PhD Perrine Ruby

MSc Mickael Eskinazi

PhD Romain Bouet

MD, PhD Sylvain Rheims

MD, PhD Laure Peter-Derex
email: laure.peter-derex@chu-lyon.fr

John Wiley

Inc Sons

Dynamics of hippocampus and orbitofrontal cortex activity during arousing reactions from sleep: An intracranial electroencephalographic study

Keywords: Arousal, Hippocampus, Frontal lobe, Intra-cranial electoencephalography, Sleep, wakefulness, Dream, Humans

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Introduction

The vanishing of conscious executive and perceptive abilities [START_REF] Bastuji | Evoked potentials as a tool for the investigation of human sleep[END_REF] as well as of explicit encoding of information into memory [START_REF] Ruch | Learning During Sleep: A Dream Comes True?[END_REF]) is a central component of the changes in cognitive functioning at the passing from wake to sleep state. Its cerebral correlates are not yet fully understood, nor are those associated with the restoration of these abilities at awakening. Transient periods of activation such as arousals [START_REF] Asda | EEG arousals: scoring rules and examples: a preliminary report from the Sleep Disorders Atlas Task Force of the American Sleep Disorders Association[END_REF]) and short awakenings provide a useful model to get insight about how the brain raises its level of alertness. Notably, arousals (lasting 3 to 15 seconds) are usually not associated with a conscious perception nor are they encoded in memory, whereas awakenings, lasting longer, may be consciously perceived, encoded in long-term memory, and reported by the sleeper in the morning [START_REF] Campbell | The perception of wakefulness within sleep[END_REF][START_REF] Koulack | Dream recall and dream recall failure: An arousalretrieval model[END_REF]. During these short time windows (from 3 seconds to a few minutes) the changes in brain activity would allow the recovery of consciousness and/or the ability to encode the content of the mind (may it be the dream content, the trigger of the awakening, or the awakening itself) in long-term memory [START_REF] Koulack | Dream recall and dream recall failure: An arousalretrieval model[END_REF]. Several experimental results suggest that a minimum of about 1-2 minutes of wakefulness is required for the sleeper to recover consciousness or memory encoding abilities at awakening [START_REF] Campbell | The perception of wakefulness within sleep[END_REF][START_REF] Eichenlaub | Brain reactivity differentiates subjects with high and low dream recall frequencies during both sleep and wakefulness[END_REF]Raphael Vallat et al., 2017).

In the search for a better understanding of the changes in memory processes according to vigilance state, the hippocampus seems to be the first region of the brain to be investigated. This structure is indeed involved in memory processes during wakefulness, but also during sleep through its implication in sleep-related memory consolidation phenomena [START_REF] Albouy | Both the hippocampus and striatum are involved in consolidation of motor sequence memory[END_REF][START_REF] Squire | The medial temporal lobe memory system[END_REF][START_REF] Walker | Sleep-dependent learning and memory consolidation[END_REF]. The different aspects of memory underpinned by the hippocampus, i.e. encoding, consolidation and retrieval, are thought to be theoretically at least partially exclusive, and associated with distinct [START_REF] Axmacher | Ripples in the medial temporal lobe are relevant for human memory consolidation[END_REF][START_REF] Douchamps | Evidence for encoding versus retrieval scheduling in the hippocampus by theta phase and acetylcholine[END_REF]. In agreement with these theories, several results suggest that the hippocampus might be unable to encode a new information into memory during sleep, although simple items presented during sleep may lead to memory traces [START_REF] Aarons | Sleep-assisted instruction[END_REF][START_REF] Andrillon | Formation and suppression of acoustic memories during human sleep[END_REF][START_REF] Mizuseki | Hippocampal information processing across sleep/wake cycles[END_REF][START_REF] Suzuki | Encoding new episodes and making them stick[END_REF].

Thus, the investigation of the dynamic changes of the hippocampus, and of related areas such as the prefrontal cortex, activity during arousals and intra-sleep awakenings seems to be relevant to improve our understanding of how memory encoding/retrieval is restored upon awakening.

However, the electrophysiological investigation of hippocampal activity during sleep in human must overcome two major difficulties. The first is related to the fact that only deep stereoelectro-encephalographic recordings (S-EEG) allow access to the hippocampus which cannot be explored with scalp EEG. The second difficulty is that S-EEG recordings are performed as part of a pre-surgical evaluation in drug-resistant epilepsy patients whose hippocampus is often involved in epileptic activity, especially during non-rapid-eye-movement (NREM) sleep [START_REF] Lambert | Brain regions and epileptogenicity influence epileptic interictal spike production and propagation during NREM sleep in comparison with wakefulness[END_REF]. However, intracranial recording of apparently normal hippocampus is sometimes required during pre-surgical evaluation, in particular to exclude bi-temporal epilepsy, leading the unique opportunity of studying healthy hippocampal activity in human.

Thanks to a large intracranial EEG recordings database (Epilepsy Unit of Lyon University Hospital), we were able to identify four patients presenting both a strictly normal hippocampal activity during wakefulness and sleep and a recording of the thalamic activity enabling precise scoring of vigilance stages and arousals (Michel Magnin, Bastuji, Garcia-Larrea, & Mauguiere, 2004;[START_REF] Peter-Derex | Heterogeneity of arousals in human sleep: A stereo-electroencephalographic study[END_REF]. Prefrontal (orbitofrontal) cortex was also explored in all of them, allowing to investigate neocortical activity. Previously, the analysis of S-EEG recordings from several neocortical areas allowed us to identify a high heterogeneity of brain activity during the first 3 seconds of arousals, which depended on various factors such as the on-going sleep stage at the time of the arousal, the stimulus which had triggered arousal, homeostatic factors and overall the brain area considered (L. [START_REF] Peter-Derex | Heterogeneity of arousals in human sleep: A stereo-electroencephalographic study[END_REF]. In the present study, we aimed to explore more specifically the hippocampus and to focus not only on the first seconds of the arousal but also on several time windows at the beginning, in the middle and at the end of both arousals and short awakenings.

These analyses allowed us to characterize the dynamics of hippocampal and neocortical activity in the first tens of seconds of wakefulness after an awakening from sleep. We investigated the hippocampus and the prefrontal cortex activity during NREM and REM sleep thalamic arousal reactions, and compared this activity with that of wakefulness, NREM, and REM sleep in order to assess (i) the dynamics of restoration of the hippocampus typical wake activity, which is supposed to be associated with the restoration of its memory functions, as compared to neocortex activity during arousals (ii) if the modification of hippocampus activity during arousal/awakenings depends on the preceding sleep stage as can be expected from our previous results (L. [START_REF] Peter-Derex | Heterogeneity of arousals in human sleep: A stereo-electroencephalographic study[END_REF], which may suggest functional differences between NREM and REM sleep awakenings (iii) if hippocampal and neocortical activity are modulated by the duration of the arousing reaction, with greater activation during long as compared to short events.

