REVIEW
published: 14 January 2020
doi: 10.3389/fnins.2019.01402

Molecular Mechanisms of REM Sleep
Rikuhiro G. Yamada 1 and Hiroki R. Ueda 1,2*
1

Laboratory for Synthetic Biology, RIKEN Center for Biosystems Dynamics Research, Osaka, Japan, 2 Department
of Systems Pharmacology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

Edited by:Michael Lazarus,
University of Tsukuba, Japan
Reviewed by:
Akihiro Yamanaka,
Nagoya University, Japan
Hiroaki Norimoto,
Max-Planck-Institut für Hirnforschung,Germany*Correspondence:
Hiroki R. Ueda
uedah-tky@umin.ac.jp
Specialty section:
This article was submitted toSleep and Circadian Rhythms,
a section of the journal
Frontiers in Neuroscience
Received: 03 September 2019
Accepted: 12 December 2019
Published: 14 January 2020
Citation:
Yamada RG and Ueda HR (2020)
Molecular Mechanisms of REM Sleep.
Front. Neurosci. 13:1402.
doi: 10.3389/fnins.2019.01402

Rapid-eye movement (REM) sleep is a paradoxical sleep state characterized bybrain activity similar to wakefulness, rapid-eye-movement, and lack of muscle tone.
REM sleep is a fundamental brain function, evolutionary conserved across species,
including human, mouse, bird, and even reptiles. The physiological importance of
REM sleep is highlighted by severe sleep disorders incurred by a failure in REM sleep
regulation. Despite the intense interest in the mechanism of REM sleep regulation,
the molecular machinery is largely left to be investigated. In models of REM sleep
regulation, acetylcholine has been a pivotal component. However, even newly emerged
techniques such as pharmacogenetics and optogenetics have not fully clarified thefunction of acetylcholine either at the cellular level or neural-circuit level. Recently,
we discovered that the Gq type muscarinic acetylcholine receptor genes, Chrm1
and Chrm3, are essential for REM sleep. In this review, we develop the perspectiveof current knowledge on REM sleep from a molecular viewpoint. This should be astarting point to clarify the molecular and cellular machinery underlying REM sleep
regulation and will provide insights to explore physiological functions of REM sleep andits pathological roles in REM-sleep-related disorders such as depression, PTSD, andneurodegenerative diseases.
Keywords: REM sleep, theta oscillation, hippocampus, bursting, muscarinic acetylcholine receptors

INTRODUCTION
Rapid-eye movement (REM) sleep is a prominent brain state which is accompanied withmultiple features such as random movements of eyes, vivid dreaming, quiet muscle tone, lessened
homeostatic regulation of body (e.g., temperature, heart rate, etc.), and brain activity marked by
the enhancement of specific brain oscillation. As indicated by the multiple features of REM sleep,
the mechanisms of sleep, in general, involve multiple regulatory components at different layers ofscales ranging from molecule level to organism level. The brain oscillation is an electrophysiologicalactivity widely used to define stages of sleep. The identification of the brain oscillation associatedwith specific sleep stages has enabled researchers to untangle such intermingled systems in
consideration of neural activity of the brain. There are largely three classes of oscillations in
the brain of sleeping mice; slow-wave oscillation (SWO, <1 Hz), delta oscillation (1–4 Hz), andtheta oscillation (4–10 or 12 Hz; this range slightly varies depending on literature). The SWO
and delta oscillation are characteristic to non-REM (NREM) sleep, and the theta oscillation ischaracteristic to REM sleep. The early investigations into the SWO and delta oscillations provided
the basis for current understanding of molecular and cellular mechanisms of NREM sleep. In
contrast to the relatively well-described mechanisms of NREM sleep, that of REM sleep has beenleft unclear. Looking back some historical milestones of sleep research is helpful to grasp how the

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Importantly, all of the three brain oscillations, SWO,
delta oscillation, and theta oscillation, are originated fromsynchronized activity of a population of neurons. The cellular
property shared among synchronous neurons is the bimodalityof membrane potentials. The alternating sequence of theactive state (UP state) and the silent state (DOWN state)rises to the brain oscillations. The UP state is associatedwith vigorous firings due to the depolarized membranepotential and the DOWN state associated with the ceasingof firing due to the hyperpolarized membrane potential(McCormick et al., 2015). Some early studies suggested thatthe essence of the alternating sequence is the interaction
between the relatively slow Ca2+ oscillation and the fast action
potentials, and suggested ion channels involved in the slow
oscillation and action potentials (Jahnsen and Llinas, 1984;
Steriade et al., 1993b; McCormick and Bal, 1997). Following
the description of the SWO and the delta oscillation in
the neocortex and the thalamus which underly the NREM
sleep, the identification of involved brain regions and theirbrain-wide neural circuits have rapidly advanced, and we
see further advancement in that direction thanks to therecent advent of innovative techniques such as opto- andpharmacogenetics (Weber and Dan, 2016; Saper and Fuller, 2017;
Scammell et al., 2017).
While the neural circuits are relatively well described, themolecular and cellular properties essential to sleep regulation
have been less investigated in the last decades. Moreover, thefunction of even basic neurotransmitters in regulating the cellular
properties for sleep, especially the necessity of acetylcholine for
REM sleep has been controversial for decades. Early studies
implied the importance of acetylcholine for REM sleep bydemonstrating that the injection of cholinergic agonists into
the brainstem induced REM sleep-like state (Cordeau et al.,
1963; George et al., 1964). Also, acetylcholine release wasfound to be abundant in the brainstem during REM sleep(Kodama et al., 1990; Leonard and Lydic, 1997). Therefore,a long-standing hypothetical model of the transition between
NREM sleep and REM sleep incorporated acetylcholine as the
key factor (Hobson et al., 1975; McCarley and Hobson, 1975;
Sakai et al., 2001). However, the necessity of acetylcholine
for REM sleep has been elusive, because lesioning of brain
regions such as cholinergic neurons in the basal forebrain (BF),
the laterodorsal tegmentum (LDT), and the pedunculopontine
tegmentum (PPT) in the brainstem results in relatively minor
effects (Lu et al., 2006; Blanco-Centurion et al., 2007). Hence,a proposed model for regulating REM sleep incorporates
GABAergic and glutamatergic neurons as its core components(Luppi et al., 2013). Although recent opto- and pharmacogenetic approaches consolidated the role of acetylcholine in sleep
regulation at neural-circuit level, the necessity of acetylcholine
in REM sleep regulation remained unclear (Shi et al., 2015; Xu
et al., 2015; Chen et al., 2016; Zant et al., 2016). Despite thecontroversy over the importance of cholinergic regulation on
REM sleep, multiple lines of in vivo pharmacological evidence
consistently indicated muscarinic acetylcholine receptors areimportant for REM sleep regulation. Muscarinic receptor
agonists and acetylcholinesterase inhibitors increase REM sleep

