Rapid automatized naming neural networks in children and adults: Connections to reading and arithmetic fluency

Abstract

Emphasizing the rapid transition from written symbols to phonological information, rapid automatized naming (RAN) serves as a robust predictor of proficiency in both reading and arithmetic. The current study aimed to uncover the neural mechanism underlying RAN from childhood to adulthood and how its maturity contributes to the development of reading and arithmetic. Using resting-state functional magnetic resonance imaging (fMRI) data from 34 children (mean age = 11.82 years, SD = 1.13) and 29 adults (mean age = 23.47 years, SD = 2.41), we examined the relationship between RAN and the intrinsic whole-brain functional connectome. The findings revealed a thalamus-centric RAN network in children, whereas adults exhibited a distinct network dominated by left cortical regions. Additionally, two development-related indices were computed: the ‘adult-like’ network maturity, which assesses the degree of similarity between each child's RAN network pattern and the averaged adult network pattern; the ‘child-unique’ network strength, which measures the strength of connections within the RAN network specific to children. Significant positive correlations were observed between the adult-like maturity index and reading and arithmetic fluency in children, alongside the segregation of the reading and arithmetic networks. Notably, a validation analysis confirmed that these correlations were not attributed to the overall brain maturation. By shedding light on the specific contribution of neural mechanisms underlying RAN, this study offers insightful perspectives on the neural underpinnings of the developmental covariance between reading and arithmetic.