Workflow diagrams for model simulation and parameter search.
(A) A schematic of simulating resting-state cortical activity using a system of coupled phase oscillators, known as the Kuramoto model. Each oscillator was assigned to a cortical node and was coupled based on connection strengths and fiber lengths of brain structural connectivity. (B) A schematic of converting modeled cortical activity to modeled BOLD signal. (C) Workflow diagram of model parameter search. 1. For all 28 × 16 parameter sets, long-timescale functional connectivity and the correlation distribution of time-resolved functional connectivity over time (framed by rectangles in the panel 1) were computed from the modeled BOLD signal and were compared to their empirical counterparts (10 simulation samples per each parameter set). 2. For the parameter sets with better matches between the modeled and empirical data in the first stage, community detection was performed on time-resolved functional connectivity to obtain its modules (100 simulation samples per each parameter set). Then, time series of mean participation coefficient Pt and modularity Qt were computed and their SDs (framed by rectangles in the panel 2) were compared between the modeled and empirical data. 3. For the parameter set yielding the best match between the modeled and empirical data in the second stage, changes in functional connectivity across networks states (segregated and integrated states or high, middle, and low modularity periods) were compared between the modeled and empirical data.