Development of the default-mode network during childhood and adolescence: A longitudinal resting-state fMRI study.

Abstract:

:The default-mode network (DMN) is a set of functionally connected regions that play crucial roles in internal cognitive processing. Previous resting-state fMRI studies have demonstrated that the intrinsic functional organization of the DMN undergoes remarkable reconfigurations during childhood and adolescence. However, these studies have mainly focused on cross-sectional designs with small sample sizes, limiting the consistency and interpretations of the findings. Here, we used a large sample of longitudinal resting-state fMRI data comprising 305 typically developing children (6-12 years of age at baseline, 491 scans in total) and graph theoretical approaches to delineate the developmental trajectories of the functional architecture of the DMN. For each child, the DMN was constructed according to a prior parcellation with 32 brain nodes. We showed that the overall connectivity increased in strength from childhood to adolescence and became spatially similar to that in the young adult group (N = 61, 18-28 years of age). These increases were primarily located in the midline structures. Global and local network efficiency in the DMN also increased with age, indicating an enhanced capability in parallel information communication within the brain system. Based on the divergent developmental rates of nodal centrality, we identified three subclusters within the DMN, with the fastest rates in the cluster mainly comprising the anterior medial prefrontal cortex and posterior cingulate cortex. Together, our findings highlight the developmental patterns of the functional architecture in the DMN from childhood to adolescence, which has implications for the understanding of network mechanisms underlying the cognitive development of individuals.

journal_name

Neuroimage

journal_title

NeuroImage

authors

Fan F,Liao X,Lei T,Zhao T,Xia M,Men W,Wang Y,Hu M,Liu J,Qin S,Tan S,Gao JH,Dong Q,Tao S,He Y

doi

10.1016/j.neuroimage.2020.117581

subject

Has Abstract

pub_date

2021-02-01 00:00:00

pages

117581

eissn

1053-8119

issn

1095-9572

pii

S1053-8119(20)31066-1

journal_volume

226

pub_type

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