anesthesia is qualitatively distinct from sleep

Journal Pre-proof Dose-dependent alcohol effects on electroencephalogram: Sedation/anesthesia is qualitatively distinct from sleep Karina P. Abrahao, Matthew J. Pava, David M. Lovinger PII:

S0028-3908(19)30484-8

DOI:

https://doi.org/10.1016/j.neuropharm.2019.107913

Reference:

NP 107913

To appear in:

Neuropharmacology

Received Date: 9 September 2019 Revised Date:

27 November 2019

Accepted Date: 13 December 2019

Please cite this article as: Abrahao, K.P., Pava, M.J., Lovinger, D.M., Dose-dependent alcohol effects on electroencephalogram: Sedation/anesthesia is qualitatively distinct from sleep, Neuropharmacology (2020), doi: https://doi.org/10.1016/j.neuropharm.2019.107913. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.

ACUTE INTOXICATION BY ETHANOL Light Cycle

Dark Cycle

TIME

TIME

↑ DISCO-T ↓ Wake ↑ NREM ↓ REM ↑delta ↓theta ↓alpha ↓gamma

↑ DISCO-T ↓ Wake ↑ NREM ↑ REM ↑delta ↓theta ↓alpha ↓gamma

Dose-dependent alcohol effects on electroencephalogram: sedation/anesthesia is qualitatively distinct from sleep

Authors: Karina P Abrahao, PhD1*; Matthew J Pava, PhD2* and David M Lovinger, PhD**

Laboratory for Integrative Neuroscience, Division of Intramural Clinical and Biological Research, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland, USA.

* Both authors contributed equally to this manuscript ** Corresponding author: [email protected]

Funding: This work was supported by the Division of Intramural Clinical and Biological Research of the National Institute on Alcohol Abuse and Alcoholism [grant number ZIA AA000407].

1

Present address: Assistant Professor, Departamento de Psicobiologia, Universidade Federal de São Paulo, Campus São Paulo, SP, Brazil. Email: [email protected]

2

Present address: Arlington, VA, USA. Email: [email protected]

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Highlights

• • •

Alcohol induces an altered state with electrographic features distinct from sleep. High dose alcohol increases/stabilizes NREM sleep and suppresses/fragments REM sleep. Alcohol produces changes in the frequency composition of EEG specific to the circadian phase.

• NMDA antagonism and GABAA enhancement recapitulates the altered state induced by high dose ethanol Abstract Alcohol is commonly used as a sleep inducer/aid by humans. However, individuals diagnosed with alcohol use disorders have sleep problems. Few studies have examined the effect of ethanol on physiological features of sedation and anesthesia, particularly at high doses. This study used polysomnography and a rapid, unbiased scoring of vigilance states with an automated algorithm to provide a thorough characterization of dose-dependent acute ethanol effects on sleep and electroencephalogram (EEG) power spectra in C57BL/6J male mice. Ethanol had a narrow dose-response effect on sleep. Only a high dose (4.0 g/kg) dose produced a unique, transient state that could not be characterized in terms of canonical sleep-wake states, so we dubbed this novel state Drug-Induced State with a Characteristic Oscillation in the Theta Band (DISCO-T). After this anesthetic effect, the high dose of alcohol promoted NREM sleep by increasing the duration of NREM bouts while reducing wake. REM sleep was differentially responsive to the circadian timing of ethanol administration. EEG power spectra proved more sensitive to ethanol than sleep measures as there were clear effects of ethanol at 2.0 and 4.0 g/kg doses. Ethanol promoted delta oscillations and suppressed faster frequencies, but there were clear, differential effects on wake and REM EEG power based on the timing of the ethanol injection. Understanding the neural basis of the extreme soporific effects of high dose ethanol may aid in treating acute toxicity brought about by patterns of excessive binge consumption commonly observed in young people.

