Brain Topography

, Volume 27, Issue 3, pp 338–352 | Cite as

Low-Dimensional Dynamics of Resting-State Cortical Activity

  • Saeid Mehrkanoon
  • Michael Breakspear
  • Tjeerd W. Boonstra
Original Paper

Abstract

Endogenous brain activity supports spontaneous human thought and shapes perception and behavior. Connectivity-based analyses of endogenous, or resting-state, functional magnetic resonance imaging (fMRI) data have revealed the existence of a small number of robust networks which have a rich spatial structure. Yet the temporal information within fMRI data is limited, motivating the complementary analysis of electrophysiological recordings such as electroencephalography (EEG). Here we provide a novel method based on multivariate time–frequency interdependence to reconstruct the principal resting-state network dynamics in human EEG data. The stability of network expression across subjects is assessed using resampling techniques. We report the presence of seven robust networks, with distinct topographic organizations and high frequency (∼5–45 Hz) fingerprints, nested within slow temporal sequences that build up and decay over several orders of magnitude. Interestingly, all seven networks are expressed concurrently during these slow dynamics, although there is a temporal asymmetry in the pattern of their formation and dissolution. These analyses uncover the complex temporal character of endogenous cortical fluctuations and, in particular, offer an opportunity to reconstruct the low dimensional linear subspace in which they unfold.

Keywords

Resting-state network Functional connectivity Neuronal synchronization Electroencephalography 

Notes

Acknowledgments

This research was supported by the ARC Thinking Systems grant TS0669860; the National Health and Medical Research Council; BrainNRG collaborative award JSMF22002082, and the Netherlands Organization for Scientific Research (NWO #45110-030). The authors wish to thank Angela Langdon and James Roberts for their comments on a draft manuscript.

Supplementary material

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Supplementary material 1 (JPEG 4 MB)
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Supplementary material 2 (PNG 867 kb)

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Saeid Mehrkanoon
    • 1
  • Michael Breakspear
    • 1
    • 2
  • Tjeerd W. Boonstra
    • 1
    • 3
  1. 1.Black Dog InstituteThe University of New South WalesSydneyAustralia
  2. 2.Queensland Institute of Medical ResearchBrisbaneAustralia
  3. 3.Research Institute MOVEVU University Amsterdam AmsterdamThe Netherlands

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