brain oscillations became established as definitive features of
sleep stages and contributed to the current understanding of
the mechanisms of NREM sleep. This retrospective detour into
NREM sleep studies should be beneficial to make extrapolations
on how the brain oscillations provide insights into themechanisms of REM sleep.
The first measurement of the electrical activity of brain
dates back to 1875 when the pioneer electrophysiologist; Caton(1875) reported that the electrical current in a cortical region
varies depending on the functional activity of the region usingdog, rabbit, and monkeys. Notably, he already described thatthe suspension of functional activity increased the electricalcurrent, and the current diminished when the cortical area
was functionally active (Cohen of Birkenhead, 1959). His
notion is consistent with today’s knowledge that the sleeping
cortex shows the relatively high amplitude of SWO and delta
oscillation while the waking brain shows low amplitude fast
oscillation. Without knowing Caton’s work, in 1890, Beck (1890)
observed spontaneous rhythms of electrical brain activity andthat the rhythm changes upon sensory stimulation using frogs,
dogs, and rabbits. In 1910s, W. Práwdicz-Neminski identified
the distinguishable patterns of the spontaneous rhythms andreferred them as A-waves and B-waves using dogs (Coenen
and Zayachkivska, 2013). In 1920s, the first electrical recordingof a human brain was made by Berger (1929), who called
his method “electro encephalogram (EEG).” He also observed
distinct patterns of spontaneous rhythms which consisted of slow
and fast oscillations. The slow and fast oscillations are around 10
and 30 Hz, respectively. Berger (1929) referred those oscillations
as alpha and beta waves and reported that the alpha wave was
replaced with the beta wave in response to physiological stimuli.
Importantly, his extensive investigation of brain oscillations invarious pathological and pharmacological conditions revealed
that the slower alpha wave, which is referred as delta oscillation
in today’s term, appeared when the subject was unconscious
under anesthesia or epilepsy (Walter, 1938). The term of “deltawave” was first introduced by Walter in 1936 to describe slow
oscillations produced in a cortical region adjacent to cerebral
tumors when he studied the location of tumors by using EEG
signal. Later, Loomis et al. (1937) used the term (delta wave)
to describe the slow oscillations discovered in natural sleep ofhuman and many other conditions (Walter, 1938). Loomis et al.
(1937) built a large recording drum of EEG to observe a humansubject continuously throughout a night, and they discovered
several distinct stages of sleep and characteristic brain oscillations(Davis et al., 1937; Loomis et al., 1937). Later, these findings
led to the identification of the sleep stage associated with REM
and frequent dreaming (Aserinsky and Kleitman, 1953), andto the formulation of an objective method for studying sleep(Dement and Kleitman, 1957a,b). Since those seminal studies,
EEG signal has been the definitive information for staging sleep.
However, the understanding of the neuronal and molecular basisthat underlie the characteristic EEG signals had to wait for theworks of Steriade that attributed the high amplitude and lowfrequency EEG oscillations, that is SWO and delta oscillation,
to the synchronized activity of the population of neocortical andthalamocortical neurons (Steriade et al., 1993a,c,d).

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strong extracellular electrical field readily measurable on the skull(Buzsaki et al., 2012). In contrast, the cerebellum which also has
the layer structure of giant Purkinje neurons generate very small
extracellular fields because the cerebellar activity is mainly local,
and the Purkinje cells are not synchronized. Thalamocorticalcells, which have more circular morphology emanating dendrites
in all directions with relatively equal size compared to pyramidal
neurons, can form limited dipoles and their contribution to
extracellular fields is small even when their action is highly
synchronized. Besides the neocortex, the hippocampus is a major
influencer on the EEG signal. The hippocampus has a layered
structure, hippocampal pyramidal neurons are densely aligned inparallel, and they act in a synchronized manner to generate strong
electrical fields (Colgin, 2013, 2016). Because the hippocampus
is located deeper in the brain compared to the neocortex, thedetailed recording of the extracellular electrical field requires
deep electrodes placed close to the tissue (Figures 1A,B).
However, the characteristic oscillation at the theta frequency
band (4–10 Hz) recorded in EEG is thought to originate fromthe hippocampus. Supporting evidence includes that the averagemagnitude of theta power measured by multisite recordings
along the hippocampus–neocortex axis monotonically decreased
with distance from the hippocampus and that the distributionof theta power on the neocortical surface reflects the physicallayout of the underlying hippocampus (Bland and Whishaw,
1976; Sirota et al., 2008).

and shorten the REM latency (the time-delay of REM start
after the NREM start) (Sitaram et al., 1976; Hohagen et al.,
1993; Lauriello et al., 1993; Riemann et al., 1994). On theother hand, muscarinic receptor antagonist decreased REM
sleep and lengthened the REM latency (Gillin et al., 1991;
Rauniar et al., 1998; Kim and Jeong, 1999). Nonetheless, genetic
approaches to assess the contribution of muscarinic receptors
to sleep-regulation have been limited (Goutagny et al., 2005),
leaving the molecular component in the regulation of REM
sleep unidentified.
To obtain deeper insights into the molecular mechanismof REM sleep, we need to address two issues: (1) identifying
specific molecular components among the family members ofacetylcholine receptors and (2) understanding the molecularfunction in regulating cellular properties of the identified
receptors. A recent comprehensive reverse genetic study revealed
that the Gq protein-coupled muscarinic acetylcholine receptors,
Chrm1 and Chrm3, are essential for REM sleep, as REM sleep
and its associated enrichment of EEG theta oscillation could
be hardly detected in Chrm1 and Chrm3 double-knockout(DKO) mice during sleep (Niwa et al., 2018). Also, a series ofour studies suggested that the Ca2+ -hyperpolarization pathway
plays an important role in regulating cellular properties for thesynchronized activity for NREM sleep, i.e., for the SWO and thedelta oscillation. Because the synchronized activity of populationof neurons is also a mechanism that underlies the theta
oscillation; a definitive feature of REM sleep, the investigation
into the molecular mechanisms involved in the synchronizedactivity should be a future direction of REM sleep research. In thisreview, we intend to give a perspective on molecular mechanismsof REM sleep by focusing on the EEG theta oscillation in sleeping
mice. First, we summarize the cellular basis of synchronizedneurons underling the SWO and the delta oscillations, then we
shift our viewpoint to the theta oscillation and look neural circuits
involved in generation and regulation of the theta oscillation.
We also discuss the current views about the function of Chrm1
and Chrm3 in the theta oscillation, and a potential molecularbasis for sleep homeostasis. Previous excellent reviews haveextensively described the regulatory neural circuits of REM sleep,
the characteristic muscle activities associated with REM sleep
such as REM and muscle atonia, the evolutional perspective of
REM sleep, or the mechanism and function of SWO in the neuralnetwork (Brown et al., 2012; Luppi et al., 2013; Neske, 2015;
Miyazaki et al., 2017). Here, we put our focus on the molecularmechanisms of EEG brain oscillations.

