Fast transient networks in spontaneous human brain activity

Author:

Baker Adam P12,Brookes Matthew J3,Rezek Iead A4,Smith Stephen M5,Behrens Timothy67,Probert Smith Penny J4,Woolrich Mark51

Affiliation:

1. Oxford Centre for Human Brain Activity, University of Oxford, Oxford, United Kingdom

2. Centre for Doctoral Training in Healthcare Innovation, Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom

3. Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom

4. Department of Engineering Science, University of Oxford, Oxford, United Kingdom

5. Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom

6. Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neuroscience, Oxford University, Oxford, United Kingdom

7. Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom

Abstract

To provide an effective substrate for cognitive processes, functional brain networks should be able to reorganize and coordinate on a sub-second temporal scale. We used magnetoencephalography recordings of spontaneous activity to characterize whole-brain functional connectivity dynamics at high temporal resolution. Using a novel approach that identifies the points in time at which unique patterns of activity recur, we reveal transient (100–200 ms) brain states with spatial topographies similar to those of well-known resting state networks. By assessing temporal changes in the occurrence of these states, we demonstrate that within-network functional connectivity is underpinned by coordinated neuronal dynamics that fluctuate much more rapidly than has previously been shown. We further evaluate cross-network interactions, and show that anticorrelation between the default mode network and parietal regions of the dorsal attention network is consistent with an inability of the system to transition directly between two transient brain states.

Funder

Research Councils UK Digital Economy programme

Wellcome Trust

NIHR Oxford Biomedical Research Centre

Leverhulme Trust

National Institutes of Health Human Connectome Project

The Wellcome Trust

UK MEG Partnership Award

Engineering and Physical Sciences Research Council

The Wellcome Trust and the Engineering and Physical Sciences Research Council

Research Councils UK

National Institute for Health Research

National Institutes of Health

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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5. BOLD correlates of EEG topography reveal rapid resting-state network dynamics;Britz;NeuroImage,2010

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