A person's level of consciousness can be assessed by how the brain reacts to stimulation, but this study shows that the brain's unperturbed activity already contains that information. Using personalized whole-brain models fitted to resting-state fMRI data from people in altered states of consciousness (deep sleep, disorders of consciousness), the researchers measured the brain's out-of-equilibrium dynamics—specifically, the asymmetry of effective connections and time irreversibility. They found that states with lower arousal or awareness had less asymmetric connectivity, less irreversibility, and lower complexity in simulated responses compared to controls. The asymmetry in connections drives the nonequilibrium state and, in turn, the differences in complexity.
Signal complexity in intracranial electroencephalography (iEEG) recordings from healthy brain tissue decreases with reduced consciousness, being highest during wakefulness and REM sleep and lowest under propofol anesthesia. Complexity is more variable during N2 and N3 sleep stages, and frontoparietal regions show the highest complexity during conscious states. Epileptic cortex exhibits lower complexity than healthy cortex during wake and REM sleep. A random forest classifier reliably classified sleep stages using complexity markers. These normative data support using iEEG signal complexity as a marker of physiological consciousness, cortical integrity, and sleep-stage detection.