Pierre-Hervé Luppi
email: luppi@sommeil.univ-lyon1.fr

Amarine Chancel

Justin Malcey

Sébastien Cabrera

Patrice Fort

Renato M Maciel

M Vitello

P.-H Luppi

P.-H Luppi

Which structure generates paradoxical (REM) sleep: The brainstem, the hypothalamus, the amygdala or the cortex?

Keywords:

Paradoxical or Rapid eye movement (REM) sleep (PS) is a state characterized by REMs, EEG activation and muscle atonia. In this review, we discuss the contribution of brainstem, hypothalamic, amygdalar and cortical structures in PS genesis. We propose that muscle atonia during PS is due to activation of glutamatergic neurons localized in the pontine sublaterodorsal tegmental nucleus (SLD) projecting to glycinergic/GABAergic premotoneurons localized in the ventro-medial medulla (vmM). The SLD PS-on neurons are inactivated during wakefulness and slow-wave sleep by PS-off GABAergic neurons localized in the ventrolateral periaqueductal gray (vPAG) and the adjacent deep mesencephalic reticular nucleus. Melanin concentrating hormone (MCH) and GABAergic PS-on neurons localized in the posterior hypothalamus would inhibit these PS-off neurons to initiate the state. Finally, the activation of a few limbic cortical structures during PS by the claustrum and the supramammillary nucleus as well as that of the basolateral amygdala would also contribute to PS expression. Accumulating evidence indicates that the activation of these limbic structures plays a role in memory consolidation and would communicate to the PS-generating structures the need for PS to process memory. In summary, PS generation is controlled by structures distributed from the cortex to the medullary level of the brain.

Introduction

REM (Paradoxical) sleep (PS) characterized by EEG activation and rapid eye movements (REMs) was discovered in 1953 by Aserinsky and Kleitman in humans. It was shown to correlate with dream activity [START_REF] Aserinsky | Regularly occurring periods of eye motility and concomitant phenomena during sleep[END_REF][START_REF] Dement | The relation of eye movements during sleep to dream activity: an objective method for the study of dreaming[END_REF]. In 1959, Jouvet and Michel discovered in cats that PS is also characterized by a disappearance of muscle tone, paradoxically associated with cortical activation and REMs [START_REF] Jouvet | Corrélations électromyographiques du sommeil chez le chat décortiqué et mésencéphalique chronique[END_REF][START_REF] Jouvet | Sur un stade d'activité électrique cérébrale rapide au cours du sommeil physiologique[END_REF]. Soon after, it was shown that a state characterized by muscle atonia and REMs persists following decortication, cerebellar ablation or brainstem transections rostral to the pons and in the "pontine cat", a preparation in which structures rostral to the pons have been removed [START_REF] Jouvet | Recherches sur les structures nerveuses et les mécanismes responsables des différentes phases du sommeil physiologique[END_REF]. These results indicate that the brainstem is necessary and sufficient to generate PS. However, in the following sixty years, it has been proposed that neuronal systems upstream to the pons might modulate PS expression in particular the posterior hypothalamus or more recently the amygdala and the cortex. The goal of the present review is to examine each of these possibilities.

Brainstem glutamatergic and GABAergic neurons trigger PS

Early transection studies in cats indicated that the brainstem is necessary and sufficient to trigger and maintain the state of PS. Electrolytic and chemical lesions then demonstrated that the dorsal part of pontis oralis (PnO) and caudalis (PnC) nuclei contain the neurons responsible for PS onset [START_REF] Jouvet | Recherches sur les structures nerveuses et les mécanismes responsables des différentes phases du sommeil physiologique[END_REF]. It was thought for decades that these neurons are cholinergic since injection of carbachol (a cholinergic agonist) in this cat pontine region induced PS with a short latency [START_REF] Mitler | Cataplectic-like behavior in cats after micro-injections of carbachol in pontine reticular formation[END_REF][START_REF] Amatruda | Sleep cycle control and cholinergic mechanisms: differential effects of carbachol injections at pontine brain stem sites[END_REF]. However, we did not confirm such effect in rats [START_REF] Boissard | The rat ponto-medullary network responsible for paradoxical sleep onset and maintenance: a combined microinjection and functional neuroanatomical study[END_REF] and it was shown that cholinergic neurons of the laterodorsal tegmental nucleus and the pedunculopontine nucleus are active during both waking (W) and PS [START_REF] Boucetta | Discharge profiles across the sleep-waking cycle of identified cholinergic, GABAergic, and glutamatergic neurons in the pontomesencephalic tegmentum of the rat[END_REF]. Further, in rats, most of the neurons activated in this pontine region (as cFoslabeled) after 2,5 h of PS hypersomnia induced by 72 h of PS deprivation using the flowerpot method are localized in the sublaterodorsal tegmental nucleus (SLD) and express the vesicular glutamate transporter 2 (vGlut2) indicating they are glutamatergic in nature [START_REF] Clement | Evidence that neurons of the sublaterodorsal tegmental nucleus triggering paradoxical (REM) sleep are glutamatergic[END_REF]. Fur-ther, a large number of the glutamatergic neurons recorded in the SLD are specifically active during PS [START_REF] Boucetta | Discharge profiles across the sleep-waking cycle of identified cholinergic, GABAergic, and glutamatergic neurons in the pontomesencephalic tegmentum of the rat[END_REF] although other pontine glutamatergic neurons are W and PS-active indicating the heterogeneity of the region and its potential role in W. It is also unlikely that the GABAergic neurons of the SLD are involved in controlling PS since they do not specifically express cFos after PS deprivation or rebound [START_REF] Sapin | Localization of the brainstem GABAergic neurons controlling paradoxical (REM) sleep[END_REF]. Further, we showed that inactivation of glutamatergic transmission in SLD neurons using genetic method induced a 30 % decrease of PS quantities and removal of muscle atonia with abnormal and violent motor activity during the state like in REM sleep behavioral disorder (RBD) [START_REF] Garcia | Genetic inactivation of glutamate neurons in the rat sublaterodorsal tegmental nucleus recapitulates REM sleep behaviour disorder[END_REF]. Conversely, chemogenetic activation of SLD glutamatergic neurons induced muscle atonia whereas their inactivation induced RBD [START_REF] Torontali | The sublaterodorsal tegmental nucleus functions to couple brain state and motor activity during REM sleep and wakefulness[END_REF].

Several results further indicate that SLD PS-on glutamatergic neurons generate muscle atonia via descending projections to medullary GABAergic/glycinergic neurons [START_REF] Boissard | The rat ponto-medullary network responsible for paradoxical sleep onset and maintenance: a combined microinjection and functional neuroanatomical study[END_REF][START_REF] Garcia | Genetic inactivation of glutamate neurons in the rat sublaterodorsal tegmental nucleus recapitulates REM sleep behaviour disorder[END_REF][START_REF] Holstege | A glycinergic projection from the ventromedial lower brainstem to spinal motoneurons. An ultrastructural double labeling study in rat[END_REF][START_REF] Garcia | Ventromedial medulla inhibitory neuron inactivation induces REM sleep without atonia and REM sleep behavior disorder[END_REF](Fig. 1). Indeed, it has been shown that the SLD sends direct efferent projections to glycinergic neurons in the ventromedial medulla (vmM that includes the ventral (GiV) and alpha gigantocellular nuclei (Gia) and the nucleus raphe magnus (RMg) [START_REF] Garcia | Genetic inactivation of glutamate neurons in the rat sublaterodorsal tegmental nucleus recapitulates REM sleep behaviour disorder[END_REF]. In addition, glycinergic vmM neurons express cFos after induction of PS by bicuculline (a GABAa antagonist) injection in the SLD [START_REF] Boissard | The rat ponto-medullary network responsible for paradoxical sleep onset and maintenance: a combined microinjection and functional neuroanatomical study[END_REF] or PS hypersomnia [START_REF] Garcia | Ventromedial medulla inhibitory neuron inactivation induces REM sleep without atonia and REM sleep behavior disorder[END_REF]. Further, glycinergic neurons of vmM monosynaptically project to lumbar spinal motoneurons [START_REF] Holstege | A glycinergic projection from the ventromedial lower brainstem to spinal motoneurons. An ultrastructural double labeling study in rat[END_REF][START_REF] Garcia | Ventromedial medulla inhibitory neuron inactivation induces REM sleep without atonia and REM sleep behavior disorder[END_REF]. Finally, glycinergic interneurons in the spinal cord do not express cFos [START_REF] Garcia | Ventromedial medulla inhibitory neuron inactivation induces REM sleep without atonia and REM sleep behavior disorder[END_REF]. These results suggest that vmM glycinergic neurons hyperpolarize motoneurons during PS. It is likely that these neurons are also GABAergic since a large majority of the cFos-labeled vmM neurons after PS hypersomnia express mRNAs for the synthesizing enzyme for GABA [START_REF] Sapin | Localization of the brainstem GABAergic neurons controlling paradoxical (REM) sleep[END_REF]. Further, it has been shown that combined microdialysis of bicuculline, strychnine and phaclophen (a GABAb antagonist) in the trigeminal motor nucleus restored muscle tone in masseter muscles during PS [START_REF] Brooks | Role for GABAB-mediated inhibition in the control of somatic motoneurons during REM sleep[END_REF][START_REF] Brooks | Identification of the transmitter and receptor mechanisms responsible for REM sleep paralysis[END_REF]. Finally, genetic inactivation of glycinergic and GABAergic vmM neurons induced a state of PS closed to RBD [START_REF] Garcia | Ventromedial medulla inhibitory neuron inactivation induces REM sleep without atonia and REM sleep behavior disorder[END_REF][START_REF] Uchida | A discrete glycinergic neuronal population in the ventromedial medulla that induces muscle atonia during REM sleep and cataplexy in mice[END_REF]. Altogether, these results indicate that the pre-motoneurons responsible for muscle atonia of PS are localized in the vmM and co-release GABA and glycine.

