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      Cellular and neurochemical basis of sleep stages in the thalamocortical network

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          Abstract

          The link between the combined action of neuromodulators in the brain and global brain states remains a mystery. In this study, using biophysically realistic models of the thalamocortical network, we identified the critical intrinsic and synaptic mechanisms, associated with the putative action of acetylcholine (ACh), GABA and monoamines, which lead to transitions between primary brain vigilance states (waking, non-rapid eye movement sleep [NREM] and REM sleep) within an ultradian cycle. Using ECoG recordings from humans and LFP recordings from cats and mice, we found that during NREM sleep the power of spindle and delta oscillations is negatively correlated in humans and positively correlated in animal recordings. We explained this discrepancy by the differences in the relative level of ACh. Overall, our study revealed the critical intrinsic and synaptic mechanisms through which different neuromodulators acting in combination result in characteristic brain EEG rhythms and transitions between sleep stages.

          DOI: http://dx.doi.org/10.7554/eLife.18607.001

          eLife digest

          There are several stages of sleep that cycle repeatedly through the night with each producing distinctive patterns of electrical activity in the brain. It is thought that these patterns may help us to remember things that have happened throughout the day. Cells in parts of the brain called the hypothalamus and the brainstem control transitions between sleep stages. They regulate the release of chemicals known as neuromodulators in many parts of the brain, including the cortex and thalamus, which play the roles in memory and learning. Researchers now know how the neuromodulators influence the properties of individual brain cells. However, it is not clear how coordinated action of many neuromodulators result in the patterns of electrical activity seen in the brain during each stage of sleep.

          Krishnan et al. used a computer model to investigate how three of these neuromodulators – acetylcholine, histamine and GABA – shift electrical activity in the brain between sleep stages. The computer model was able to recreate the network of brain cells in the cortex and thalamus and how this network responds to the changes in the levels of neuromodulators. The study found that simultaneous and balanced changes of acetylcholine, histamine, and GABA work together to shift the brain between the stages of sleep and to initiate patterns of the brain electrical activity specific to the different sleep stages.

          Krishnan et al. predict that the relative differences in the level of acetylcholine in the brains of humans, cats and mice may explain why different species have different patterns of electrical activity during sleep. The study also found that an anesthetic drug called propofol may induce sleep-like patterns of electrical activity in the human brain by affecting the levels of all three of the neuromodulators. More studies are needed to look at how the networks of cells in the cortex and thalamus communicate with the brainstem, and how changes in the levels of neuromodulators affect memory and learning.

          DOI: http://dx.doi.org/10.7554/eLife.18607.002

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          Most cited references84

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          Activity of norepinephrine-containing locus coeruleus neurons in behaving rats anticipates fluctuations in the sleep-waking cycle.

          Spontaneous discharge of norepinephrine-containing locus coeruleus (NE-LC) neurons was examined during the sleep-walking cycle (S-WC) in behaving rats. Single unit and multiple unit extracellular recordings yielded a consistent set of characteristic discharge properties. (1) Tonic discharge co-varied with stages of the S-WC, being highest during waking, lower during slow wave sleep, and virtually absent during paradoxical sleep. (2) Discharge anticipated S-WC stages as well as phasic cortical activity, such as spindles, during slow wave sleep. (3) Discharge decreased within active waking during grooming and sweet water consumption. (4) Bursts of impulses accompanied spontaneous or sensory-evoked interruptions of sleep, grooming, consumption, or other such ongoing behavior. (5) These characteristic discharge properties were topographically homogeneous for recordings throughout the NE-LC. (6) Phasic robust activity was synchronized markedly among neurons in multiple unit populations. (7) Field potentials occurred spontaneously in the NE-LC and were synchronized with bursts of unit activity from the same electrodes. (8) Field potentials became dissociated from unit activity during paradoxical sleep, exhibiting their highest rates in the virtual absence of impulses. These results are generally consistent with previous proposals that the NE-LC system is involved in regulating cortical and behavioral arousal. On the basis of the present data and those described in the following report (Aston-Jones, G., and F. E. Bloom (1981) J. Neurosci.1: 887-900), we conclude that these neurons may mediate a specific function within the general arousal framework. In brief, the NE-LC system may globally bias the responsiveness of target neurons and thereby influence overall behavioral orientation.
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            Natural waking and sleep states: a view from inside neocortical neurons.

