2.6 Whole-brain computational modeling of resting-state network
To be able to assess the resting-state functional architecture of the brain beyond the conventional large sample statistical approach, we used our previously developed whole-brain model that is based on weakly coupled oscillators [Here, every individual’s brain was parceled into 68 regions based on Desikan-Killiany parcellation, and each region was modeled as a nonlinear oscillator. To achieve the macroscopic computational model of the brain, local oscillators are coupled through a structural connectome which was obtained by applying streamline tractography to the large sample diffusion-weighted MRI data from HCP 500 release [When coupled together, the collective behavior of interacting oscillators reproduces key features of brain dynamics, including functional connectivity (FC) patterns. The dynamics of each oscillator is defined by coupled differential equations as below:
Where, z and ω are each oscillator’s state variables and describe the regional amplitude and angular frequency. The real part of the variable z (i.e., Rel{z}) acts as an indirect measure of brain activity acquired by the MR scanner, whereas the imaginary part (i.e., Imag{z}) can be interpreted as the hidden state of the system that is unobservable. In the 