Ketamine affects homeostatic sleep regulation in the absence of the circadian sleep-regulating component in freely moving rats

Pharmacological effects of ketamine may affect homeostatic sleep regulation via slow wave related mechanisms. In the present study effects of ketamine applied at anesthetic dose (80 mg/kg) were tested on neocortical electric activity for 24 h in freely moving rats. Ketamine effects were compared to changes during control (saline) injections and after 6 h gentle handling sleep deprivation (SD). As circadian factors may mask drug effects, an illumination protocol consisting of short light-dark cycles was applied. Ketamine application induced a short hypnotic stage with characteristic slow cortical rhythm followed by a long-lasting hyperactive waking resulting pharmacological SD. Coherence analysis indicated an increased level of local synchronization in broad local field potential frequency ranges during hyperactive waking but not during natural- or SD-evoked waking. Both slow wave sleep and rapid eye movement sleep were replaced after the termination of the ketamine effect. Our results show that both ketamine-induced hypnotic state and hyperactive waking can induce homeostatic sleep pressure with comparable intensity as 6 h SD, but ketamine-induced waking was different compared to the SD-evoked one. Both types of waking stages were different compared to spontaneous waking but all three types of wakefulness can engage the homeostatic sleep regulating machinery to generate sleep pressure dissipated by subsequent sleep. Current-source density analysis of the slow waves showed that cortical transmembrane cur- rents were stronger during ketamine-induced hypnotic stage compared to both sleep replacement after SD and ketamine application, but intracortical activation patterns showed only quantitative differences. These findings may hold some translational value for human medical ketamine applications aiming the treatment of depression-associated sleep problems, which can be alleviated by the homeostatic sleep effect of the drug without the need for an intact circadian regulation.


Introduction
Ketamine is a frequently used dose-dependent surgical anesthetic agent with profound analgesic-but absent sedative effect (Rebuelto et al., 2002). Its main mechanism of action is noncompetitive antagonism on the N-methyl D-aspartic acid (NMDA) receptor. Ketamine also interacts with opioid receptors, monoamine, cholinergic, purinergic and adrenoreceptor systems and has a local anesthetic effects (Ahnaou et al., 2017). Dissociative anesthetics like ketamine and dizocilpine  with antagonist properties on the NMDA receptor produce analgesia without inducing complete loss of consciousness (Kovacic and Somanathan, 2010;Lavender et al., 2020). Ketamine dose-dependently affected local field potentials (LFPs) and sleep patterns in rats (Feinberg and Campbell, 1993). Ketamine at anesthetic concentrations (75-100 mg/kg) was found to induce active waking with behavioral excitation associated with fast LFP activity and prominent LFP theta component. Subanesthetic doses (30-60 mg/kg) also induced waking with stereotypical behaviors associated by strong theta LFP activity. High anesthetic doses (150 mg/kg) evoked an initial sedative (hypnagogic) state with slow cortical rhythm for 40-60 min (Lu et al., 2008). Ketamine only at concentrations highly exceeding the clinical dosage (300 mg/kg) was able to induce long-lasting anesthesia with slow cortical rhythm (Lu Abbreviations: CSD, current source density; EMG, electromyography; FFT, fast Fourier transform; LD, light-dark; LFP, local field potential; NMDA, N-methyl Daspartic acid; MUA, multiple-unit activity; REM sleep, rapid eye movements sleep; SD, sleep deprivation; SSRI, selective serotonin reuptake inhibitor; SWS, slow wave sleep. et al., 2008). Sleep effects of ketamine and its role in the homeostatic sleep regulation regained recent interest as ketamine was found to have rapid antidepressant effects both in rodent models (Autry et al., 2011) and human trials for treatment-resistant major depressive disorder (MDD) involving severe sleep problems (Pradhan et al., 2015;Zarate and Machado-Vieira, 2017;Mandal et al., 2019;Muscat et al., 2021). A major therapeutic advantage of ketamine over the dominantly used selective serotonin reuptake inhibitors (SSRI)-type compounds (Edinoff et al., 2021) is its very rapid onset of action. Ketamine was found to alleviate the core symptoms of MDD and suicidal ideation within only a few hours (Pennybaker et al., 2017;Kohtala et al., 2021), while the onset of action can be counted as weeks in case of SSRIs (Taylor et al., 2006).
In MDD, sleep problems can be related to the alteration of the homeostatic sleep regulation based on both human (Frey et al., 2012a;Frey et al., 2012b) and animal studies (Savelyev et al., 2012;Radwan et al., 2021). Among the numerous neurotransmitter systems and receptors involved in homeostatic sleep regulation (Brown et al., 2012;Deboer, 2018), both NMDA receptor agonism (Burgdorf et al., 2019) and antagonism Feinberg, 1996b, a, Campbell et al., 2002) were suggested to play a prominent role.
In the present study, ketamine effects were analyzed using an ultra short light-dark (LD) regime to overcome the problem caused by the circadian rhythm potentially masking long-term drug effects on vigilance levels (Luczak and Bartho, 2012;Basso et al., 2020;Szalontai et al., 2021). Rats were exposed to short LD cycles (LD1:1) which were found to eliminate circadian rhythm in behavior, motor activity (Borbely and Huston, 1974) and sleep (Borbely et al., 1975;Szalontai et al., 2021). The short period LD cycling used in the present study allowed the examination of the homeostatic sleep regulation by sleep deprivation (SD) and ketamine applications in a condition lacking the circadian sleep-regulating component but at the same time, the direct sleepregulatory role of light was maintained. Deterioration of the circadian component of the sleep regulation is a prominent feature both in human MDD (Germain and Kupfer, 2008;Nutt et al., 2008;Salgado-Delgado et al., 2011) and rodent disease models (Imamura and Takumi, 2022). Both pharmacological (Rebuelto et al., 2002) and sleep effects of ketamine were found to be dependent on circadian timing (Sato et al., 2004). Ketamine administration (15-50 mg/kg) in the dark phase was found to enhance slow wave sleep (SWS) in rodent models (Feinberg and Campbell, 1993) while SWS suppression was seen in the case of light phase ketamine treatments (Livingston and Waterman, 1976;Ahnaou et al., 2017;Burgdorf et al., 2019). According to these previous data, elimination of the circadian influences beared strong importance as confirmed by our present study, too.
Ketamine may ensure its antidepressant effect by increasing wakefulness via its pharmacological actions. Subsequently, evoked waking can induce the build-up of the homeostatic sleep pressure finally resulting a rebound sleep with increased depth reflected by increased slow wave activity measured by an increase in the LFP delta power. In the present study, we addressed this phenomena by examining sleep and LFP effects of ketamine applied at anesthetic doses (80 mg/kg) in freely moving male rats. Homeostatic sleep response after ketamine application was compared to that could be seen after 6 h total SD performed by the gentle handling method.

