Time-resolved resting-state brain networks

Andrew Zalesky, Alex Fornito, Luca Cocchi, Leonardo L Gollo, Michael Breakspear

Research output: Contribution to journalArticleResearchpeer-review

557 Citations (Scopus)

Abstract

Neuronal dynamics display a complex spatiotemporal structure involving the precise, context-dependent coordination of activation patterns across a large number of spatially distributed regions. Functional magnetic resonance imaging (fMRI) has played a central role in demonstrating the nontrivial spatial and topological structure of these interactions, but thus far has been limited in its capacity to study their temporal evolution. Here, using high-resolution resting-state fMRI data obtained from the Human Connectome Project, we mapped time-resolved functional connectivity across the entire brain at a subsecond resolution with the aim of understanding how nonstationary fluctuations in pairwise interactions between regions relate to large-scale topological properties of the human brain. We report evidence for a consistent set of functional connections that show pronounced fluctuations in their strength over time. The most dynamic connections are intermodular, linking elements from topologically separable subsystems, and localize to known hubs of default mode and frontoparietal systems. We found that spatially distributed regions spontaneously increased, for brief intervals, the efficiency with which they can transfer information, producing temporary, globally efficient network states. Our findings suggest that brain dynamics give rise to variations in complex network properties over time, possibly achieving a balance between efficient information-processing and metabolic expenditure
Original languageEnglish
Pages (from-to)10341-10346
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume111
Issue number28
DOIs
Publication statusPublished - 15 Jul 2014

Keywords

  • network efficiency
  • dynamic connectivity
  • time-dependent network

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