Nonequilibrium dynamics elicited as the origin of perturbative complexity

Assessing the level of consciousness someone is in, is not a trivial question and physicians have to rely on behavioural evaluations instead of quantifiable metrics. Many studies have empirically investigated measures related to the complexity elicited after the brain is stimulated to quantify and assess the level of consciousness across different states. Here we hypothesized that the level of non-equilibrium dynamics of the unperturbed brain already contains the information needed to know how the system will react to an external stimulus. We created personalized whole-brain models fitted to resting state fMRI data recorded in participants in different states of reduced consciousness (such as deep sleep and disorders of consciousness) to infer the effective connections underlying their brain dynamics. We then measured the out-of-equilibrium nature of the unperturbed brain by evaluating the level of asymmetry of the inferred connectivity, the time irreversibility in each model and compared this with the elicited complexity generated after in silico perturbations. Crucially, we found that states of reduced consciousness had a lower level of asymmetry in their effective connectivities compared to control subjects, as well as a lower level of irreversibility in their simulated dynamics, and a lower complexity. We demonstrated that the asymmetry in the underlying connections drives the nonequilibrium state of the system and in turn the differences in complexity as a response to the external stimuli.