Understanding the neural correlates of consciousness has important ramifications for the theoretical understanding of consciousness and for clinical anaesthesia. A major limitation of prior studies is the use of responsiveness as an index of consciousness. We identified a collection of measures derived from unresponsive subjects and more specifically their association with consciousness (any...
While consciousness never fades during wakefulness, there is a paradoxical coexistence of consciousness during dreaming states. It’s also possible for sensory awareness to be either present or absent when awakened from seemingly-identical states of sedation and anaesthesia. Traditionally, these states have been characterised in terms of their electroencephalographic neural correlates, however,...
Sensory disconnection is a key feature of sleep and anaesthesia. We have proposed that predictive coding offers a framework for understanding the mechanisms of disconnection. Low doses of ketamine that do not induce disconnection should thus diminish predictive coding, but not abolish it. Ketamine was administered to 14 participants up to a blood concentration of 0.3 μg ml-1 Participants were...
The neural mechanisms through which individuals lose sensory awareness of their environment during anesthesia remains poorly understood despite being of vital importance to the field. Prior research has not distinguished between sensory awareness of the environment (connectedness) and consciousness itself. In the current study, we investigated the neural correlates of sensory awareness by...
Background: How conscious experience becomes disconnected from the environment, or disappears, across arousal states is unknown. We sought to identify the neural correlates of sensory disconnection and unconsciousness using a novel serial awakening paradigm. Methods: Volunteers were recruited for sedation with dexmedetomidine i.v., propofol i.v., or natural sleep with high-density EEG...
Learned associations between stimuli allow us to model the world and make predictions, crucial for efficient behavior (e.g., hearing a siren, we expect to see an ambulance and quickly make way). While there are theoretical and computational frameworks for prediction, the circuit and receptor-level mechanisms are unclear. Using high-density EEG, Bayesian modeling, and machine learning, we show...