Keywords: sedation, mouse, polysomnography, sleep states, power spectra

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1. Introduction

Ethanol (commonly referred to as alcohol) one of the most frequently used drugs worldwide (WHO, 2014). Although ethanol has a myriad of behavioral effects, its effects on sleep and as a sedative/anesthetic are pronounced and well known (Colrain et al., 2014). These soporific effects are correlated with specific changes in brain activity measured mainly by polysomnography. While sleep states are characterized by specific macro and microscopic structures of the EEG and electromyogram (EMG) recordings; anesthesia and sedative states are related to other features of the EEG that can be different for each type of sedative drug. Sleep is a reversible state of reduced sensory responsiveness that affects several body and brain functions (Miyazaki et al., 2017; Siegel, 2005). In mammals, sleep cycles between two states: rapid eye movement (REM), or paradoxical sleep, and non-REM (NREM) sleep. The use of ethanol as a sleep aid is common among healthy people (Johnson et al., 1998; Roehrs and Roth, 2012). However, acute ethanol effects on sleep may induce maladaptative changes during chronic exposure and withdrawal. Indeed, patients with alcohol use disorders (AUDs) frequently report suffering from sleep problems (Brower et al., 2001; Roncero et al., 2012; Steinig et al., 2011); and sleep disruption has been indicated as one of the greatest predictors of relapse during abstinence (Brower and Perron, 2010; Feige et al., 2007). In humans, acute ethanol intake increases NREM sleep in the beginning of the night and diminishes sleep quality later in the night (reviewed in Colrain et al., 2014). Ethanol also increases NREM sleep in rodents (Fang et al., 2017; Hattan and Eacho, 1978; Hill and Reyes, 1978; Kubota et al., 2002; Mendelson and Hill, 1978), and REM sleep is suppressed by acute ethanol intake in humans (reviewed in Colrain et al., 2014). In addition to the sleep effects, ethanol also produces sedative and anesthetic effects (Hendler et al., 2013; Morean and Corbin, 2010; Stevenson and Fox, 2013), which are characterized by a neurophysiological state comprised of one or more of the following symptoms: unconsciousness, amnesia, analgesia, and immobility. Sedation and anesthesia are associated with changes in the EEG power spectrum, but these

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states are neurophysiologically distinct from sleep (Akeju and Brown, 2017) as indicated by differences in the EEG. Few investigations have examined the acute effect of different doses of ethanol on EEG power spectra. Studies in humans suggest a variety of effects including increased alpha activity, decreased beta and sigma activity, and increased delta activity at different ethanol doses and sleep epochs, using different analysis methods (Dijk et al., 1992; Landolt et al., 1996; Rundell et al., 1972; Van Reen et al., 2006). In rodents, changes in the EEG power spectra may be specific to the light photoperiod when ethanol is administered (Fang et al., 2017; Kubota et al., 2002). Less is known about the power spectrum changes of the complete EEG induced by different doses of ethanol. To provide information about dose-dependent ethanol sedative effects and alterations in sleep, this study characterizes the dose-response relationship for ethanolinduced changes in EEG. We performed polysomnography recordings to analyze the sleep time/architecture and the quantitative features of the EEG: sleep states and power spectra.

2. Methods

2.1.

Ethical Statement:

All methods used in this work were approved by the Animal Care and Use Committee of the National Institute on Alcohol Abuse and Alcoholism (protocol #: LINDL-22) and were within the guidelines described in the NIH Guide to the Care and Use of Laboratory Animals.

2.2.

