The maturation and cognitive relevance of structural brain network organization from early infancy to childhood

The interactions of brain regions with other regions at the network level likely provide the infrastructure nec-essary for cognitive processes to develop. Specifically, it has been theorized that in infancy brain networks be -come more modular, or segregated, to support early cognitive specialization, before integration across networks increases to support the emergence of higher-order cognition. The present study examined the maturation of structural covariance networks (SCNs) derived from longitudinal cortical thickness data collected between in-fancy and childhood (0-6 years). We assessed modularity as a measure of network segregation and global effi-ciency as a measure of network integration. At the group level, we observed trajectories of increasing modularity and decreasing global efficiency between early infancy and six years. We further examined subject-based mat-urational coupling networks (sbMCNs) in a subset of this cohort with cognitive outcome data at 8-10 years, which allowed us to relate the network organization of longitudinal cortical thickness maturation to cognitive outcomes in middle childhood. We found that lower global efficiency of sbMCNs throughout early develop-ment (across the first year) related to greater motor learning at 8-10 years. Together, these results provide novel evidence characterizing the maturation of brain network segregation and integration across the first six years of life, and suggest that specific trajectories of brain network maturation contribute to later cognitive outcomes.

Automated summary

The study observed increasing modularity and decreasing global efficiency in brain networks from early infancy to six years old. Furthermore, lower global efficiency during early development was found to be associated with greater motor learning at 8-10 years old, suggesting specific trajectories of brain network maturation contribute to later cognitive outcomes.