Fig. 5. Model-based framework revealed significant perturbative differences for different brain states.
a We show the evolution of the error of the whole-brain model FC fitting to the empirical fMRI data as a function of the global coupling strength, G. The error of the FC fitting was given by the square root of the difference between the simulated and empirical FC matrix. The optimal working point of the model was defined as the minimum value of the FC fitting, i.e., where the model shows maximal similarity to the empirical fMRI data. b We show the results of the susceptibility measure, which estimates how these models react to external periodical force perturbations. In all datasets, the resting state was the most susceptible to be perturbed. c We show the information encoding capability of the whole-brain models, which captures how different external stimulations are encoded in the dynamics. Similar to the susceptibility measure, the resting state was more susceptible to react to the perturbations. Susceptibility and information capability measures differentiated each brain state and between RMCS and RUWS groups. These results show that each brain state encodes the whole-brain dynamics with a particular complexity. P-values were assessed using the Wilcoxon rank-sum test and corrected for multiple comparisons; ***P < 0.001.