Besides, several results indicate that two other subsets of medullary PS-active GABAergic neurons located laterally to the vmM neurons in the lateral paragigantocellular nucleus (LPGi) and or dorsally to them in the dorsal paragigantocellular reticular nucleus (DPGi) are ascending and play a crucial role in the generation of PS by means of their inhibition of wake-active serotonergic and noradrenergic neurons [START_REF] Gervasoni | Role and origin of the GABAergic innervation of dorsal raphe serotonergic neurons[END_REF]. Indeed, the application of bicuculline during slow-wave sleep (SWS) or PS on dorsal raphe nucleus (DRN) serotonergic and noradrenergic locus coeruleus (LC) neurons restores a tonic firing [START_REF] Gervasoni | Role and origin of the GABAergic innervation of dorsal raphe serotonergic neurons[END_REF][START_REF] Gervasoni | Electrophysiological evidence that noradrenergic neurons of the rat locus coeruleus are tonically inhibited by GABA during sleep[END_REF]. By combining retrograde tracing with cholera toxin B subunit (CTb) and GAD immunohistochemistry in rats, we found that the LC and DRN receive GABA and glycinergic inputs from the ventrolateral periaqueductal gray (vlPAG) and the LPGi and DPGi [START_REF] Gervasoni | Role and origin of the GABAergic innervation of dorsal raphe serotonergic neurons[END_REF][START_REF] Rampon | Origins of the glycinergic inputs to the rat locus coeruleus and dorsal raphe nuclei: a study combining retrograde tracing with glycine immunohistochemistry[END_REF]. We then demonstrated by using cFos that these nuclei contain numerous LC-projecting neurons selectively activated during PS rebound following PS deprivation [START_REF] Verret | Localization of the neurons active during paradoxical (REM) sleep and projecting to the locus coeruleus noradrenergic neurons in the rat[END_REF]. Further, the LPGi/DPGi contain numerous PS-on neurons that are silent during waking and SWS and fire tonically during PS [START_REF] Goutagny | Role of the dorsal paragigantocellular reticular nucleus in paradoxical (rapid eye movement) sleep generation: a combined electrophysiological and anatomical study in the rat[END_REF][START_REF] Sirieix | Role of the lateral paragigantocellular nucleus in the network of paradoxical (REM) sleep: an electrophysiological and anatomical study in the rat[END_REF][START_REF] Weber | Control of REM sleep by ventral medulla GABAergic neurons[END_REF][START_REF] Weber | Regulation of REM and non-REM sleep by periaqueductal GABAergic neurons[END_REF][START_REF] Stucynski | Regulation of REM sleep by inhibitory neurons in the dorsomedial medulla[END_REF]. In addition, inactivation of the DPGi with muscimol (a GABAa agonist) induced wakefulness and cFos expression in LC, A1, A2 and A5 noradrenergic neurons suggesting that GABAergic neurons of the DPGi inhibit all of these noradrenergic groups during PS. Interestingly, a subpopulation of Calbindin-D28K-glutamatergic neurons located in the DPGi are also active during PS, project to the three contralateral eyemuscle nuclei and increase their firing prior to the onset of REMs during PS. Optogenetic activation of these neurons triggers eye movements selectively during PS, while their genetic ablation or optogenetic silencing suppresses them [START_REF] Herrera | Neurons in the Nucleus papilio contribute to the control of eye movements during REM sleep[END_REF]. None of these perturbations led to a change in the duration of PS episodes. In contrast, optogenetic and chemogenetic activation and inactivation of DPGi corticotropin releasing factor (CRH) neurons coexpressing glutamate increased and decreased PS quantities respectively [START_REF] Schott | A medullary hub for controlling REM sleep and pontine waves[END_REF]. Calcium imaging of these neurons showed that they are specifically active during PS, with a phasic activation just before the occurrence of P-waves. The authors proposed that they generate P-waves by means of their projection to the P-wave generator localized in the SLD. It is very likely that the DPGi CRH and calbindin neurons belong to the same population since they are glutamatergic. Further, their activity is linked with REMs and P-waves i.e. phasic REMs. Altogether, these results indicate that the DGPi contains both inhibitory GABAergic and excitatory glutamatergic PS-active neurons. In addition, it has been shown that optogenetic stimulation during SWS of GABAergic LPGi neurons or of their ascending fibers located in the vl-PAG/dDPMe induced PS [START_REF] Weber | Control of REM sleep by ventral medulla GABAergic neurons[END_REF]. However, combining CTb injection into The onset of PS would be due to the activation by intrinsic "clock-like" mechanisms of PS-on MCH+/Glutamatergic and/or MCH-/GABAergic neurons located in the posterior hypothalamus. A subpopulation of the zona incerta GABAergic neurons co-expresses Lhx6. All or a subpopulation of the PH neurons could also be responsible of the rebound of PS occurring after its deprivation. The PH PS-on neurons would inactivate directly (GABA neurons) or indirectly (MCH neuron) the PS-off vl-PAG/dDpMe GABAergic neurons and the histaminergic and orexinergic neurons. The inhibition of the PS-off vlPAG/dDpMe GABAergic neurons would induce the desinhibition of the PS-on glutamatergic SLD neurons. These neurons would directly excite glycinergic/GABAergic premotor neurons in the vmM which in turns hyperpolarize spinal and cranial motoneurons. The SLD neurons also project to and excite DPGi and LPGi ascending GABAergic neurons responsible for inhibiting the dorsal raphe serotonergic neurons and the locus coeruleus noradrenergic neurons. The SLD neurons also excite the glutamatergic neurons of the DPGi which project to oculomotor nuclei and induce REMs. The role of the PS-on glutamatergic and GABAergic neurons of the lateral preoptic area still needs to be determined. the vlPAG/dDPMe with cFos staining after PS hypersomnia, we did not find double-labeled cells in the LPGi [START_REF] Clement | The lateral hypothalamic area controls paradoxical (REM) sleep by means of descending projections to brainstem GABAergic neurons[END_REF] suggesting that the effect obtained is rather due to stimulation of axons on their way to the DRN or LC. In summary, a large body of data indicates that GABA/glycinergic PS-on neurons localized in the vlPAG and the LPGi/DPGi hyperpolarize the serotonergic and noradrenergic neurons during PS. Another set of DPGi neurons is glutamatergic and is involved in phasic REM sleep and might also play a role in controlling the state itself (Fig. 1). What are the mechanisms triggering the activation of the LPGi and DPGi neurons? We previously showed that after injecting CTb in the LPGi, cFos/CTb labeled neurons were in their vast majority localized in the SLD [START_REF] Goutagny | Role of the dorsal paragigantocellular reticular nucleus in paradoxical (rapid eye movement) sleep generation: a combined electrophysiological and anatomical study in the rat[END_REF][START_REF] Sirieix | Role of the lateral paragigantocellular nucleus in the network of paradoxical (REM) sleep: an electrophysiological and anatomical study in the rat[END_REF]. Anterogradely labeled fibers and cFos-labeled neurons were localized in the DPGi and LPGi after injection of the anterograde tracer Phaseolus leucoagglutinin (PHA-L) in the SLD and induction of PS hypersomnia [START_REF] Boissard | The rat ponto-medullary network responsible for paradoxical sleep onset and maintenance: a combined microinjection and functional neuroanatomical study[END_REF]. In summary, it is likely that the activation of the LPGi and DPGi PS-on ascending neurons is due to an excitatory projection from the SLD.

GABAergic PS-off neurons in the vlPAG gate the onset of PS

A long-lasting PS-like episode can be pharmacologically induced with a short latency in head-restrained unanesthetized rats by iontophoretic applications of bicuculline or gabazine, two GABAa receptor antagonists, specifically into the SLD [START_REF] Boissard | The rat ponto-medullary network responsible for paradoxical sleep onset and maintenance: a combined microinjection and functional neuroanatomical study[END_REF]. Neurons at the origin of the GABAergic innervation of SLD are localized in the vlPAG and the dorsal deep mesencephalic reticular nuclei (dDpMe) [START_REF] Boissard | Localization of the GABAergic and non-GABAergic neurons projecting to the sublaterodorsal nucleus and potentially gating paradoxical sleep onset[END_REF]. Further, these two structures contain a large number of cFos-positive neurons expressing GAD67mRNA after 72 h of PS deprivation [START_REF] Sapin | Localization of the brainstem GABAergic neurons controlling paradoxical (REM) sleep[END_REF]. Compared to the PS-on neurons also localized in the vlPAG, the PS-off neurons seem to be located more ventrally at its ventral border adjacent to the dDpMe [START_REF] Sapin | Localization of the brainstem GABAergic neurons controlling paradoxical (REM) sleep[END_REF]. Injection of muscimol in the vlPAG and/or the dDpMe or their neurochemical lesion induce a strong increase in PS quantities [START_REF] Sapin | Localization of the brainstem GABAergic neurons controlling paradoxical (REM) sleep[END_REF][START_REF] Sastre | Importance of the ventrolateral region of the periaqueductal gray and adjacent tegmentum in the control of paradoxical sleep as studied by muscimol microinjections in the cat[END_REF][START_REF] Lu | A putative flip-flop switch for control of REM sleep[END_REF]. Further, optogenetic or chemogenetic stimulation of PS-off GABAergic neurons within vlPAG/dDpMe almost completely suppresses PS by shortening the duration of PS episodes [START_REF] Weber | Control of REM sleep by ventral medulla GABAergic neurons[END_REF][START_REF] Weber | Regulation of REM and non-REM sleep by periaqueductal GABAergic neurons[END_REF][START_REF] Hayashi | Cells of a common developmental origin regulate REM/non-REM sleep and wakefulness in mice[END_REF]. Conversely, their pharmacogenetic inhibition increases PS, mainly by increasing the number of PS episodes [START_REF] Hayashi | Cells of a common developmental origin regulate REM/non-REM sleep and wakefulness in mice[END_REF]. Unit recording and calcium imaging revealed that most vlPAG GABAergic neurons start to be active at the end of PS episodes and decrease gradually their activity until the next PS episode. To our knowledge, such progressive decrease of activity has never been reported for PS-off neurons like the monoaminergic ones.