Surgery
Male Wistar rats (n = 6, weighing between 305 and 335 g at the time of surgery) were anesthetized with ketamine/xylazine (80 mg/kg ketamine and 10 mg/kg xylazine, i.p.) and fixed in a stereotaxic frame (David-Kopf). Male rats were selected for the experiments to avoid estrus cycle-related changes in spontaneous homeostatic sleep drive characteristic in females (Toth et al., 2020). 14-channel stainless steel tube array electrodes with 40 μm insulated platinum-iridium wire contacts, spaced by 150 μm vertically in a (Neuronelektrod Ltd., Budapest, Hungary) were implanted in the left motor cortex (Br: 2.0, L: 2.0). Stainless steel screws (diameter: 0.8 mm; Fine Science Tools, USA) were placed above the frontal sinus and cerebellum for reference and grounding purposes. To record electromyographic (EMG) activity, a pair of 250 μm diameter, teflon-insulated stainless steel wires (California Fine Wire, CA, USA) were inserted into the neck musculature, close to the skull. All wires were soldered to a miniature female connector fixed to the skull with cranioplastic cement (PlasticsOne Inc., VA, USA). During surgery, body temperature was maintained at 37 • C by a heating pad (Supertech Ltd., Pecs, Hungary). Recording sessions started after 1-2 weeks of recovery. The surgery and electrode implantation was similar to that published earlier by our laboratory (Hajnik et al., 2013). Following surgery, the animals were kept warm and painkillers (50 mg/ kg metamizole, i.p.) were administered for 3 days.
Experiments were carried out in accordance with the Hungarian Act of Animal Care and Experimentation (1998, XXVIII) and with the directive 2010/63/EU of the European Parliament and of the Council of 22 September 2010 on the protection of animals used for scientific purposes. Experimental protocols were approved by the Ethical Board of Eötvös Loránd University. Efforts were made to minimize the number of animals used.

Housing
After the surgery, rats were kept under LD 12:12 cycle (light-dark 12 h: 12 h) during the recovery period (10 days) then transferred to LD 1:1 (light-dark 1 h: 1 h) lighting condition for another 21 days. Recordings started at 9:00 AM (bright hour). The intensity of lighting during bright hours was 90-100 lx. All animals were housed individually in Plexiglas cylinders (height: 345 mm, diameter: 350 mm). Cages were located in a sound-attenuated room with controlled ambient temperature of 21 • C. Water and standard laboratory chow (ToxiCoop Ltd., Budapest) were available ad libitum. Rats were connected to the recording system through flexible zig-zag flat cables attached to fixed swivels (Plastic One or Litton) above the home cages. This arrangement provided free movements for the rats. Cables were connected to the rats three days before the recordings started enabling the habituation of the animals. General experimental setup was similar to that previously described (Bertram et al., 1997;Hajnik et al., 2013;Toth et al., 2020;Szalontai et al., 2021).

Electrophysiological recordings
LFP was measured through home-designed headstages based on the TLC2264I amplifiers (Texas Instruments, USA) built into the male connector. Signals were amplified and filtered (500×, 0.3 Hz -4 kHz, Elsoft Bt.) then digitized and saved by an analog-to-digital converter card (National Instruments, Austin, TX, USA, LabView). The sampling rate was set to 8192 Hz (a power of 2) to facilitate fast Fourier transform (FFT). Original recordings were downsampled to 128 Hz to yield 512 data points per 4-s recording time for LFP analysis. All LFP and EMG data collected during the recording sessions were stored on hard disk for offline analysis.
The relationship between the phase of the extracellularly recorded slow LFP rhythm and the de-and hyperpolarized states (UP-and DOWN states, respectively) of the neocortical cells is not completely unequivocal (Mukovski et al., 2007). However, the small surface of the array electrodes enabled the recording of multiple unit activity (MUA) from a previously selected electrode in layer V. Slow waves and simultaneously recorded cortical MUA enabled the analysis of DOWN state occurrence and duration in different situations (Saleem et al., 2010).

Sleep deprivation
Total SD was performed by gentle handling of the animals for 6 h starting at the lights-on period at the first (bright) hour. Gentle handling was performed in the home cages and involved presentation of new objects, acoustic and if necessary, tactile stimulation to the rats (Tobler et al., 1994).

Drug treatments
Drug administration was carried out at the onset of the first (bright) hour. Effect of ketamine single injection (80 mg/kg i.p.; Calypsol 50 mg/ ml; Gedeon Richter Plc.) was controlled by single saline application. After the injections, recordings started immediately and lasted for 24 h. Each rat received all treatments and the control (saline) injections in random order. At least three days elapsed between subsequent injections for the same rat.

Data analysis
The analysis was carried out off-line using custom-designed software used in several previous studies of our laboratory (Toth et al., 2008;Toth et al., 2012;Hajnik et al., 2013;Toth et al., 2020;Szalontai et al., 2021). The software enabled visual inspection of the recorded signals, digital filtering and spectral analysis of the LFP curves, spike extraction from the raw MUA signal and semi-automatic sleep scoring.

Sleep scoring
Power spectra were calculated using the FFT algorithm for all consecutive 4-s periods from all recordings. Power was integrated in the delta (0.5-4 Hz), theta (4-10 Hz), alpha (10-14 Hz), beta (14-30 Hz) and gamma (30-48 Hz) frequency ranges and the ratio of the theta/delta power was determined. EMG data were also processed using the FFT method and the total power (variance) was calculated in the 5-48 Hz range.
Epochs containing movement artifacts (high delta power and high EMG variance) and rapid eye movement (REM) sleep epochs (low delta power, high theta/delta ratio, and low muscle tone) were manually selected in all recordings by visual inspection of the LFP and EMG signals.
Epochs containing artifacts were excluded from further analysis (<1 % of the baseline recording and recovery and around 5 % during SD and ketamine-evoked hyperactive waking).
There are several scoring methods to distinguish SWS and wakefulness, either automatic, based on calculation of sophisticated variables from the recorded data (Robert et al., 1999) or manually, relying on the decision of an experienced scorer visually inspecting the LFP, EMG and power curves (Neckelmann et al., 1994). In all cases, slow wave (<4 Hz) content of the LFP and the level of EMG activity are the most important indicators used as delta power changes are closely and inversely related with the level of cortical arousal (Trachsel et al., 1989). The semiautomated scoring method used here had been published earlier (Détári et al., 1993) and was used in several studies published by our laboratory later (Tóth et al., 2007;Hajnik et al., 2016;Borbely et al., 2018;Toth et al., 2020;Szalontai et al., 2021).
In the present experiments, delta power and EMG thresholds were set individually for each rat by visually inspecting of the raw LFP and EMG data from control recordings. These objective thresholds were then used to score recordings obtained after the treatments. Epochs in which delta power was above and EMG value below these thresholds. Were marked as SWS, while epochs with lower delta power or higher EMG activity as wakefulness. Raw hypnograms were smoothed, i.e. every 32 s period was assigned to the dominant sleep-wake stage (Figueroa Helland et al., 2010).