Molecular Mechanisms of the
Bimodality: UP and DOWN States of the
Burst Firing
The synchronized activity of neurons emerges from the burstingof individual neurons. The bursting consists of repeating cycles ofthe vigorous-firing state (UP state) and the silent state (DOWN
state). The cycle can be observed in the neocortex and thalamus
where a population of neurons synchronously generate the SWO
and delta oscillation, respectively. The transition between UP
and DOWN states is marked by a clear change of membranepotential, which traces the bimodality of neurons (Figure 2).
The depolarized membrane potential underlies the UP state, andthe hyperpolarized membrane potential underlies the DOWN
state (Crunelli and Hughes, 2010). Some early studies focused onthalamic cells and depicted the molecular mechanism underlying
the bimodality. In the classical explanation, the burst firing
occurs from a hyperpolarized membrane potential. A burst firingconsists of a series of ionic flows: (1) the hyperpolarization
activated-cation channels (HCN) depolarizes the membrane (I h )to activate the transient slow low-threshold Ca2+ spike (I T ),(2) the low-threshold Ca2+ spike triggers action potentials
consisting of the fast in- and out-flow of sodium (I Na ) andpotassium (I K ). In addition, the fast Na+ spikes also activate
high-threshold Ca2+ current (I Ca ), (3) after the burst of action
potentials, the membrane repolarizes as the low-threshold Ca2+
spike (I T ) ceases, (4) and the reduced depolarizing effect of I T
is followed by the overshooting after-hyperpolarization whichis caused by the outflows of K+ due to the activation of Ca2+
dependent potassium channels (I K[Ca] ) (Jahnsen and Llinas, 1984;

THE CELLULAR MECHANISM OF THE
BRAIN OSCILLATIONS
Although any cell types in the brain may contribute to the
EEG signal as ionic flows are generated, the primary contributor
is the pyramidal neuron in the neocortex. The neocorticalpyramidal neurons reside under the skull, aligned in parallel
to each other, and have thick dendrite that can form strong
dipoles along the somatodendritic axis. The synchronizedactivation of those layered pyramidal neurons generates the

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and McCormick, 2000). However, this view does not exclude
the possibility that the ionic-flow mechanism similar to thalamic
neurons also works in the neocortex. Indeed, the bursting
persists in at least two groups of neocortical neurons even
without synaptic connections at the frequency range of SWO (LeBon-Jego and Yuste, 2007). Moreover, the neocortical burstingneurons have the electrophysiological properties characteristic
to specific neurons that exhibit the slow Ca2+ oscillation (lowthreshold Ca2+ spike), such as the rebound burst of action
potentials following negative current injection (Huguenard, 1996;
Le Bon-Jego and Yuste, 2007). Although it is to be confirmedthat the intrinsic oscillatory property of neocortical cells isrelevant to natural sleep, the property as ubiquitous as the
low-threshold spike observed throughout brain regions withsynchronized bursting for functions seems to play an importantrole in the neocortex (Huguenard, 1996; Li et al., 2009). Notably,
it is recently shown that the changes in the composition ofcortical interstitial Ca2+ and K+ ions influence the sleep–wakecycle (Ding et al., 2016). This study suggests that the intrinsic
properties of neural oscillation may depend on the intracellularconcentration of Ca2+ and K+ ions, which is in line with theobservations that the loss of Ca2+ and K+ channels, such as SK2(Kcnn2) and SK3 (Kcnn3), Cav3.1 (Cacna1g), Cav3.2 (Cacna1h),
and TASK3 (Kcnk9), affected the sleep duration in vivo (Tatsuki
et al., 2016; Yoshida et al., 2018).

FIGURE 1 | The brain region and the neural connections in the
MS-DBB–hippocampus system. (A) The MS-DBB–hippocampus system
depicted in 3D space. The blue region is the hippocampal formation; theorange region is the medial septal complex (including MS-DBB). The purple
region is the somatomotor areas in the neocortex (isocortex) presented forvisual aid to highlight the deep locations of the hippocampus and the medial
septal complex. (B) The thalamocortical system depicted in 3D space. The
transparent blue region represents the neocortex. The orange region
represents thalamus. The purple region is the somatomotor areas in the
neocortex presented for visual aid to highlight the deep location of thethalamus. (C) Schematic diagram of the MS-DBB–hippocampus system. The
hippocampal pyramidal neurons (blue triangles) are aligned in parallel so thatthey produce the strong alteration in the electrical field measurable by EEG.
The pyramidal neurons receive excitatory cholinergic and glutamatergic inputs
from the MS-DBB and inhibitory inputs from hippocampal interneurons. The
pyramidal neurons innervate cholinergic and GABAergic neurons in MS-DBB.
Dark brown ellipsoids represent GABAergic neurons; light brown ellipsoids
represent cholinergic neurons; blue ellipsoids and triangles represent
glutaminergic neurons. Red connection and blue connections represent
excitatory and inhibitory connections, respectively. The 3D plots were drawn
with cocoframer available at a public mouse brain atlas for parts (A) and (B)(Allen Institute for Brain Science, 2018).

Ca2+ -Dependent Hyperpolarization
Pathway for SWO
The investigations with emphasis on the circuit of SWO haveprovided the detailed view of intra-neocortical network ofglutamatergic excitatory neurons and GABAergic inhibitory
neurons and the inter-regional interaction between the thalamus
and the neocortex (Crunelli et al., 2015; Neske, 2015).
The circuit-based investigation has also been successful indescribing the brain-wide regulatory neural circuits of sleep
and wake cycle (Weber and Dan, 2016; Saper and Fuller,
2017; Scammell et al., 2017). On the other hand, the essential
properties of oscillatory neurons remain elusive due to thecomplex nature of the interaction within the circuit. One
approach is to simplify the neural circuit by constructing acomputational model of “averaged” homogenous populationof neurons (Tatsuki et al., 2016). The averaged-neuron (AN)model includes the excitatory glutamatergic AMPA and NMDA
receptors that mediate Na+ and Ca2+ currents (I AMPA , I NMDA ),respectively, and the inhibitory GABAA receptors that regulate
Cl− currents (I GABA ). The model also contains voltage-gated
Ca2+ current (I Ca ), voltage-gated and persistent sodium current(I Na , I NaP ), several types of K+ currents including voltagegated (I K ), leak (I L ), fast A-type (I A ), inwardly rectifying(I AR ), slowly inactivating (I KS ), and Ca2+ -dependent potassium
currents (I K[Ca] ). The unbiased search over the almost 20
million sets of parameters demonstrated that the AN model
could generate bursting in a homogenous population ofneurons. Moreover, the model predicted that the cellular
Ca2+ plays a pivotal role in the alternation between UP
and DOWN states.