Materials and Methods

Patients

Four patients (3 men and 1 woman, mean age 33 years, range 19-45 years) suffering from focal refractory temporal lobe epilepsy were included in this study (Table 1). To delineate the extent of the epileptogenic zone and plan a tailored surgical treatment, depth EEG electrodes were implanted according to the stereotactic technique of Talairach and Bancaud [START_REF] Bancaud | Methodology of stereo EEG exploration and surgical intervention in epilepsy[END_REF][START_REF] Guenot | Neurophysiological monitoring for epilepsy surgery: the Talairach SEEG method. StereoElectroEncephaloGraphy. Indications, results, complications and therapeutic applications in a series of 100 consecutive cases[END_REF]. The choice of cortical anatomic targets was guided by data from non-invasive investigations (clinical history, video-scalp-EEG monitoring, morphologic MRI, [18F]-fluorodeoxyglucose position emission tomography). Three of the four patients underwent bitemporal exploration in order to rule out bitemporal seizures. The thalamus, and more specifically the medial pulvinar nucleus (PuM), was a target of stereotactic implantation because it might be an important relay in the propagation of epileptic discharges, given its reciprocal connections with temporal cortical areas [START_REF] Rosenberg | Involvement of medial pulvinar thalamic nucleus in human temporal lobe seizures[END_REF].

Explorations of temporal neocortical areas and PuM was possible using a single multi-contact electrode, so that thalamic exploration did not increase the risk of the procedure by requiring an additional electrode track specifically devoted to the PuM activity recording. Anti-seizure drugs were tapered down in order to increase the occurrence probability of spontaneous seizures. In agreement with the French legislation relative to invasive investigations with a direct individual benefit, patients were fully informed about electrode implantation and stereotactic EEG recordings. They gave written informed consent for the use of recordings for research purposes. The procedure was approved by the national Ethics Committee (Comité de Protection des Personnes CPP 09-CHUG-12, no 0907).

Electrode implantation and anatomical localization of recording sites

The electrode implantation procedure was carried out using multiple contact electrodes introduced into the brain perpendicular to the midsagittal plane with a stereotactic frame. Each platinum-iridium electrode had a diameter of 0.8 mm, and contained 5 to 15 recording contacts (2 mm long, spaced by 1.5 mm; Dixi®, Besançon, France). The stereotactic implantation procedure was derived from the one first described by Talairach and Bancaud [START_REF] Bancaud | Methodology of stereo EEG exploration and surgical intervention in epilepsy[END_REF] and is detailed in Ostrowsky et al. [START_REF] Ostrowsky | Representation of pain and somatic sensation in the human insula: a study of responses to direct electrical cortical stimulation[END_REF]. Anatomical localization of the cortical electrodes contacts was counterchecked using post-implantation (http://www.bic.mni.mcgill.ca:brainweb/). Superimposition of cortical contacts on the MNI brain template was performed using a MATLAB routine (Figure 1). The placement of the contacts within the thalamus was assessed using Morel's atlas of the human thalamus [START_REF] Morel | Multiarchitectonic and stereotactic atlas of the human thalamus[END_REF]. Thalamic contacts were in the PuM in all patients but one. In patient 2, the electrode was more anterior and reached the lateral posterior and ventral lateral posterior nuclei (Figure 1).

Data acquisition

Night sleep recordings under stereo-EEG (S-EEG) video monitoring were conducted in the patient's own room at least 5 days after electrode implantation. S-EEG signals were obtained using both referential and bipolar montages with Micromed® software (Treviso, Italy) (sampling frequency: 256 Hz; band pass filter: 0.53-128 Hz; 32dB/octave). The reference electrode was chosen for each patient on an implanted contact located in the skull. Blinks and saccades were recorded with two electro-oculograms (EOG) electrodes placed on the superoand infero-lateral right canthus. EOG, electrocardiogram (EKG) and Video were recorded continuously during the night.

Sleep scoring and Intra Sleep Awakening Reaction (ISAR) detection

Sleep stages were visually scored using 30 s epochs by one of the authors (L.P-D) trained in scoring intra-cerebral sleep, using AASM criteria adapted to intra-cerebral recordings and thalamic activity especially for REM sleep [START_REF] Berry | The AASM Manual for the Scoring of Sleep and Associated Events: Rules, Terminology and Technical Specifications[END_REF]Michel Magnin et al., 2004).

Intra Sleep Awakening Reaction (ISAR) were defined as an abrupt EEG frequency shift which F o r P e e r R e v i e w 9 may include theta, alpha, and/or frequency greater than 16 Hz except spindles, following 10 s of stable sleep, lasting 3 to 15 s for arousals according to the ASDA standard definition and more than 15 sec for awakenings, and ending with sleep [START_REF] Asda | EEG arousals: scoring rules and examples: a preliminary report from the Sleep Disorders Atlas Task Force of the American Sleep Disorders Association[END_REF]. We investigated awakenings up to 2 minutes long since this time duration was pointed out in previous work as being related to the restoration of metacognitive abilities such as awareness or explicit memory recall [START_REF] Campbell | The perception of wakefulness within sleep[END_REF]J.-B. Eichenlaub et al., 2014). ISAR visual detection (performed by M.E. and countercheck by L.P-D) was based on thalamic activity, as we had previously shown that the pattern of thalamic activation during arousals was easily detectable and highly reproducible as it manifests as an abrupt shift to high-frequency activity (L. [START_REF] Peter-Derex | Heterogeneity of arousals in human sleep: A stereo-electroencephalographic study[END_REF]. For each arousal, onset and end were visually marked. As medial pulvinar nucleus is connected on the one hand to the reticular thalamus and to brainstem nuclei which belong to the ascending reticular activation system and on the other hand to limbic mesial temporal structures, the choice of this structure was particularly relevant to explore arousing reactions although we had already observed that clear arousing reactions could be also seen in other thalamic nuclei such as the lateral posterior nuclei [START_REF] Benarroch | Pulvinar: associative role in cortical function and clinical correlations[END_REF][START_REF] Peter-Derex | Heterogeneity of arousals in human sleep: A stereo-electroencephalographic study[END_REF]. In one patient (N°4), scalp EEG recording was also available, which allowed us to quantify sensitivity and specificity of thalamus-based arousal detection as compared to scalp EEG-based detection. S-EEG channel contacts selected for power analysis were located inside the hippocampus and the orbitofrontal cortex. All contacts considered in the present work were located outside the seizure onset zone and/or any structural brain lesion. In addition, all recordings were systematically reviewed by a board-certified neurophysiologist (LPD) to confirm that the EEG activity recorded in these contacts was free of epileptic interictal abnormalities, whatever the sleep stage considered.

Signal analyses

Temporal windows of interest -First analysis

This analysis was designed to assess the possible difference in the spectral content of the hippocampus signal between the 4 following time windows (Figure 2A). Such analysis entailed that the "bodies" of the ISAR time windows (see below) could be of different durations, but it allowed to assess a possible global evolution of the signal between the beginning and the end of the ISAR for the ISARs of all durations (i.e. ≥ 3s).

Baseline-tw.

This time window corresponded to the 10 seconds of sleep (N2 or REM) immediately preceding the ISAR (according to the ASDA definition [START_REF] Asda | EEG arousals: scoring rules and examples: a preliminary report from the Sleep Disorders Atlas Task Force of the American Sleep Disorders Association[END_REF]).

Onset-tw.

