Brain Structure and Function

, Volume 220, Issue 1, pp 37–46

Dynamic brain functional connectivity modulated by resting-state networks

Original Article

DOI: 10.1007/s00429-013-0634-3

Cite this article as:
Di, X. & Biswal, B.B. Brain Struct Funct (2015) 220: 37. doi:10.1007/s00429-013-0634-3


Studies of large-scale brain functional connectivity using the resting-state functional magnetic resonance imaging have advanced our understanding of human brain functions. Although the evidence of dynamic functional connectivity is accumulating, the variations of functional connectivity over time have not been well characterized. In the present study, we aimed to associate the variations of functional connectivity with the intrinsic activities of resting-state networks during a single resting-state scan by comparing functional connectivity differences between when a network had higher and lower intrinsic activities. The activities of the salience network, default mode network (DMN), and motor network were associated with changes of resting-state functional connectivity. Higher activity of the salience network was accompanied by greater functional connectivity between the fronto-parietal regions and the DMN regions, and between the regions within the DMN. Higher DMN activity was associated with less connectivity between the regions within the DMN, and greater connectivity between the regions within the fronto-parietal network. Higher motor network activity was correlated with greater connectivity between the regions within the motor network, and smaller connectivity between the DMN regions and fronto-parietal regions, and between the DMN regions and the motor regions. In addition, the whole brain network modularity was positively correlated with the motor network activity, suggesting that the brain is more segregated as sub-systems when the motor network is intrinsically activated. Together, these results demonstrate the association between the resting-state connectivity variations and the intrinsic activities of specific networks, which can provide insights on the dynamic changes in large-scale brain connectivity and network configurations.


Default mode network Dynamic connectivity fMRI Nonlinear connectivity Resting-state Salience network 

Supplementary material

429_2013_634_MOESM1_ESM.docx (4.3 mb)
Supplementary material 1 (DOCX 4365 kb)

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Biomedical Engineering, New Jersey Institute of TechnologyUniversity HeightNewarkUSA

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