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Broadband Criticality of Human Brain Network Synchronization
Open accessAbstract
Self-organized criticality is an attractive model for human brain dynamics, but there has been little direct evidence for its existence in large-scale systems measured by neuroimaging. In general, critical systems are associated with fractal or power law scaling, long-range correlations in space and time, and rapid reconfiguration in response to external inputs. Here, we consider two measures of phase synchronization: the phase-lock interval, or duration of coupling between a pair of (neurophysiological) processes, and the lability of global synchronization of a (brain functional) network. Using computational simulations of two mechanistically distinct systems displaying complex dynamics, the Ising model and the Kuramoto model, we show that both synchronization metrics have power law probability distributions specifically when these systems are in a critical state. We then demonstrate power law scaling of both pairwise and global synchronization metrics in functional MRI and magnetoencephalographic data recorded from normal volunteers under resting conditions. These results strongly suggest that human brain functional systems exist in an endogenous state of dynamical criticality, characterized by a greater than random probability of both prolonged periods of phase-locking and occurrence of large rapid changes in the state of global synchronization, analogous to the neuronal "avalanches" previously described in cellular systems. Moreover, evidence for critical dynamics was identified consistently in neurophysiological systems operating at frequency intervals ranging from 0.05-0.11 to 62.5-125 Hz, confirming that criticality is a property of human brain functional network organization at all frequency intervals in the brain's physiological bandwidth.
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“Several lines of evidence point to fractal-like (1/f) self-similarity over different spatio-temporal scales in brain dynamics and structure [76,77].”
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“there does appear to be evidence for some kind of scale-invariance in neurophysiological processes (Section 3.2 [76,77]).”
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Metadata
- Authors
- Kitzbichler, M. G., Smith, M. L., Christensen, S. R., & Bullmore, E.
- Affiliations
- University of Cambridge (GB)
- MRC Cognition and Brain Sciences Unit (GB)
- GlaxoSmithKline (United Kingdom) (GB)
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2009-03-20
- Volume
- 5
- Issue
- 3
- Pages
- e1000314
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC2647739
- OpenAlex
- W2115990221
- Cited by
- 527
- References
- 52
- Citations by year
- 2026: 10 · 2025: 16 · 2024: 14 · 2023: 28 · 2022: 28 · 2021: 31 · 2020: 25 · 2019: 38 · 2018: 37 · 2017: 37 · 2016: 24 · 2015: 24 · 2014: 39 · 2013: 44 · 2012: 54
- FWCI
- 21.21
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- BIROn (Birkbeck, University of London) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Apollo (cc-by)
- Funders
- GlaxoSmithKline
- Wellcome Trust
- Medical Research Council
- National Institute of Mental Health
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Physical Sciences › Physics and Astronomy › Condensed Matter Physics › Theoretical and Computational Physics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- self-organized criticality, functional brain networks, phase synchronization, power-law scaling, neuronal avalanches, Ising model, Kuramoto model, resting-state brain dynamics, functional MRI, magnetoencephalography
- MeSH terms
- Action Potentials, Animals, Biological Clocks, Brain, Computer Simulation, Cortical Synchronization, Humans, Models, Neurological, Nerve Net, Synaptic Transmission, Neurons
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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