These results suggest that vlPAG GABAergic neurons powerfully gate PS by tonically inhibiting PS-on glutamatergic neurons from the SLD and may contribute to the ultradian rhythm of PS and the SWS/PS alternation [START_REF] Weber | Regulation of REM and non-REM sleep by periaqueductal GABAergic neurons[END_REF]. It will be crucial in the future to identify the intrinsic mechanisms responsible for the slow decrease of activity of these neurons between subsequent PS episodes (Fig. 2).

The hypothalamus controls PS occurrence

In addition to the brainstem, a very large number of cFos-positive cells was also unexpectingly observed in the posterior hypothalamus (PH) including zona incerta (ZI), perifornical area and lateral hypothalamic area (LHA) after PS hypersomnia in rats [START_REF] Verret | A role of melanin-concentrating hormone producing neurons in the central regulation of paradoxical sleep[END_REF]. Around 75 % of these cFos-labeled cells express GAD67 mRNA and are likely GABAergic [START_REF] Sapin | A very large number of GABAergic neurons are activated in the tuberal hypothalamus during paradoxical (REM) sleep hypersomnia[END_REF]. Besides, one third of the cFos-GAD67 neurons co-express melanin concentrating hormone (MCH) [START_REF] Verret | A role of melanin-concentrating hormone producing neurons in the central regulation of paradoxical sleep[END_REF] and nesfatin-1 [START_REF] Jego | Tuberal hypothalamic neurons secreting the satiety molecule nesfatin-1 are critically involved in paradoxical (REM) sleep homeostasis[END_REF]. Unit recordings in head-restrained rats confirmed that MCH neurons fire mostly during PS [START_REF] Hassani | Melanin-concentrating hormone neurons discharge in a reciprocal manner to orexin neurons across the sleep-wake cycle[END_REF]. Recent calcium imaging data showed that these neurons are indeed less active during SWS and quiet waking compared to PS [START_REF] Blanco-Centurion | Dynamic network activation of hypothalamic MCH neurons in REM sleep and exploratory behavior[END_REF][START_REF] Kosse | Natural hypothalamic circuit dynamics underlying object memorization[END_REF][START_REF] Gonzalez | Awake dynamics and brain-wide direct inputs of hypothalamic MCH and orexin networks[END_REF]. The authors also reported that a large majority of MCH neurons are activated specifically during the exploration of new objects during active waking [START_REF] Blanco-Centurion | Dynamic network activation of hypothalamic MCH neurons in REM sleep and exploratory behavior[END_REF][START_REF] Kosse | Natural hypothalamic circuit dynamics underlying object memorization[END_REF][START_REF] Gonzalez | Awake dynamics and brain-wide direct inputs of hypothalamic MCH and orexin networks[END_REF]. Intracerebroventricular administration of MCH induced a strong dose-dependent increase in PS and, to a minor extent SWS quantities in rats [START_REF] Verret | A role of melanin-concentrating hormone producing neurons in the central regulation of paradoxical sleep[END_REF]. Such sleep increase was also obtained using chronic (24 h) optogenetic activation of MCH neurons [START_REF] Konadhode | Optogenetic stimulation of MCH neurons increases sleep[END_REF]. Their acute optogenetic activation at the onset of SWS epoch did not increase SWS duration but increased the probability of SWS-to-PS transitions. This effect was reproduced by using a chemogenetic approach to modulate the firing activity of MCH neurons [START_REF] Varin | Melanin-concentrating hormone-expressing neurons adjust slow-wave sleep dynamics to catalyze paradoxical (REM) sleep[END_REF]. When similar optogenetic stimulations were applied at PS onset, the duration of PS episodes was significantly prolonged [START_REF] Jego | Optogenetic identification of a rapid eye movement sleep modulatory circuit in the hypothalamus[END_REF]. It was also recently shown that the increase in PS quantities induced by a rise in ambient temperature was abolished when inactivating MCH neurons by optogenetic manipulation [START_REF] Komagata | Dynamic REM sleep modulation by ambient temperature and the critical role of the melanin-concentrating hormone system[END_REF]. Based on the finding that MCH neurons express GAD67 mRNAs, it was first thought that they are GABAergic and thus inhibitory. However, three independent molecular studies demonstrated that they do not express vGAT but vGlutT2, the vesicular glutamate transporter 2 [START_REF] Mickelsen | Single-cell transcriptomic analysis of the lateral hypothalamic area reveals molecularly distinct populations of inhibitory and excitatory neurons[END_REF][START_REF] Schneeberger | Functional analysis reveals differential effects of glutamate and MCH neuropeptide in MCH neurons[END_REF] and that they indeed release glutamate to excite neurons, as in lateral septum [START_REF] Chee | Melanin-concentrating hormone neurons release glutamate for feedforward inhibition of the lateral septum[END_REF].

Besides, it has been shown that a large population of MCH-negative vGAT-positive neurons in PH discharge maximally during PS [START_REF] Hassani | GABAergic neurons intermingled with orexin and MCH neurons in the lateral hypothalamus discharge maximally during sleep[END_REF].

Fig. 2. State of PS network during wakefulness.

The exit from PS would be due to the activation of the PS-off GABAergic neurons and the neuronal systems responsible for inducing wakefulness During PS, the PS-off GABAergic neurons located in the vlPAG and dDPMe would progressively increase their activity until they will reach a level high enough to induce the inhibition of the SLD glutamatergic neurons. The activity of the PS-off GABAergic neurons would be reinforced by monoaminergic and hypocretin/orexin inputs. Their activity will gradually decrease between two PS episodes releasing at the end the SLD from inhibition. The inhibition of the MCH and GABAergic neurons of the PH would be due to the activation of local Wake-active GABAergic neurons excited by the hypocretin/orexin neurons.

Since these neurons anticipate PS onset, they could play a role in triggering the state. GABAergic neurons co-expressing Lhx6 localized in the ZI could constitute a subpopulation of these MCH-/vGAT + PS-on neurons [START_REF] Liu | Lhx6-positive GABAreleasing neurons of the zona incerta promote sleep[END_REF][START_REF] Yamazaki | Targeted recombination in active populations as a new mouse genetic model to study sleepactive neuronal populations: demonstration that Lhx6+ neurons in the ventral zona incerta are activated during paradoxical sleep hypersomnia[END_REF]. Indeed, it has been shown that chemogenetic activation of Lhx6+/vGAT + neurons increases PS whereas their inhibition decreases it [START_REF] Liu | Lhx6-positive GABAreleasing neurons of the zona incerta promote sleep[END_REF]. Further, it has been shown that they are activated during PS hypersomnia [START_REF] Yamazaki | Targeted recombination in active populations as a new mouse genetic model to study sleepactive neuronal populations: demonstration that Lhx6+ neurons in the ventral zona incerta are activated during paradoxical sleep hypersomnia[END_REF]. Finally, it has been shown with calcium imaging that 45.5 % of the Lhx6 neurons were more active during PS than the two other states. Further, unilateral optogenetic stimulation of the ZI Lhx6 neurons significantly increased the percentage of PS [START_REF] Vidal-Ortiz | Unilateral optogenetic stimulation of Lhx6 neurons in the zona incerta increases REM sleep[END_REF].

To determine whether hypothalamic neurons indeed play a crucial role in PS, muscimol was bilaterally injected in the rat LH [START_REF] Clement | The lateral hypothalamic area controls paradoxical (REM) sleep by means of descending projections to brainstem GABAergic neurons[END_REF]. It induced a total inhibition of PS and an increase in SWS quantities. Further, the vlPAG/dDpMe region contained many cFos/GAD67+ and of cFos/CTb + neurons in animals with a CTb injection in the SLD [START_REF] Clement | The lateral hypothalamic area controls paradoxical (REM) sleep by means of descending projections to brainstem GABAergic neurons[END_REF]. These results indicate that the activation of PH neurons is a necessary step for PS to occur. They further suggest that MCH+/vGluT2+ and MCH-/vGAT + PS-on neurons control PS onset and maintenance by means of direct or indirect inhibitory projections to vlPAG/dDpMe PSoff GABAergic neurons. From these results, it can be proposed that these MCH+/vGluT2+ and MCH-/vGAT + neurons of the PH constitute a "master" generator of PS that controls a "slave" generator located in the brainstem. To fit with Jouvet's hypothesis (i.e. brainstem is necessary and sufficient to generate a state characterized by muscle atonia and REMs) [START_REF] Jouvet | Recherches sur les structures nerveuses et les mécanismes responsables des différentes phases du sommeil physiologique[END_REF], it can be proposed that few days after removal of the forebrain, the brainstem generator is able to induce by itself a state with muscle atonia and REMs. However, the brainstem generator is under control of the PH generator in intact animals (Fig. 1).

