Time-resolved resting-state brain networks

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 spa...

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Bibliographic Details
Published in:Proceedings of the National Academy of Sciences - PNAS 2014-07, Vol.111 (28), p.10341-10346
Main Authors: Zalesky, Andrew, Fornito, Alex, Cocchi, Luca, Gollo, Leonardo L., Breakspear, Michael
Format: Article
Language:English
Subjects:
Adult
Biological Sciences
Brain
Brain - diagnostic imaging
Brain - physiology
Connected regions
Connectivity
Correlations
Datasets
Dynamic efficiency
Humans
Information processing
Magnetic Resonance Imaging
Male
Mental Processes - physiology
Nerve Net - diagnostic imaging
Nerve Net - physiology
Neuroscience
NMR
Nuclear magnetic resonance
Null set
Radiography
Time series
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Summary: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 fronto-parietal 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.
ISSN:0027-8424
1091-6490
DOI:10.1073/pnas.1400181111