Propofol-induced unconsciousness is linked to decreased connectivity within frontoparietal networks (the default-mode and executive-control networks) and between the thalamus and these networks, with a negative correlation between thalamic and cortical activity emerging during unconsciousness. In contrast, connectivity in low-level sensory cortices (auditory and visual networks) is preserved, including their thalamocortical connections. Loss of consciousness is associated with a breakdown of cross-modal interactions between visual and auditory networks. These findings suggest that unconsciousness results from disrupted communication between sensory and higher-order frontoparietal cortices, preventing conscious perception.
Variability in how people perceive the same sensory stimulus from one moment to the next may stem from ongoing fluctuations in baseline brain activity. This review examines evidence that activity levels in sensory brain areas before a stimulus predict whether that stimulus will be consciously perceived. The findings are discussed in the context of recent discoveries about the structure of spontaneous BOLD signal fluctuations in the awake human brain, and possible sources of these baseline fluctuations are considered.
A machine-learning classifier trained on fluorodeoxyglucose PET brain scans from 37 healthy controls and 13 patients in a vegetative state achieved 100% accuracy in distinguishing between conscious awareness and the vegetative state during cross-validation. When tested on 8 patients with locked-in syndrome, all scans were classified as "conscious" with a mean probability of .95. The authors conclude that relevance vector machine classification of cerebral metabolic images could become a useful tool for automated PET-based diagnosis of altered states of consciousness in coma survivors.