Subjects

Thirty 8-10 week-old male mice (Mus musculus, C57BL/6J strain) were obtained from the Jackson Laboratory (Bar Harbor, ME), and housed 2-4 per cage. After surgical implantation of chronic electrodes, mice were single-housed for the remainder of the

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study. Initially, mice weighed 25-30 g, and their body weight did not change substantially throughout the study. Upon arrival to the animal colony, all mice were maintained on a 12:12 hr light:dark cycle with lights turning on at 06:30 EST and off at 18:30 EST. Because alteration of the light cycle served as an independent variable in the experiment with ethanol administration, we denote time of day relative to the light cycle by referring to Zeitgeber time (ZT) on the x-axis of all time-domain representations of data. ZT 00:00 refers to the onset of the light photoperiod (LP), and ZT 12:00 refers to the onset of the dark photoperiod (DP) in the 12:12 cycle used in all experiments described herein. Throughout all parts of the study, subjects were provided with ad libitum access to food and water and housed in an environment maintained at 22.2°C and 50% humidity.

2.3.

Implantation of polysomnographic electrodes:

Surgeries were performed on subjects anesthetized with isoflurane anesthesia. Custom electrode implants were prepared as described in Pava et al., 2016). Stereotaxic surgery was performed to implant electrodes over medial frontal cortex (FC, RC: +1.50, ML: +/-1.00) and occipital cortex (OC, RC: -2.50, ML: +/-2.00). A ground/reference electrode was also implanted over the cerebellum (Gnd/Ref, RC: -5.7, ML: +/-1.7). Electrodes consisted of stainless steel screws (Small Parts# AMS90/1P-25, Amazon Supply, Seattle, WA) that were placed in contact with the surface of the brain at the specified coordinates (Figure 1). During surgery, the three wire leads of the implant were wrapped around these screws, and mechanical stability and electrical connectivity of the wires to the screws was augmented by applying a small amount of electrically conductive glue (Bare Paint, Bare Conductive Ltd., London, UK). Thus, two independent EEG channels were created for FC and OC. The suture pad comprised the EMG channel and was implanted under the nuchal muscle, and all channels were referenced to the ground electrode over cerebellum. The entire implant was sealed to the skull with standard cold-cure dental acrylic. Post-operative pain and discomfort were mitigated by administering ketoprofen (5 mg/kg i.p.) analgesic solution immediately after the surgery was completed and once daily for the next two days. Following surgery,

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subjects were individually housed and allowed to recovery for two weeks before being tethered to recording equipment.

2.4.

Polysomnographic Sleep Recordings

The first week of recovery took place in the colony room. For the second week of recovery, the subjects were moved to the recording room, still in their home cages, and began entrainment to a reversed 12:12 hr light cycle (ZT 00:00 corresponded to 18:30 EST). After the second week of recovery, subjects were placed into the recording cages (custom fabricated, 4 L polycarbonate buckets, Cambro RFSCW4135, Webstaurant Store, Lancaster, PA) and tethered to commutators (SL6C/SB, Plastics One) to acclimate them to the recording environment and to habituate them to being tethered. These cages were placed into electromagnetically shielded chambers that provided sound and light attenuation (SAE chambers; 5 cages/chamber; CT-ENV-018MD-EMSX1, MED Associates, Fairfax, VT), with several cages present in each chamber such that mice could see and smell one another. The chambers were outfitted with white LED light strips (#10434, General Electric, Fairfield, CT) controlled by a timer synchronized with ambient room lighting. Thus, circadian entrainment to the reversed light cycle continued during the 7-day habituation to tethering and the recording environment. Standard food pellets were placed on the cage bedding and access to water was provided via glass tubes (#9019, Bio-serve, Frenchtown, NJ). Recordings of polysomnographic signals (EEG/EMG) were obtained from the chronically tethered mice over 23.5 hr periods. During the intervening half hour, data acquisition was halted to check on the animals to ensure ad libitum food and water were available, to obtain body weights, and perform injections (on select days of the experiment). EEG/EMG signals were amplified 1000x (20x HST/16V-G20 headstage followed by 50x wide-band PBX, Plexon, Dallas, TX) and digitized at 1kHz (PCI-6071E, National Instruments, Austin, Tx). Data collection used a standard PC computer (Optiplex GX620, Dell Computers, Round Rock, Tx) running Recorder v2 software (Plexon). A 60 Hz digital notch filter was applied to attenuate line noise on all channels. EEG channels were then low-pass filtered at 120 Hz with a 2-pole Bessel filter, and

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EMG channels were high-pass filtered 40 Hz with a 4 pole Bessel filter. Data were saved to disk for analysis offline. The use of the sleep monitoring equipment precludes the use of several measurements and manipulations (e.g. LORR, blood sampling, warming pads, other intrusions) that might normally be performed in acute alcohol experiments.