McCormick and Bal, 1997). The essence of this ionic-flow modelis the interaction between the relatively slow Ca2+ oscillation andthe fast action potentials (Steriade et al., 1993b). Synaptic input
is not critical part of the model. Indeed, the isolated thalamic
neuron displays firing patterns similar to those of intact neurons
in slice or in vivo (Hernandez-Cruz and Pape, 1989; Suzuki andRogawski, 1989), and simple theoretical models generate bursting
without explicit synaptic connections (Izhikevich, 2007).
In contrast to the established model of the cellular mechanism
for the thalamic delta oscillation, cellular mechanisms forthe neocortical SWO are less understood. This disparity ispresumably because the neocortical SWO has been widely
accepted to emerge from a finely tuned neural circuit consistingof balanced excitatory and inhibitory synaptic connections (Shuet al., 2003; Crunelli et al., 2015). One piece of supporting
evidence of the view comes from the observation that theapplication of antagonist of non-NMDA glutamate receptor
diminishes the SWO in the neocortical slices (Sanchez-Vives

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FIGURE 2 | Bursting and intracellular Ca2+ concentration in a simple model. The membrane potential (orange line) and the intracellular Ca2+ concentration (blue line)
are plotted. The bursting consists of UP and DOWN states alternating with each other. In the DOWN state (light blue background), the membrane potential is
hyperpolarized to be quiet, and in the UP state (light orange background), the membrane potential is depolarized to generate a series of fast action potentials. In thefirst DOWN state, deactivation of the Ca2+ -dependent potassium outward current (IK[Ca] ) raise the membrane potential toward the threshold of Na+ and K+
dependent fast action potentials (INa/K ), entering the UP state. In the UP state, the fast Na+ spikes also activate high-threshold Ca2+ current (ICa ), building up theintracellular Ca2+ concentration. At the end of the UP state, due to the activation of the Ca2+ -dependent potassium current (IK[Ca] ), the membrane potential
repolarizes, going to the DOWN state. In the second DOWN state, the hyperpolarized membrane then deactivates the IK[Ca] to evoke another raise of membranepotential. The plot was calculated by the simplified-average neuron (SAN) model with arbitrary y-axis scales for visual aid (Yoshida et al., 2018).

The AN model demonstrated that theoretical models could
provide fundamental insight into the complex nature of
bursting neurons. However, the AN model, which contains
13 components, is too complicated to interpret its detailed
mathematical structure. Because it was important to elucidate
how the transition between UP and DOWN states occurs,
mathematical analyses, for example, to reveal the currents
responsible for the transition were demanded. This point
was addressed by constructing a simplified AN (SAN) model(Yoshida et al., 2018). Bifurcation and detailed mathematicalanalyses of the SAN model predicted that leak K+ channels
play a role in generating bursting. Furthermore, the following
comprehensive phenotype assays with 14 KO mice of leakK+ channels family identified that potassium two pore domainchannel subfamily K member 9 (Kcnk9) gene is involved insleep regulation, validating the prediction of the mathematicalanalysis (Yoshida et al., 2018). It is interesting to note that thisdata of the involvement of constant K+ currents suggested thatthe conductance of leak K+ channels may alter the thresholdfor transition from UP to DOWN state mediated by theCa2+ -dependent K+ channels. Collectively, the Ca2+ -dependent
hyperpolarization pathway and leak K+ channels are involved inregulating SWO. The mathematical insight given by the potential
role for constant currents such as leak K+ currents in affecting

To validate the prediction of the model, a series of knockout(KO) mice were generated. The KOs covered following genes:
Ca2+ dependent K+ channels (eight genes) including SK2(Kcnn2) and SK3 (Kcnn3), the voltage-gated Ca2+ channels (10genes) including Cav3.1 (Cacna1g) and Cav3.2 (Cacna1h), theplasma membrane calcium pumps (four genes) including Atb2b3(PMCA3), and NMDA receptors (seven genes) including Nr3a
(GRIN3A) (Sunagawa et al., 2016; Tatsuki et al., 2016). The
results demonstrated that the changes of sleep duration observedin the mutant mice were consistent with the predictions. In
addition, the acute or chronic pharmacological inhibition of
NMDA receptors (possibly Nr1/Nr2b) in WT mice reduced theduration of sleep, suggesting the contribution of Nr1 or Nr2b,
the KO of which is embryonically lethal, in sleep regulation(Tatsuki et al., 2016). Building upon these results, they further
tested the role of the major calcium-dependent protein kinase,calcium-/calmodulin-dependent protein kinase type II (CaMKII)in sleep regulation. Among the four different subunits of the
CaMKII tested, CaMK2a KO and CaMK2b were found to be
involved in the regulation of sleep/wake cycle (Tatsuki et al.,2016). Taken together, these results provided a hypothesisthat the Ca2+ -dependent hyperpolarization pathway plays animportant role in regulating sleep duration through modulating
the neural bimodality.

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Molecular Mechanisms of REM Sleep2013). The loss of major afferent input from MS-DBB abolishes
the theta oscillation in the hippocampal–entorhinal regions inurethane-anesthetized animals or awake animals indicating that
the MS-DBB plays a critical role in hippocampal oscillation(Brazhnik and Fox, 1997; Yoder and Pang, 2005).
The MS-DBB is a region of the BF and composed of aheterogeneous population of neurons including GABAergic,
cholinergic, and glutamatergic neurons. The large portion of
the GABAergic neurons exhibits bursting activity at the theta
frequency while the cholinergic neurons have a low firing rate
not related to the theta oscillation (Simon et al., 2006). However,
the targeted lesion of cholinergic neurons in MS-DBB by 192
IgG-saporin injections reduces the amplitude of the hippocampal
theta oscillation indicating that the cholinergic projection also
plays a role in the hippocampal theta (Lee et al., 1994; Yoder
and Pang, 2005). The selective lesion of GABAergic neurons
and potentially other non-cholinergic neurons by kainic acid
reduces the hippocampal theta oscillation more than cholinergic
lesion. The combined lesion of cholinergic and GABAergic
neurons almost eliminates the hippocampal theta oscillation(Yoder and Pang, 2005). In addition, the isolated MS-DBB
can exhibit oscillation at the theta frequency band in vitro
when it is bathed in acetylcholine agonist (Konopacki et al.,1987a,b; Goutagny et al., 2009; Pignatelli et al., 2012). Theseobservations supported the view that the MS-DBB, especially the
GABAergic projection, provides the hippocampus with critical
inputs to mediate the theta oscillation (Manseau et al., 2005;
Teles-Grilo Ruivo and Mellor, 2013).
The MS-DBB-hippocampus system has afferent input from
nuclei in the brainstem from which the major sleep/wakeregulatory pathways arise (Figure 3; Petsche et al., 1962; Buzsaki,2002). The pons of the brainstem contains a population of REMon neurons (i.e., neurons that are active during REM sleep) in
the sublaterodosal nucleus (SLD), the REM-off neurons (i.e.,
neurons that are inactive during REM sleep) in ventrolateralperiaqueductal gray matter (vlPAG), and the adjacent lateral
pontine tegmentum (LPT) which is also known as the deep
mesencephalic reticular nucleus (DpME) (Boissard et al., 2002;
Lu et al., 2006; Scammell et al., 2017). The pathways ascend
through the midbrain and then split into a dorsal pathway andventral pathway. The dorsal pathway innervates the thalamus
which projects to neocortical areas, while the ventral pathway
innervates the BF including the MS-DBB, the hypothalamus, andthe cortex (Brown et al., 2012).

the bifurcation explains that the other constant synaptic currents
mediated by, for example, AMPA receptors and GABA receptors
can contribute to wakefulness and sleep.

