Critical Dynamics in the Association Cortex predict Higher Intelligence in Typically Developing Children

Neuronal network models have indicated that so-called critical dynamics facilitate efficient information processing, while criticality disruptions were linked to neuropathology through excitation/inhibition (E/I) imbalances. However, there is limited empirical evidence for a relationship between critical brain dynamics and cognition in healthy children and adolescents. Here, we investigate how these dynamics relate to intelligence in a developing cohort. We recorded eyes-open resting EEG in 128 children (6–19 years, 72 female) and quantified near-critical brain dynamics in the alpha band using functional excitation/inhibition ratio ( f E/I), and in non-oscillatory activity using the 1/f aperiodic exponent of the power spectrum. We devised models relating intelligence to f E/I and 1/f exponent across seven Yeo7 functional brain networks ranked from lower-order sensorimotor to higher-order association networks. We observed significant correlations between f E/I and 1/f exponent and IQ in association cortices, in contrast to sensorimotor cortices. Children in the high-IQ group had f E/I ratios closer to the theoretical critical value of 1 in association cortices compared to the low-IQ group. The association–sensorimotor axis rank moderated the associations between 1/f exponent and IQ, these associations decreasing on a gradient across the hierarchy of the Yeo7 networks. Age and rank moderated the f E/I–IQ association, with the association–sensorimotor effect size gradient most visible in adolescents. Together, the results suggest that individual variation in criticality-sensitive biomarkers in association networks may be linked to IQ differences in an age-dependent manner, consistent with the hypothesis that developmental modulation of critical dynamics across the cortical hierarchy may support more efficient cognitive processing. Significance statement The healthy brain is posited to operate near a critical transition between a sub-critical state, characterized by excessive neural inhibition, and a super-critical state, marked by excessive neural excitability. Preclinical and computational modelling studies have shown that this critical state is conducive to optimal information processing. The present study provides insight, using electroencephalographic (EEG) brain recordings, into how brain criticality is linked to intelligence during development. The study offers important empirical evidence in agreement with computational studies linking brain criticality to optimal functioning, and may help to better understand the role of criticality in brain disorders.