2.5.

Vigilance State Scoring

Polysomnographic data were scored as wake, NREM, or REM using software written in MATLAB and CUDA C that was developed and validated in our laboratory as previously described (Pava et al., 2016). Briefly, data were scored in 2 sec epochs by clustering power spectral features in a 3-dimensional state space. A 4 sec Hann windowed fast-Fourier transform (FFT) with a 2 sec step was calculated from raw EEG and EMG data to yield a time frequency response with 2 sec temporal resolution and 0.25 Hz frequency bins. From the FC EEG channel, we calculated a power spectral ratio (0.5 to 20 Hz/0.5 to 100 Hz) known to separate NREM from wake and REM (Gervasoni et al., 2004). Because the placement of the OC EEG channel was optimized to capture more robust theta rhythms, we obtained a second power spectral ratio from this channel to compute the prominence of theta and low alpha relative to delta power (5 to 10 Hz/0.5 to 4 Hz). This ratio has been used to help separate REM epochs which are characterized by an overall increase in the theta bandwidth (Bastianini et al., 2014; Diniz Behn et al., 2010; Weber et al., 2015). Finally, the root mean square values of the EMG power spectra were obtained for each epoch, and together with the two power spectral ratios, these values comprised 3 orthogonal vectors representing the statespace. Next, each vector was smoothed by convolution with a 10 sec Hann window, and then median-centered and normalized to the maximum absolute value yielding a smoothed state-space that was bounded by ±1 on all axes. The classification of the state-space proceeded through three steps as previously described (Pava et al., 2016). The first step was implemented to obtain a rough estimate of the boundaries for each state based on the univariate distributions along each axis. These boundaries were used to produce a starting point for establishing a

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preliminary score. Next, based on this preliminary score a 3-dimensional product kernel estimate using a Gaussian kernel function was calculated for each cluster (i.e. wake, NREM, REM, and unassigned). These estimates were scaled such that their maximal values were equal to the value in the corresponding peak of the overall density function. From this estimate we established 99% confidence intervals that formed inclusion criteria for the three clusters. Finally, to clean up unassigned points that were bounded by epochs of the same state, we applied a transitional classifier. The scoring results for each subject were visually inspected to ensure accuracy, and subjects with excessive noise in the EEG/EMG signals that interfered with scoring were eliminated from further analyses. Two mice were eliminated of the first experiment because of pour EMG and another seven did not start the second experiment. The visual inspection of temporally aligned waveforms, FFT results, and vigilance state scoring was performed with a custom graphical user interface written in MATLAB. The scoring algorithm used here is predicated on the assumption that there are three vigilance states (wake, NREM, and REM) with periods of transition between these states that are ambiguous because the pattern of EEG activity within the 4 sec window is changing as the animal moves between states. In this case, we leave these epochs unclassified because it is difficult to assign them to one state or another. This is reflected in the fact that these points reside at the boundaries between clusters in the state-space (Pava et al., 2016). However, during the course of reviewing data obtained following a 4 g/kg ethanol injection, we noted that the visual appearance of time and frequency domain signals from EEG channels did not conform to standard definitions of any of the three vigilance states (Mang and Franken, 2012) (see results section). Therefore, we manually adjusted the score for these epochs (exclusively at the beginning of files from the 4 g/kg dose) to a fifth state using the same custom MATLAB program used to review scored files. These changes were saved to disk, and the modified score was used in subsequent analyses.

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2.6.