It was a 5s time window, starting 2s before and ending 3s after the onset of the thalamic arousal (T0). This choice resulted from 1) previous observation of early delta frequency increase in several cortical areas 1 to 2 s before thalamic activation and asynchrony between cortical areas during arousals [START_REF] Nobili | Dissociated wake-like and sleep-like electro-cortical activity during sleep[END_REF][START_REF] Peter-Derex | Heterogeneity of arousals in human sleep: A stereo-electroencephalographic study[END_REF], 2) the ASDA rules stating that the minimal duration for an arousal is 3s [START_REF] Asda | EEG arousals: scoring rules and examples: a preliminary report from the Sleep Disorders Atlas Task Force of the American Sleep Disorders Association[END_REF]. This allowed us to make sure that we were able to investigate the very beginning of the arousal in every studied area and Body-tw. This time window started at T0+3s and ended at arousal offset. The duration of this window was consequently variable between arousals/awakenings reactions and its longest possible duration was set at 1 min 57s i.e starting at T0+3s and ending at T0+2min. It shortest duration was set at 2s as we wanted to study frequencies over 0.5Hz.

Wake-tw.

A period of ten seconds of daytime wakefulness was randomly chosen for each patient among a 30 minutes period of quiet wakefulness selected during the evening before the recorded night, at least 30 min away from sleep onset, while patients were sitting in their bed, eyes open, watching TV. These non-overlapping 10 s segments were used to compare arousals with stabilized wakefulness (each segment was used no more than one time), and were merged for that purpose to the Baseline-Onset-Body segments.

-Second analysis This analysis was designed to assess the possible difference in the spectral content of the hippocampus signal in 5 seconds time windows at the beginning, the middle and the end of the ISAR (Figure 2B). Such analysis enabled to have a more precise idea of the evolution of the signal across time and to explore more specifically the last seconds of the ISAR (before falling asleep again) but it entailed that such analysis was only possible for the ISAR of 13s or longer.

* Baseline-tw. This time window corresponded to the 10s of sleep (N2 or REM) immediately preceding the ISAR (according to the ASDA definition ASDA, 1992). * Middle-tw. This 5 sec time window was centered on the middle of the ISAR i.e. at equal distance from T0 and the end of the ISAR.

* End-tw. This 5 sec time window started at the end of the ISAR minus 5s and ended at the ISAR offset.

Frequency bands of interest

The mean spectral power of the signal during each time window was calculated for each ISAR in the following frequency bands (FB): low-delta [0.5-1 Hz], delta [1.5-3.5 Hz], theta [4-7.5 Hz], alpha [8][9][10][11], sigma [12][13][14][15][16], beta and gamma . The choice of these frequency bands was supported by previous works about neocortex and hippocampus activity during sleep and wakefulness (B. [START_REF] Frauscher | Atlas of the normal intracranial electroencephalogram: neurophysiological awake activity in different cortical areas[END_REF][START_REF] Von Ellenrieder | How the Human Brain Sleeps: Direct Cortical Recordings of Normal Brain Activity[END_REF]. They notably enable to investigate rhythms typical of sleep like slow activity (slow delta and higher delta including the "rhythmic slow activity" described in the hippocampus during REM and wakefulness) but also spindles and gamma oscillations [START_REF] Bodizs | Rhythmic hippocampal slow oscillation characterizes REM sleep in humans[END_REF][START_REF] Brazier | Studies of the EEG activity of limbic structures in man[END_REF][START_REF] Cantero | Gamma EEG dynamics in neocortex and hippocampus during human wakefulness and sleep[END_REF]Birgit Frauscher et al., 2015;[START_REF] Montplaisir | Sleep spindles in the human hippocampus: normal or epileptic activity?[END_REF][START_REF] Moroni | Sleep in the human hippocampus: a stereo-EEG study[END_REF]Laure Peter-Derex, Comte, Mauguiere, & Salin, 2012).

Normalization

A normalization of the signal was performed to ensure that the power in the different frequency bands of interest, time windows and sleep stages could be compared within and across subjects. For each segment and each frequency band, we extracted the mean and standard deviation of the wake window. We used them to apply the geometric Z-score along all the segments. The geometric mean was preferred to the 13 arithmetic mean because it is less sensitive to extreme values and better suited to the distribution (normal log) of our data. Geometric Z-score was calculated in MATLAB® using the following formula

• = ln ( !) -ln (#) ln ($) geometric mean: µ = [ ∏ & ' = 1 ( ' ] 1 & geometric standard deviation: $ = ) !*+(ln (• ))
xs corresponds to each power value in the sleep and ISAR time windows xw corresponds to each power value in the wake windows Afterwards, average signal power during each time window of interest was extracted for each patient, each sleep stage, and each frequency band of interest.

Statistical analyses

Statistical analyses were conducted using R®. Our aim was to model spectral power (in several 1). We found that, for N2 ISAR, signal power in low delta [0.5-1 Hz], delta [1.5-3.5 Hz],

Results

F

and sigma [11.5-16 Hz] frequency bands was significantly lower during arousal reactions (onset and body) than during preceding sleep (except for low delta, which did not significantly differed from baseline), and remained significantly higher than during wakefulness. Gamma [60-128 Hz] power was higher during baseline N2 than during wakefulness and decreased significantly at the end of the ISAR as compared to baseline, whereas no or few differences were observed for theta [4-7.5 Hz], alpha [8][9][10][11] and beta [17-40 Hz] frequency bands, except for alpha power which was lower during both sleep, onset-tw and body-tw than during wake, and beta power which decreased in the second part of the ISAR (body-tw) as compared to baseline sleep and wake. For REM ISAR, signal power in low delta [0.5-1 Hz] band remained significantly higher during both baseline sleep, onset and body-tw than during wakefulness. In alpha, sigma and beta bands, signal power was lower during both baseline sleep and, for beta, body-tw, as compared to wakefulness whereas the very onset of the ISAR was similar to wakefulness. No significant differences between the four temporal windows were observed for delta, theta, and gamma bands.

Dynamic of hippocampal activity along the ISAR, from sleep back to sleep

In order to further explore intra-ISAR dynamics, we performed an analysis with 5 time windows including the onset, the middle and the last part of arousing reactions. For this second analysis, only 211 ISAR longer than 13s were selected: 16 N2 arousals, 114 N2 short awakenings, 9

REM arousals and 72 REM short awakenings. As previously, a significant interaction between frequency band, time window and sleep stage was found (Chi 2 = 107.4; p < 0.001). Results of post hoc comparisons are depicted Figure 4B and statistical data are detailed in Supplementary Table 2). Overall, we observed, for N2 ISAR, a decrease in low delta signal power from the onset to the middle part of the ISAR and a stagnation in the end-part was observed, but power during this end-part remained significantly higher than during wakefulness. For delta and sigma, signal power was lower than during sleep and higher than during wakefulness for each intra-ISAR time window. For theta band, signal power remained stable across temporal windows, and for alpha band it remained overall at lower values than during wakefulness, without any evident dynamics within the ISAR. For beta band, only the middle-tw exhibited a lower signal power than both baseline-tw and wake-tw. Finally, a progressive decrease in signal power in gamma band was observed from the beginning to the end of the ISAR but only baseline and wakefulness significantly differed, with higher gamma power during sleep. For REM ISAR, signal power in low delta was higher during baseline sleep and during each intra-ISAR time window than during wakefulness and even higher during onset-tw than during baseline sleep and middle-tw. No difference between the five temporal time windows was observed for delta, theta, and gamma bands, and few differences were observed for alpha, sigma and beta bands with overall a stable intra-arousal profile.

