Future research should investigate if children use this understanding to select social partners, evaluate their own relationships, or decide when to express empathy toward others.
Project description:Personal identity critically depends on the creation of stories about the self and one's life. The present study investigates the neural substrates of autobiographical reasoning, a process central to the construction of such narratives. During functional magnetic resonance imaging scanning, participants approached a set of personally significant memories in two different ways: in some trials, they remembered the concrete content of the events (autobiographical remembering), whereas in other trials they reflected on the broader meaning and implications of their memories (autobiographical reasoning). Relative to remembering, autobiographical reasoning recruited a left-lateralized network involved in conceptual processing [including the dorsal medial prefrontal cortex (MPFC), inferior frontal gyrus, middle temporal gyrus and angular gyrus]. The ventral MPFC--an area that may function to generate personal/affective meaning--was not consistently engaged during autobiographical reasoning across participants but, interestingly, the activity of this region was modulated by individual differences in interest and willingness to engage in self-reflection. These findings support the notion that autobiographical reasoning and the construction of personal narratives go beyond mere remembering in that they require deriving meaning and value from past experiences.
Project description:Geometric reasoning has an inherent dissonance: its abstract axioms and propositions refer to perfect, idealized entities, whereas its use in the physical world relies on dynamic perception of objects. How do abstract Euclidean concepts, dynamics, and statistics come together to support our intuitive geometric reasoning? Here, we address this question using a simple geometric task - planar triangle completion. An analysis of the distribution of participants' errors in localizing a fragmented triangle's missing corner reveals scale-dependent deviations from a deterministic Euclidean representation of planar triangles. By considering the statistical physics of the process characterized via a correlated random walk with a natural length scale, we explain these results and further predict participants' estimates of the missing angle, measured in a second task. Our model also predicts the results of a categorical reasoning task about changes in the triangle size and shape even when such completion strategies need not be invoked. Taken together, our findings suggest a critical role for noisy physical processes in our reasoning about elementary Euclidean geometry.
Project description:Oxytocin (OT) has an important role in bond formation and social reciprocity, and animal studies indicate that OT functioning is transferred from parent to child through patterns of parental care. Perspectives on attachment suggest that the individual's various attachment bonds are underpinned by the oxytocinergic system. However, prospective human studies that demonstrate the cross-generation transfer of OT as mediated by early caregiving and its impact on children's multiple attachments are lacking. To address these concerns, the current study included 160 mothers and fathers and their firstborn child who participated in a 3-year longitudinal study. At the first and sixth postpartum months, parents' plasma OT was assayed, parent-infant interactions were videotaped and micro-coded, and allelic variations on the OXTR(rs2254298, rs1042778) and CD38rs3796863 genes were measured. At 3 years, parents' and child's salivary OT was assessed and children's social reciprocity observed during interactions with mother, father, and their first best friend. Parents' OT levels were individually stable across the 3-year period, correlated with low-risk OXTR and CD38 alleles, and predicted child OT. Child's social reciprocity with friend was associated with child OT levels, mother's OT-related genes and hormones, and mother-child reciprocity, but not with father's genes, hormones, or behavior. A cross-generation gene-by-environment effect emerged, with low child OT levels predicted by the interaction of maternal high-risk CD38 allele and diminished maternal care in infancy. These results demonstrate individual stability in peripheral OT across several years and describe a cross-generation transfer of OT through caregiving in humans within a prospective longitudinal design. Consistent with other mammals, biobehavioral experiences within the parent-infant bond shape children's affiliative biology and social behavior across multiple attachments. Our findings bear important implications for conditions involving disruptions to maternal-infant bonding and underscore the potential for peer-based interventions.
Project description:Implicit math = male stereotypes have been found in early childhood and are linked to girls' disproportionate disengagement from math-related activities and later careers. Yet, little is known about how malleable children's automatic stereotypes are, especially in response to brief interventions. In a sample of 336 six- to eleven-year-olds, we experimentally tested whether exposure to a brief story vignette intervention with either stereotypical, neutral, or counter-stereotypical content (three conditions: math = boy vs. neutral vs. math = girl) could change implicit math-gender stereotypes. Results suggested that children's implicit math = male stereotypes were indeed responsive to brief stories that either reinforced or countered the widespread math = male stereotype. Children exposed to the counter-stereotypical stories showed significantly lower (and non-significant) stereotypes compared to children exposed to the stereotypical stories. Critically, exposure to stories that perpetuated math = male stereotypes significantly increased math-gender stereotypes over and above baseline, underscoring that implicit gender biases that are readily formed during this period in childhood and even brief exposure to stereotypical content can strengthen them. As a secondary question, we also examined whether changes in stereotypes might also lead to changes in implicit math self-concept. Evidence for effects on implicit self-concept were not statistically significant.
Project description:Narratives, and other forms of discourse, are powerful vehicles for informing, entertaining, and making sense of the world. But while everyday language often describes discourse as moving quickly or slowly, covering a lot of ground, or going in circles, little work has actually quantified such movements or examined whether they are beneficial. To fill this gap, we use several state-of-the-art natural language-processing and machine-learning techniques to represent texts as sequences of points in a latent, high-dimensional semantic space. We construct a simple set of measures to quantify features of this semantic path, apply them to thousands of texts from a variety of domains (i.e., movies, TV shows, and academic papers), and examine whether and how they are linked to success (e.g., the number of citations a paper receives). Our results highlight some important cross-domain differences and provide a general framework that can be applied to study many types of discourse. The findings shed light on why things become popular and how natural language processing can provide insight into cultural success.
