Cited by 527Neural dynamics and brain functionTheoretical and Computational PhysicsFunctional Brain Connectivity Studies

Broadband criticality of human brain network synchronization

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Kitzbichler, Manfred G., Smith, Marie L., Christensen, Søren R., Bullmore, Ed·2009·PLoS Computational Biology

Abstract

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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Crossref · 10.1371/journal.pcbi.1000314

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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.

    “Several lines of evidence point to fractal-like (1/f) self-similarity over different spatio-temporal scales in brain dynamics and structure [76,77].”

    From Consciousness in the universe (2014) · cites this paper as [77]

    The Introduction (page not available) reports fractal or power-law scaling in brain activity across a wide range of spatial and time scales, and self-similarity in the topology of functional networks across frequency scales. The Discussion (page not available) reports power-law scaling of synchronization in fMRI and MEG data. These passages support the claim about brain dynamics, but do not establish 1/f scaling specifically or self-similarity of anatomical brain structure. (LLM, conf=0.84)

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  • There is evidence for scale-invariance in neurophysiological processes.

    “there does appear to be evidence for some kind of scale-invariance in neurophysiological processes (Section 3.2 [76,77]).”

    From Consciousness in the universe (2014) · cites this paper as [77]

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Research works printed but not linked: 1

  1. [33]Hindmarsh A 1983 ODEPACK, a systematized collection of ODE solvers. Stepleman R Scientific Computing: Applications of Mathematics and Computing to the Physical Sciences. Amsterdam, The Netherlands; New York North-Holland 55 64 Volume 1 of IMACS Transactions on Scientific Computing

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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
Published
2009-03-20
Volume
5
Issue
3
Pages
e1000314
ISSN
  • 1553-734X (ISSN-L)
  • 1553-7358
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
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

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