THE NEURAL CIRCUITS OF THE EEG
THETA OSCILLATIONThe extensive multisite measurements of local field potentials inrodents found the hippocampus as the cardinal source of thetheta oscillation (Green and Arduini, 1954). The hippocampal
theta oscillation was later to be found associated with REM sleep(Jouvet, 1969). Since then, the hippocampal theta oscillation insleeping animal is recognized as a definitive feature of REM sleep.
The EEG theta oscillation is a summation of multiple signals
generated by spatially distributed oscillators in the hippocampal–
entorhinal regions, and the oscillation amplitude and phase varyas a function of behavior (Sirota et al., 2008; Buzsaki et al.,2012). Notably, the isolated hippocampal neurons can exhibit
oscillations at the theta frequency band in vitro when it is bathedin acetylcholine or kainate receptor agonist (Williams and Kauer,
1997; Garner et al., 2005; Manseau et al., 2005; Fuller et al., 2007).
Moreover, the hippocampus neurons, such as CA3 pyramidal
neurons, exhibit low-threshold Ca2+ spike and bursting (Llinas,
1988; Huguenard, 1996). Therefore, it is plausible to assume
that the neurons of hippocampus possess an intrinsic ability togenerate the theta oscillation. Interestingly, a recent study showedthat a majority of hippocampal neurons are self-oscillatory, andthe properties of oscillation, including frequency, are affected byenvironmental ions and cellular Ca2+ (Penn et al., 2016). Thiseffect occurs without changes in synaptic connectivity or neuralcircuit, suggesting that the intrinsic neural properties directly
affect circuit-level oscillation.
Together, the body of evidence suggests that the brain
oscillations, including hippocampal theta oscillation, originate
from intrinsic cellular properties. The intrinsic oscillation
resonates and is amplified in neural circuits to operate
physiological function implemented in each brain region. Thisview is consistent with the observed function of neural circuits.
The intensive studies on neural circuits for regulating REM
sleep have revealed multiple brain regions and extracellular
neurotransmitters. The following sections briefly review theneural circuits focusing on the regulation of hippocampal
theta oscillation.

The Brain Regions Involved in theRegulation of the Hippocampal Theta
Oscillation

The Direct Projection From the Pons to
MS-DBBThe cholinergic inputs from the brainstem are the major
neuromodulators of MS-DBB (Mesulam et al., 1983). Thischolinergic input consists of two different pathways (Figure 3).
The one pathway is the direct cholinergic projection fromthe PPT and the LDT (Hallanger and Wainer, 1988). The
activation of PPT and LDT by injection of glutamate results inneocortical desynchronization and hippocampal theta oscillationaccompanied by wakefulness or REM sleep (Datta and Siwek,
1997). Additionally, the optogenetic activation of cholinergic

Similar to the model of SWO or delta oscillation which consists ofinteracting intrinsic oscillators in the neocortex or the thalamus(Crunelli et al., 2015), the widely accepted model of hippocampal
theta oscillation adopted the view of neural circuits as an
oscillatory unit. In the model, the interaction between the
medial septum (MS) and diagonal band of Broca (MS-DBB)
and hippocampus mediates the generation of theta oscillation(Figure 1; Brown et al., 2012; Teles-Grilo Ruivo and Mellor,

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dorsal part of the SLD project to the MS. On the other hand, theglutaminergic neurons in the ventral part of the SLD project tothe spinal cord and regulate muscle atonia (Lu et al., 2006; Wenget al., 2014). Thus, lesions of the ventral SLD and PC produce a
specific loss of REM sleep components; that is, the muscle atonia
and the EEG theta, respectively (Fuller et al., 2007).

The Indirect Projection From the Pons to
MS-DBBThe other pathway is the indirect projection mediated by nuclei
in the hypothalamus (Woodnorth et al., 2003; Figure 3). The
supramammillary nucleus (SuM) in the hypothalamus is one
candidate which may relay the regulation from the nucleus pontis
oralis (PnO). PnO is a region of the brainstem reticular formation
which is projected by PPT. The PnO activity is associated withthe presence of hippocampal theta (Kirk and McNaughton, 1991;
Oddie et al., 1994; Vertes and Kocsis, 1997; Pignatelli et al., 2012).
Since the neurons in the PnO did not show rhythmic firing,
the SuM has been assumed to translate the tonic firing of PnO
into rhythmic firing. However, the lesion of SuM fails to affecttheta rhythm (Thinschmidt et al., 1995; Renouard et al., 2015)
while the inactivation of SuM by procaine injection reduces both
frequency and amplitude of theta rhythm in the hippocampus(Kirk and McNaughton, 1993). The recent finding of the role for
SuM in the creation of oscillatory interference between the theta
oscillation of itself and the ongoing oscillations in its target areas
suggested that the SuM is a coordinator of phase coherence oftheta oscillations among brain regions (Ito et al., 2018).

FIGURE 3 | Schematic diagram of the neural circuit for EEG theta oscillation.
Light brown ellipsoids represent cholinergic neurons, blue ellipsoids represent
glutaminergic neurons, dark brown ellipsoids represent GABAergic neurons,
and green ellipsoid represents monoaminergic neurons. Blue connections andred connections represent excitatory and inhibitory connections, respectively.
Blue and dark brown letters for neurons represent glutamatergic and
GABAergic neurons, respectively. The neurons represented by only letters are
not depicted in ellipsoid because the definition of their residing brain regions
has not been established yet.

THE ESSENTIAL GENES FOR REM
SLEEP AND THE ASSOCIATED EEG
THETA OSCILLATION: Chrm1 AND
Chrm3

neurons in PPT and LDT increased the initiation of REM sleep(Van Dort et al., 2015). However, selective lesions of PPT and
LDT do not much affect REM sleep (Lu et al., 2006).
Importantly, retrograde tracer injected in the MS
found positive cells in the precoerulueus (PC) region, theperiventricular gray matter, and a dorsal extension of the SLD
which shows high levels of activity (c-Fos expression) in REM
sleep (Lu et al., 2006; Fuller et al., 2007). The projected PC
neurons are glutamatergic, and the selective lesion of the PC and
SLD abolished the theta oscillations during sleep (Lu et al., 2006),
providing support for the concept that glutamatergic neurons in
the PC regions play a critical role in mediating the emergenceof theta oscillation from the cellular intrinsic oscillations in
the MS-DBB–hippocampus system during REM sleep (Fuller
et al., 2007). These observations give rise to the hypothesisof the “flip-flop model” in which the bidirectional inhibition
between REM-on regions (PC and SLD) and REM-off regions(LPT and vlPAG) works like a flip-flop switch via GABAergic
projections. The state of the switch is regulated by the excitatory
inputs from serotoninergic dorsal raphe nucleus and locus
coeruleus (DRN-LC) to the REM-on neurons (Lu et al., 2006),
glutaminergic inputs from neurons located rostrolateral of SLD(Atoh1-E10.5 medial neurons) to REM-off neurons (Hayashi
et al., 2015), and by the inhibitory inputs from the GABAergic
ventral medulla neurons to REM-off neurons (Weber et al.,2015; Figure 3). The glutamatergic neurons in the PC and theFrontiers in Neuroscience | www.frontiersin.org

