Development of modularity in the neural activity of children's brains

TL;DR

This study investigates how brain modularity develops from childhood to adulthood using fMRI data, suggesting that increased modularity enhances cognitive performance and could serve as a biomarker for neurological health.

Contribution

It provides empirical evidence of increasing brain modularity with age and introduces a theoretical model explaining its role in cognitive performance development.

Findings

Modularity increases during childhood and peaks in young adulthood.

Head motion does not affect the observed age-modularity relationship.

A model predicts modularity evolution based on cognitive performance selection.

Abstract

We study how modularity of the human brain changes as children develop into adults. Theory suggests that modularity can enhance the response function of a networked system subject to changing external stimuli. Thus, greater cognitive performance might be achieved for more modular neural activity, and modularity might likely increase as children develop. The value of modularity calculated from fMRI data is observed to increase during childhood development and peak in young adulthood. Head motion is deconvolved from the fMRI data, and it is shown that the dependence of modularity on age is independent of the magnitude of head motion. A model is presented to illustrate how modularity can provide greater cognitive performance at short times, i.e.\ task switching. A fitness function is extracted from the model. Quasispecies theory is used to predict how the average modularity evolves with age, illustrating the increase of modularity during development from children to adults that arises from selection for rapid cognitive function in young adults. Experiments exploring the effect of modularity on cognitive performance are suggested. Modularity may be a potential biomarker for injury, rehabilitation, or disease.