Criticality in large-scale brain fmri dynamics unveiled by a novel point process analysis

Enzo Tagliazucchi, Pablo Balenzuela, Daniel Fraiman, Dante R. Chialvo

Research output: Contribution to journalArticlepeer-review

521 Scopus citations

Abstract

Functional magnetic resonance imaging (fMRI) techniques have contributed significantly to our understanding of brain function. Current methods are based on the analysis of gradual and continuous changes in the brain blood oxygenated level dependent (BOLD) signal. Departing from that approach, recent work has shown that equivalent results can be obtained by inspecting only the relatively large amplitude BOLD signal peaks, suggesting that relevant information can be condensed in discrete events. This idea is further explored here to demonstrate how brain dynamics at resting state can be captured just by the timing and location of such events, i.e., in terms of a spatiotemporal point process. The method allows, for the first time, to define a theoretical framework in terms of an order and control parameter derived from fMRI data, where the dynamical regime can be interpreted as one corresponding to a system close to the critical point of a second order phase transition. The analysis demonstrates that the resting brain spends most of the time near the critical point of such transition and exhibits avalanches of activity ruled by the same dynamical and statistical properties described previously for neuronal events at smaller scales. Given the demonstrated functional relevance of the resting state brain dynamics, its representation as a discrete process might facilitate large-scale analysis of brain function both in health and disease.

Original languageEnglish
Article numberArticle 15
JournalFrontiers in Physiology
Volume3 FEB
DOIs
StatePublished - 2012
Externally publishedYes

Keywords

  • Brain dynamics
  • Criticality
  • Fmri
  • Point processes

Fingerprint

Dive into the research topics of 'Criticality in large-scale brain fmri dynamics unveiled by a novel point process analysis'. Together they form a unique fingerprint.

Cite this