Maturation Trajectories of Cortical Resting-State Networks Depend on the Mediating Frequency Band

TL;DR

This study reveals that cortical resting-state networks mature differently depending on the frequency band, with gamma networks showing asymptotic development and beta networks following a linear trajectory, highlighting distinct neural mechanisms.

Contribution

It demonstrates for the first time that beta and gamma band mediated networks have different maturation trajectories, advancing understanding of neural development.

Findings

Gamma networks show asymptotic maturation with increased integration.

Beta networks follow a linear maturation with increased local segregation.

Distinct hub changes occur in beta and gamma mediated networks with age.

Abstract

The functional significance of resting state networks and their abnormal manifestations in psychiatric disorders are firmly established, as is the importance of the cortical rhythms in mediating these networks. Resting state networks are known to undergo substantial reorganization from childhood to adulthood, but whether distinct cortical rhythms, which are generated by separable neural mechanisms and are often manifested abnormally in psychiatric conditions, mediate maturation differentially, remains unknown. Using magnetoencephalography (MEG) to map frequency band specific maturation of resting state networks from age 7 to 29 in 162 participants (31 independent), we found significant changes with age in networks mediated by the beta (13-30Hz) and gamma (31-80Hz) bands. More specifically, gamma band mediated networks followed an expected asymptotic trajectory, but beta band mediated networks followed a linear trajectory. Network integration increased with age in gamma band mediated networks, while local segregation increased with age in beta band mediated networks. Spatially, the hubs that changed in importance with age in the beta band mediated networks had relatively little overlap with those that showed the greatest changes in the gamma band mediated networks. These findings are relevant for our understanding of the neural mechanisms of cortical maturation, in both typical and atypical development.