The accumulated evidence indicated that acetylcholine plays
an important role in regulating REM sleep. However, it isdemonstrated that the cholinergic function in a specific neuralcircuit can be limited (Grace et al., 2014). A possible functionof acetylcholine is the regulation of cellular properties involvedin the theta oscillation rather than of switching neural circuits.
Indeed, isolated hippocampal and MS-DBB neurons can exhibit
oscillations at the theta frequency band in vitro when it is bathedin acetylcholine receptor agonist (Williams and Kauer, 1997;
Fellous and Sejnowski, 2000; Manseau et al., 2005). However,
the molecular investigation into the necessity of acetylcholine
for REM sleep has been hindered, because of the formidable
redundancy resulting from the multitude of genes involved in theregulation: the 11 neuronal-type nicotinic acetylcholine receptors
and 5 muscarinic acetylcholine receptors. The identificationof critical cholinergic receptors has been unfeasible until the
recent emergence of the efficient techniques in genetics suchas CRISPR and ES-mice (Sunagawa et al., 2016; Ukai et al.,2017). The comprehensive study with these techniques onacetylcholine receptors revealed that DKO mice of Gq proteincoupled muscarinic acetylcholine receptors: Chrm1 and Chrm3

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Molecular Mechanisms of REM Sleeprole for the cholinergic pathway in REM sleep. Indeed, cultured
hippocampal slice bathed in the acetylcholine agonist, carbachol,shows oscillation at the range of frequencies, including theta band
depending on the drug concentration (Fellous and Sejnowski,2000). The hippocampus intrinsic oscillation was inhibited either
by Chrm1 or Chrm3 inhibitors (Williams and Kauer, 1997).
Although the current knowledge of the essential role for
Chrm1 and Chrm3 in REM sleep is based on the wholebody KO mice, investigations into the intrinsic cellularmechanisms involving Chrm1 and Chrm3 may contributeto understanding REM sleep regulation, much as the studyof thalamocortical oscillations benefited from investigations
into regulatory mechanisms of cellular excitability (Steriade
et al., 1993b). In the thalamocortical cells, the membrane
depolarization is mediated to a large part by the inhibitionof a leak K+ conductance (I Kleak ), the molecular instance of
which is the two-pore domain K+ channels TASK1 (Kcnk3) andTASK3 (Kcnk9) (Meuth et al., 2006; Yoshida et al., 2018). The
metabotropic glutamate and muscarinic acetylcholine receptors
competitively activate Gq pathway, which in turn inhibit theleak K+ conductance (Chen et al., 2006; Coulon et al., 2010).
A relatively small shift of membrane potential (∼10 mV) issufficient to mediate a switch of firing mode in vivo. Moreover,the depolarization induced by the activation of muscarinic
acetylcholine receptors Chrm1 and Chrm3 mediated by Gq
proteins can mediate the switch in thalamocortical neurons(Broicher et al., 2008; Coulon et al., 2010). Because the levelof acetylcholine is elevated in the hippocampus during REM
sleep (Teles-Grilo Ruivo et al., 2017), it may be plausible toassume a similar mechanism works in the hippocampus toswitch the hippocampal neurons between the oscillating modes.
Notably, carbachol-induced depolarization of hippocampal CA1
neurons is eliminated from Chrm1/3 DKO mice while thedepolarization remained in single KO mice, suggesting that
Chrm1 and Chrm3 receptors are each redundantly capable ofdepolarizing hippocampus neurons (Dasari and Gulledge, 2011).
However, further studies are necessary to dissect the functions of
Chrm1 and Chrm3 in the MS-DBB–hippocampus system.

abolish REM sleep and the associated enrichment of EEG theta
oscillation during sleep, leaving the theta oscillation largely
unaffected during wakefulness (Niwa et al., 2018; Figure 4). This
work demonstrated the necessity of acetylcholine for REM sleep
and the EEG theta oscillation during sleep, which is in line withthe previous pharmacological studies that demonstrated that themuscarinic blockers, such as atropine or scopolamine, diminish
the EEG theta oscillation in anesthetized animals (Kim and Jeong,
1999; Buzsaki, 2002).
In contrast to the drastic sleep phenotypes observed in
the DKO mice of muscarinic receptors, the comprehensive
KO study of nicotinic acetylcholine receptors did not show
significant sleep phenotype (Niwa et al., 2018). Nicotinic
acetylcholine receptors are ionotropic, and their response isfast compared to the metabotropic muscarinic acetylcholine
receptors. In consistent with the slow property of muscarinic
acetylcholine receptors relevant to sleep regulation, the majority(80–90%) of cholinergic axon terminals in hippocampus are
diffusely organized (Descarries et al., 1997), and do not associatewith distinct postsynaptic sites suggesting that the cholinergic
signaling in the hippocampus is primarily mediated by volumetransmission as an ambient cholinergic tone instead of synaptictransmission (Teles-Grilo Ruivo and Mellor, 2013). Indeed, theelevated level of acetylcholine in the hippocampus is foundassociated with REM sleep in vivo (Teles-Grilo Ruivo et al.,2017). Together, these observations imply that acetylcholine
contributes to the EEG theta oscillation of hippocampal
neurons mainly through the slow regulation and modulate theintrinsic neuronal properties to generate the bursting activity attheta frequency band.

The Possible Molecular Mechanism of
the Theta Oscillation With Chrm1 and
Chrm3
The important insight given by the finding of the essential role
for Chrm1 and Chrm3 in REM sleep is that, in contrast to theconventional neural-circuit view that the GABAergic input from
MS-DBB neurons is primarily driving the EEG theta oscillationand the cholinergic regulation plays subsidiary role (Brown
et al., 2012; Teles-Grilo Ruivo and Mellor, 2013), the cholinergic
regulation in the MS-DBB–hippocampus system is comparably
critical for the EEG theta oscillation at molecular and cellularlevel. The conventional view was based on the observations
that the combined lesion of cholinergic and GABAergic
neurons in MS-DBB almost eliminated the hippocampal theta
oscillation (Yoder and Pang, 2005), theta activity survives in
the hippocampus following the selective lesion of cholinergic
neurons in MS-DBB (Lee et al., 1994), the selective lesionof GABAergic neurons and potentially other non-cholinergic
neurons reduces the hippocampal theta oscillation more thancholinergic lesion (Yoder and Pang, 2005), and the large portionof the GABAergic neurons exhibits burst firing activity at thetheta frequency while the cholinergic neurons have a low firing
rate not related to the theta oscillation in MS-DBB (Simon
et al., 2006). However, the almost complete absence of REM
sleep in the Chrm1 and Chrm3 DKO mice re-emphasized theFrontiers in Neuroscience | www.frontiersin.org