LFP analysis
LFP power values were analyzed by both independently and in relation to the vigilance stages (Maloney et al., 1997). Power values in the delta (1-4 Hz), beta (16-30 Hz) and gamma (30-48 Hz) frequency bands independently from vigilance levels (wakefulness, SWS, REM sleep) were averaged for 1 h periods and normalized using the data of the control day which were used as reference for all other recordings regardless of their type. Grand average of the power values of all hours and frequency bands of the baseline day was calculated as 'normalization factor'. Next, each power value belonging to any time point was divided by the same 'normalization factor' for both baseline and treatment recordings. Normalized values were then summarized for 1 h periods. After that, values of the 1 h periods of the baseline day were averaged separately in the different bands. Actual values of the 1 h periods were divided by this daily average. Normalized values belonging to the treatment days (ketamine; SD) were also divided by the baseline daily average separately for each frequency band.
Vigilance stage dependent LFP analysis was performed when the independent analysis showed significant power changes in a given frequency band in one or more time points to assign the changes of the power to one or more sleep-wake stages. For this, LFP power values in all five frequency bands were computed by vigilance levels. Next, power values were normalized separately for all three vigilance levels using a separate averaged power ('normalization factor') value for each of the vigilance level. Normalizing values were derived from the control recording with saline injection. Normalized values belonging to a given frequency band were compared between control versus treatment days separately for wakefulness, SWS and REM sleep. Aside from the comparisons between control and treatments, this kind of analysis also demonstrated the inherent differences in the distribution of power values of a given frequency band between the different sleep-wake stages.
Data from the 0-1 Hz LFP range were completely excluded from the analysis as artifacts originating from cable movements.

Detection of multiunit activity
In the current study, MUA refers to the spikes of many neurons surrounding the selected contact of the array electrode located in layer V in the frontal cortex, which makes the signal of the individual cells inseparable, but spike waveforms can be still measured. To analyze MUA, the signal was digitally high-pass filtered at 128 Hz then spikes were separated from noise by setting a threshold level. To make individual rats comparable, threshold level was defined as a value equal to 5× standard deviation value of the baseline noise (Quiroga et al., 2004) calculated from control recordings. The threshold was applied to the negative phase of the spike waveforms (Rasch et al., 2008). Artifacts were eliminated by spike shape discrimination (Detari et al., 1997). Time stamps of the extracted spikes were exported to Microsoft Excel and analyzed in 2 s bins using a custom-written Visual Basic macro.

Coherence analysis
Intrahemispheric LFP coherence was calculated to examine correlation of pairs of LFP curves using ipsilateral layer II/III and layer V LFP pairs. Coherence was calculated for 40 s long epochs taken from the same circadian hours to compare control (saline-injected), ketaminetreated and SD stages. Coherence values were calculated using a custom-written Matlab script. Period length was selected according to the idea that the reliability of the analysis decrease with decreasing epoch length (Shaw, 1984). With 10 % overlap, 24 blocks of 256 points each was analyzed. Before calculation, artifacts were removed from the LFP signals, trends were eliminated using linear detrending. LFP epochs were multiplied by a Hanning window (256 points), then Fast Fourier Transformation was carried out. Coherence [Cxy(f)] was defined for the paired signals (x, y) as follows (Stoica and Moses, 1997): where |Pxy(f)|2 is the square of the cross-spectrum of the two electrode channels x and y divided by the product of the spectra of the individual channels [Pxx(f)Pyy(f)]. Coherence values were calculated between 0 and 64 Hz for each individual rat then the matrices were averaged between animals (n = 6) then depicted as heat maps. In addition to the LFP frequency ranges used for sleep scoring as delta (0.5-4 Hz), theta (4-10 Hz), alpha (10-14 Hz), beta (14-30 Hz) and gamma (30-48 Hz), high gamma range (48-64 Hz) was defined for coherence analyses.

CSD calculation
To accurately locate synaptic currents inducing local extracellular potential changes, one dimensional current source density (CSD) analysis was performed using the averaged slow field potential waves recorded with the 14-channel array electrodes. CSD plots were calculated using the second derivative of the LFP in space by a custom written MATLAB script implementing the following formula (Mitzdorf, 1985): where CSD(h,t) is the CSD at time t and depth h, while Φ(h,t) is the averaged extracellular field potential at time t and depth h. The distance of electrode surfaces (Δh) was 150 μm. Data were smoothed by a 3-point Hamming spatial filter. To eliminate background noise, a threshold level (10 % of the maximum value) was defined.

Histology
At the end of the experiments, the position of the 14-channel electrode array was marked by current injections. 50 μA positive direct current was passed through the deepest positioned contact of the recording array to evoke a small lesion at the border between layer 6 and the white matter.
After the marking of the recording sites, animals were perfused transcardially with 150 ml of 0.9 % saline followed by 300-400 ml of fixative containing 4 % of paraformaldehyde. Brains were removed and post-fixed overnight at 4 • C in the same fixative. Coronal sections (50-70 μm) were cut with a vibroslicer, mounted and stained in gallocyanin solution overnight. After dehydration, slices were coverslipped with Depex.
Bright-field light microscopy was used to locate recording sites, using the appropriate plates of the stereotaxic atlas of the rat (Paxinos and Watson, 1998). The thickness of the cortex at the recording site and the distance of the lesion site in deep layer 6 from the cortical surface were measured on photographs taken by an Olympus BFX51 microscope equipped with an Fview-2 CCD camera. Photographs were analyzed using an image-analysis program (Analysis; Olympus, Japan). Distances were measured in parallel with the apical dendrites of pyramidal cells. Borders of cortical layers were determined by inspecting the microphotograph and comparing them with data available in the literature (Kenan-Vaknin and Teyler, 1994;Skoglund et al., 1996Skoglund et al., , 1997. This way, position of recording points of the electrode array in different cortical layers was determined. Sub-layers Va and Vb were not distinguished within layer V.

