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      Coordinated infraslow neural and cardiac oscillations mark fragility and offline periods in mammalian sleep


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          Mammalian sleep alternates between sensory-responsive and protected offline periods via coordinated neural and cardiac rhythms.


          Rodents sleep in bouts lasting minutes; humans sleep for hours. What are the universal needs served by sleep given such variability? In sleeping mice and humans, through monitoring neural and cardiac activity (combined with assessment of arousability and overnight memory consolidation, respectively), we find a previously unrecognized hallmark of sleep that balances two fundamental yet opposing needs: to maintain sensory reactivity to the environment while promoting recovery and memory consolidation. Coordinated 0.02-Hz oscillations of the sleep spindle band, hippocampal ripple activity, and heart rate sequentially divide non–rapid eye movement (non-REM) sleep into offline phases and phases of high susceptibility to external stimulation. A noise stimulus chosen such that sleeping mice woke up or slept through at comparable rates revealed that offline periods correspond to raising, whereas fragility periods correspond to declining portions of the 0.02-Hz oscillation in spindle activity. Oscillations were present throughout non-REM sleep in mice, yet confined to light non-REM sleep (stage 2) in humans. In both species, the 0.02-Hz oscillation predominated over posterior cortex. The strength of the 0.02-Hz oscillation predicted superior memory recall after sleep in a declarative memory task in humans. These oscillations point to a conserved function of mammalian non-REM sleep that cycles between environmental alertness and internal memory processing in 20- to 25-s intervals. Perturbed 0.02-Hz oscillations may cause memory impairment and ill-timed arousals in sleep disorders.

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          Most cited references 47

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          Electrophysiological signatures of resting state networks in the human brain.

          Functional neuroimaging and electrophysiological studies have documented a dynamic baseline of intrinsic (not stimulus- or task-evoked) brain activity during resting wakefulness. This baseline is characterized by slow (<0.1 Hz) fluctuations of functional imaging signals that are topographically organized in discrete brain networks, and by much faster (1-80 Hz) electrical oscillations. To investigate the relationship between hemodynamic and electrical oscillations, we have adopted a completely data-driven approach that combines information from simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Using independent component analysis on the fMRI data, we identified six widely distributed resting state networks. The blood oxygenation level-dependent signal fluctuations associated with each network were correlated with the EEG power variations of delta, theta, alpha, beta, and gamma rhythms. Each functional network was characterized by a specific electrophysiological signature that involved the combination of different brain rhythms. Moreover, the joint EEG/fMRI analysis afforded a finer physiological fractionation of brain networks in the resting human brain. This result supports for the first time in humans the coalescence of several brain rhythms within large-scale brain networks as suggested by biophysical studies.
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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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              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.

                Author and article information

                Sci Adv
                Sci Adv
                Science Advances
                American Association for the Advancement of Science
                February 2017
                08 February 2017
                : 3
                : 2
                [1 ]Department of Fundamental Neurosciences, University of Lausanne, 1005 Lausanne, Switzerland.
                [2 ]Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, 72076 Tübingen, Germany.
                Author notes

                These authors contributed equally to this work.

                []Corresponding author. Email: anita.luthi@ 123456unil.ch
                Copyright © 2017, The Authors

                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 work is properly cited.

                Funded by: FundRef http://dx.doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung;
                Award ID: ID0E4JAI13799
                Award ID: 146244
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung;
                Award ID: ID0EITAI13800
                Award ID: 166318
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: ID0ET3AI13801
                Award ID: SFB 654
                Award Recipient :
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