• Duan Li, Phillip E Vlisides, Max B Kelz, Michael S Avidan, George A Mashour, and ReCCognition Study Group.
• From the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan (D.L., P.E.V., G.A.M.) the Department of Anesthesiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania (M.B.K.) the Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri (M.S.A.). From the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan From the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan From the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan From the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan From the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan From the Center for Consciousness Science, Department of Anesthesiology, University of Michigan Medical School, Ann Arbor, Michigan From the Department of Anesthesiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania From the Department of Anesthesiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania From the Department of Anesthesiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania From the Department of Anesthesiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania From the Department of Anesthesiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania From the Department of Anesthesiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania From the Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri From the Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri From the Department of Anesthesiology, Washington University School of Medicine, St. Louis, Missouri.
• Anesthesiology. 2019 Jun 1; 130 (6): 870-884.

What We Already Know About This TopicAnesthetic-induced loss of consciousness is accompanied by changes in functional connectivity within and between brain networks.What This Article Tells Us That Is NewDespite a stable surgical level of anesthesia and the absence of noxious stimuli, connectivity patterns are not static but rather fluctuate dynamically and nonrandomly over time. These results suggest that single or static connectivity patterns may not be able to discriminate levels of consciousness.BackgroundRecent studies of anesthetic-induced unconsciousness in healthy volunteers have focused on functional brain connectivity patterns, but the protocols rarely parallel the depth and duration of surgical anesthesia. Furthermore, it is unknown whether there is a single functional connectivity pattern that correlates with general anesthesia for the duration of prolonged anesthetic exposure.MethodsThe authors analyzed electroencephalographic data in 30 healthy participants who underwent induction of anesthesia with propofol followed by 3 h of isoflurane anesthesia at age-adjusted 1.3 minimum alveolar concentration. Functional connectivity was assessed by frequency-resolved weighted phase lag index between frontal and parietal channels and between prefrontal and frontal channels, which were classified into a discrete set of states through k-means cluster analysis. Temporal dynamics were evaluated by the occurrence rate and dwell time distribution for each state as well as the transition probabilities between states.ResultsBurst suppression was present, with mean suppression ratio reducing from 44.8 ± 32.3% to 14.0 ± 20.2% (mean ± SD) during isoflurane anesthesia (P < 0.001). Aside from burst suppression, eight connectivity states were classified by optimizing the reproducibility of clustering solutions, with each characterized by distinct properties. The temporal progression of dominant states revealed a successive shifting trajectory from the state associated with alpha frontal-parietal connectivity to those associated with delta and alpha prefrontal-frontal connectivity during induction, which was reversed during emergence. Cortical connectivity was dynamic during maintenance period, and it was more probable to remain in the same state (82.0 ± 8.3%) than to switch to a different state (P < 0.001). However, transitions to other states were structured, i.e., occurred more frequently than expected by chance.ConclusionsAnesthesia-induced alterations of functional connectivity are dynamic despite the stable and prolonged administration of isoflurane, in the absence of any noxious stimuli. Changes in connectivity over time will likely yield more information as a marker or mechanism of surgical anesthesia than any single pattern.

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