Statistical analysis
Sleep-wake parameters and normalized LFP power values were analyzed statistically by two-way ANOVA with time and treatment as factors, followed by Bonferroni's multiple comparisons test. The same post-hoc test was applied for MUA data analyzed in 1 h blocks for 24 h. To evaluate MUA data as functions of LD hours, Tukey's multiple comparisons was applied. Tukey's test was selected as this method tests every possible pair of all groups which was the case for these data (Lee and Lee, 2018). For the characterization of the homeostatic sleep pressure after ketamine applications and SD, significance was tested by calculating Pearson correlation coefficients.
In each series of experiments, homogeneity of variances and normal distribution of data was tested before statistical analysis. All tests were two-tailed and p < 0.05 was accepted as the lowest limit of significant difference. Data are shown as mean ± S.E.M. in figures. The term "interaction" reflects "timeXtreatment" connection between the factors indicated by the two-way ANOVA. Statistical analysis was performed using Prism 8.0 (GraphPad Software, San Diego, USA). Data were plotted in Microcal Origin 2018 (OriginLab Corporation, Northampton, USA). Final editing was performed using Adobe Photoshop CC 14.2 × 64.

Sleep changes
To assess the effect of ketamine applications on homeostatic sleep regulation, ketamine (80 mg/kg i.p.) injections were applied at the onset of the first (bright) hour in LD 1:1 lighting conditions in feely moving rats. Sleep changes were compared to control (saline) injections and 6 h gentle handling SD data.
After the application of ketamine, the drug induced a hypnotic state lasted for 32.2 ± 14.1 min in average. This state was characterized by prominent slow cortical rhythm (Fig. 1A, B) with prominent LFF gamma (20-48 Hz) activity in all cortical layers (Fig. 1C). Hypnotic state was sharply transitioned (Fig. 1A) to long-lasting (244.8 ± 48.6) hyperactive waking stage resulting pharmacological SD. Hyperactive waking was characterized with more intense LFP gamma (30-48 Hz) activity compared to the hypnotic state and within the gamma range, activity was shifted towards the higher frequencies (Fig. 1C).
According to the Lomb-Scargle periodogram analysis (data not shown), the circadian rhythmicity of the sleep-wake stages was completely absent after at least 21 days spent in LD 1:1 condition as it was seen after control (saline) injections (Figs. 2, 3). Ketamine application significantly increased wakefulness and reduced both SWS and REM sleep in the first 5 h after application (Fig. 2A1, B1, C1) without a dependence on LD conditions in the consecutive hours in case of SWS (Fig. 3B). Decrease of REM sleep was significantly stronger in the light hours compared to the dark ones (interaction; F (2,30) = 27.5, p < 0.001, Fig. 3C). Wakefulness-inducing and sleep-attenuating effect of ketamine was weaker but comparable to the similar effect of 6 h SD. Average SWS loss in the 5th hour after application compared to control was 57 min for ketamine and 88 min for SD (Fig. 2A2, A3, B2, B3). Using a similar comparison to REM sleep, its loss was 15 min versus 18 min (ketamine versus SD, respectively) ( Fig. 2C2, C3).

Homeostatic sleep response
Termination of the ketamine effect was followed by replacement of both SWS and REM sleep. As direct pharmacological sleep effect of ketamine was shorter than the duration of the 6 h SD, SWS replacement started in the 6th hour in case of ketamine while it was seen only from the 7th hour in case of the SD. SWS replacement became similar in the 9th hour in case of both treatments and showed similar trend until the end of the day (Fig. 2 B1, C1). Delta power (1-4 Hz) increased tremendously during the hypnotic state (Fig. 5A1) and lost delta power in the hyperactive waking state was recovered after the termination of the ketamine effect with similar temporal dynamics seen in SWS replacement. Net loss in delta power was smaller in case of ketamine compared to SD in the 2nd-5th hours (Fig. 5A1), but both delta power and SWS replacement showed similar relative intensity after ketamine applications compared to that seen after SD. In the first 6 h, no significant difference was seen in delta power during light versus dark hours in any of the treatment groups including control (Fig. 5A2). In contrast with SWS, REM sleep replacement remained incomplete at the end of the day after ketamine application (Fig 2C1, C2). Significantly more REM sleep was present in the dark hours compared to the light ones in control in the whole (24 h) recording period (interaction; F (2, 30) = 27.5, p < 0.001, Fig. 3C). This LD REM sleep difference persisted after both ketamine treatment and 6 h SD (interaction; F (2, 30) = 27.5, p < 0.001 in both cases, Fig. 3C).

Homeostatic sleep pressure
For the quantification of the homeostatic sleep pressure generated by ketamine application and 6 h SD, correlations were calculated between the length of the ketamine-evoked hyperactive waking stages and the subsequent sleep replacement. Similar comparisons were made for the 6 h SD.
The length of the hypnagogic stage correlated strongly (r = 0.984; p = 0.0004, Fig. 4A) with the length of the subsequent hyperactive waking and with the onset of the first REM sleep episode after ketamine application (r = 0.892; p = 0.017, Fig. 4B) showing that hypnotic state itself may be considered to generate sleep pressure even the high slow wave content of this state due to the presence of the slow cortical rhythm.
After 6 h SD, forced waking (320.2 ± 7.8 min) was followed by SWS replacement in the next 6 h after the termination of the SD, but the net amount of the SWS replacement was less (168.2 ± 34.4 min) compared to the length of the waking resulting non-significant correlation (r = − 0.444; p = 0.3782; Fig. 4E). The trend between the length of the hyperactive waking and subsequent SWS replacement was similar in case of the ketamine application resulting non-significant correlation too (r = 0.751; p = 0.0852; Fig. 5C). When the sum of the length of the hypnotic state and the hyperactive waking was correlated with the subsequent SWS replacement, the correlation also showed no significance (r = 0.746; p = 0.0888, Fig. 5D).