Prefrontal cortex activity during thalamic Intra Sleep Awakening Reactions

Prefrontal signal during ISAR differs from both wakefulness and baseline sleep in N2 only

Like in the hippocampus, a significant interaction between frequency band, time window and sleep stage was found (Chi 2 = 285.9; p < 0.0001). Results of post hoc comparisons are depicted in Figure 5A and statistical data are detailed in Supplementary Table 3. For N2 ISAR, an early increase in signal power was observed between baseline sleep and ISAR onset, significant for delta but also for theta, sigma and gamma band. Then, a decrease in signal power in low delta, delta, sigma bands was found between the onset and the end of the arousal and between the end of the arousal and wakefulness. For all these frequency bands, power values were higher during baseline sleep than during wakefulness. No differences between time windows were observed for alpha and beta frequencies. For REM ISAR, no differences between time windows were observed, except for a slight increase in delta frequencies during the ISAR onset as compared to baseline sleep (ns, p = 0.053) and to the end of the arousal (p = 0.017).

Dynamic of frontal activity along the ISAR, from sleep back to sleep

A significant interaction between frequency band, time window and sleep stage was also found for the 5 time windows analysis (Chi 2 = 179.4; p < 0.0001). Results of post hoc comparisons are depicted Figure 5B and statistical data are detailed in Supplementary Table 4. This complementary analysis confirmed the profile described above, and added information about the very last part of the arousal in N2 ISAR. It showed that, for low delta and delta, whereas a progressive decrease in signal power between onset and middle time windows was found, no further decrease was observed for the last time window, with rather a non-significant reincrease (low delta) or a stagnation (delta) in power values. These values remained higher than during wakefulness. In contrast, for all higher frequency bands (theta to gamma), signal power during the last time window did not differ from wakefulness. For REM ISAR, no difference between the five time windows was observed. window with the wake time window. In N2, the early increase in low and fast frequencies at the beginning of the ISAR was more intense for long than for short ISAR (delta, p = 0.046; theta, p = 0.0008; sigma, p < 0.0001; gamma, p < 0.0001) and the decrease in signal power in these frequency bands was also greater during the second part of long than short ISAR (low delta, p < 0.0001; delta, p < 0.0001; sigma, p < 0.0001, gamma, p = 0.0003). Interestingly, the difference between the last part of long ISAR and wake was lower than the difference between the last part of short ISAR and wake in delta and sigma bands (low delta, p = 0.0002; delta, p < 0.0001; sigma, p = 0.0003). In REM, long and short ISAR differed in delta and sigma band, where the increase in signal power between baseline sleep and onset time window and the decrease between onset and body time window were higher for long than for short events (p = 0.003 and p = 0.001 respectively for delta and p = 0.011 and p = 0.023 respectively for sigma).

A highly significant linear positive correlation between the intensity of the initial change in spectral power and ISAR duration was found in N2 for theta and sigma bands (r = 0.23 95% CI [0.12; 0.33], p=<0.0001 and r = 0.24 95% CI [0.13; 0.34], p=<0.0001 respectively).

Discussion

Awakening as a progressive and local process

We found that EEG activity during N2 arousals and awakenings in the hippocampus and the prefrontal cortex differs from both sleep and wakefulness in most frequency bands and that the pattern of activation exhibits specificities associated to each anatomical structure. The study of transitions between vigilance states in animals and humans, using electrophysiological and intracranial studies, have brought strong arguments in favor of progressive rather than clear-cut switches from one state to another, underpinned by both spatial ("local wake" or "local sleep" in different areas) and temporal (mixed wake-like and sleep-like activity within the same structure) heterogeneities (M. [START_REF] Magnin | Thalamic deactivation at sleep onset precedes that of the cerebral cortex in humans[END_REF][START_REF] Nobili | Dissociated wake-like and sleep-like electro-cortical activity during sleep[END_REF][START_REF] Peter-Derex | Heterogeneity of arousals in human sleep: A stereo-electroencephalographic study[END_REF]Sarasso, Pigorini, et al., 2014;[START_REF] Vyazovskiy | The dynamics of cortical neuronal activity in the first minutes after spontaneous awakening in rats and mice[END_REF]. With respect to sleep onset, an asynchrony between cortical regions, between the cortex and the thalamus, and between the cortex and the hippocampus has been reported ( [START_REF] Magnin | Thalamic deactivation at sleep onset precedes that of the cerebral cortex in humans[END_REF]Sarasso, Proserpio, et al., 2014). Imaging and EEG studies in humans have suggested that awakening was also a progressive process associated with the sequential re-activation of brain structures and the persistence of sleep slow oscillations, all of these components underlying the phenomenon of sleep inertia [START_REF] Balkin | The process of awakening: a PET study of regional brain activity patterns mediating the re-establishment of alertness and consciousness[END_REF][START_REF] Marzano | Electroencephalographic sleep inertia of the awakening brain[END_REF][START_REF] Vallat | Hard to wake up? The cerebral correlates of sleep inertia assessed using combined behavioral, EEG and fMRI measures[END_REF]. However, few S-EEG studies have specifically studied the sleep-to-wake transition except in pathological situations such as parasomnia [START_REF] Flamand | Confusional arousals during non-rapid eye movement sleep: evidence from intracerebral recordings[END_REF][START_REF] Terzaghi | Evidence of dissociated arousal states during NREM parasomnia from an intracerebral neurophysiological study[END_REF]. Regarding physiological awakening from NREM sleep, Magnin et al. did not report thalamo-cortical nor intra-cortical asynchrony, but it is possible that the dimension of activation (which was used to quantify signal complexity and to differentiate vigilance states) was not suitable to explore brief events such as arousals and short awakenings (M. [START_REF] Magnin | Thalamic deactivation at sleep onset precedes that of the cerebral cortex in humans[END_REF].

Local phenomena may however occur during arousing processes as Nobili et al. reported shortlasting local activations during NREM sleep in the motor cortex (blockage of slow waves and increase in alpha-beta frequencies) whereas other areas, especially the dorsolateral prefrontal cortex, exhibited an increase in slow wave activity [START_REF] Nobili | Dissociated wake-like and sleep-like electro-cortical activity during sleep[END_REF]. In a previous study on arousals recorded in the thalamus and in the cortex, we also observed local arousals and found that the level of "activation", as assessed by the spectral composition of the signal, differed between the arousals and wakefulness (L. [START_REF] Peter-Derex | Heterogeneity of arousals in human sleep: A stereo-electroencephalographic study[END_REF].