In addition to the descending pathway to the PS-off GABAergic neurons, the MCH neurons might also promote PS by means of their projections to the histaminergic, serotonergic, noradrenergic and hypocretin/ orexin PS-off neurons. Indeed, Jego et al. [START_REF] Jego | Optogenetic identification of a rapid eye movement sleep modulatory circuit in the hypothalamus[END_REF] showed that optogenetic activation of MCH axons in the tuberomammillary nucleus (TMN) inhibits histaminergic cells through activation of GABA A receptors. It was also shown that stimulation of MCH fibers in CA1 field of the hippocampus induced IPSP in local pyramidal cells [START_REF] Izawa | REM sleepactive MCH neurons are involved in forgetting hippocampus-dependent memories[END_REF]. These results in line with the initial hypothesis that MCH neurons are GABAergic are contradictory to recent results showing that they are glutamatergic and thus excitatory. One possibility is that they excite local inhibitory interneurons. Additional studies are required to confirm that MCH neurons are indeed glutamatergic and that they inhibit the vlPAG PS-off and other types of PS-off neurons by means of GABAergic PS-on interneurons.

The excitatory inputs at the origin of the activation of the MCH neurons at the entrance of PS remain to be identified. Many studies indicate that MCH neurons also play a key role in metabolism control and food intake [START_REF] Schneeberger | Functional analysis reveals differential effects of glutamate and MCH neuropeptide in MCH neurons[END_REF][START_REF] Qu | A role for melanin-concentrating hormone in the central regulation of feeding behaviour[END_REF]. Therefore, the activation of these neurons at the onset and during PS could be influenced by the metabolic state in addition to temperature increase as shown recently [START_REF] Komagata | Dynamic REM sleep modulation by ambient temperature and the critical role of the melanin-concentrating hormone system[END_REF]. It is possible that the preoptic area which projects to the LH and contains PS-on neurons is involved. Indeed, it has been shown that lesion of the lateral preoptic area (LPO) induced a decrease in PS [START_REF] Lu | Effect of lesions of the ventrolateral preoptic nucleus on NREM and REM sleep[END_REF]. Further, GABAergic and glutamatergic neurons of the LPO selectively raised calcium activity in PS and this calcium entry depends on NMDA receptors. In this study, they also deleted the GluN1 NMDA receptor subunit in the LPO and obtained a marked "insomnia" phenotype with high sleep-wake fragmentation and greatly diminished PS [START_REF] Miracca | NMDA receptors in the lateral preoptic hypothalamus are essential for sustaining NREM and REM sleep[END_REF]. Additional studies are necessary to determine whether the LPO controls PS by means of descending projection to PH neurons. In addition, it is possible that, yet undiscovered endogenous cellular or molecular clock-like mechanisms may play a role in the activation of the PS-on neurons and the increase in its quantity after PS deprivation, depression and acute or chronic stress. It is in fact probable that different mechanisms and pathways are involved in each case. We propose that the increase of PS after its deprivation is due to intrinsic molecular and cellular mechanisms occurring in LPO or PH PSon neurons. The increase induced by chronic stress and depression could be due to the activation of systems upstream of the PS-generating systems like the basolateral amygdala or the limbic cortex (see below).

Conversely, the cessation of activity of the MCH/vGluT2+ PS-on neurons and more largely of all the PS-on neurons at the end of PS episodes may be due to a different mechanism than at the entrance into the state since animals enter PS slowly from SWS, while in contrast they exit abruptly from it by a micro-arousal. The most likely hypothesis is that PS-on neurons are rapidly inhibited by the reactivation of the arousal circuits (PH GABAergic neurons, orexin, histamine, norepinephrine, serotonin, and acetylcholine). In that context, it has been shown that acetylcholine, serotonin and norepinephrine inhibit MCH neurons in-vitro while hypocretin/orexin surprisingly excite them [START_REF] Van Den | Physiological properties of hypothalamic MCH neurons identified with selective expression of reporter gene after recombinant virus infection[END_REF]. Besides, it has been shown that if hypocretin/orexin neurons are mainly active during W, 7 % of them projecting to the SLD are also active during PS and contribute to muscle atonia [START_REF] Feng | Orexin signaling modulates synchronized excitation in the sublaterodorsal tegmental nucleus to stabilize REM sleep[END_REF]. In addition, Lhx6+ neurons receive inputs from dopaminergic neurons of the ventral tegmental area, serotoninergic neurons of the dorsal raphe nucleus, and GABAergic neurons of both the ventrolateral periaqueductal gray and lateral hypothalamus [START_REF] Liu | Lhx6-positive GABAreleasing neurons of the zona incerta promote sleep[END_REF]. From all these results, we propose that PS-on hypothalamic neurons are inhibited during W by GABAergic W-active neurons excited by hypocretin/orexin neurons and direct monoaminergic inputs (Fig. 2). The vlPAG PS-off could be also be responsible for stopping PS since they are the only PS-off neurons showing a progressive increase of activity during PS episodes and a progressive decrease of activity in between two PS episodes. They might contain intrinsic molecular and cellular mechanisms inducing their progressive rise of activity during PS episodes. However, these neurons are known to control brainstem but not hypothalamic PS-on neurons and it therefore remains to be shown whether they could also induce their inactivation.

The potential role of the basolateral amygdala in PS control

Hasegawa et al. [START_REF] Hasegawa | Rapid eye movement sleep is initiated by basolateral amygdala dopamine signaling in mice[END_REF] recently observed that a phasic peak of dopamine occurred at the SWS-PS transition, specifically in the basolateral amygdala (BLA). Then, they showed that 1 s optogenetic stimulations during SWS of dopamine terminals in the BLA using a stabilized step function opsin (SSFO) causes transitions to PS after a long latency. Such stimulation every 30 min for 3 h induced a 200 % increase in PS quantities (from 10 % to more than 30 % of total time). Following the inhibition of the dopamine D2-expressing neurons in the BLA, several surrounding BLA and central amygdala neurons expressed cFos with some of them projecting to the brainstem structures generating PS. Further, the optogenetic inhibition (5 min per 25 min during 3 h) of BLA dopaminergic axons expressing vertebrate low-wavelength opsin (vLWO) was followed by a near disappearance of PS. They finally demonstrated that ventral tegmental area (VTA) dopaminergic neurons projecting to the BLA are different than those projecting to the nucleus accumbens and the LHA. These results are very surprising since the amygdala has not been previously involved in PS generation, but in cataplexy occurring during narcolepsy. Indeed, lesions of the amygdala reduced cataplexy in mice but had no effect on PS [START_REF] Burgess | Amygdala lesions reduce cataplexy in orexin knock-out mice[END_REF]. Further, amygdala lesions in monkeys did not induce a decrease in PS [START_REF] Benca | Effects of amygdala lesions on sleep in rhesus monkeys[END_REF]. Finally, although VTA dopaminergic neurons have similar level of activity during wakefulness and PS [START_REF] Dahan | Prominent burst firing of dopaminergic neurons in the ventral tegmental area during paradoxical sleep[END_REF], their chemogenetic inhibition inhibits wakefulness and induces sleep with an increase in PS quantities [START_REF] Eban-Rothschild | VTA dopaminergic neurons regulate ethologically relevant sleep-wake behaviors[END_REF]. Conversely, optogenetic excitation of DA VTA neurons by optogenetic induced wakefulness. In addition, the fact that the induction of PS occurred after very long latencies clearly indicates that the BLA is not a core element of the PS generating network but is rather acting upstream to it. What could be the mechanisms and the neuronal network involved? It is known that D2 dopamine receptors are inhibitory, and the authors reported that some neurons of the BLA are activated following D2 receptors activation. It is therefore likely that DA induced the inhibition of GABAergic interneurons by means of D2 inhibitory receptors. Such inhibition would induce a disinhibition of the pyramidal gluta- matergic neurons. They proposed that these neurons project to the brainstem PS-on neurons and induced PS by this means. However, this proposed mechanism is not possible since BLA neurons do not directly project to the brainstem. They project, instead, to central amygdala GABAergic neurons which are projecting to the brainstem. These neurons indeed project to vlPAG PS-off neurons and could therefore inhibit them and by this means induce a disinhibition of SLD glutamatergic neurons inducing PS. BLA neurons have also strong reciprocal connections with the ventral hippocampus, nucleus accumbens and medial prefrontal cortex. It is well accepted that these pathways play a role in emotional memory [START_REF] Mcdonald | Functional neuroanatomy of the basolateral amygdala: neurons, neurotransmitters, and circuits[END_REF]. One possibility is that when an emotional memory stored in the hippocampus is reactivated at the transition between SWS and PS it induces DA release in the BLA and a subsequent increase of PS to consolidate or erase such memories. Further analyses are needed to test such hypothesis and to determine the neuronal networks activated by the activation of the BLA at the transition between SWS and PS. Whole brain cFos analysis after DA stimulation of the BLA could provide a key element in that regard.

