A transition in brain state during propofol-induced unconsciousness
Eran A Mukamel1, Elvira Pirondini, Behtash Babadi
1Swartz Program for Theoretical Neuroscience, Harvard University, Cambridge, Massachusetts 02138, Center for Theoretical Biological Physics, University of California, San Diego, La Jolla, California 92093 and Computational Neurobiology Laboratory, Salk Institute for Biological Studies, San Diego, California 92037, Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114, Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts 02114, Department of Brain and Cognitive Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, Harvard Medical School, Boston, Massachusetts 02115, Division of Health Science and Technology, Harvard-Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, and Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139.
Abstract:
Rhythmic oscillations shape cortical dynamics during active behavior, sleep, and general anesthesia. Cross-frequency phase-amplitude coupling is a prominent feature of cortical oscillations, but its role in organizing conscious and unconscious brain states is poorly understood. Using high-density EEG and intracranial electrocorticography during gradual induction of propofol general anesthesia in humans, we discovered a rapid drug-induced transition between distinct states with opposite phase-amplitude coupling and different cortical source distributions. One state occurs during unconsciousness and may be similar to sleep slow oscillations. A second state occurs at the loss or recovery of consciousness and resembles an enhanced slow cortical potential. These results provide objective electrophysiological landmarks of distinct unconscious brain states, and could be used to help improve EEG-based monitoring for general anesthesia.
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