In the present study, we confirm the local specificities in arousals, including the particular "mixed slow wave and fast frequencies" activity observed at the onset of the arousal in the

Short awakenings as dynamic events

The difference between wakefulness and ISAR in hippocampus and prefrontal cortex activity may not only reflect an "inertia" effect, but also the fact that arousals and short awakenings are, by definition, unstable, heterogeneous and transient processes: they reflect both sleep-to-wake and wake-back-to-sleep phenomena. Indeed, we observed an intra-ISAR dynamics, as demonstrated by the differences observed in several frequency bands between the onset, the middle and/or the end of the arousing reaction. Interestingly, this dynamics differed between frequency bands and between structures. For example, in frontal cortex, a strong decrease in spectral power was observed in many frequency band (low and fast activities) between the onset and the middle of N2 ISAR but the last part was marked by a stagnation (or even a nonsignificant re-increase for low delta) in signal power. In hippocampus N2 ISAR, the arousing reaction was associated with an early decrease in some specific sleep oscillations (delta and sigma). In contrast, a decrease during the second part of the ISAR (body-tw for gamma and 23 beta power) was found in fast activities as compared to baseline whereas this decrease was not observed at the arousal onset. This decrease in gamma power in the hippocampus might be due to a decrease in ripples, which characterize the activity of the hippocampus during NREM and are believed to play a key role in long term memory consolidation processes [START_REF] Axmacher | Ripples in the medial temporal lobe are relevant for human memory consolidation[END_REF][START_REF] Cantero | Gamma EEG dynamics in neocortex and hippocampus during human wakefulness and sleep[END_REF]Zsofia Clemens et al., 2007;[START_REF] Staresina | Hierarchical nesting of slow oscillations, spindles and ripples in the human hippocampus during sleep[END_REF]. Such differences in temporal dynamics between distinct oscillations within a single brain structure may be associated with functional specificities of transitional stages. It can be hypothesized that the functional impairment associated with sleep fragmentation is not only the consequence of a decrease in the sleep time spent in different stages but also of an increased duration of these transitional states where neither wakefulness nor sleep activity (nor stage-specific related functions) are fully re-instored [START_REF] Bonnet | Clinical effects of sleep fragmentation versus sleep deprivation[END_REF][START_REF] Stepanski | Sleep fragmentation and daytime sleepiness[END_REF].

Sleep stage matters

Regarding full awakening, sleep inertia has been reported to be more pronounced in N3 than in REM sleep than in N2/N1 [START_REF] Tassi | Sleep inertia[END_REF][START_REF] Vallat | Hard to wake up? The cerebral correlates of sleep inertia assessed using combined behavioral, EEG and fMRI measures[END_REF]. In the present study, we also observed that the hippocampus and the prefrontal cortex activity during transitions between sleep and wakefulness depends on the ongoing sleep stage. In particular, few differences in S-EEG signal were observed for REM sleep ISAR between baseline sleep, arousing reactions and full wakefulness. This could suggest that no arousing reaction occurred in the hippocampus or in the frontal cortex at the time of thalamic arousals; however, the observation of significant changes in some frequency bands (increase in low delta frequency at the onset of the arousal in the hippocampus and decrease in delta between the first and the last part of the arousal in the prefrontal cortex) indicates that the modification in thalamic activity was associated with some subtle changes in hippocampo-frontal structures activity. This findings echoes our previous work about cortical heterogeneity in arousing patterns, as we different from wake and REM sleep activity may be explained by the fact that the spectral composition of the signal is more similar between REM and wakefulness than between NREM and wakefulness. This finding is in line with previous works about the prefrontal and hippocampus activity according to vigilance stages, explored with intracranial recordings although, unlike in our study, no direct comparison between stages was reported [START_REF] Von Ellenrieder | How the Human Brain Sleeps: Direct Cortical Recordings of Normal Brain Activity[END_REF]. Specifically, a particular slow oscillation has been described during both wakefulness and REM in the hippocampus, and referred as a "rhythmic slow activity"

(1.5-3 Hz) which may be the counterpart of the theta activity observed in rodents [START_REF] Bodizs | Rhythmic hippocampal slow oscillation characterizes REM sleep in humans[END_REF][START_REF] Brazier | Studies of the EEG activity of limbic structures in man[END_REF][START_REF] Clemens | Phase coupling between rhythmic slow activity and gamma characterizes mesiotemporal rapid-eyemovement sleep in humans[END_REF][START_REF] Moroni | Sleep in the human hippocampus: a stereo-EEG study[END_REF][START_REF] Watrous | A comparative study of human and rat hippocampal low-frequency oscillations during spatial navigation[END_REF]. This delta activity has been associated with specific cognitive functions such as navigation and memory formation [START_REF] Brazier | Studies of the EEG activity of limbic structures in man[END_REF][START_REF] Lega | Human hippocampal theta oscillations and the formation of episodic memories[END_REF][START_REF] Watrous | A comparative study of human and rat hippocampal low-frequency oscillations during spatial navigation[END_REF].

Gamma oscillations are also observed in both REM and wakefulness [START_REF] Mari | Continuous high-frequency activity in mesial temporal lobe structures[END_REF]. We found that only alpha to beta frequencies differed significantly between REM and wakefulness, with higher spectral power during the latter state.

This proximity between REM sleep and wakefullness activity in the hippocampus, also found in the prefrontal cortex, may facilitate the transition between these two stages in these structures. This may contribute to the difference in dream recall between NREM and REM awakenings (J. B. Eichenlaub et al., 2014;[START_REF] Nielsen | A review of mentation in REM and NREM sleep: "covert" REM sleep as a possible reconciliation of two opposing models[END_REF][START_REF] Stickgold | Brain-mind states: I. Longitudinal field study of sleep/wake factors influencing mentation report length[END_REF]) by allowing during arousals from REM sleep a faster reinstatement of encoding functions thought to be impaired during sleep [START_REF] Diekelmann | The memory function of sleep[END_REF]Tononi & Cirelli, 2014).

Awakening duration depends on the very first seconds of the arousing reaction

Every studied ISAR ended with a come back to sleep. However, the time needed to reach sleep again differed between arousals and awakenings. While no clear difference between short and long ISAR could be seen in the hippocampus, the duration of the ISAR was associated with the intensity of the early arousing reaction in the prefrontal cortex and the strength of the decrease in slow and fast oscillations during the second part of the event, with longer events being associated with the restoration of an activity closer to wakefulness. This result may appear as paradoxical but it refers to the complex nature of arousal (P. [START_REF] Halasz | The nature of arousal in sleep[END_REF]). The early delta increase observed during the first seconds of the arousal may correspond to a slow reactive grapho-element (K-complex or delta burst) which is mixed with high frequency activities (P. [START_REF] Halasz | Spectral features of evoked microarousals[END_REF][START_REF] Latreille | The human K-complex: Insights from combined scalp-intracranial EEG recordings[END_REF]. As the arousal reaction evolves, delta power decrease and get closer to wakefulness values. At the same time, a decrease in sigma band, corresponding to spindles which are suppressed during arousals, is observed. Thus, the very beginning of the arousing reaction in the prefrontal cortex led to different trajectories back to sleep with a positive correlation between the intensity of this initial activation and the duration of the ISAR in N2. ISAR duration, reflecting the time needed to restore sleep, may be related to the relative balance between arousal and anti-arousal processes engaged from the very onset of the arousing reaction. Individual differences in brain reactivity to auditory stimuli during sleep, as assessed by the amplitude of cognitive evoked potentials, have been reported between high and low dream recallers: a higher reactivity would enable a longer awakening duration and thus allow for a greater brain "re-activation" necessary for encoding and consolidating dream content (Raphael Vallat et al., 2017).