Analysis of Sleep-Wake States

To calculate how prominence and architecture of vigilance states changed over the circadian period, a moving window (1 hr window with 30 min increment) was passed over each subject’s sleep score for each day of the experiment. Thus, we sampled from 47 windows evenly spread over a recording day because each recording day was 23.5 hr long. To determine the probability of each vigilance state, the number of epochs in a given state were divided by the total number of epochs in the window. For sleep architecture measurements, a “bout” was defined as a contiguous block of epochs assigned to the same state. To calculate the number of bouts for a given state, we counted the number of these events occurring within each 1 hr window for each subject. To calculate the bout duration, we obtained the average number of epochs per bout of a given state within each window, and then we multiplied this number by 2 sec (duration of each epoch). Thus, for each subject on each day of the experiment we obtained timeseries estimates of the probability and architecture of each state with 30 min resolution.

2.7.

Power Spectral Analysis of EEG Signals

Power spectra were obtained from the windowed FFT calculated during the state-scoring algorithm. The same moving window technique used to analyze the sleepwake score was applied in analysis of power spectral bandwidths yielding a smoothed time-series for each subject with 30 min temporal resolution. For each subject on each recording day, we obtained measures of the following bandwidths (delta: 0.5-4 Hz, theta: 4-8 Hz, Alpha: 8-12 Hz, Gamma: 30-100 Hz). Bandwidths were measured independent of vigilance state by averaging the integrated power from a particular bandwidth from all epochs in a window, and additionally, the prominence of each bandwidth within each vigilance state was assessed by averaging the power of a particular bandwidth only from epochs of a given state in a window. In all cases, the raw integrated spectrum (i.e. without normalization) was analyzed and is presented in the graphs.

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2.8.

Experiment 1: Dose-Response Effects of Ethanol

The acute ethanol dose-response experiment was broken into two phases that proceeded identically, except that injections were given at opposite points in the circadian cycle (Figure 1). In the first phase of the experiment, all injections were given before the onset of the LP (ZT 00:00), and in the second phase, all injections were given before the onset of the DP (ZT 12:00). On the first day of phase one, subjects were removed from the SAE chambers and their home cages at ZT 23:30. They were then weighed, administered an injection of physiological (0.9%) saline (i.p. 0.03 mL/g), and returned to the recording environment. Recordings obtained from this day constituted a baseline measure of sleep-wake behavior and quantitative measures of the EEG. The purpose of this baseline recording was to obtain information that could be used to normalize data from subsequent days if there was high inter-subject variance in the data set. However, these data (i.e. the normalization) were not needed, and they are not presented here. After obtaining these baseline measures, subjects were divided evenly into 5 groups (4 mice per group) that received different patterns of injections of ethanol (0.0, 0.5, 1.0, 2.0, and 4.0 g/kg) across the next 10 days. All subjects received each dose of ethanol in a Latin square design (Figure 1). Injections were given once every 48 hr, so subjects had a full circadian cycle without an injection to recover prior to testing the next dose. We also obtained recordings on the recovery days to assess whether there were any latent effects at this extended time point. In all measures, there were no effects of ethanol 24 – 48 hr after the injection (data not shown). After completion of the first phase of the experiment, subjects were returned to standard cages (untethered) for one week, during which they began entrainment to a reversed light cycle (lights ON at 06:30 EST : OFF at 18:30 EST). Entrainment to the new cycle continued over the following week, during which time subjects were placed back into recording cages and tethered for re-habituation. The second phase of the experiment commenced after they had habituated for a week. Again, a baseline recording was obtained following a saline injection on the day prior to starting the Latin square, but these data are not presented here. During the Latin square portion of this

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phase of the study, subjects received the same pattern of ethanol injections that were administered during the first phase of the experiment. Again, there was a 24 hr recovery day included in the Latin square, so subjects only received injections once every 48 hr. There were no effects of ethanol 24 – 48 hr after the injection (data not shown).

