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      Thalamocortical control of propofol phase-amplitude coupling

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          Abstract

          The anesthetic propofol elicits many different spectral properties on the EEG, including alpha oscillations (8–12 Hz), Slow Wave Oscillations (SWO, 0.1–1.5 Hz), and dose-dependent phase-amplitude coupling (PAC) between alpha and SWO. Propofol is known to increase GABA A inhibition and decrease H-current strength, but how it generates these rhythms and their interactions is still unknown. To investigate both generation of the alpha rhythm and its PAC to SWO, we simulate a Hodgkin-Huxley network model of a hyperpolarized thalamus and corticothalamic inputs. We find, for the first time, that the model thalamic network is capable of independently generating the sustained alpha seen in propofol, which may then be relayed to cortex and expressed on the EEG. This dose-dependent sustained alpha critically relies on propofol GABA A potentiation to alter the intrinsic spindling mechanisms of the thalamus. Furthermore, the H-current conductance and background excitation of these thalamic cells must be within specific ranges to exhibit any intrinsic oscillations, including sustained alpha. We also find that, under corticothalamic SWO UP and DOWN states, thalamocortical output can exhibit maximum alpha power at either the peak or trough of this SWO; this implies the thalamus may be the source of propofol-induced PAC. Hyperpolarization level is the main determinant of whether the thalamus exhibits trough-max PAC, which is associated with lower propofol dose, or peak-max PAC, associated with higher dose. These findings suggest: the thalamus generates a novel rhythm under GABA A potentiation such as under propofol, its hyperpolarization may determine whether a patient experiences trough-max or peak-max PAC, and the thalamus is a critical component of propofol-induced cortical spectral phenomena. Changes to the thalamus may be a critical part of how propofol accomplishes its effects, including unconsciousness.

          Author summary

          Anesthetics make patients lose consciousness, but how they affect brain dynamics is still unknown. Changes in EEG brainwaves are some of the few noninvasive signals we can use to learn about this. By analyzing such data, we can develop more targeted anesthetics, expand our knowledge of sleep circuits, and better understand how diseases impact these systems. The anesthetic propofol is known, among other effects, to increase synaptic inhibition, but it is unclear how these changes induce EEG alpha (8–12 Hz) oscillations and their interaction with slow wave (0.1–1.5 Hz) oscillations; these signals have been correlated with the state of propofol-infused consciousness. We simulated a network of thalamic cells to understand the mechanisms generating these signals. Propofol-potentiated inhibition produced a novel, sustained alpha rhythm in our network. Changes to the tonic level of depolarization enabled the alpha oscillations to occur at different phases in the slow wave oscillation, as seen clinically with increasing propofol dose. The thalamus may be critical to propofol-induced alpha oscillations and their coupling to slow wave oscillations. By understanding the mechanisms generating alpha, we may be able to design experiments to dissociate alpha from slow waves and determine their independent effects on levels of consciousness.

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          Most cited references60

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          General anesthesia, sleep, and coma.

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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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              Molecular and cellular mechanisms of general anaesthesia.

              General anaesthetics are much more selective than is usually appreciated and may act by binding to only a small number of targets in the central nervous system. At surgical concentrations their principal effects are on ligand-gated (rather than voltage-gated) ion channels, with potentiation of postsynaptic inhibitory channel activity best fitting the pharmacological profile observed in general anaesthesia. Although the role of second messengers remains uncertain, it is now clear that anaesthetics act directly on proteins rather than on lipids.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: InvestigationRole: SoftwareRole: Visualization
                Role: InvestigationRole: SoftwareRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                11 December 2017
                December 2017
                : 13
                : 12
                : e1005879
                Affiliations
                [1 ] Graduate Program for Neuroscience, Boston University, Boston, Massachusetts, United States of America
                [2 ] Department of Mathematics & Statistics, Boston University, Boston, Massachusetts, United States of America
                [3 ] Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, United States of America
                [4 ] Department of Neuroscience, Brown University, Providence, Rhode Island, United States of America
                [5 ] Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
                [6 ] Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
                Université Paris Descartes, Centre National de la Recherche Scientifique, FRANCE
                Author notes

                I have read the journal's policy and the authors of this manuscript have the following competing interests: ENB and PLP are inventors on patents pending on anesthetic brain monitoring that have been licensed by Massachusetts General Hospital to Masimo Corporation. ENB and PLP have received speaker’s honoraria from and ENB has consulted for Masimo Corporation.