LFP theta (4-10 Hz) activity
Total theta (4-10 Hz) power was significantly higher at the beginning of the hyperactive waking in the 2nd hour after ketamine application compared to control (interaction; F (46, 360) = 3.79, p < 0.001; Fig. 5B1). In other time points, it was close to control values or lower compared to them. Theta activity was below the control during and after 6 h SD (Fig. 5B1). No LD variation was seen in total theta power in the first 6 h in any of the three treatment groups (Fig. 5B2).
Theta power during wakefulness was significantly higher during hyperactive waking induced by ketamine as well as during 6 h SD ( Fig. 5C1) but in the SWS restoration period (hours 6-11 for ketamine; hours 7-12 for SD) and later, theta power significantly decreased compared to control. No LD variation was seen in wakefulness theta power in the first 6 h in any of the three treatment groups (Fig. 5C2).

LFP high-frequency activity
3.2.2.1. Beta (13-30 Hz) power. High-frequency ranges of the cortical LFP were compared during ketamine application and 6 h SD for the characterization of the level of cortical arousal reflecting the intensity of the wakefulness. Total beta (13-30 Hz) power independent on the sleepwake stages was significantly suppressed after ketamine application during all day (Fig. 5D1) with no LD variation in the first 6 h (Fig. 5D2). Beta power during wakefulness was significantly elevated in the 2nd (dark) hour after ketamine application (interaction; F (46, 360) = 5.43, p < 0.001; Fig. 5D1). For the first 6 h, dark hours contained significantly more beta power compared to light ones (interaction; F (2, 30) = 24.0, p < 0.001; Fig. 5D2).

Gamma (30-48 Hz) power.
Total gamma power was significantly elevated after ketamine applications in the 2nd (dark) and 3rd (light) hours compared to control (interaction; F (46, 360) = 4.20 p < 0.001 for both hours; Fig. 5F1) with no LD variability in the first 6 h (Fig. 5F2). Hyperactive wakefulness after ketamine application was characterized by strongly elevated gamma activity in the 2nd-4th hours while hypnotic state in the 1st hour contained elevated gamma activity too (interaction; F (46, 360) = 23.7, p < 0.001; Fig. 5G1). No LD variation was seen in gamma power in the first 6 h post-application (Fig. 5G2). In the SWS replacement period (hours 6-11 for ketamine), gamma activity was significantly decreased compared to control (Fig. 5G1).
Gamma activity was significantly elevated during the 6 h SD compared to control (Fig. 5F1) with no LD variation (Fig. 5F2). During the SWS replacement period (hours 7-12), gamma power returned to the control level (Fig. 5F2). Wakefulness gamma power was significantly elevated in the whole 6 h SD (Fig. 5G1) without LD variation (Fig. 5G2), while wakefulness gamma activity was significantly reduced in the SWS replacement period (Fig. 5G1) again without light-dark variation (Fig. 5G2).

Coherence
Ketamine-induced hypnotic state in the first (light) hour was characterized by intense slow cortical rhythm with stronger intracortical (layer II/IIIlayer V) coherence below 5 Hz (Fig. 5B1) compared to control SWS in the same time period (Fig. 5A1). In the 3-5 Hz range, coherence was the strongest during SWS replacement in the 7th (bright) hour after SD from all three stages compared ( Fig. C1 versus B1, A1). Hypnotic state showed high coherence in high LFP frequency ranges (beta 13-30 Hz and gamma 30-48 Hz) (Fig. 6B1) which was not seen in control SWS (Fig. 6A1).
In contrast to control waking, coherence analysis indicated the association of the ketamine-evoked hyperactive waking stage with increased local cortical coherence in broad LFP frequency ranges (<10 Hz and > 30 Hz). In the range below 10 Hz, high coherence was seen in the theta (4-10 Hz) range (Fig. 6B2, B3). Coherence was particularly high in the high gamma range (48-64 Hz) and wakefulness epochs during the dark hours showed higher coherence in this range compared to the light hours ( Fig. 6B2 versus 6B3). Coherence values showed no LD-dependent differences in control waking epochs (Fig. 6A2, A3). Both in the theta (4-10 Hz) range and in the high-frequency (>30 Hz) ranges, coherence values were lower compared to the ones seen in case of ketamine-induced hyperactive waking (Fig. 6B2 versus 6A2; 6B3 versus 6A3). In case of wakefulness during SD, coherence was generally high below 20 Hz in the dark hours (Fig. C2), while high coherence values were limited to <10 Hz in case of the bright hours (Fig. C3). Similarly to control waking, SD waking showed no high coherence in the gamma and high gamma ranges neither in the bright (Fig. C3 versus A3), nor in the dark hours ( Fig. C2 versus A2).

Multiple unit activity
Layer 5 MUA was significantly higher during ketamine-induced hyperactive waking compared to control but showed a decreasing trend parallelly with the decreasing drug effect (Fig. 7A). However, this decreasing trend was not present during 6 h SD where cortical firing became more intense as a function of time spent in SD and MUA remained higher also in the SWS replacement period (hours 7-12) (Fig. 7A).
During both the 6 h SD and ketamine-induced hyperactive waking, short and sporadic SWS epochs appeared. MUA in both cases was significantly higher compared to control SWS (Fig. 7B). In the SWS replacement period (hours 7-12), MUA during SWS was higher in hours 8th and 9th after 6 h SD compared to control, but no change was seen in later hours (Fig. 7B) In case of ketamine application, no change was seen neither in the SWS replacement period (hours 7-12), nor later (Fig. 7B). MUA did not showed any LD-related changes in any of the treatment groups neither during wakefulness (Fig. 7D) nor during SWS (Fig. 7E).
During 6 h SD, REM sleep was totally deprived while ketamine applications strongly suppressed REM sleep in the first 6 post-injection hours (Fig. 2C1). At the MUA level, spiking was significantly reduced in the first 6 h after ketamine injections (Fig. 7C) with more reduction in the dark hours (interaction; F (2, 30) = 27.5, p = 0.009; Fig. 7F) while reduced spiking was also maintained in the SWS replacement period On each panel, cumulative difference of the averages from the corresponding control average is depicted helping to assess the direction of the changes as well as the accumulating sleep-wake deficit or excess regarding homeostatic sleep regulation. Data were analyzed in 1-h long bins and expressed as minutes/h (n = 6 for all three treatment groups). White and black bars at the X axis represent light-and dark hours, respectively. Significance was tested with two-way ANOVA with time and treatment as factors, followed by Bonferroni's multiple comparisons test. Significance levels: *,* -p < 0.05; **,** -p < 0.01; ***,*** -p < 0.001. Data are expressed as mean ± S.E.M.
(hours 6-12). In case of 6 h SD, spiking during REM sleep showed no difference compared to control in most of the sleep replacement period (hours 7-12) when REM sleep epochs could be allowed to generate again. Spiking was significantly enhanced only in the 7th hour (interaction; F (46, 360) = 32.3, p < 0.001; Fig. 7C) when REM sleep time was also elevated after the 6 h SD (Fig. 2C1).

