The critical brain hypothesis suggests that efficient neural computation can be achieved through critical brain dynamics. However, the relationship between human cognitive performance and scale-free brain dynamics remains unclear. In this study, we investigated the whole-brain avalanche activity and its individual variability in the human resting-state functional magnetic resonance imaging (fMRI) data. We showed that though the group-level analysis was inaccurate because of individual variability, the subject wise scale-free avalanche activity was significantly associated with maximal synchronization entropy of their brain activity. Meanwhile, the complexity of functional connectivity, as well as structure-function coupling, is maximized in subjects with maximal synchronization entropy. We also observed order-disorder phase transitions in resting-state brain dynamics and found that there were longer times spent in the subcritical regime. These results imply that large-scale brain dynamics favor the slightly subcritical regime of phase transition. Finally, we showed evidence that the neural dynamics of human participants with higher fluid intelligence and working memory scores are closer to criticality. We identified brain regions whose critical dynamics showed significant positive correlations with fluid intelligence performance and found that these regions were located in the prefrontal cortex and inferior parietal cortex, which were believed to be important nodes of brain networks underlying human intelligence. Our results reveal the possible role that avalanche criticality plays in cognitive performance and provide a simple method to identify the critical point and map cortical states on a spectrum of neural dynamics, ranging from subcriticality to supercriticality.
Keywords: avalanche criticality; fluid intelligence; large-scale brain network; phase transition; resting-state fMRI; working memory.
© 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.