The Distinct Roles of Chrm1 and Chrm3
for REM Sleep
Comprehensive investigation on the acetylcholine receptors
found that the combinatorial function of Chrm1 and Chrm3 isessential for REM sleep and associated EEG theta oscillation
during sleep, whereas the function of each gene has yet to beinvestigated. Especially, single KO of either gene showed different
phenotypic responses. The Chrm1 KO mice had a reduced REM
sleep duration, but NREM sleep duration was only moderately
reduced. On the other hand, Chrm3 KO mice had a reduced
NREM sleep duration, but REM sleep duration was similar tothat of WT mice (Niwa et al., 2018). These observations raised aquestion of what molecular mechanisms account for the observed
difference. Muscarinic acetylcholine receptors consist of fiveisoforms and coupled with Gq proteins (M1, M3, and M5) or
Gi proteins (M2 and M4). Differences in the preference of G
protein coupling come from the difference in an amino acid

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FIGURE 4 | Power of EEG theta and delta oscillations in Chrm1 and Chrm3 DKO mice. (A) Pie charts presenting the proportions of sleep stages detected inwild-type mice (top) and double knockout (DKO) mice (bottom). REM sleep in wild-type mice was 72 min a day while almost undetected in DKO mice.
(B) Hypnogram of a wild-type mouse. Delta power (normalized mV2 ), the ratio of theta/delta power, and total power of EMG signal. (C) Hypnogram of a Chrm1 andChrm3 DKO mice. Orange for wakefulness, yellow for REM, and blue for NREM are shown. The enrichment of theta oscillation (increase in the value of θ/δ), that is
associated with REM sleep in (A), was hardly detected during sleep in the DKO mice (C). The plots were reproduced from the data published in the literature (Niwaet al., 2018).

pathways from the identified receptors: Chrm1 and Chrm3 may
reveal the mechanism of REM sleep and their physiological roles.
Especially, several functions related to the long-term potentiation(LTP) have been shown to be mediated particularly by Chrm1. For
example, Chrm1-dependent inhibition of SK channels enhances
NMDA receptor function to facilitate the induction of LTP(Buchanan et al., 2010), and the Chrm1-dependent inhibitionof voltage-activated Kv7 potassium channels facilitate LTP(Petrovic et al., 2012; Teles-Grilo Ruivo and Mellor, 2013), while
involvement of Chrm3 in this context is unknown.

sequence in the third intracellular loop between the M1, M3,
and M5 sequences compared to the M2 and M4 sequences (Wesset al., 1997). However, several studies have shown that receptors
coupling predominantly to one G protein family can also couple
with other G proteins, though less efficiently. For example,
Chrm3 receptor associates to both Gq and Gi in rat parotid
glands (Dai et al., 1991), Chrm1 receptor also has Gs activity
when ectopically expressed in Chinese hamster ovary (CHO) cells(Burford and Nahorski, 1996), whereas both Chrm1 and Chrm3
predominantly link to Gq . In addition, a short variable sequenceof the amphipathic helix (H8), typically three turns long andwith palmitoylation sites at its C terminus, is present in several
GPCRs including Chrm3 (Qin et al., 2011; Venkatakrishnan et al.,2013). The H8 forms the preassembly with Gq proteins, which
may contribute to the possible difference in the rate of receptor
activation, compared with Chrm1 (Qin et al., 2011). Anotherpossibility is the different spatial distribution of Chrm1 andChrm3 in the brain (Levey et al., 1995). Indeed, about 60% of
the total muscarinic acetylcholine receptors of the hippocampus
is Chrm1 receptors, whereas Chrm3 receptor is up to 10%(Dasari and Gulledge, 2011). Future investigation of downstream

Frontiers in Neuroscience | www.frontiersin.org

PHOSPHORYLATION HYPOTHESIS FOR
THE HOMEOSTATIC REGULATION OFSLEEPThe amount of sleep is regulated to be in a physiologically feasible
range. This regulation is called the homeostatic regulation of
sleep. The homeostatic regulation can comprise two distinct
hypothetical processes: “process C” and “process S” (Borbely,1982). Process C is the circadian component that regulates

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Nonetheless, REM sleep is also under the homeostatic regulation;that is, the loss of REM sleep is compensated for by the increasein the duration of REM sleep (Franken, 2002). Selective REM
sleep deprivation induces a rebound increase in subsequent
REM sleep. Because the selective REM sleep deprivation does
not largely affect the amount of NREM sleep, the homeostatic
regulation of REM sleep seems to be likely independent to thatof NREM sleep (McCarthy et al., 2016). However, prolonged
REM sleep increases the delta power in the subsequent NREM
sleep indicating there is profound interaction between REM and
NREM sleep homeostatic regulatory mechanisms (Hayashi et al.,2015). Although the molecular machinery of the REM sleep
homeostasis has yet to be investigated, it is plausible to assume
mechanisms similar to the NREM sleep homeostasis, such as
phosphorylation process, also work in REM sleep homeostasis.
Notably, while most antidepressants suppress REM sleep, thephysiologically induced REM sleep deficits are compensated forregardless of the subsequent pharmacological suppression of
REM sleep (McCarthy et al., 2016). This observation implies
that the homeostatic regulation of REM sleep consists ofmolecular and cellular mechanisms distinct from the neuralcircuits mediated by neurotransmitters, which are targeted by theantidepressants, such as serotonin and acetylcholine pathways.
This insight is in line with the hypothetical involvement of
the phosphorylation process in the homeostatic regulation,suggesting that the homeostasis is implemented at the cellularlevel rather than at the neural circuits level.

the propensity of sleep with the rhythm of 24 h. The process
S is a sleep-dependent process that monitors accumulated
amount of sleep and compensates the detected loss or excess
of sleep. The mechanism of the homeostasis is under vigorous
investigation at present.

Homeostatic Regulation of NREM Sleep
The EEG power in the delta frequency band reflects the pressure
for the NREM-sleep resulting from the loss of NREM sleep. The
NREM-sleep need increases during wakefulness period, while
it decreases during the sleep period. The changes of NREMsleep need are well described by exponential function (Borbely,1982). An apparent but unresolved question is by what molecularmechanism NREM-sleep need is represented. One importantcriterion to be satisfied is that the molecular mechanism must
work in the time scale of minutes to hours, which is slower inorder of magnitude compared to the time scale of neural action
potentials. Candidate components of the mechanism include ion
concentration, gene expression, post-translational modification,and production/degradation of ion channels or pumps.
Interestingly, in the context of Process C, the phosphorylation
plays an important role in keeping the circadian period about 24 h(Tomita et al., 2005; Isojima et al., 2009; Shinohara et al., 2017).
Phosphorylation was indicated to play a role also in Process S, as
the loss of calcium/CaMKII gene resulted in significant reductionof sleep (Tatsuki et al., 2016). This finding is further supportedby the observation that the wakefulness induced phosphorylationin the extracellular signal-regulated kinase (ERK) proteins, which
are upstream of a group of genes expressed in activity-dependent
manner and involved in sleep regulation (Mikhail et al., 2017).
Moreover, the following phosphoproteomics studies revealed
a number of genes in the intracellular signaling pathways
change their states of phosphorylation along with the sleep/wakecycles (Diering et al., 2017; Wang et al., 2018; Bruning et al.,2019). Because protein functions can be modulated by sitespecific phosphorylation or by cumulative phosphorylation ofmultiple sites, all of this evidence strongly suggests that thephosphorylation process is a component of the homeostatic
regulation of sleep.
Because the Ca2+ -dependent hyperpolarization pathway plays
an important role in switching UP and DOWN states of neurons(Tatsuki et al., 2016, 2017), and the persistent UP state is
associated with wakefulness, Ca2+ -dependent phosphorylation isa promising regulatory component for the homeostasis in sleep
and wake cycle (Ode et al., 2017; Shi and Ueda, 2018). A candidate
gene family to be involved in Ca2+ -dependent phosphorylation
is calcium/CaMKII. Indeed, the KO mice of the CaMKII family
revealed that either KO of CaMKIIα and CaMKIIβ results insignificant reduction of sleep duration (Tatsuki et al., 2016),
implying that CaMKII may be link between the actions of Ca2+in the time domain of second to the activity of the kinase in thetime domain of hours.