Limitations

Several limitations should be kept in mind when interpreting the present findings. First, the results were obtained in patients with epilepsy taking anti-seizure drugs with more disrupted Although we applied very strict criteria for hippocampus and orbitofrontal channels selection, we cannot definitely rule out the fact that the underlying epileptic condition may have influenced arousing processes on a quantitative (arousal threshold) or qualitative (spectral composition of the signal) way. However, all works about electrophysiological activity in the hippocampus during wakefulness and sleep have used such a methodology as intracranial recordings are obviously only performed for clinical purposes [START_REF] Bodizs | Rhythmic hippocampal slow oscillation characterizes REM sleep in humans[END_REF][START_REF] Brazier | Studies of the EEG activity of limbic structures in man[END_REF][START_REF] Moroni | Sleep in the human hippocampus: a stereo-EEG study[END_REF]Sarasso, Proserpio, et al., 2014). Moreover, our results are in line with non-invasive scalp EEG works about sleep-wake transition, which demonstrated a progressive restoration of wakefulness activity [START_REF] Marzano | Electroencephalographic sleep inertia of the awakening brain[END_REF][START_REF] Vallat | Hard to wake up? The cerebral correlates of sleep inertia assessed using combined behavioral, EEG and fMRI measures[END_REF].

Last, our findings about wake and sleep activity in the hippocampus and the frontal cortex are consistent with results reported by many other groups in patients taking different types of antiseizure drugs, which argues for the fact that main EEG features of vigilance states are robust [START_REF] Bodizs | Rhythmic hippocampal slow oscillation characterizes REM sleep in humans[END_REF][START_REF] Brazier | Studies of the EEG activity of limbic structures in man[END_REF][START_REF] Frauscher | Atlas of the normal intracranial electroencephalogram: neurophysiological awake activity in different cortical areas[END_REF][START_REF] Moroni | Sleep in the human hippocampus: a stereo-EEG study[END_REF][START_REF] Von Ellenrieder | How the Human Brain Sleeps: Direct Cortical Recordings of Normal Brain Activity[END_REF]. Another limitation is the small number of patients, which is the counterpart of our strict selection criteria: however, the high number of arousals/awakenings allowed us to overcome this limitation. We also acknowledge that we investigated the hippocampus activity during thalamic arousals without assumptions about the presence or not of a concomitant detectable scalp EEG arousal (we provide nonetheless in one patient data and figures which suggest a good correspondence between the thalamic and scalp EEG arousals).

As arousals have been shown to be local phenomena [START_REF] Nobili | Dissociated wake-like and sleep-like electro-cortical activity during sleep[END_REF][START_REF] Peter-Derex | Heterogeneity of arousals in human sleep: A stereo-electroencephalographic study[END_REF] it is not clear what is best, the use of scalp EEG or of S-EEG activity from selected cortical brain area to detect arousals. There is currently no ideal brain structure to identify ISAR or gold standard strictly and precisely defining arousals at the local and global level. However, the particular connection of the medial pulvinar thalamus with subcortical, cortical and limbic 27 structures makes the thalamus a good candidate for a pertinent structure to detect arousal in the context of hippocampus activity study [START_REF] Benarroch | Pulvinar: associative role in cortical function and clinical correlations[END_REF][START_REF] Gattass | Modulation of Pulvinar Neuronal Activity by Arousal[END_REF].

Finally, the fact that this study was retrospective did not allow us to standardize arousals regarding the trigger (all arousals were "spontaneous", i.e. we do not know what internal or external stimulation had triggered them) and to explore the cognitive correlates of our findings, regarding memory of arousing reactions for example.

Conclusions

As a conclusion, thanks to the unique opportunity of simultaneous recordings of the thalamus and of healthy hippocampus and prefrontal cortex in humans, we found that awakening from sleep in the hippocampus and orbitofrontal cortex is a progressive and dynamic process, modulated by the stage of sleep and, in the frontal cortex, by the intensity of the initial arousing response. Such findings may explain variability in dream recall, REM sleep-related and longer awakenings allowing the hippocampus activity to get closer to wakefulness activity and thus to recover encoding and consolidation functions. These results are in line with dream recall theories regarding the key role of brain reactivity and awakening length in memory formation [START_REF] De Gennaro | Recovery sleep after sleep deprivation almost completely abolishes dream recall[END_REF]J.-B. Eichenlaub et al., 2014;[START_REF] Ruby | Alpha reactivity to first names differs in subjects with high and low dream recall frequency[END_REF]Raphael Vallat et al., 2017). Further studies will be necessary to confirm this hypothesis. Notably, the investigation in the same study of the activity in memory-related brain areas, and of functional connectivity between these areas, along with subjective perception and memory of arousals/awakenings and of dreams would help to understand which particular activity is critical to these cognitive processes. For the first analysis (A), body time window (body-tw, variable duration, min 2s, max 1min57s) is represented in orange. For the second analysis (B), the 5s long middle-tw (5s in the middle of the ISAR) and end-tw (5 last seconds of the ISAR) are represented in orange.

F

The vertical red dashed line represents the onset of the thalamic-detected arousal reaction. In N2, sleep spindles are observed in the thalamus and the hippocampus structures (black arrows). In REM, the typical high delta activity is observed in the thalamus. Note the discrete asynchrony between the three structures: in the N2 example, the increase in high frequencies in the hippocampus (dashes black arrow) and a high amplitude slow wave in the prefrontal cortex (dotted black arrow) precede the ISAR onset of the thalamus; in the REM example, the increase in high frequencies in the hippocampus (dashes black arrow) is observed before the ISAR onset in the thalamus, while few modifications are observed in the prefrontal cortex. 1 and2). 3 and4). Statistically significant differences between arousals and short awakenings for contrast between baseline-tw and onset-tw, between onset-tw and body-tw and between body and wake-tw are indicated with stars. In N2, and in a less extent in REM, longer ISAR are associated with a greater early increase and greater secondary decrease in low and fast activities, with activity during the second part of the arousing reaction being closer to wake-like activity than is the case for short ISAR. In REM, the typical high delta activity is observed in the thalamus. Note the discrete asynchrony between the three structures: in the N2 example, the increase in high frequencies in the hippocampus (dashes black arrow) and a high amplitude slow wave in the prefrontal cortex (dotted black arrow) precede the ISAR onset of the thalamus; in the REM example, the increase in high frequencies in the hippocampus (dashes black arrow) is observed before the ISAR onset in the thalamus, while few modifications are observed in the prefrontal cortex. Figure 3B. Time frequency-representation of ISAR ordered by duration in the same patient in N2. The signal power in the delta band is represented in the thalamus, in the hippocampus and in the prefrontal cortex. N arousals are ordered by duration so that the shortest is at the top and the longest is at the bottom. White 1 and2). 3 and4). Statistically significant differences between arousals and short awakenings for contrast between baseline-tw and onset-tw, between onset-tw and bodytw and between body and wake-tw are indicated with stars. In N2, and in a less extent in REM, longer ISAR are associated with a greatest early increase and greatest secondary decrease in low and fast activities, with activity during the second part of the arousing reaction being closer to wake-like activity than is the case for short ISAR.