CSD analysis of slow waves
Cortical CSD profiles showed a complex series of sink-source patterns during slow waves. For the sake of clarity, sinks were marked by numbers (1-5), while sources by letters (a-e) on the maps (Fig. 8). Slow waves were averaged around its maxima at 0 ms representing the DOWN states of the slow cortical rhythm preceding and following by UP states at around − 100 ms and 100 ms, respectively.
The sink-source patterns were highly consequent among individual slow waves events and rats. Sink-source configurations were the most pronounced in case of the ketamine-derived hypnotic state. During this period, UP state at around − 100 ms was characterized by a strong sink in layer V (sink 1) with a corresponding source in layer II/III (source a). During the DOWN state at around 0 ms, a strong sink was present in layer V (sink c), while a weaker sink was seen at the border of the layer III/IV (sink b). Corresponding sinks appeared in layer VI and layer II/III (sink 2 and sink 3, respectively) (Fig. 8A).
Following both ketamine sleep replacement period after hyperactive waking (Fig. 8B) and SD (Fig. 8C), only moderate differences were seen in the sink-source patterns. Differences were more quantitative than qualitative, as all sinks and sources became weaker in amplitude and involved smaller areas in time showing that cortical transmembrane currents were the strongest during ketamine-induced hypnotic stage among the three compared slow-wave dominant stages.

Homeostatic sleep effects of ketamine
In the recent study, the effect of ketamine was investigated using anesthetic dose (80 mg/kg) (Smith et al., 2019). After ketamine application, complex sleep-wake effects were seen forming a triphasic effect. After a short (~ 32 min) hypnotic state with prominent slow cortical rhythm, a long-lasting (~ 244 min) hyperactive waking state was induced followed by an SWS sleep replacement period lasted for 5-6 h. In the case of REM sleep, a long-lasting (~6 h) suppression was not followed by a rebound. REM sleep debt was also seen at the end of the 24 h recording period.
According to a variety of previous sleep studies, ketamine exerted its effect on cortical LFPs and sleep patterns in a strong dose-dependent manner (Feinberg and Campbell, 1993). In rats, anesthetic dose (75-100 mg/kg) of ketamine was found to induce active waking with behavioral excitation associated by fast LFP activity with prominent theta component as it was seen in the recent experiments. Subanesthetic dose (30-60 mg/kg) also induced waking with stereotypical behaviors associated by strong theta LFP activity. High anesthetic dose (150 mg/ kg) induced an initial sedative (hypnotic) state with slow cortical rhythm in the LFP for 40-60 min. Ketamine only at doses highly (caption on next column) Fig. 3. Sleep-wake changes for all (12− 12) LD hours and for the first 3-3 lightdark hours in LD1:1 lighting regime after ketamine (80 mg/kg. i.p.) application and 6 h gentle handling SD. Saline injections were used as control. Control and drug injections were applied at the onset of the first (light) hour in LD1:1 lighting regime. SD was started from the same time point. Panel A: W; panel B: SWS; panel C: REM sleep. Data were analyzed in 1-h long bins and expressed as minutes/h (n = 6 for all three treatment groups). Significance was tested with two-way ANOVA with time and treatment as factors, followed by Bonferroni's multiple comparisons test. Significance levels: * -p < 0.05; ** -p < 0.01; *** -p < 0.001. Data are expressed as mean ± S.E.M. exceeding the clinical dosage (300 mg/kg) was able to induce longlasting anesthesia with slow cortical rhythm (Lu et al., 2008). Ketamine applied at a low dose (2,5-10 mg/kg) was found to acutely suppress both SWS and REM sleep followed by a rebound increase both in SWS and REM sleep. SWS was suppressed for 2-3 h with rebound in the next 2 h while REM sleep was reduced for 2 h but a late rebound response was seen in hours 5-10 (Ahnaou et al., 2017;Burgdorf et al., 2019).
In the present study, ketamine evoked pharmacological SD with comparable duration to 6 h gentle handling SD. Similarly to SD, replacement of the lost SWS was completed at the end of the day in case of ketamine applications with a small amount of overcompensation Significance was tested by calculating Pearson correlation coefficients. Significance levels: * -p < 0.05; ** -p < 0.01; *** -p < 0.001. Data are expressed as mean ± S. E.M.

Fig. 5.
Changes of the normalized LFP power after ketamine (80 mg/kg. i.p.) application and 6 h gentle handling SD. Saline injections were used as control. Control and drug injections were applied at the onset of the first (light) hour in LD1:1 lighting regime. SD was started from the same time point. Panel A1: sum delta (1-4 Hz) power irrespectible to sleep-wake stages; panel B1: sum theta (4-10 Hz) power; panel C1: wakefulness theta (4-10 Hz) power; panel D1: sum beta (13-30 Hz) power; panel E1: wakefulness beta (13-30 Hz) power; panel F1: sum gamma (30-48 Hz) power; panel G1: wakefulness gamma (30-48 Hz) power. On panel A2, B2, C2, D2, E2, F2, G2 power in the same frequency ranges was compared between LD hours in the first 6 h period after ketamine application and SD. Data were analyzed in 1 h long periods (n = 6 for all three treatment groups). White and black bars at the X axis represent light-and dark hours, respectively. Significance was tested with two-way ANOVA with time and treatment as factors, followed by Bonferroni's multiple comparisons test. Significance levels: *,* -p < 0.05; **,** -p < 0.01; ***,*** -p < 0.001. Data are expressed as mean ± S.E.M. Fig. 6. Intracortical coherence between layer II/III and layer V LFP curves recorded from the same site in the frontal cortex (Br. AP 2 mm, L: 2 mm). Averaged (n = 6) coherence values are depicted as heat map calculated from the LFP frequency range 0-64 Hz. Panel A1, A2, A3: control (saline) injections; panel B1, B2, B3: ketamine (80 mg/kg. i.p.) injections; panel C1, C2, C3: recovery sleep after SD and wakefulness during SD. Horizontal position panels show same-duration (40 s) sleep-wake epochs were compared taken form the relatively same circadian hours. Light hour data were taken from the first hour, dark hour data were taken from the second hour. compared to control. Ketamine-induced waking was followed by SWS rebound with a similar ratio regarding durations as seen in case of the 6 h SD. However, two factors weakened the correlation between waking duration and SWS replacement in the case of ketamine. First, duration of the pharmacological effect of ketamine showed significant variability between individual rats while during the 6 h SD, the duration of the forced waking was defined strengthen the correlation with the consecutive SWS replacement. Second, variability in the effect of ketamine was found to be due to the different pharmacokinetics of the drug in individual rats (Saland and Kabbaj, 2018) which factor was not present in case of the 6 h SD.
As the main pharmacological mechanism of ketamine action is the antagonism on NMDA receptors, these findings together support the view that homeostatic sleep regulation has strong NMDA receptordependent mechanisms. These mechanisms are promising targets to manipulate homeostatic sleep regulation for medical use as suggested previously by rodent studies (Campbell and Feinberg, 1996a, 1996bCampbell et al., 2002;Burgdorf et al., 2019).

