Cover Image

Abstract

COVER ILLUSTRATION The self-organized criticality hallmarked by avalanche events whose sizes follow a power-law distribution is a statistical physics notion exemplified by the archetypical sandpile model. The critical brain hypothesis proposes that efficient neural computation can be achieved through critical brain dynamics. This idea was explored in the study using large-scale brain dynamics recorded by resting-state fMRI data. It was shown that subjects could be divided into three groups: those with more ordered or disordered brain dynamics, and those with critical dynamics between order and disorder, characterized by a power-law distribution of neural avalanche activities. Furthermore, in subjects with critical dynamics, their complexity of functional connectivity, as well as their coupling between structural and functional networks, is maximized. Finally, it was discovered that subjects with dynamics that are closer to criticality have higher fluid intelligence and working memory scores. These findings reveal the important role of large-scale critical dynamics in brains in cognitive performance and demonstrate the possibility to map cortical states on a spectrum of neural dynamics, ranging from subcriticality to supercriticality.