Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 114, Issue 48, Pages 12827-12832Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1705120114
Keywords
resting-state networks; metastates; dynamic functional connectivity; hidden Markov model
Categories
Funding
- Wellcome Trust Strategic Award [098369/Z/12/Z]
- Wellcome Trust [203139/Z/16/Z, 106183/Z/14/Z]
- National Institute for Health Research (UK)
- Oxford Health Biomedical Research Centre
- Medical Research Council UK Magnetoencephalography (MEG) Partnership Grant [MR/K005464/1]
- MRC [MR/K005464/1] Funding Source: UKRI
- Wellcome Trust [106183/Z/14/Z, 098369/Z/12/Z] Funding Source: Wellcome Trust
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The brain recruits neuronal populations in a temporally coordinated manner in task and at rest. However, the extent to which large-scale networks exhibit their own organized temporal dynamics is unclear. We use an approach designed to find repeating network patterns in whole-brain resting fMRI data, where networks are defined as graphs of interacting brain areas. We find that the transitions between networks are nonrandom, with certain networks more likely to occur after others. Further, this nonrandom sequencing is itself hierarchically organized, revealing two distinct sets of networks, or metastates, that the brain has a tendency to cycle within. One metastate is associated with sensory and motor regions, and the other involves areas related to higher order cognition. Moreover, we find that the proportion of time that a subject spends in each brain network and metastate is a consistent subject-specific measure, is heritable, and shows a significant relationship with cognitive traits.
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