Variability of Brain Signals Processed Locally Transforms into Higher Connectivity with Brain Development

A number of studies have characterized the changes in variability of brain signals with brain maturation from the perspective of considering the human brain as a complex system. Specifically, it has been shown that complexity of brain signals increases in development. On one hand, such an increase in complexity can be attributed to more specialized and differentiated brain regions able to express a higher repertoire of mental microstates. On the other hand, it can be explained by increased integration between widely distributed neuronal populations and establishment of new connections. The goal of this study was to see which of these two mechanisms is dominant, accounting for the previously observed increase in signal complexity. Using information-theoretic tools based on scalp-recorded EEG measurements, we examined the trade-off between local and distributed variability of brain signals in infants and children separated into age groups of 1-2, 2-8, 9 -24, and 24 -66 months old. We found that developmental changes were characterized by a decrease in the amount of information processed locally, with a peak in alpha frequency range. This effect was accompanied by an increase in the variability of brain signals processed as a distributed network. Complementary analysis of phase locking revealed an age-related pattern of increased synchronization in the lower part of the spectrum, up to the alpha rhythms. At the same time, we observed the desynchronization effects associated with brain development in the higher beta to lower gamma range.