The limited cortical activation compared to wakefulness

It has been shown that during PS hypersomnia compared to control and PS deprivation, the dentate gyrus (DG), claustrum, parasubiculum, presubiculum, cortical amygdaloid nucleus, anterior cingulate, medial entorhinal and retrosplenial cortices (RSC) are the only cortical structures containing neurons with an increased expression of Bdnf, cFos and/or Arc, known markers of activation and/or synaptic plasticity [START_REF] Renouard | The supramammillary nucleus and the claustrum activate the cortex during REM sleep[END_REF]. Among these cortical areas, DG was the only structure that contained more cFos-labeled neurons during PS hypersomnia than during wakefulness [START_REF] Renouard | The supramammillary nucleus and the claustrum activate the cortex during REM sleep[END_REF]. In addition, using a new type of genetically modified mice (TRAP2) allowing us to determine in the same animal whether the same neurons are activated during two states, we recently reported that different neurons are activated during W and PS in the retrosplenial and anterior cingulate cortices, claustrum and dentate gyrus Fare clic o toccare qui per immettere il testo [START_REF] Yamazaki | Sleep Medicine Reviews xxx (xxxx) 101907 paradoxical (REM) sleep hypersomnia but not during wakefulness: a study using TRAP mice[END_REF][START_REF] Maciel | Is REM sleep a paradoxical state?: different neurons are activated in the cingulate cortices and the claustrum during wakefulness and paradoxical sleep hypersomnia[END_REF].(Fig. 3). Corroborating these results, it has been shown that the RSC contains many neurons specifically activated during PS and phase-locked with theta oscillations [START_REF] Koike | Electrophysiological evidence that the retrosplenial cortex displays a strong and specific activation phased with hippocampal theta during paradoxical (REM) sleep[END_REF]. It was also recently confirmed using calcium imaging that the RSC is the only neocortical structure significantly more activated during PS than W and SWS [START_REF] Dong | Cortical regulation of two-stage rapid eye movement sleep[END_REF]. Further, neurons more activated during PS were located in layer 2/3 and not layer 5 like those activated during wakefulness [START_REF] Dong | Cortical regulation of two-stage rapid eye movement sleep[END_REF]. Finally, the inactivation of the retrosplenial cortex induced a shortening of PS, a disappearance of facial movements and a decrease in sympathetic tone [START_REF] Dong | Cortical regulation of two-stage rapid eye movement sleep[END_REF].

In contrast, the number of cFos-labeled neurons was very low in the somatosensory cortices after PS hypersomnia compared to PS deprivation and wakefulness indicating that these cortices are rather deactivated during PS compared to wakefulness [START_REF] Renouard | The supramammillary nucleus and the claustrum activate the cortex during REM sleep[END_REF]. These results are in line with the finding of local slow waves in the middle and the superficial layers of primary sensory and motor cortices [START_REF] Funk | Local slow waves in superficial layers of primary cortical areas during REM sleep[END_REF][START_REF] Nazari | Regional variation in cholinergic terminal activity determines the non-uniform occurrence of cortical slow waves during REM sleep in mice[END_REF]. Further, the activity of pyramidal cells within somatosensory cortices is decreased during PS compared to SWS and wakefulness [START_REF] Niethard | Sleep-Stagespecific regulation of cortical excitation and inhibition[END_REF]. Such decrease was accompanied by activation of parvalbumin inhibitory interneurons [START_REF] Niethard | Sleep-Stagespecific regulation of cortical excitation and inhibition[END_REF]. Interestingly in that regard, It has been also shown in mice, that the somatic activity of pyramidal neurons of the dorsal prefrontal cortex (dPFC) is decreased during PS compared to other states because their soma are inhibited by parvalbumin (PV) interneurons [START_REF] Aime | Paradoxical somatodendritic decoupling supports cortical plasticity during REM sleep[END_REF]. However, these authors further found that the dendrites of pyramidal neurons are disinhibited during PS by the activation of vasoactive intestinal peptide (VIP) interneurons inhibiting somatostatin interneurons responsible for dendritic inhibition. Further, they demonstrate that optogenetic inhibition of PS-active neurons from the central medial thalamus that project to the dPFC induces the inactivation of parvalbumin interneurons and the activation of pyramidal neurons. The origin of the activation of VIP interneurons during PS remains to be determined.

Finally, it was recently shown using calcium imaging that pyramidal neurons of the infralimbic cortex and prelimbic cortices projecting to the lateral hypothalamic area are more active during PS than the other states [START_REF] Hong | Prefrontal cortical regulation of REM sleep[END_REF]. It was further shown that optogenetic activation of these neurons induced a 20 % increase in PS and conversely a 20 % decrease in SWS quantities. Inhibition of these neurons during PS shortened PS episodes and decreased phasic PS [START_REF] Hong | Prefrontal cortical regulation of REM sleep[END_REF]. These results are at variance with the data showing that the soma of dPFC neurons are inhibited during PS [START_REF] Niethard | Sleep-Stagespecific regulation of cortical excitation and inhibition[END_REF]. More data is now necessary to confirm the data obtained and to extend them to other prefrontal regions.

In summary, recent results strongly suggest that only a few limbic cortical structures are strongly activated during PS whereas other cortices such as the somatosensory one are rather deactivated. It has also been shown that PFC pyramidal soma are inactivated while their dendrites are activated. Finally, the fact that RSC inhibition strongly decreases PS duration and that this structure contains neurons specifically active during PS suggest that such cortical regions could play an active role in the regulation of PS quantity and its function (see below). It has been shown that the claustrum is the only subcortical structure containing a large number of cFos-positive neurons projecting to the anterior cingulate and RSC after PS hypersomnia [START_REF] Renouard | The supramammillary nucleus and the claustrum activate the cortex during REM sleep[END_REF]. In addition, the lateral supramammillary nucleus (SumL) was the only subcortical structure containing cFos-positive neurons projecting to the dorsal part of the DG [START_REF] Renouard | The supramammillary nucleus and the claustrum activate the cortex during REM sleep[END_REF] whereas the medial entorhinal cortex was the only structure containing many cFos-labeled neurons projecting to the ventral part of the DG [START_REF] Billwiller | Differential origin of the activation of dorsal and ventral dentate gyrus granule cells during paradoxical (REM) sleep in the rat[END_REF]. After lesion of the SumL, cFos-labeled neurons were no longer visible in the dorsal, but were still visible in the ventral, DG after PS hypersomnia and theta power was decreased during PS [START_REF] Billwiller | Differential origin of the activation of dorsal and ventral dentate gyrus granule cells during paradoxical (REM) sleep in the rat[END_REF]. Of particular interest, SumL neurons activated during PS hypersomnia and projecting to the DG display a dual glutamatergic and GABAergic phenotype [START_REF] Billwiller | Differential origin of the activation of dorsal and ventral dentate gyrus granule cells during paradoxical (REM) sleep in the rat[END_REF][START_REF] Soussi | Heterogeneity of the supramammillary-hippocampal pathways: evidence for a unique GABAergic neurotransmitter phenotype and regional differences[END_REF](Fig. 3). Finally, optogenetic activation of the SumL-DG pathway increased both the power and frequency of theta oscillations as well as gamma power in the DG during PS [START_REF] Billwiller | GABAglutamate supramammillary neurons control theta and gamma oscillations in the dentate gyrus during paradoxical (REM) sleep[END_REF]. Based on these results, it has been proposed that SumL neurons could simultaneously hyperpolarize the soma and depolarize the dendrites of dentate granule neurons [START_REF] Soussi | Heterogeneity of the supramammillary-hippocampal pathways: evidence for a unique GABAergic neurotransmitter phenotype and regional differences[END_REF]. The release of glutamate on the dendrites of granule neurons during PS could activate NMDA receptors and initiate an intracellular cascade inducing the expression of genes involved in synaptic plasticity like cFos, Bdnf, Arc and Cox2. The fact that only a subset of granule cells expresses these proteins during PS hypersomnia suggests that these neurons might receive additional excitatory input during PS from other afferent structures such as the medial entorhinal cortex. It has also recently been shown that glutamatergic neurons located in the claustrum project to the medial entorhinal cortex [START_REF] Kitanishi | Organization of the claustrum-to-entorhinal cortical connection in mice[END_REF]. It is therefore likely that the claustrum is also responsible for the direct and indirect activation of the medial entorhinal cortex and the ventral dentate gyrus, although it remains to be demonstrated. Besides, optogenetic silencing during PS of GABAergic neurons within the medial septum dramatically reduces theta power indicating that these neurons also contribute to PS-specific hippocampal activity [START_REF] Boyce | Causal evidence for the role of REM sleep theta rhythm in contextual memory consolidation[END_REF]. Finally, it has been shown that basal forebrain acetylcholine release during PS is significantly greater than during wakefulness suggesting that it could play a role in cortical activation during PS [START_REF] Vazquez | Basal forebrain acetylcholine release during REM sleep is significantly greater than during waking[END_REF]. Further, it was recently shown that the amount of cholinergic innervation is negatively correlated with the likelihood of a cortical region to exhibit synchronized activity during PS whereas the midline desynchronized cortical areas receive the strongest cholinergic innervation from the BF [START_REF] Nazari | Regional variation in cholinergic terminal activity determines the non-uniform occurrence of cortical slow waves during REM sleep in mice[END_REF]. These results suggest that acetylcholine release is contributing to localized neocortical activation during PS.