2.9.

Experiment 2: Effect of NMDA Antagonism and GABAA Activation

In an initial experiment, 5 mg/kg diazepam was unsuccessful in producing anesthesia even when administered in conjunction with MK-801 (data not shown). After pilot studies, we observed that 15 mg/kg diazepam + 0.4 mg/kg MK-801 produced substantial sedation (ataxia, hypolocomotion, and reduced response to manual perturbation) (data not shown). Therefore, we used 20 mg/kg diazepam thinking that substantial anesthesia should be observed at this dose in combination with 0.4 mg/kg MK-801. Mice received diazepam, MK801 or both drugs before the onset of the LP (ZT 00:00). Drug administration and polysomnography recordings followed the procedures in the previous experiment.

2.10. Statistical Analysis In analysis of data from all experiments, time of day (ToD) and the effect of photoperiod (Photo) were included as repeated factors along with drug dose (Tx), yielding a three-way repeated measures design: Tx x ToD x Photo. All analyses were performed as marginal models using the MIXED command in SPSS (IBM, Bethesda, MD). Bonferroni corrected pair-wise comparisons were performed between different drug doses and saline using the model-derived estimated marginal means, and the corrected P-values are reported for these tests. For all analyses α = 0.05.

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3. Results

3.1.

High dose ethanol produces a novel vigilance state that differs from the EEG pattern of normal NREM sleep

During the process of data acquisition, waveforms were visualized with a built-in scope function in Recorder software. Observations with this function revealed that all subjects receiving the highest dose of ethanol (4.0 g/kg) displayed a marked theta oscillation in both EEG channels. This was confirmed during post-hoc review of scoring results, where this pattern of activity was found to last between 45 min and 1 hr and gave way to a pattern of activity resembling NREM sleep with very robust slow-waves (Figure 2A). The secondary, slow-wave-rich NREM phase of the response to high-dose ethanol is consistent with EEG patterns observed following GABAergic general anesthetics (Feinberg and Campbell, 1997; Purdon et al., 2015; Staudacherová et al., 1979), but the initial response was qualitatively different from this pattern despite the fact that the mice were behaviorally inactive. While REM sleep in rodents is characterized by a robust theta oscillation, REM sleep is also associated with a complete loss of muscle tone (Mang and Franken, 2012). Paradoxically, there was a low level of increasing muscle tone evident throughout the altered state, until the initiation of the slow-wave rich NREM phase of the response to the 4.0 g/kg dose. The presence of this muscle tone stands in contrast to the classical definition of REM, despite the robust theta oscillation. These differences observed in the time domain voltage traces are clearly illustrated in the time-frequency periodograms following saline, 2.0, and 4.0 g/kg ethanol injections (Figure 2B). Relative to the saline injection, 2.0 g/kg ethanol briefly produced a slight increase in low frequencies in the FC channel during a bout of NREM sleep, but the 4.0 g/kg dose substantially altered the shape of the frequency distribution for about 45 min following the injection in both FC and OC. This phenomenon was consistent across all subjects as indicated by a comparison between average power spectra from wake, NREM, and REM epochs obtained during the first hour following the saline

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injection and the mean from all epochs labelled as the altered state during the first hour following 4 g/kg ethanol (Figure 2C). These data show that 4.0 g/kg ethanol synchronized EEG oscillations around 5.5 Hz, while suppressing other frequencies. To yield a completely unbiased assessment of ethanol effects on the overall distribution of frequencies in the EEG, the power spectra from each epoch during the first hour of recording were averaged for each channel from each subject (Figure 2D). Again, there was a peak evident at 5.5 Hz following the 4.0 g/kg dose in both channels that was not evident after saline or 2.0 g/kg ethanol administration, and furthermore, other frequencies were suppressed relative to saline. Given the stark differences between the time- and frequency-domain response of the EEG signal during the initial response following 4 g/kg ethanol, epochs in the first hour of recording that displayed the 5.5 Hz oscillatory peak and suppression of other rhythms with little to moderate EMG tone were classified as the Drug-Induced State with a Characteristic Oscillation in the Theta Band (DISCO-T).