                Author information
                http://orcid.org/0000-0002-1680-6936
                http://orcid.org/0000-0001-7264-5658
                Article
                PCOMPBIOL-D-17-01506
                10.1371/journal.pcbi.1005879
                5739502
                29227992
                48c5b3ee-effb-42b5-a2ef-ef926b1382e1
                © 2017 Soplata et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 6 September 2017
                : 2 October 2017
                Page count
                Figures: 9, Tables: 0, Pages: 24
                Funding
                Funded by: National Institutes of Health (US)
                Award ID: P01GM118269
                Award Recipient :
                Funded by: Army Research Office (US)
                Award ID: ARO W911NF-12-R-0012-02
                Award Recipient :
                Funded by: National Science Foundation (US)
                Award ID: DMS-1042134-5
                Award Recipient :
                Funded by: National Institutes of Health (US)
                Award ID: R01-GM104948
                Award Recipient :
                Funded by: National Institutes of Health (US)
                Award ID: DP2-OD006454
                Award Recipient :
                Funded by: National Institutes of Health (US)
                Award ID: CRCNS-1131850
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/100000016, U.S. Department of Health and Human Services;
                Award ID: T90DA32484
                Award Recipient :
                Funded by: U.S. Department of Health and Human Services (US)
                Award ID: 5T90DA32484
                Award Recipient :
                AES received funding from Department of Health and Human Services https://www.hhs.gov grant 5T90DA32484, National Institutes of Health https://www.nih.gov grant P01GM118269, National Science Foundation https://www.nsf.gov/ grant DMS-1042134-5, the Institute for Medical Engineering and Science at Massachusetts Institute of Technology http://imes.mit.edu/, the Center for Computational Neuroscience and Neural Technology at Boston University http://compnet.bu.edu/, and the Graduate Program for Neuroscience at Boston University https://www.bu.edu/neuro/graduate/. MMM received funding from National Institutes of Health https://www.nih.gov grant P01GM118269. JS received funding from Department of Health and Human Services https://www.hhs.gov grant T90DA32484 and Army Research Office at United States Army Laboratory http://www.arl.army.mil/www/default.cfm?page=29 grant ARO W911NF-12-R-0012-02. SL received funding from National Institute of Mental Health https://www.nimh.nih.gov/index.shtml grant T32MH019118, National Science Foundation/National Institutes of Health https://www.nsf.gov/ https://www.nih.gov grant CRCNS-1131850, and Brown Institute for Brain Science, Brown University https://www.brown.edu/academics/brain-science/. PLP received funding from National Institutes of Health https://www.nih.gov grants DP2-OD006454 and P01GM118269. ENB received funding from Guggenheim Fellowship in Applied Mathematics at John Simon Guggenheim Memorial Foundation https://www.gf.org/, National Institutes of Health https://www.nih.gov grants R01-GM104948 and P01GM118269, and Massachusetts General Hospital http://www.massgeneral.org/. NK received funding from National Science Foundation https://www.nsf.gov/ grant DMS-1042134-5, Army Research Office at United States Army Laboratory http://www.arl.army.mil/www/default.cfm?page=29 grant ARO W911NF-12-R-0012-02, and National Institutes of Health https://www.nih.gov grant P01GM118269. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
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                Custom metadata
                vor-update-to-uncorrected-proof
                2017-12-21
                All MATLAB code necessary to run our simulations is available at https://github.com/asoplata/propofol-coupling-2017-full and the mechanisms files alone for usage with the DynaSim simulator ( https://github.com/dynasim/dynasim) are available at https://github.com/asoplata/propofol-coupling-2017-mechanisms.

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