Altogether, these results indicate that GABAergic neurons of the medial septum strongly promote theta oscillation in hippocampal neurons during PS while those of the SumL activate specifically dorsal DG granule cells and increase theta pacing. They also suggest that glutamatergic neurons of the claustrum activate anterior cingulate and retrosplenial cortices and also likely the medial entorhinal cortex during PS (Fig. 3). One important remaining question is to determine which structure(s) involved in PS generation is (are) responsible for activating the medial septum, claustrum and SumL. The MCH neurons could be responsible since they are excitatory and project to all these structures [START_REF] Barbier | Melanin-concentrating hormone axons, but not orexin or tyrosine hydroxylase axons, innervate the claustrum in the rat: an immunohistochemical study[END_REF][START_REF] Bittencourt | The melanin-concentrating hormone system of the rat brain: an immuno-and hybridization histochemical characterization[END_REF].

Function (s) of the limbic cortical activation during PS

Optogenetic inhibition during PS of GABAergic neurons in the medial septum known to project to the hippocampus, medial entorhinal and RSC cortices decreased theta power and induced contextual memory impairments [START_REF] Boyce | Causal evidence for the role of REM sleep theta rhythm in contextual memory consolidation[END_REF]. Besides, Kumar and colleagues [START_REF] Kumar | Sparse activity of hippocampal adult-born neurons during REM sleep is necessary for memory consolidation[END_REF] found that optogenetic silencing specifically of 4-weeks adult born dentate gyrus granule cells activity during PS alters the structural remodeling of spines on adult born neurons dendrites and impairs spatial memory consolidation. These results provided a causal link between the activity of these neurons during PS and spatial memory consolidation. Recently, Qin et al. [START_REF] Qin | REM sleep-active hypothalamic neurons may contribute to hippocampal social-memory consolidation[END_REF] also found that neurons of the supramammillary nucleus (SuM) projecting to CA2 are highly active during PS and nearly inactive during SWS or quiet wakefulness. PS-selective optogenetic silencing of these neurons impaired social memory (Fig. 4). By contrast, the silencing of PS-active SuM neurons that project to the DG impaired spatial memory but had no effect on social memory [START_REF] Qin | REM sleep-active hypothalamic neurons may contribute to hippocampal social-memory consolidation[END_REF]. We also recently found that a training-induced modulation of causality between hippocampus and RSC during PS was correlated with spatial memory retrieval 24 h later. Retrieval was positively correlated with an increased influence of the RSC over the hippocampus during PS. Importantly, causality peaks during theta acceleration occur in synchrony with phasic PS. Altogether, these results open a window for the study of the contribution of phasic PS in hippocampo-cortical memory consolidation and suggest that causality modulation between RSC and hippocampus during PS plays a functional role in the phenomena [START_REF] De Almeida-Filho | Hippocampus-retrosplenial cortex interaction is increased during phasic REM and contributes to memory consolidation[END_REF]. It has been also shown that PS prunes newly formed small postsynaptic dendritic spines on pyramidal neurons in the motor cortex both during development and after exposure to a rotarod motor task and on the contrary strengthen and maintain the larger newly formed spines [START_REF] Li | REM sleep selectively prunes and maintains new synapses in development and learning[END_REF]. These authors also showed that calcium spikes within dendrites are increased during PS. Such processes of selective spine modifications could play a key role in learning and memory consolidation. Recently, Aime et al. [START_REF] Aime | Paradoxical somatodendritic decoupling supports cortical plasticity during REM sleep[END_REF] showed in mice that unit activity of dPFC pyramidal neurons decreased during PS while their dendritic activity increased. They further showed that the soma of pyramidal neurons are inhibited during PS by parvalbumin (PV) interneurons. In contrast, their dendrites are disinhibited because vasoactive intestinal peptide (VIP) interneurons inhibit somatostatin interneurons responsible for dendritic inhibition. They also found that after inhibition of VIP interneurons during PS mice were less able to discriminate conditional auditory stimuli (CS) and the AMPA/NMDA ratio was decreased in pyramidal neurons. In contrast, PV interneuron inhibition induced a significant increase in CS discrimination and an increase in the AMPA/NMDA ratio in pyramidal neurons.

Besides, induction of both long-term synaptic potentiation (LTP) and depression (LTD) in CA1 were also impaired in MCH receptor 1 knockout (R1-/-) mice [START_REF] Pachoud | Major impairments of glutamatergic transmission and long-term synaptic plasticity in the hippocampus of mice lacking the melanin-concentrating hormone receptor-1[END_REF]. It was also shown that MCH/ataxin3 mice were slow in performing a short-term memory T-maze task, displayed retardation in acquiring a reference memory task in a Morris water maze, and showed a habituation deficit in an open field task [START_REF] Barillier | Genetic deletion of melanin-concentrating hormone neurons impairs hippocampal short-term synaptic plasticity and hippocampal-dependent forms of short-term memory[END_REF]. Activation or inhibition of MCH neurons impairs or improves hippocampus-dependent memories, respectively. Activation of MCH axonal terminals in vitro reduced firing of hippocampal pyramidal neurons by increasing inhibitory inputs, suggesting that the activation of the MCH projection to the hippocampus during PS may contribute to forgetting [START_REF] Izawa | REM sleepactive MCH neurons are involved in forgetting hippocampus-dependent memories[END_REF]. Altogether, these results indicate that MCH activation during PS plays a role in memory consolidation. The link between such a role and that of activation of the medial septum GABAergic neurons, dentate adult born neurons and prefrontal pyramidal neurons remains to be identified. Further, the function in memory consolidation of additional cortical structures activated during PS such as the retrosplenial and medial entorhinal cortices and the claustrum remains to be determined.

In summary, a large body of evidence in rodents indicates that PS is involved in both spatial and social memory consolidation and forgetting (Fig. 4). Such processes have been identified in the hippocampus but also in the motor, prefrontal and retrosplenial cortices. Based on these and our results, we propose that the retrosplenial and the medial entorhinal cortices are at the origin of the replay of memories during PS. Further, we hypothesize that they may stimulate subcortical PS generating structures such as the MCH neurons to increase the quantity of PS required to consolidate or erase memories. Besides, the role of the activation of the BLA in memory consolidation and the pathways involved remain to be identified. Finally, it is also likely that activation of all these structures during PS plays a role well beyond consolidation of recent memories. Indeed, PS is highly expressed during development and strongly modified by stress and in mood disorders. Its role in longlasting memory and insight has also not yet been explored. Additional works are therefore necessary to explore its involvement in such functions by examining the activity of the limbic cortices more broadly than in control PS episodes or after recent learning.

General conclusion

Considering available data, it can be concluded that as stated in the past, the brainstem is necessary and sufficient to generate a state with muscle atonia and REMs. However, growing body of evidence indicates that the posterior hypothalamus controls the brainstem and PS occurrence by descending pathways. Finally, although there is recent evidence that the cortex and the amygdala directly control PS occurrence, more data are necessary to determine whether such effects are direct or indirect and linked to the functions of the state, such as emotional control and memory consolidation.

Fig. 1 .

 1 Fig. 1. PS onset and maintenance.The onset of PS would be due to the activation by intrinsic "clock-like" mechanisms of PS-on MCH+/Glutamatergic and/or MCH-/GABAergic neurons located in the posterior hypothalamus. A subpopulation of the zona incerta GABAergic neurons co-expresses Lhx6. All or a subpopulation of the PH neurons could also be responsible of the rebound of PS occurring after its deprivation. The PH PS-on neurons would inactivate directly (GABA neurons) or indirectly (MCH neuron) the PS-off vl-PAG/dDpMe GABAergic neurons and the histaminergic and orexinergic neurons. The inhibition of the PS-off vlPAG/dDpMe GABAergic neurons would induce the desinhibition of the PS-on glutamatergic SLD neurons. These neurons would directly excite glycinergic/GABAergic premotor neurons in the vmM which in turns hyperpolarize spinal and cranial motoneurons. The SLD neurons also project to and excite DPGi and LPGi ascending GABAergic neurons responsible for inhibiting the dorsal raphe serotonergic neurons and the locus coeruleus noradrenergic neurons. The SLD neurons also excite the glutamatergic neurons of the DPGi which project to oculomotor nuclei and induce REMs. The role of the PS-on glutamatergic and GABAergic neurons of the lateral preoptic area still needs to be determined.

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Fig. 3 . 7 .

 37 Fig. 3. Cortical activation during PS.Cortical activation during PS is limited to a few limbic cortices (the retrosplenial, anterior cingulate and medial entorhinal cortices and the dentate gyrus). The activation of the the retrosplenial, anterior cingulate and medial entorhinal cortices and the ventral dentate gyrus would be induced by direct and indirect projections from the claustrum. The dorsal DG would be activated by a projection from GABA/glutamatergic neurons located in the lateral supramammillary nucleus. The MCH neurons would excite and induce the activation of the neurons of the claustrum and the lateral supramammillary nucleus. In addition the GABAergic neurons of the medial septum would play a crucial role in the genesis of the theta waves recorded in the hippocampus and the retrosplenial cortex.

CFig. 4 .