3.2.

High dose ethanol increases NREM sleep time while suppressing wake

To quantify the dose-response effect of acute ethanol administration on vigilance states, the probability of being in each state (Wake, NREM, REM, and DISCO-T) was estimated using a moving window average for each subject. Surprisingly, only the 4.0 g/kg dose produced consistent, large magnitude effects on the probability of vigilance states. As indicated above, the DISCO-T state was only observed following this dose, and as the probability of DISCO-T declined over the first hour of recording following the injection, there was a large increase in the amount of NREM sleep with reduced wake and REM (Figure 3A). Importantly, these effects, including the ability to induce DISCOT, were observed independent of the time of day the ethanol was administered (top x bottom row of Figure 3A), albeit the magnitude of the effects were clearly susceptible to modulation by ongoing circadian activity. Because DISCO-T was observed for a relatively brief period only following the highest dose of ethanol used in this study, we did not include this state in dose-response quantifications of state probability, architecture, or EEG power spectra. Nevertheless, the presence of this state (in

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preference to other states) did affect the resulting quantifications of wake, NREM, and REM during the first hour of recording after a 4 g/kg ethanol injection. Next, ethanol effects on specific sleep-wake states (wake, NREM, and REM) were compared as a function of dose and time (Figure 3B). In the first phase of the experiment when ethanol was administered before the LP (top row of graphs, Figure 3B), there was a significant overall interaction on the probability of wake (Tx x ToD x Photo, F(176, 1398.78) = 2.06, p < 0.001) with main effects of treatment (F(4, 1175.90) = 5.61, p < 0.001) and photoperiod (F(1,1227.01) = 1667.62, p < 0.001). While wake probability is usually low throughout much of the LP, there was a significant reduction in wake probability following the 2.0 and 4.0 g/kg doses when compared with saline (ZT 00:00 – 00:30, p ≤ 0.015). There was also an attenuation of wake probability in the middle of the DP following the 2.0 g/kg dose (ZT 18:00 – 19:00, p ≤ 0.009). Additionally, there was a significant 3-way interaction for NREM probability (Tx x ToD x Photo, F(176, 1397.07) = 1.83, p < 0.001) with main effects of treatment (F(4, 1192.41) = 2.48, p = 0.043) and photoperiod (F(1, 1243.54) = 1439.26, p ≤ 0.001). The 4.0 g/kg dose initially reduced NREM sleep during the first hour of the recording (ZT 00:00 – 01:00, p ≤ 0.004) in favor of the DISCO-T state, but following this period, there was a significant increase in the probability of NREM (ZT 02:00 – 03:00, p ≤ 0.001). There was also a significant increase in NREM probability late in the recording following 2.0 g/kg ethanol administration (ZT 18:00 – 19:00, p ≤ 0.011) at the same time point where wake was diminished. Finally, for REM there was an overall interaction (Tx x ToD x Photo, F(176, 1362.36) = 1.52, p < 0.001) with main effects of treatment (F(4, 1174.34) = 3.32, p = 0.010) and photoperiod (F(1, 1225.25) = 1238.59, p < 0.001). The 4.0 g/kg dose suppressed REM across the first 3.5 hr of the recording (ZT 00:00 – 03:30, p ≤ 0.031) and later in the LP (ZT 07:00 – 08:00, p ≤ 0.043). Both the 0.5 g/kg and 1.0 g/kg dose slightly increased REM probability toward the middle of the LP (ZT 04:00 – 04:30, p ≤ 0.039), and the 2.0 g/kg dose increased REM in the DP around the same time when wake was reduced and NREM increased (ZT 18:00 – 18:30, p = 0.025). More generally, the 4.0 g/kg dose had biphasic effects on REM probability, inducing a significant suppression of REM across the LP (p < 0.001) and increasing REM in the DP (p = 0.002).