FUTURE PERSPECTIVE
The pioneering studies focused on the electrophysiologicalactivity of brains and identified characteristic EEG signatures
such as SWO, delta, and theta oscillation to define sleep
stages. The investigations revealed the underlying cellular levelmachinery to generate bursting activity for explaining the
population level EEG signals. Based on those findings, inthe last couple of decades, the focused study on the neuralcircuits of sleep regulation has been successful in identifying
brain regions and detailed interactions among the regions(Scammell et al., 2017). However, the conventional way toinvestigate the electrophysiological properties of neurons has
been mostly pharmacological approaches, hence an identified
molecular component in the machinery is a cluster of molecules
responsive to the applied drug. This restriction has hindered
the identification of specific genes involved in sleep regulation.
The recent advent of so-called next-generation genetics suchas CRISPR and ES-mouse methods has been easing the longstanding restriction by significantly reducing the time and cost
to produce KO or knockin mice of specifically targeted genes(Sunagawa et al., 2016; Ukai et al., 2017). Using these methods,
researchers can generate a variety of KO mice covering thecluster of genes involved in a sub-system of sleep regulation. The
application of the methods revealed that the genes involved in
the Ca2+ -dependent hyperpolarization pathway are importantin sleep regulation (Sunagawa et al., 2016; Tatsuki et al.,2016; Yoshida et al., 2018). Besides identifying genes involved

Homeostatic Regulation of REM Sleep
In contrast to the EEG delta power established as an indicatorof NREM-sleep need, any single component of EEG spectral
power has not been established to represent REM-sleep need.

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in NREM sleep duration, the next-generation genetics also
identified genes essential for REM sleep: muscarinic acetylcholine
receptors Chrm1 and Chrm3 (Niwa et al., 2018).
It is also notable that the reverse genetics approachdemonstrated the role of the major calcium-dependent protein
kinase, CaMKII in sleep regulation (Tatsuki et al., 2016),
suggesting that the phosphorylation is involved in the sleep
regulation. In addition to the reverse-genetic approach, the effort
of forward-genetics also demonstrated that the mutation of Sik3
protein kinase gene causes a profound increase in sleep duration
by a gain-of-function mutation (Funato et al., 2016). The
phosphorylation process may occur in the time scale of hours,
and be modulated by cumulative phosphorylation of multiple
sites, e.g., casein kinase I (CKI) in the circadian regulation(Isojima et al., 2009; Shinohara et al., 2017). We note that thegenes involved both in phosphorylation and sleep regulation are
attractive candidates for the future studies on the homeostatic
regulation of sleep (Ode et al., 2017; Tatsuki et al., 2017; Shi andUeda, 2018).
The finding of the almost abolished REM sleep in theChrm1 and Chrm3 DKO mice may provide a useful tool toclarify the function of REM sleep in learning and memory(Niwa et al., 2018). The dominance of theta oscillation in EEG
signal during REM sleep indicates the synchronized activityof hippocampal neurons. The synchronization is believed tobe critical for transferring information between neocortex andhippocampus and the sleep-related neural plasticity (Sirota et al.,2008; Grosmark et al., 2012). The optogenetic silencing of
GABAergic neurons during REM sleep in the MS-DBB hindered
the mice from properly consolidating what they learned prior
to the sleep (Boyce et al., 2016), indicating the important roles
for the theta oscillation in REM sleep and associated learningand memory. This function of theta oscillation is coinciding
with that of delta or SWO in the thalamocortical system.
SWO promotes learning and memory consolidation (Marshallet al., 2006; Miyamoto et al., 2016). On the other hand, apharmacogenetic study revealed that reduction or induction of
REM sleep attenuates or enhances SWO, respectively, in thesubsequent NREM sleep (Hayashi et al., 2015). Thus, REM sleep
might indirectly regulate memory formation in the neocortex
through NREM sleep (Miyazaki et al., 2017).
Aside learning and memory in the hippocampus, otherphysiological functions of REM sleep remain obscure.
Interestingly, the duration of REM sleep increases in somedepression and the most antidepressants inhibit REM sleep

in animals and humans (McCarthy et al., 2016). This strong
correlation between REM sleep and psychiatric disorders
including post-traumatic stress disorder (PTSD) implies that
controlling REM sleep may help PTSD patients to alleviate thesymptoms. The further elucidation of the molecular mechanismof theta oscillation will provide significant insights on how tocontrol the amount of REM sleep both in mice and humans andmay facilitate, for example, to refine antidepressants and to reveal
the physiological roles of REM sleep in its closely related higher
cognitive functions such as dreaming or consciousness.

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AUTHOR CONTRIBUTIONS
All authors listed have made a substantial, direct and intellectual
contribution to the work, and approved it for publication.

FUNDING
This work was supported by grants from the Japan Agency
for Medical Research and Development – Core Research
for Evolutional Science and Technology (AMED-CREST)[AMED/Ministry of Education Culture Sports Science andTechnology (MEXT) Grant JP17gm0610006 to HU], Brain
Mapping by Integrated Neurotechnologies for Disease Studies(Brain/MINDS) (AMED/MEXT Grant JP17DM0207049 to HU),
Basic Science and Platform Technology Program for Innovative
Biological Medicine (AMED/MEXT Grant JP17AM0301025 to
HU), World Premier International Research Center Initiative(MEXT; HU), a Grant-in-Aid for Scientific Research (S) (JSPS
KAKENHI Grant Number 18H05270, HU), HFSP (Human
Frontier Science Program) Research Grant Program (HFSP
RGP0019/2018), and an intramural Grant-in-Aid from the
RIKEN Center for Biosystems Dynamics Research (to HU).

ACKNOWLEDGMENTS
We thank all the laboratory members at the RIKEN Center
for Biosystems Dynamics Research and the University ofTokyo, particularly Dr. S. Shi and Dr. H. Ono, for kind help
in preparing figures and discussions. We also thank Kylius
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