Short LD cycle (LD 1:1) eliminating the circadian component of drug effect and sleep regulation
In the present study, short LD cycles (LD1:1) were used to eliminate the circadian component of sleep regulation (Szalontai et al., 2021) and possible circadian time-dependent pharmacological actions of ketamine considered by previous studies (Rebuelto et al., 2002;Sato et al., 2004). The short period LD cycling used in the present study allowed the examination of the homeostatic sleep regulation by SD in a condition lacking the circadian sleep-regulating component but allowed the light to express its direct regulatory role (Deboer, 2018;Szalontai et al., 2021) as light was found to directly induce sleep in rodents (Hubbard et al., 2013;Lazzerini Ospri et al., 2017). This study is the first to characterize the sleep-wake effects of ketamine using such a condition. According to our data, ketamine effects were not different as a function of the actual illumination conditions (light versus dark) showing that pharmacological effects of ketamine can overcome the direct sleep-inducing effect of light (Hubbard et al., 2013) to facilitate waking even in the light hours.
It is worth to consider that even hypnotic states with prominent slow wave activity can generate homeostatic sleep pressure in LD1:1 conditions as the correlation between the duration of the hyperactive waking and the duration of the SWS replacement afterward was very similar when the duration of the hypnotic state was involved in the analysis. This phenomena can be explained by three factors. (i) It was previously shown by our laboratory that there is a decoupling of the slow wave activity from the homeostatic sleep drive in LD1:1 lighting condition (Szalontai et al., 2021). (ii) Ketamine enhances the high-frequency (beta and gamma) LFP activity as seen in the present data and several previous studies (Nicolás et  Data were analyzed in 1-h long periods (n = 6 for all three treatment groups) and expressed as average spike/s in 2 s bins scored as wakefulness, SWS or REM ± S.E. M. White and black bars at the X axis represent light-and dark hours, respectively. Significance was tested with two-way ANOVA with time and treatment as factors, followed by Bonferroni's multiple comparisons test for data on panel A, B, C. For LD averaged data depicted on panel D, E, F, Tukey's multiple comparison was used. Significance levels: *,* -p < 0.05; **,** -p < 0.01; ***,*** -p < 0.001. even the effect of ketamine in the gamma band was found to be dosedependent (Qi et al., 2018). (iii) Similar level of beta and gamma LFP activity can be seen during active waking reflecting high cortical arousal (Maloney et al., 1997) and these activities may mediate the homeostatic sleep pressure even the actual state is not wakefulness. Gamma power shows reciprocal connection with delta activity during normal SWS (Maloney et al., 1997). However, during the action of the ketamine, high delta activity was associated with high gamma activity as it was the case in our data during the hypnotic state. These findings may reflect the uniqueness of the ketamine-evoked LFP states regarding homeostatic sleep regulation.

Ketamine-induced waking differs from the spontaneous one but both can generate homeostatic sleep response
In the present study, ketamine-induced hyperactive waking, SDinduced forced waking and control waking were compared using various parameters. Ketamine-induced waking was characterized by higher theta (4-10 Hz), beta (13-30 Hz) and gamma (30-48 Hz) LFP activity and higher intracortical coherence in the theta (4-10 Hz), gamma (30-48 Hz) and high gamma (48-64 Hz) range compared to control waking. In the high gamma (48-64 Hz) band, coherence was elevated during the dark hours compared to the bright ones which may show interference of the wakefulness-inducing effect of the dark environment (Borbely et al., 1975) and the pharmacological effect of the drug. During control waking, no coherence differences were seen in bright versus dark hours.
Ketamine-induced hyperactive waking may be generated by NMDA receptor-mediated modulation of different sleep-regulating systems. Among these, orexin system may be a reasonable candidate as several lines of evidence showed strong connections between NMDA receptors, NMDA antagonists and orexin functions. OX1 receptor knockout mice had a blunted glutamate release response to the NMDA antagonist MK-801 and exhibited about half of the glutamate release observed in wildtype mice (Aluisio et al., 2014). Orexin A application significantly decreased ketamine anesthesia time when ketamine was administered in 50-125 mg/kg dose range via OX1 receptors expressed on noradrenergic neurons (Tose et al., 2009). Although the direct effect of ketamine on spontaneous release of orexin is unknown, orexin A was found to decrease the expression of NMDA receptor mRNA in vitro (Yamada et al., 2008), possibly limiting the number of pharmacological targets of ketamine resulting the suppression of the anesthetic effect of ketamine and may promote the appearance of hyperactive waking. This hypothesis was also supported by findings that activation of orexin system facilitated anesthesia emergence (Zhou et al., 2018) and plasma orexin A level was significantly elevated during emergence from propofol-fentanyl anesthesia (Kushikata et al., 2010).
MUA during wakefulness was elevated both in case of 6 h SD and ketamine applications compared to control, but SD evoked higher elevation in MUA compared to ketamine. Increased firing after ketamine application was suggested to cause by the blockade of the NMDA receptor-induced firing of gamma aminobutyric acid (GABA)ergic interneurons resulting disinhibition of the glutamatergic pyramidal cells (Moghaddam et al., 1997;Miller et al., 2016). Increased cortical firing during SD was found to be crucial to mediate homeostatic sleep need and systematic increase of firing during wakefulness is counterbalanced by staying asleep (Vyazovskiy et al., 2009). According to these findings, elevated firing after ketamine application could mediate the homeostatic sleep need both during hypnotic and hyperactive waking induced by the drug.
According to the higher level of the high-frequency LFP activity and coherence in these bands together with intense cortical firing, ketamineevoked waking states represent higher cortical arousal compared to both SD-evoked and control ones. Increased coherence after ketamine application reflects higher functional interconnection between cortical layers (Ahnaou et al., 2017;Michelson and Kozai, 2018). This may show that even the patterns of neuronal activity and synchronization are different during the three kinds of wakefulness stages, all three can engage the homeostatic sleep regulating machinery to generate sleep pressure dissipated by the subsequent sleep.