  focused our analyses on electrodes leads located inside the hippocampus and in the orbitofrontal cortex which was explored in all patients (ipsilateral to the hippocampus selected for our study in 3 patients). In each patient, stereotactic coordinates electrode contacts were reported within the anatomical model of normal brain proposed by the McConnell Brain Imaging Center of the Montréal Neurological Institute (MNI), McGill University

  script S-EEG files were segmented into pieces including the whole ISAR and ten seconds of the preceding sleep. The spectral analysis of the SEEG signal of the hippocampus and of the orbitofrontal cortex was performed on bipolar derivation (adjacent contacts of the S-EEG electrode) with Morlet wavelet transform between 0.5 and 128 Hz (step = 1 sample; frequency resolution = 0.5 Hz; ω [width of the wavelet, determines the temporal and spectral resolution] = 7 Hz; σ [the length of the used wavelets in standard deviations of the implicit Gaussian kernel] = 3 sec).

  not include any early arousing activity in the baseline time window. As a result, the baseline started -12 sec and ended -2 sec before the onset of the thalamic arousal.

  frequency bands) of the hippocampus and the orbitofrontal cortex S-EEG signal between different sleep stages (N2 and REM sleep), time windows (Baseline, Onset, Body and Wake or Baseline, Onset, Midde, End, and Wake) and ISAR type (arousal and short awakenings) within a subject. To take into account possible variability of power in the frequency bands of interest and in the sleep stage, ISAR type and time window effects between subjects, we used a Linear mixed-effects model (lme4 package, Linear Mixed Effects version 4;Bates et al., 2015). We accounted for the heterogeneity of power values by defining them as effects with a random intercepts and slopes, thus instructing the model to correct for any systematic differences between these variability. To confirm the need for mixed, nested model, a likelihood ratio test, Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to test and after sequential addition of random effects. To optimize our model, we checked the normality of the model residual.We analyzed the influence of four possible fixed effects on power: (i) sleep stage (two levels: N2 and REM sleep); (ii) frequency band (seven levels: [0.5-1]Hz, [1.5-3.5]Hz, [4-7.5]Hz, [8-11]Hz, [11.5-16]Hz, [17-40]Hz and [60-128]Hz); (iii) time window (four or five levels:Baseline, Onset, Body and Wake or Baseline, Onset, Midde, End, Wake) and (iiii) ISAR type (two levels: arousal (3s to 15s) and short awakening (15s to 2min)). We ran a type III analysis of variance. Wald chi-square tests were used (Car package, version 3.0-0; Fox and Weisberg, 2011) for fixed effects in linear mixed-effects models.For post hoc tests we used the Lsmean package(Lsmean version 2.20-23; Searle et al., 1980).For most of the post hoc tests, we contrasted signal power in each specific frequency band and sleep stage in two conditions (Win 2 -Win 1 where Win 1 and Win 2 are two time windows). We used a complex contrast to highlight the ISAR duration effect according to time window factor for each sleep stage and frequency band (Win 2 -Win 1 ) awakening -(Win 2 -Win 1 ) arousals . We computed the correlation between the intensity of the initial change in spectral power (contrast onset -baseline) and the duration of the ISAR with a Pearson's correlation test. The significance threshold was set p < 0.05 and we take the correlation of the model parameters into account.Dealing with General Linear Hypothesis, we use the model error (from the variance-covariance matrix of the main parameters of a fitted model). The random effect model that we used allowed us to model power variability between different sleep stage, time windows and ISAR type within a subject. The fixed effect represent the mean effect across all subjects after residual variability was removed and takes the correlation of the model parameters into account.

  on the intensity of the first seconds of the arousal reaction in the frontal cortexIn order to compare the dynamics of EEG signal in the hippocampus and in the prefrontal cortex between short (≤15 s i.e. arousal) and long (>15 s) ISAR, we explored the interaction between type of ISAR (arousal or short awakening), frequency band, sleep stage and time window. This interaction was significant in the prefrontal cortex only (Chi 2 = 40.0; p = 0.01). Visual examination of results presented in Figure6prompted us to contrast more specifically the onset time window with baseline sleep and with the body time window, as well as the body time

  changes in frontal area between baseline REM sleep and arousals whereas, at the same time, obvious modifications (especially in alpha band) were found in posterior areas (L.[START_REF] Peter-Derex | Heterogeneity of arousals in human sleep: A stereo-electroencephalographic study[END_REF]. The fact that, unlike what was observed for NREM sleep arousals, both prefrontal cortex and hippocampus activities during REM sleep arousals were not very

  individuals as evidenced by the high number of ISAR detected in our study.

(

  Figures legends

Figure 2 .

 2 Figure 2. Temporal windows of interest for analyses of Intra-Sleep Arousal Reactions

  presented in the middle of the figure (patient #1), the intra-sleep arousal reaction occurs in N2 (see the thalamic and prefrontal cortex spindles, black arrows). A slow wave is observed in the prefrontal cortex just before the thalamic arousal onset (dotted black arrow).

Figure 3 .Figure 3A .

 33A Figure 3. Examples Intra-Sleep Arousal Reactions (ISAR) in the hippocampus and in the

Figure 3B .Figure 4 .

 3B4 Figure 3B. Time frequency-representation of ISAR ordered by duration in the same patient in

Figure 4A :

 4A Figure 4A: First analysis, during selected temporal windows: baseline-tw, onset-tw and body-

Figure 4B :

 4B Figure 4B: Second analysis, during selected temporal windows: baseline-tw, onset-tw, middle-

Figure 5 .

 5 Figure 5. Evolution of spectral power of the signal during sleep, Intra-Sleep Arousal

Figure 5A :

 5A Figure 5A: First analysis, during selected temporal windows: baseline-tw, onset-tw and body-

Figure 5B :

 5B Figure 5B: Second analysis, during selected temporal windows: baseline-tw, onset-tw, middle-

Figure 6 .

 6 Figure 6. Evolution of spectral power of the signal during sleep, Intra-Sleep Arousal

Figure 1 .Figure 2 .Figure 3 .

 123 Figure 1. Recording contact locations represented on MNI Brain template and Morel's thalamic atlas. The reconstruction of hippocampus, orbito-frontal cortex and thalamus contacts locations on the MNI brain template is presented for the 4 patients. For the thalamus, left and right side are merged in the zoom window which shows the location of the different nuclei on the Morel's atlas. R=right L=left. Each color refers to a patient: Patient 1: blue circle; patient 2: red circle; patient 3: green circle; patient 4: yellow circle. Thalamic nuclei: PuM = medial pulvinar; CL = central lateral; L = lateral posterior; VLp = ventral lateral posterior. The two horizontal lines indicates the positions of the anterior and posterior commissures. D8.1: horizontal plane 8.1 mm dorsal to the horizontal inter-commissural plane.

Figure 4 .