 4 Fig. 4. PS and memory.During PS, learning and memory consolidation occur in the prefrontal cortex, motor cortex and retrosplenial cortex (RSC) and in the dentate gyrus (DG). The medial septum (MS) induces theta in the hippocampus and retrosplenial cortex during PS and plays a role in memory consolidation. The pathway from the supramammillary nucleus (SuM) to the DG activates all granule cells during PS. We propose that in addition the pathway from the RSC to the hippocampus more strongly activates 4weeks adult born (4WK-ABN) neurons forming memory engrams to consolidate spatial memory. Another set of glutamatergtic supramammillary neurons activates during PS the CA2 pyramidal neurons to induce memory consolidation of social memory. Besides, the MCH neurons excite local GABAergic neurons in CA1 and by this mean induce inhibition of CA1 pyramidal neurons and forgetting. Motor learning is also consolidated during PS by means of pruning newly formed small postsynaptic dendritic spines and on the contrary strengthening and maintaining the larger newly formed spines on pyramidal neurons in the primary motor cortex (M1) both during development and after exposure to a motor task. Finally, memory consolidation is also induced by reactivation of dendrites of pyramidal neurons of the dorsal prefrontal cortex (dPFC) during PS. Such reactivation is induced by the disinhibition of their dendrites by the removal of the input of somatostatin interneurons inhibited during PS by VIP interneurons. The soma of the pyramidal cells is inhibited during PS by the parvalbumin interneurons excited by a pathway originating from the thalamus.

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  Muscle atonia during PS is produced by a network of glutamatergic and GABA/Glycinergic neurons located in the brainstem. -GABAergic and MCH (glutamatergic) PS-on neurons located in the posterior hypothalamus control PS expression by means of descending projections to the brainstem GABAergic PS-off structures. -The claustrum and the lateral supramammillary nucleus activate the limbic cortex during PS. -A limited number of cortical limbic areas control PS duration and play a role in memory consolidation during PS. Research agenda -The mechanisms responsible for PS homeostasis need to be identified. It could be taking place in the PS-off GABAergic neurons of the brainstem, the MCH or GABAergic PS-on PH neurons or the PS-on neurons of the lateral preoptic area. -The exact role of the basolateral amygdala in PS control needs to be examined in further detail. It could be implicated in emotional memory processing during the state. -The role played by the lateral preoptic area in PS regulation needs to be further assessed. It could control PS-on neurons of the posterior hypothalamus. -The role of the different subpopulations of neurons in PS of the posterior hypothalamus beyond the MCH neurons like those expressing Lhx6 should be identified. -The respective functions and links between each cortical limbic region activated during PS need to be identified. -The role of the claustrum in the activation of the limbic neocortical structures during PS should be confirmed. -The potential role of PS in functions other than short memory consolidation like life-long lasting memory, development and mood regulation needs to be identified Uncited references []; []; []; []. C O R R E C T E D P R O O F P.-H. Luppi et al. Sleep Medicine Reviews xxx (xxxx) 101907 C O R R E C T E D P R O O F

Acknowledgements

This work was supported by the Centre National de la Recherche Scientifique, Université de Lyon and Université Lyon 1.

Declaration of competing interest

The authors do not have any conflicts of interest to disclose.

Abbreviations


Sid Ahmed

Walid Talha

Anthony Fleury

Stephane Lecoeuche

Hierarchical classification scheme for real-time recognition of physical activities and postural transitions using smartphone inertial sensors

Hierarchical classification scheme for real-time recognition of physical activities and postural transitions using smartphone inertial sensors

Sid Ahmed Walid Talha 1 , Anthony Fleury 1 Member, IEEE and Stéphane Lecoeuche 1

Abstract-This paper introduces a novel approach for realtime classification of human activities using data from inertial sensors embedded in a smartphone. We propose a hierarchical classification scheme to recognize seven classes of activities including postural transitions. Its structure has three internal nodes composed of three Support Vector Machines (SV Ms) classifiers, each one is associated with a set of activities. Moreover, each SV Ms is fed with a feature vector from an adapted and optimal frequency band. Experimental results conducted on a challenging publicly available dataset named SBHAR show that our method is effective and outperforms various state-of-the-art approaches. We also show the suitability of our method to recognize postural transitions.

I. INTRODUCTION

Human activity recognition (HAR) has become an important research area due to a high demand in various application domains, including healthcare monitoring. Computer vision has been the canonical way to develop HAR systems for decades, using several types of cameras as RGB [START_REF] Tran | Human activity recognition with metric learning[END_REF] or more recently RGB-D cameras [START_REF] Talha | Features and classification schemes for view-invariant and real-time human action recognition[END_REF]. However, these approaches suffer from some limitations due to environmental restriction, such as illumination conditions or occlusions due to people and objects. Moreover, regarding the privacy context, cameras are more intrusive and disruptive for users.

Recent developments in wearable sensing technologies such as inertial sensors offer an interesting choice since it allows a continuous monitoring compatible with the user's privacy. However, wearable based approaches employ several sensors placed on different body locations. In addition to the cost, it can be uncomfortable to wear these sensors, especially for a long-term monitoring purpose.

More recently, sensors embedded in smartphones have gained the attention of researchers. Indeed, almost all smartphones include a complete Inertial Motion Unit (IMU) with a triaxial accelerometer, gyroscope and magnetometer. Nowadays, smartphones become more ubiquitous and widely used in our daily life, it can be a very good alternative to wearable devices. Moreover, smartphone-based approaches do not require any infrastructure to operate.

Several HAR approaches using inertial sensors have been proposed by researchers. The general architecture of a HAR system can be divided into the following modules: windowing, pre-processing, feature extraction and classification. The first main step is the windowing operation, it prepares the *This work is supported by DRESS, Région Haut-de-France, and Institut Mines-Télécom Lille Douai 1 IMT Lille Douai, Univ. Lille, Unité de Recherche Informatique Automatique, F-59000 Lille, France. E-mails: {firstname.lastname}@imt-lilledouai.fr continuous data streaming for feature extraction process, i.e., inertial signals are divided into equal segments of size T w , with a degree of overlap named O v between consecutive segments. A wide range of window sizes has been used in HAR literature, from T w = 1s in [START_REF] Attal | Physical human activity recognition using wearable sensors[END_REF], until T w = 30s in [START_REF] Liu | Multisensor data fusion for physical activity assessment[END_REF]. The size T w is generally determined in an empirical way based on system accuracy. In [START_REF] De La Concepción | Mobile activity recognition and fall detection system for elderly people using ameva algorithm[END_REF], [START_REF] Atallah | Sensor positioning for activity recognition using wearable accelerometers[END_REF], after testing different window sizes, T is fixed to 5 seconds. The obtained segments can be pre-processed (optional) using filtering techniques in order to remove undesirable information. A Butterworth low-pass filter was employed in [START_REF] Reyes-Ortiz | Transition-aware human activity recognition using smartphones[END_REF], the cutoff frequency was fixed to 20Hz. In [START_REF] Khan | A triaxial accelerometer-based physical-activity recognition via augmentedsignal features and a hierarchical recognizer[END_REF], a moving average filter was applied.

To describe each human activity, a vector of relevant features noted F is constructed. Features can be divided into three categories: time domain features (first and second order statistics, correlation coefficient, histogram, etc.), frequency domain features, extracted from Discrete Fourier Transform (DFT) using Fast Fourier Transform (FFT) algorithm, and time-frequency domain features, extracted from Discrete Wavelet Transform (DWT) or Wavelet Packet Decomposition (WPD). In order to obtain better accuracy, features are generally extracted from both frequency and time domains resulting in a high dimensional feature vector. In [START_REF] Reyes-Ortiz | Transition-aware human activity recognition using smartphones[END_REF], [START_REF] Hassan | A robust human activity recognition system using smartphone sensors and deep learning[END_REF] F ∈ R 512 . However, This method may require a high computational complexity and energy consumption to extract a large number of features or carry out the classification.

For the classification stage, various methods have been investigated in the state-of-the-art. Traditional classifiers such as k-Nearest Neighbors (kNN), Naive Bayes or decision trees are widely used. More recently, deep neural networks are employed [START_REF] Ronao | Human activity recognition with smartphone sensors using deep learning neural networks[END_REF], [START_REF] Mohammad | Primitive activity recognition from short sequences of sensory data[END_REF], mostly Convolutional Neural Networks.

In addition to physical activities, some researchers used wearable devices to detect transitions between postures [START_REF] Khan | A triaxial accelerometer-based physical-activity recognition via augmentedsignal features and a hierarchical recognizer[END_REF], [START_REF] Gupta | Feature selection and activity recognition system using a single triaxial accelerometer[END_REF]. However, a few works fulfilled the classification of postural transitions using a smartphone. In [START_REF] Reyes-Ortiz | Transition-aware human activity recognition using smartphones[END_REF], two different implementations are proposed: in the first one, only physical activities are learned by the classifier, transitions on the other hand, are considered as a switch of activities detected by the system. In the second approach, in addition of physical activities, transitions are learned by the classifier, they are considered as an additional class.

In this paper, a novel HAR method using inertial signals from a smartphone is proposed. It aims to carry out a real-time classification of physical activities and postural transitions. The main contribution of this work is the development of a hierarchical classification scheme to classify three groups of activities: postures, dynamic activities and postural transitions. Each internal node of the model is We demonstrate experimentally that the proposed method is effective and outperforms various state-of-the-art approaches. The remaining of the paper is organized as follows: Section II introduces the proposed methodology. Section III describes the experimental setups, then presents the results with a comparison over existing approaches. Finally, section IV concludes this work.

II. METHOD

The overview of our approach is shown in Figure 1. Inertial signals collected from a triaxial accelerometer and gyroscope sensors are employed in our methodology, it involves: acceleration (A x , A y , A z ), angular rate (G x , G y , G z ), and their magnitudes A m and G m with

A m = A 2 x + A 2 y + A 2 z and G m = G 2 x + G 2 y + G 2 z .

A. Windowing

In the state-of-the-art approaches, a rectangular window function is generally employed in windowing operation.

