Abstract

The brain interdependencies can be studied from either a structural or functional perspective. The former typically focuses on structural connectivity (SC), while the latter considers statistical interactions (usually functional connectivity, FC). Notably, while SC is inherently pairwise because it describes white-matter fibers projecting from one region to another, FC is not limited to pairwise interdependencies. Despite this, FC analyses predominantly concentrate on pairwise statistics, usually neglecting the possibility of higher-order interactions. Moreover, the precise relationship between high-order and SC is largely unknown, partly due to the absence of mechanistic models that can efficiently map brain connectomics to functional connectivity. To investigate these interlinked issues, we have built whole-brain computational models using anatomical and functional MRI data in two applications: healthy aging and transcranial ultrasound stimulation (TUS). We show that non-linear variations in the structural connectome can largely explain the differences in high-order functional interactions between age groups. Moreover, we demonstrated the extent of perturbations in dynamical models to describe the high-order effects of TUS in two different brain targets.