Project description:Children's early language knowledge-typically assessed using standardized word comprehension tests or through parental reports-has been positively linked to a variety of later outcomes, from reasoning tests to academic performance to income and health. To better understand the mechanisms behind these links, we examined whether knowledge of certain "seed words"-words with high inductive potential-is positively associated with inductive reasoning. This hypothesis stems from prior work on the effects of language on categorization suggesting that certain words may be important for helping people to deploy categorical hypotheses. Using a longitudinal design, we assessed 36 2- to 4-year-old children's knowledge of 333 words of varying levels of generality (e.g., toy vs. pinwheel, number vs. five). We predicted that adjusting for overall vocabulary, knowledge of more general words (e.g., toy, number) would predict children's performance on inductive reasoning tasks administered 6 months later (i.e., a subset of the Stanford-Binet Intelligence Scales for Early Childhood-Fifth Edition [SB-5] and Woodcock-Johnson Tests of Cognitive Abilities [WJ] concept formation tasks). This prediction was confirmed for one of the measures of inductive reasoning (i.e., the SB-5 but not the WJ) and notably for the task considered to be less reliant on language. Although our experimental design demonstrates only a correlational relationship between seed word knowledge and inductive reasoning ability, our results are consistent with the possibility that early knowledge of certain seed words facilitates performance on putatively nonverbal reasoning tasks.
Project description:Research on distributive justice indicates that preschool-age children take issues of equity and merit into account when distributing desirable items, but that they often prefer to see desirable items allocated equally in third-party tasks. By contrast, less is known about the development of retributive justice. In a study with 4- to 10-year-old children (n = 123) and adults (n = 93), we directly compared the development of reasoning about distributive and retributive justice. We measured the amount of rewards or punishments that participants allocated to recipients who differed in the amount of good or bad things they had done. We also measured judgments about collective rewards and punishments. We found that the developmental trajectory of thinking about retributive justice parallels that of distributive justice. The 4- to 5-year-olds were the most likely to prefer equal distributions of both rewarding and aversive consequences; older children and adults preferred deservingness-based allocations. The 4- to 5-year-olds were also most likely to judge collective rewards and punishments as fair; this tendency declined with increasing age. Our results also highlight the extent to which the notion of desert influences thinking about distributive and retributive justice; desert was considered equally when participants allocated reward and punishments, but in judgments about collective discipline, participants focused more on desert in cases of punishment compared with reward. We discuss our results in relation to theories about preferences for equality versus equity, theories about how desert is differentially weighed across distributive and retributive justice, and the literature on moral development and fairness.
Project description:Connectomics is a subfield of neuroscience that aims to map the brain's intricate wiring diagram. Accurate neuron segmentation from microscopy volumes is essential for automating connectome reconstruction. However, current state-of-the-art algorithms use image-based convolutional neural networks that are limited to local neuron shape context. Thus, we introduce a new framework that reasons over global neuron shape with a novel point affinity transformer. Our framework embeds a (multi-)neuron point cloud into a fixed-length feature set from which we can decode any point pair affinities, enabling clustering neuron point clouds for automatic proofreading. We also show that the learned feature set can easily be mapped to a contrastive embedding space that enables neuron type classification using a simple KNN classifier. Our approach excels in two demanding connectomics tasks: proofreading segmentation errors and classifying neuron types. Evaluated on three benchmark datasets derived from state-of-the-art connectomes, our method outperforms point transformers, graph neural networks, and unsupervised clustering baselines.
Project description:Social Stories™ is one of the most popular interventions for autistic children and has been researched extensively. However, effectiveness data has been gathered mainly through single-participant designs which generate outcomes which can lack generalizability and social validity. Stories Online For Autism (SOFA) is a digital application which supports the development and delivery of Social Stories in a real-world setting and has the potential to contribute toward furthering (1) Social Stories research and (2) research on digital applications for autism by gathering large data sets from multiple participants. Three data sets (N = 856) were gathered through the SOFA app and were analyzed to investigate three key variables: What predicted closeness-to-goal of the Social Stories (as rated by an adult/parent/guardian, n = 568); the child's comprehension of the Social Stories (assessed by story comprehension questions, n = 127); and the child's rating of the enjoyability of the Social Stories (n = 161). A merged data set then investigated correlations between these three key variables. Age range (≤15), gender, autism diagnosis, and the child's level of language understanding were the potential predictors for these three key variables. Regression analysis indicated that parental closeness-to-goal ratings for their children were highest for children who were younger and more verbal. Regression analysis also indicated that older children scored higher in comprehension assessment, and autistic children rated the Social Stories as more enjoyable. Closeness-to-goal, comprehension scores and enjoyment ratings did not significantly correlate with each other. This is the largest study of Social Stories effectiveness, which was enabled through the collection of data through a digital app from multiple participants. The results indicate that digital social stories are particularly effective for younger verbal children. While this was the case for all children, it was particularly true for autistic children and female (and gender-diverse) children. For the first time, the gathering of large digital data sets has highlighted that while digital Social Stories can be effective for autistic males, they can be more effective for autistic females and gender-diverse autistic individuals. Thus, the SOFA app can support the investigation of the factors which influence Social Stories outcomes that are generalizable and with high social validity.