However, in our methodology, features are extracted from frequency domain of inertial signals, hence, a rectangular window is not an advantageous choice, it presents a high leakage factor (ratio of power in the side lobes to the total window power), therefore, to minimize this effect, a Hamming window is employed instead. The size of the window is fixed at 2.56s, and the degree of overlap O v at 50% of the window size, these parameters are set equal to HAR approaches experimented on SBHAR dataset, so a fair comparison can be carried out.

B. Feature extraction and classification algorithms

In our approach, features are extracted from frequency domain following the algorithm 1: for each signal, after windowing operation, DFT is obtained by the FFT, then the Energy Spectral Density (ESD) containing the energy distribution at each frequency bin is calculated. Afterwards, feature vector is constructed from coefficients included in frequency band [0Hz -FrHz] (Fr denote the cutoff frequency). The size of the frequency band depends on the classification problem. As displayed in Figure 1, a hierarchical classification method composed of three SV Ms classifiers is fed with three vectors of features named: F C , F D and F P ({C,D,P} denotes "category of activity", "dynamic activity" and "posture"). Each couple (F i , SV Ms i ) with i ∈ {C, D, P} is designed to solve a specific classification problem. In the first level of the scheme, activities are separated into three categories: dynamic activities, postures and postural

F C ← [S 1 (1 : k 1 ) S 2 (1 : k 1 ) S 3 (1 : k 1 ) S 4 (1 : k 1 )]; F D ← [S 1 (1 : k 2 ) S 2 (1 : k 2 ) S 3 (1 : k 2 ) S 4 (1 : k 2 )]; F P ← [S 1 (1 : k 3 ) S 2 (1 : k 3 ) S 3 (1 : k 3 ) S 4 (1 : k 3 )]; end Function Spectrum(S)
S f ←fft(S); // Fast Fourier transform calculation S ESD ← S f .S * f ; // Energy spectral density calculation (S * f is the complex conjugate of S f ) return S ESD ; end transitions. Here, SV Ms C classifier is fed by feature vector

F C = [C 1 , ..,C 7 ] containing ESD coefficients in [0Hz-2.3Hz].
In the second level, dynamic activities are classified using SV Ms D classifier, the vector F D = [C 1 , ..,C 10 ] is employed as input (Fr 2 = 3.5Hz). In a similar way, postures are recognized employing SV Ms P classifier fed by F P = [C 1 , ..,C 10 ] with Fr 3 = 3.5Hz. Noted that the frequency bands presented here are determined empirically based on system accuracy, i.e., the model is evaluated by varying Fr for each feature vector from 0Hz (DC components) to 25Hz (all coefficients). The results of this experiment are detailed in section III-B.

C. Correction of misclassification

The output label given by SV Ms classifiers is put in a misclassification correction process.The impulsive prediction error is rectified based on the following hypothesis: in our experiments, as O v = 50%, then a segmented window at an instant t named W t shares 50% of data with W t-1 , and the remaining 50% with W t+1 . It implies that in the case of W t-1 and W t+1 outputs the same activity label, it should be equal to W t output label. The implementation of the proposed solution is reported in the algorithm 2.

III. EXPERIMENTS

A. Experimental setup

The experiments are conducted on SBHAR dataset [START_REF] Reyes-Ortiz | Transition-aware human activity recognition using smartphones[END_REF], it contains acceleration and angular rate signals sampled at F s = 50Hz. Six activities are performed by thirty subjects, each one wore a Samsung Galaxy S2 smartphone on the waist. Three of collected activities are static (standing, sitting and lying) and three are dynamic (walking, up and down stairs). In addition, the dataset also contains transitions between static activities named postural transitions (stand to sit, sit to stand, sit to lie, lie to sit, stand to lie, lie to stand). Each subject performed a scenario of sequential activities twice.

In order to estimate the overall recognition performance of our system and to compare it to state-of-the-art methods, four metrics are calculated: recall, precision, F 1 score and accuracy. In the state-of-the-art methods evaluated on SBHAR dataset, different scores are calculated, mostly accuracy. Hence, in order to make a fair comparison with these approaches, for each method, recall, precision, accuracy and F 1 scores are either recovered if it was already estimated like in our paper or recomputed using the confusion matrix that is given in the article. For papers where two methods are proposed, a comparison with each method noted m 1 and m 2 is carried out.

A subject-independent validation is carried out using leave-one-subject-out-cross-validation (LOSOCV) and holdout subjects (proposed by [START_REF] Anguita | Human activity recognition on smartphones using a multiclass hardwarefriendly support vector machine[END_REF]), where data from 21 randomly selected subjects are used for training, and the remaining 9 subjects for the test.

B. Optimal frequency band

Before presenting the results, an experimental study is carried out to determine the optimal frequency bands to construct F D and F P vectors. In this experiment, LOSOCV strategy is applied. The recall score is calculated for each value of cutoff frequency Fr. The obtained results are shown in the Figure 2. We can see clearly a growth of the score for postures and dynamic activities, the maximum is reached at the frequency Fr 3.5Hz, a slight decrease is observed beyond this frequency. Noted that in this experiment, the vector F C is constructed from coefficients included in the band [0Hz -2.3Hz], a perfect separation between the postures and dynamic activities is then achieved (score of 100%).

C. Experimental results

In the state-of-the-art, a few works investigated the recognition of postural transitions using a smartphone, hence, in our experiments, the performances of physical activities and transitions are presented separately. 1) Physical activities: Table I reports performance scores of our system to recognize the physical activities and a comparison with state-of-the-art methods. It shows scores around 97% for both LOSOCV and hold-out subjects strategies, outperforming the existing approaches tested on SBHAR dataset. The confusion matrix is shown in Table II. All activities achieve a good performance score. However, some confusions appear for "sitting" and "standing" postures due to the position of the smartphone (waist), making the output signals similar for these postures.

2) Postural transitions: Table III reports performance scores of our method to recognize postural transitions and comparison with two methods proposed by [START_REF] Reyes-Ortiz | Transition-aware human activity recognition using smartphones[END_REF] (the only existing method performing recognition of PTs on SBHAR dataset). It shows that the proposed approach achieves a recall score of 99.81% using LOSOCV strategy, outperforming both methods proposed by [START_REF] Reyes-Ortiz | Transition-aware human activity recognition using smartphones[END_REF]. With hold-out subjects strategy, an overall recall of 99.63% is obtained.

IV. CONCLUSIONS

In this paper, we introduced a novel method to carry out a real-time recognition of physical activities and postural transitions. Three meta-classes representing the different categories of activity (postures, dynamic activities and postural transitions) have been created. A hierarchical classification scheme has been proposed to classify efficiently each group of activity. Each internal node is composed of SV Ms classifier and made of frequency domain features extracted from an optimal frequency band determined empirically. The experimental results on a challenging publicly available dataset named SBHAR have demonstrated that our method is effective and outperforms various state-of-the-art approaches, reaching overall scores around 97% for physical activities and 99.81% for postural transitions.

Fig. 1 :

 1 Fig. 1: Overview of the proposed system.

Algorithm 1 :

 1 Feature construction algorithmData: A: Segments of acceleration signals // (A x , A y , A z ) A m : Segments of magnitude of acceleration signals G: Segments of angular rate signals // (G x , G y , G z ) G m : Segments of magnitude of angular rate signals T w : Window size Fr 1 = 2.3: Frequency range for SV M C // [0 Hz -2.3 Hz] Fr 2 = 3.5: Frequency range for SV M D // [0 Hz -3.5 Hz] Fr 3 = 3.5: Frequency range for SV M P // [0 Hz -3.5 Hz] Function Feature construction(A,A m ,G,G m ) w = 0.54 -0.46 cos 2πn M-1 ; // Hamming window S 1 ←Spectrum(A.w); // Spectrum of A x , A y and A z S 2 ←Spectrum(A m .w); S 3 ←Spectrum(G.w); S 4 ←Spectrum(G m .w); k 1 = round(T w .Fr 1 ); k 2 = round(T w .Fr 2 ); k 3 = round(T w .Fr 3 );

Algorithm 2 :

 2 Correction of misclassification Data: F(t): Feature extracted from inertial signals at an instant t PR(t -1) = [pred(t -N), .., pred(t -2), pred(t -1)]: Vector containing labels of predicted activities pr ← SV M Predict(F(t)); if [pr = PR(end)] AND [pr == PR(end -1)] then PR(end) ← pr; end PR = [PR pr];

Fig. 2 :

 2 Fig. 2: Recall score depending on Fr.

TABLE I :

 I Scores of relevant studies on SBHAR dataset.

		W	WU WD	Si	St	L	PT
	Walking	97.83 2.07	0	0	0	0	0.1
	W. upstairs	0.19 95.49 3.5	0	0	0	0.82
	W. downstairs 0.23 1.37 98.25	0	0	0	0.15
	Sitting	0	0	0	95.05 4.78	0	0.17
	Standing	0	0	0	5.26 94.69	0	0.05
	Laying	0	0	0	0	0	99.58 0.42
	P. transition	0	0	0	0.14 0.05	0	99.81

TABLE II :

 II Confusion matrix on SBHAR dataset (%).

	Validation	Relevant	Recall	Precision	F-score
	strategy	Studies	(%)	(%)	(%)
		[7] (m 1 )	92.18
	LOSOCV 1	[7] (m 2 )	99.76
		Ours	99.81	98.29	99.04
	HS 2	Ours	99.63	97.89	98.75
	1 Leave-one-subject-out cross-validation.

2

Hold-out subjects.

TABLE III :

 III Scores of postural transitions.