 4 Figure 4. Evolution of spectral power of the signal during sleep, Intra-Sleep Arousal Reactions (ISAR) and wakefulness in the hippocampus. Mean power (± sd) in different frequency bands (from low delta to gamma).Figure 4A: First analysis, during selected temporal windows: baseline-tw, onset-tw and body-tw, and waketw. Figure 4B: Second analysis, during selected temporal windows: baseline-tw, onset-tw, middle-tw, end-tw and wake-tw. Transparent circle: N2 sleep; Black circle: REM sleep Significant differences between time windows (adjusted p-values) are presented on the figure with horizontal lines located at the top (N2) or the bottom (REM) of each frequency-band graph (detailed statistical analyses are presented in supplementary Tables1 and 2).

Figure 4A :

 4A Figure 4. Evolution of spectral power of the signal during sleep, Intra-Sleep Arousal Reactions (ISAR) and wakefulness in the hippocampus. Mean power (± sd) in different frequency bands (from low delta to gamma).Figure 4A: First analysis, during selected temporal windows: baseline-tw, onset-tw and body-tw, and waketw. Figure 4B: Second analysis, during selected temporal windows: baseline-tw, onset-tw, middle-tw, end-tw and wake-tw. Transparent circle: N2 sleep; Black circle: REM sleep Significant differences between time windows (adjusted p-values) are presented on the figure with horizontal lines located at the top (N2) or the bottom (REM) of each frequency-band graph (detailed statistical analyses are presented in supplementary Tables1 and 2).

Figure 5 .

 5 Figure 5. Evolution of spectral power of the signal during sleep, Intra-Sleep Arousal Reactions (ISAR) and wakefulness in the prefrontal cortex. Mean power (± sd) in different frequency bands (from low delta to gamma).Figure 5A: First analysis, during selected temporal windows: baseline-tw, onset-tw and body-tw, and waketw. Figure 5B: Second analysis, during selected temporal windows: baseline-tw, onset-tw, middle-tw, end-tw and wake-tw. Transparent circle: N2 sleep; Black circle: REM sleep Significant differences between time windows (adjusted p-values) are presented on the figure with horizontal lines located at the top (N2) or the bottom (REM) of each frequency-band graph (detailed statistical analyses are presented in supplementary Tables3 and 4).

Figure 5A :

 5A Figure 5. Evolution of spectral power of the signal during sleep, Intra-Sleep Arousal Reactions (ISAR) and wakefulness in the prefrontal cortex. Mean power (± sd) in different frequency bands (from low delta to gamma).Figure 5A: First analysis, during selected temporal windows: baseline-tw, onset-tw and body-tw, and waketw. Figure 5B: Second analysis, during selected temporal windows: baseline-tw, onset-tw, middle-tw, end-tw and wake-tw. Transparent circle: N2 sleep; Black circle: REM sleep Significant differences between time windows (adjusted p-values) are presented on the figure with horizontal lines located at the top (N2) or the bottom (REM) of each frequency-band graph (detailed statistical analyses are presented in supplementary Tables3 and 4).

Figure 6 .

 6 Figure 6. Evolution of spectral power of the signal during sleep, Intra-Sleep Arousal Reactions (ISAR) andwakefulness in the prefrontal cortex according to the duration of ISAR Signal power in selected time windows (baseline-tw, onset-tw and body-tw, and wake-tw) is shown in the prefrontal cortex for arousals (3 to 15 s, transparent circles and dotted lines) and awakening (15 s to 2 min, full circles, continuous line) in N2 (black) and REM (grey) sleep. Statistically significant differences between arousals and short awakenings for contrast between baseline-tw and onset-tw, between onset-tw and bodytw and between body and wake-tw are indicated with stars. In N2, and in a less extent in REM, longer ISAR are associated with a greatest early increase and greatest secondary decrease in low and fast activities, with activity during the second part of the arousing reaction being closer to wake-like activity than is the case for short ISAR.

Table 1 .

 1 All patients suffered from temporal lobe epilepsy. The hippocampus selected for the study was contralateral to the epileptic hemisphere in 3 patients, homolateral but only late involved in the seizure propagation in the remaining patient.

	Clinical characteristics of the patients are described in Intra Sleep Awakening Reactions detection
	Six hundred and seventeen thalamic ISAR were selected during the four whole nights analyzed:
	379 in N2, 38 in N3 and 200 in REM sleep (respectively, in patient 1: 121, 16 and 39; in patient
	2: 105, 7 and 65; in patient 3: 30, 3 and 62 and in patient 4: 123, 12 and 34). Examples of
	o r
	P e
	e r
	R e
	v i e
	w
	ISAR lasted between 3 and 25 sec, with a median duration of 11.1 s (interquartile range 15.1 s)
	and a mean ± sd duration of 20.6 ± 25.5 s for N2 and REM ISAR together (median 10.7 s in
	N2 and 12.5 s in REM). Time-frequency representations of ISAR according to their duration
	are shown in Figure 3B.
	Hippocampus activity during thalamic Intra Sleep Awakening Reactions
	15

NREM and REM arousals observed in scalp EEG and S-EEG are presented in the supplementary Figure. The low number of ISAR in N3 prevented us from performing analyses in this stage, and no ISAR was selected for analysis in N1 because of the difficulty to recognize this sleep stage in S-EEG recordings, especially given local aspects of sleep during transition states with possible discrepancies between thalamic and cortical activity and between cortical areas (M. Magnin et al., 2010). The following results therefore relate to N2 and REM sleep ISAR. Examples of hippocampal EEG activity during ISAR selected upon thalamic activity in N2 and REM sleep are presented in Figure 3A. In patient 4, availability of scalp EEG recordings allowed us to quantify the sensitivity (99%) and the specificity (86%) of thalamus-based detection of arousals as compared to scalp EEG-based detection. Most selected wakefulness was quite similar in REM sleep (except for low delta), whereas it differed in many frequency bands, especially low delta, delta, sigma and gamma, in N2. Results of Post hoc comparisons are depicted in Figure 4A and statistical data are detailed in Supplementary Table

Table 1 :

 1 clinical and demographic characteristics of the patients

	o r
	P e
	e r
	R e
	v i e
	w

Funding Statement

No funding was received for this study

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Ethics approval statement and patient consent statement

The procedure was approved by the national Ethics Committee (Comité de Protection des Personnes CPP 09-CHUG-12, no 0907).

Patients were fully informed and gave written informed consent for the use of intra-cerebral recordings for research purposes.

Contributions of the authors:

Perrine Ruby, Romain Bouet and Laure Peter-Derex: research design, data analysis, writingediting.

Mickël Eskinazi: data analysis, writing-editing. -In N2, the arousal consists in a desynchronized fast activity observed in every intracranial channels and in scalp; note the mixed slow waves in all channels except for the thalamus.

contrasts with the preceding slow waves, whereas mixed slow and fast activities are observed at the same time in the hippocampus, the orbitofrontal cortex and scalp channels (black arrow).

-In REM, the very particular slow activity in the thalamus allows for a clear temporal delimitation of the arousal, which is also observed in the hippocampus and orbitofrontal cortex (increase in fast frequencies) as well as scalp channels (alpha activity). Note the electromyographic artifacts (dotted black arrow) in the scalp EEG where the arousal seems to start 1 second before the thalamic arousal.

Supplementary Table 1. Comparison of spectral power between four time windows (first analysis) in the hippocampus

Supplementary