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      Distinguishing Anesthetized from Awake State in Patients: A New Approach Using One Second Segments of Raw EEG

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          Abstract

          Objective: The objective of this study was to test whether properties of 1-s segments of spontaneous scalp EEG activity can be used to automatically distinguish the awake state from the anesthetized state in patients undergoing general propofol anesthesia.

          Methods: Twenty five channel EEG was recorded from 10 patients undergoing general intravenous propofol anesthesia with remifentanil during anterior cervical discectomy and fusion. From this, we extracted properties of the EEG by applying the Directed Transfer Function (DTF) directly to every 1-s segment of the raw EEG signal. The extracted properties were used to develop a data-driven classification algorithm to categorize patients as “anesthetized” or “awake” for every 1-s segment of raw EEG.

          Results: The properties of the EEG signal were significantly different in the awake and anesthetized states for at least 8 of the 25 channels ( p < 0.05, Bonferroni corrected Wilcoxon rank-sum tests). Using these differences, our algorithms achieved classification accuracies of 95.9%.

          Conclusion: Properties of the DTF calculated from 1-s segments of raw EEG can be used to reliably classify whether the patients undergoing general anesthesia with propofol and remifentanil were awake or anesthetized.

          Significance: This method may be useful for developing automatic real-time monitors of anesthesia.

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          Most cited references52

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          Neural correlates of consciousness: progress and problems.

          There have been a number of advances in the search for the neural correlates of consciousness--the minimum neural mechanisms sufficient for any one specific conscious percept. In this Review, we describe recent findings showing that the anatomical neural correlates of consciousness are primarily localized to a posterior cortical hot zone that includes sensory areas, rather than to a fronto-parietal network involved in task monitoring and reporting. We also discuss some candidate neurophysiological markers of consciousness that have proved illusory, and measures of differentiation and integration of neural activity that offer more promising quantitative indices of consciousness.
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            Consciousness and anesthesia.

            When we are anesthetized, we expect consciousness to vanish. But does it always? Although anesthesia undoubtedly induces unresponsiveness and amnesia, the extent to which it causes unconsciousness is harder to establish. For instance, certain anesthetics act on areas of the brain's cortex near the midline and abolish behavioral responsiveness, but not necessarily consciousness. Unconsciousness is likely to ensue when a complex of brain regions in the posterior parietal area is inactivated. Consciousness vanishes when anesthetics produce functional disconnection in this posterior complex, interrupting cortical communication and causing a loss of integration; or when they lead to bistable, stereotypic responses, causing a loss of information capacity. Thus, anesthetics seem to cause unconsciousness when they block the brain's ability to integrate information.
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              Electroencephalogram signatures of loss and recovery of consciousness from propofol.

              Unconsciousness is a fundamental component of general anesthesia (GA), but anesthesiologists have no reliable ways to be certain that a patient is unconscious. To develop EEG signatures that track loss and recovery of consciousness under GA, we recorded high-density EEGs in humans during gradual induction of and emergence from unconsciousness with propofol. The subjects executed an auditory task at 4-s intervals consisting of interleaved verbal and click stimuli to identify loss and recovery of consciousness. During induction, subjects lost responsiveness to the less salient clicks before losing responsiveness to the more salient verbal stimuli; during emergence they recovered responsiveness to the verbal stimuli before recovering responsiveness to the clicks. The median frequency and bandwidth of the frontal EEG power tracked the probability of response to the verbal stimuli during the transitions in consciousness. Loss of consciousness was marked simultaneously by an increase in low-frequency EEG power (<1 Hz), the loss of spatially coherent occipital alpha oscillations (8-12 Hz), and the appearance of spatially coherent frontal alpha oscillations. These dynamics reversed with recovery of consciousness. The low-frequency phase modulated alpha amplitude in two distinct patterns. During profound unconsciousness, alpha amplitudes were maximal at low-frequency peaks, whereas during the transition into and out of unconsciousness, alpha amplitudes were maximal at low-frequency nadirs. This latter phase-amplitude relationship predicted recovery of consciousness. Our results provide insights into the mechanisms of propofol-induced unconsciousness, establish EEG signatures of this brain state that track transitions in consciousness precisely, and suggest strategies for monitoring the brain activity of patients receiving GA.
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                Author and article information

                Contributors
                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                20 February 2018
                2018
                : 12
                : 40
                Affiliations
                [1] 1Department of Molecular Medicine, Brain Signaling, Institute of Basic Medical Science, University of Oslo , Oslo, Norway
                [2] 2Department of Anesthesiology, Rikshospitalet, Oslo University Hospital , Oslo, Norway
                [3] 3Department of Neurosurgery, Rikshospitalet, Oslo University Hospital , Oslo, Norway
                Author notes

                Edited by: Juliana Yordanova, Institute of Neurobiology (BAS), Bulgaria

                Reviewed by: Srivas Chennu, University of Kent, United Kingdom; Logan James Voss, Waikato District Health Board, New Zealand

                *Correspondence: Bjørn E. Juel b.e.juel@ 123456medisin.uio.no
                Pål G. Larsson pall@ 123456ous-hf.no
                Article
                10.3389/fnhum.2018.00040
                5826260
                564c9005-b6d4-4aad-a84e-f6c153248229
                Copyright © 2018 Juel, Romundstad, Kolstad, Storm and Larsson.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 02 November 2017
                : 24 January 2018
                Page count
                Figures: 5, Tables: 1, Equations: 2, References: 56, Pages: 14, Words: 9612
                Funding
                Funded by: Norges Forskningsråd 10.13039/501100005416
                Award ID: 214079/F20
                Award ID: 262950/F20
                Funded by: Horizon 2020 10.13039/501100007601
                Award ID: 720270-HBP-SGA1-H2020
                Categories
                Neuroscience
                Original Research

                Neurosciences
                monitoring general anesthesia,directed transfer function (dtf),electroencephalography (eeg),consciousness,general anesthesia

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