Ketamine-induced slow waves have similar underlying cortical transmembrane currents compared to that seen during SWS replacement after SD
CSD analysis of the slow waves showed that cortical transmembrane currents were stronger during ketamine-induced hypnotic state compared to that seen both during sleep replacement after SD and after the termination of the ketamine-induced hyperactive waking. These exclusively quantitative changes showed that intracortical generator and maintenance mechanisms for slow waves did not changed only the existed mechanisms became stronger due the pharmacological actions of ketamine. These findings also support the hypothesis that ketamineinduced waking may generate homeostatic sleep pressure which can Fig. 8. CSD profile of averaged slow waves from ketamine-evoked hypnotic state (first hourlight; panel A), rebound sleep after hyperactive waking evoked by ketamine (9th hourlight; panel B) and rebound sleep after 6 h SD (7th hourlight; panel C). Ketamine (80 mg/kg. i.p.) application and 6 h gentle handling SD were applied at the onset of the first (light) hour in LD1:1 lighting regime. Saline injections were used as control. LFP curves recorded from the same site in the frontal cortex (Br. AP 2 mm, L: 2 mm). Data depicted here are from the same representative animal. Sinks are marked by numbers (1-5) while sources by letters (a-e). Layer boundary data were adopted from Skoglund et al. (1997). be dissipated by the subsequent SWS replacement via the induction of slow waves similarly to that seen after 6 h SD in the present study.
Slow waves were considered to play a crucial role in the antidepressant effect of ketamine both in rodent and human models. Ketamine was suggested to produce its antidepressant effects through an acute suppression of emotions followed by a rebound increase in positive emotions and sleep in a rat model (Burgdorf et al., 2019). The rebound increase in SWS and REM sleep after ketamine treatment are consistent with previous rodent and human data (Feinberg and Campbell, 1995;Duncan and Zarate, 2013;Duncan et al., 2019), and may contribute to the long-lasting therapeutic effects of the drug (Duncan et al., 2019). Ketamine was found to increase the expression of the brain-derived neurotrophic factor (BDNF) (Li et al., 2010;Duncan and Zarate, 2013). As both BDNF (Colucci-D'Amato et al., 2020) and slow waves (Tononi and Cirelli, 2006;Hanlon et al., 2011) were considered to enhance synaptic plasticity which is deteriorated in depression (Yang et al., 2020), combined induction of slow waves together with increased BDNF release by ketamine may represent the electrophysiological and molecular correlates of mood improvement following ketamine treatment (Matveychuk et al., 2020).

Conclusions
Taken together the results of our study, SWS loss induced by the application of anesthetic dose of ketamine (80 mg/kg i.p.) could be replaced by the homeostatic sleep regulation with similar time course and kinetics seen after 6 h gentle handling SD. After the termination of the ketamine-induced hyperactive waking, the same amount of SWS was replaced in the time window with similar length as the waking state compared to the 6 h SD followed by 6 h replacement period.
However, REM sleep replacement was not as intense in time after ketamine-induced REM sleep suppression compared both SWS loss and replacement after ketamine and REM replacement after 6 h total SD. At the end of the 24 h recording period, REM sleep replacement became nearly complete.
Our results show that both ketamine-induced hypnotic state and hyperactive waking can induce homeostatic sleep pressure with comparable intensity as 6 h SD even the characteristics of ketamine-induced waking are different compared to waking seen during SD and both type of waking stages are different compared to spontaneous wakefulness. Although ketamine was applied at anesthetic dose, the long-lasting ketamine-induced pharmacological SD was followed by intense SWS restoration and moderately time-intensive REM sleep replacement. Which changes were firstly examined in the present study using short LD regime (LD1:1) lacking circadian influences.
In the present study, a higher ketamine dose (80 mg/kg) compared to that generally used in human MDD trials (0.1-1 mg/kg) (Fava et al., 2020;Cavenaghi et al., 2021) or rodent disease models (3-20 mg/kg) (Autry et al., 2011;Wang et al., 2015;Polis et al., 2019;McDonnell et al., 2020) was used. This anesthetic dose was selected due to two reasons. First, the applied dose induced a hypnotic state with slow cortical rhythm and concurrent high gamma activity. Presence of this state was needed as it was an important question whether this state can also generate homeostatic sleep pressure. Second, ketamine induces waking with a dose-dependent way (Feinberg and Campbell, 1995;Burgdorf et al., 2019). Present ketamine dose evoked long-lasting waking which was comparable in duration with 6 h SD. This facilitated the direct comparison between the two types of waking from the view of the homeostatic sleep pressure.
Present findings may hold some translational value for human medical ketamine applications. Recent concepts emphasize the role of rapid-acting antidepressants in the treatment of MDD shifting the focus to the normalization of sleep and circadian functions as main mechanisms of the antidepressive action (Kohtala et al., 2021). The present data provide direct experimental evidence for the usefulness of ketamine for these aspects in a rodent model. First, ketamine-induced waking seems to be similarly effective to evoke homeostatic sleep response compared to normal waking even due to the pharmacological effect of the drug, the pharmacological and neurochemical background of the drug-induced waking are significantly different compared to the spontaneous one. Second, ketamine-induced homeostatic sleep changes, which are beneficial to alleviate MDD-related sleep problems, are not dependent on intact circadian functions. Our findings are further strengthened by comparing them to previous results showing a characteristic circadian dysregulation in depressed patients manifested on the level of abnormal circadian gene expression patterns in several brain areas (Li et al., 2013), and also on the level of the central pacemaker or other brain areas directly regulated by the light but also involved in sleep regulation (Riemann et al., 2020;Kohtala et al., 2021). Important to note that as only male rats were used in the present study, any possible translational value is limited to males. Possible gender-related differences are still needs to be elucidated in future studies.

Funding
The research infrastructure for this study was supported by the VEKOP-2.3.3-15-2017-00019 grant. A travel grant to attend on Sleep Europe 2022 conference was ensured by a National Research, Development and Innovation Office Mecenatura 2021/076-P051 to A. Tóth.

Declaration of competing interest
The authors declare no conflict of interests.

Data availability
All data analyzed and presented in this work are available from the corresponding author upon reasonable request.