            In this first intracellular study of neocortical activities during waking and sleep states, we hypothesized that synaptic activities during natural states of vigilance have a decisive impact on the observed electrophysiological properties of neurons that were previously studied under anesthesia or in brain slices. We investigated the incidence of different firing patterns in neocortical neurons of awake cats, the relation between membrane potential fluctuations and firing rates, and the input resistance during all states of vigilance. In awake animals, the neurons displaying fast-spiking firing patterns were more numerous, whereas the incidence of neurons with intrinsically bursting patterns was much lower than in our previous experiments conducted on the intact-cortex or isolated cortical slabs of anesthetized cats. Although cortical neurons displayed prolonged hyperpolarizing phases during slow-wave sleep, the firing rates during the depolarizing phases of the slow sleep oscillation was as high during these epochs as during waking and rapid-eye-movement sleep. Maximum firing rates, exceeding those of regular-spiking neurons, were reached by conventional fast-spiking neurons during both waking and sleep states, and by fast-rhythmic-bursting neurons during waking. The input resistance was more stable and it increased during quiet wakefulness, compared with sleep states. As waking is associated with high synaptic activity, we explain this result by a higher release of activating neuromodulators, which produce an increase in the input resistance of cortical neurons. In view of the high firing rates in the functionally disconnected state of slow-wave sleep, we suggest that neocortical neurons are engaged in processing internally generated signals.
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              Thalamocortical oscillations in the sleeping and aroused brain.

              Sleep is characterized by synchronized events in billions of synaptically coupled neurons in thalamocortical systems. The activation of a series of neuromodulatory transmitter systems during awakening blocks low-frequency oscillations, induces fast rhythms, and allows the brain to recover full responsiveness. Analysis of cortical and thalamic networks at many levels, from molecules to single neurons to large neuronal assemblies, with a variety of techniques, ranging from intracellular recordings in vivo and in vitro to computer simulations, is beginning to yield insights into the mechanisms of the generation, modulation, and function of brain oscillations.
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                Author and article information

                Contributors
                Role: Reviewing editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                16 November 2016
                2016
                : 5
                : e18607
                Affiliations
                [1 ]deptDepartment of Medicine , University of California, San Diego , La Jolla, CA, United States
                [2 ]deptDepartment of Psychiatry and Neuroscience , Université Laval , Québec, Canada
                [3 ]deptCentre de Recherche de l’Institut Universitaire en Santé Mentale de Québec , Université Laval , Québec, Canada
                [4 ]deptDepartments of Radiology and Neurosciences , University of California, San Diego , La Jolla, CA, United States
                [5 ]deptDepartment of Neurology , Massachusetts General Hospital and Harvard Medical School , Boston, United States
                [6]Emory University , United States
                [7]Emory University , United States
                Author notes
                Author information
                http://orcid.org/0000-0002-3931-7633
                Article
                18607
                10.7554/eLife.18607
                5111887
                27849520
                45cbfbe6-e24f-4001-8212-683a4d8482aa
                © 2016, Krishnan et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 09 June 2016
                : 11 October 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;
                Award ID: MOP-136969
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;
                Award ID: MOP-136967
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000006, Office of Naval Research;
                Award ID: MURI: N000141310672
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: MH099645
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: EB009282
                Award Recipient :
                Funded by: National Sciences and Engineering Research Council of Canada;
                Award ID: 298475
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Neuroscience
                Research Article
                Custom metadata
                2.5
                A computational model of the thalamocortical network explains sleep stages by the coordinated variations in the level of neuromodulators and predicts differences of sleep pattern in human, cat and mouse recordings.

                Life sciences
                sleep stages,neuromodulator,sleep spindles,sleep slow oscillations,rem sleep,human,mouse
                Life sciences
                sleep stages, neuromodulator, sleep spindles, sleep slow oscillations, rem sleep, human, mouse

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