Literature DB >> 29462724

Maturation trajectories of cortical resting-state networks depend on the mediating frequency band.

Sheraz Khan1, Javeria A Hashmi2, Fahimeh Mamashli2, Konstantinos Michmizos2, Manfred G Kitzbichler2, Hari Bharadwaj2, Yousra Bekhti2, Santosh Ganesan2, Keri-Lee A Garel2, Susan Whitfield-Gabrieli3, Randy L Gollub4, Jian Kong4, Lucia M Vaina5, Kunjan D Rana6, Steven M Stufflebeam7, Matti S Hämäläinen7, Tal Kenet2.   

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 (13-30 Hz) and gamma (31-80 Hz) 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.
Copyright © 2018. Published by Elsevier Inc.

Entities:  

Keywords:  Brain connectivity; Development; Graph theory; Magnetoencephalography; Rhythms

Mesh:

Year:  2018        PMID: 29462724      PMCID: PMC5949275          DOI: 10.1016/j.neuroimage.2018.02.018

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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