Neural activity that is evoked naturalistically in children during educational television viewing can be used to predict math and verbal knowledge.

Metacognition, the ability to assess one’s own knowledge, has been targeted as a critical learning mechanism in mathematics education. Yet, the early childhood origins of metacognition have proven difficult to study. Using a novel nonverbal task and a comprehensive set of metacognitive measures, we provide the strongest evidence to date that young children are metacognitive. We show that children as young as 5 years make metacognitive “bets” on their numerical discriminations in a wagering task. However, contrary to previous reports from adults, children’s metacognition proved to be domain-specific: children’s metacognition in the numerical domain was unrelated to their metacognition in another domain (emotion discrimination). Moreover, children’s metacognitive ability in only the numerical domain predicted their school-based mathematics knowledge. The data provide novel evidence that metacognition is a fundamental, domain-dependent cognitive ability in children. The findings have implications for theories of uncertainty and reveal new avenues for training metacognition in children.

Efforts to map the functional architecture of the developing human brain have shown that connectivity between and within functional neural networks changes from childhood to adulthood. Although prior work has established that the adult precuneus distinctively modifies its connectivity during task versus rest states [Utevsky, A. V., Smith, D. V., & Huettel, S. A. Precuneus is a functional core of the default-mode network. Journal of Neuroscience, 34, 932–940, 2014], it remains unknown how these connectivity patterns emerge over development. Here, we use fMRI data collected at two longitudinal time points from over 250 participants between the ages of 8 and 26 years engaging in two cognitive tasks and a resting-state scan. By applying independent component analysis to both task and rest data, we identified three canonical networks of interest—the rest-based default mode network and the task-based left and right frontoparietal networks (LFPN and RFPN, respectively)—which we explored for developmental changes using dual regression analyses. We found systematic state-dependent functional connectivity in the precuneus, such that engaging in a task (compared with rest) resulted in greater precuneus–LFPN and precuneus–RFPN connectivity, whereas being at rest (compared with task) resulted in greater precuneus–default mode network connectivity. These cross-sectional results replicated across both tasks and at both developmental time points. Finally, we used longitudinal mixed models to show that the degree to which precuneus distinguishes between task and rest states increases with age, due to age-related increasing segregation between precuneus and LFPN at rest. Our results highlight the distinct role of the precuneus in tracking processing state, in a manner that is both present throughout and strengthened across development.

Cognitive development research shows that children use basic “child-unique” strategies for reading and mathematics. This suggests that children’s neural processes will differ qualitatively from those of adults during this developmental period. The goals of the current study were to 1) establish whether a within-subjects neural dissociation between reading and mathematics exists in early childhood as it does in adulthood, and 2) use a novel, developmental intersubject correlation method to test for “child-unique”, developing, and adult-like patterns of neural activation within those networks. Across multiple tasks, children’s reading and mathematics activity converged in prefrontal cortex, but dissociated in temporal and parietal cortices, showing similarities to the adult pattern of dissociation. “Child-unique” patterns of neural activity were observed in multiple regions, including the anterior temporal lobe and inferior frontal gyri, and showed “child-unique” profiles of functional connectivity to prefrontal cortex. This provides a new demonstration that “children are not just little adults” – the developing brain is not only quantitatively different from adults, it is also qualitatively different.

The phenomenon of ambiguity aversion, in which risky gambles with known probabilities are preferred over ambiguous gambles with unknown probabilities, has been thoroughly documented in adults but never measured in children. Here, we use two distinct tasks to investigate ambiguity preferences of children (8- to 9-year-olds) and a comparison group of adults (19- to 27-year-olds). Across three separate measures, we found evidence for significant ambiguity aversion in adults but not in children and for greater ambiguity aversion in adults compared to children. As ambiguity aversion in adults has been theorized to result from a preference to bet on the known and avoid the unfamiliar, we separately measured familiarity bias and found that children, like adults, are biased towards the familiar. Our findings indicate that ambiguity aversion emerges across the course of development between childhood and adolescence, while a familiarity bias is already present in childhood.