Statistical learning can be used to gain sensitivity to many important regularities in our environment, including structure that is foundational to language and visual perception. As yet, little is known about how statistical learning takes place in the human brain, especially in children's developing brains and with regard to the broader neurobiology of learning and memory. We therefore explored the relationship between statistical learning and the thickness and volume of structures that are traditionally implicated in declarative and procedural memory, focusing specifically on the left inferior PFC, the hippocampus, and the caudate during early childhood (ages 5–8.5 years). We found that the thickness of the left inferior frontal cortex and volume of the right hippocampus predicted statistical learning ability in young children. Importantly, these regions did not change in thickness or volume with age, but the relationship between learning and the right hippocampus interacted with age such that older children's hippocampal structure more strongly predicted performance. Overall, the data show that children's statistical learning is supported by multiple neural structures that are more broadly implicated in learning and memory, especially declarative memory (hippocampus) and attention/top–down control (the PFC).

Working memory develops slowly: Even by age 8, children are able to maintain only half the number of items that adults can remember. Neural substrates that support performance on working memory tasks also have a slow developmental trajectory and typically activate to a lesser extent in children, relative to adults. Little is known about why younger participants elicit less neural activation. This may be due to maturational differences, differences in behavioral performance, or both. Here we investigate the neural correlates of working memory capacity in children (ages 5–8) and adults using a visual working memory task with parametrically increasing loads (from one to four items) using fMRI. This task allowed us to estimate working memory capacity limit for each group. We found that both age groups increased the activation of frontoparietal networks with increasing working memory loads, until working memory capacity was reached. Because children's working memory capacity limit was half of that for adults, the plateau occurred at lower loads for children. Had a parametric increase in load not been used, this would have given an impression of less activation overall and less load-dependent activation for children relative to adults. Our findings suggest that young children and adults recruit similar frontoparietal networks at working memory loads that do not exceed capacity and highlight the need to consider behavioral performance differences when interpreting developmental differences in neural activation.

Cognitive conflict detection and resolution develops with age across childhood and likely supports age-related increases in other aspects of cognitive and emotional development. Little is known about the neural correlates of conflict detection and resolution in early childhood. In the current study, we investigated age-related change in neural recruitment during a blocked spatial-incompatibility task (Simon task) in children ages 5–10 years using fMRI. Cortical thickness was measured using structural MRI. Across all children, there was greater activation in right prefrontal and bilateral parietal cortices for incompatible than compatible conditions. In older children, compared with younger children, there was decreased activation and decreased gray matter thickness in the medial PFC. Thickness and activation changes across age were associated within participants, such that thinner cortex was associated with less activation in the rostral ACC. These findings suggest that developmental change in medial PFC activation supports performance on cognitive control tasks in early childhood.