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In the second phase of the experiment, when ethanol was administered before the DP (bottom row of graphs, Figure 3B), the direction of effects on NREM and wake was similar to those seen with administration before the LP, but the magnitude and duration of these effects was substantially greater when ethanol was administered before DP. Indeed, it is easier to observe decrease or increase of an effect when basal levels are higher or lower, respectively (i.e. due to reduced ceiling and floor effects). For wake probability, there was and overall interaction (Tx x ToD x Photo, F(180, 1196.76) = 3.12, p < 0.001) and main effects of treatment (F(4, 951.53) = 6.58, p < 0.001) and photoperiod (F(1, 991.19) = 1057.60, p < 0.001). Only the 4 g/kg dose altered wake probability, most obviously across the first 3 hr. of the recording (ZT 12:00 – 15:00, p ≤ 0.003). This dose also reduced wake probability later in the DP (ZT 18:30 – 19:00, p = 0.041), while increasing wake probability during the transition from DP to LP (ZT 12:30 – 1:00, p ≤ 0.039) and in the middle of the LP (ZT 04:30 – 05:00, p = 0.024). For NREM probability, there was an overall interaction (Tx x ToD x Photo, F(180, 1172.60) = 1.94, p < 0.001) as well as main effects of treatment (F(4, 951.68) = 3.09, p = 0.015) and photoperiod (F(1, 991.46) = 894.47, p < 0.001). There was a slight delay in the effect of ethanol on NREM probability due to the presence of the DISCO-T state early in the recording, but from ZT 12:30 – 15:30 the 4.0 g/kg ethanol dose significantly increased the amount of NREM sleep (p ≤ 0.005). During the transition between the LP and DP (ZT 23:30 – 00:30) and at one point in the middle of the LP (ZT 04:30 – 05:00), 4.0 g/kg ethanol significantly reduced NREM probability (p ≤ 0.045). In contrast to wake and NREM, REM probability was oppositely modulated by high dose acute ethanol administration before the DP compared to the effect when this dose was administered before the LP. For REM probability, there was an overall interaction (Tx x ToD x Photo, F(180, 1112.19) = 1.36, p = 0.002) and a main effect of photoperiod (F(1, 1044.77) = 1626.765). The 4.0 g/kg ethanol dose significantly increased REM probability early in the DP (ZT 13:30 – 14:30, p ≤ 0.004), while reducing REM sleep during the early (ZT 00:00 – 01:00) and middle (ZT 04:30 – 05:00) of the LP (p ≤ 0.044). However, later in the LP, REM probability was briefly increased (ZT 07:30 – 08:00, p = 0.028).

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3.3.

Dose-Response Effects of Acute Ethanol on Sleep-Wake Architecture

To better understand ethanol effects on sleep-wake states, measures of sleep architecture (number of bouts and bout duration) were compared across ethanol doses. Ethanol administration before the LP did not affect wake bout duration (Figure 4A, left column, top), but for the number of wake bouts (Figure 4A, left column, bottom), there was a significant overall interaction (Tx x ToD x Photo, F(176, 1298.41) = 1.27, p = 0.015) and a main effect of photoperiod (F(1, 898.68) = 50.17, p < 0.001). The 4.0 g/kg dose significantly reduced the frequency of wake bouts for the first 2 hr. of the recording (ZT 00:00 – 02:00, p ≤ 0.033), while there was an increase in wake bouts following the 2.0 g/kg dose during the middle of the DP (ZT 18:30 – 19:00, p = 0.003). For NREM bout duration (Figure 4A, middle column, top), there was an overall interaction (Tx x ToD x Photo, F(180, 2070.57) = 1.49, p < 0.001) and main effects of both treatment (F(4, 565.85) = 7.73, p < 0.001) and photoperiod (F(1, 637.26) = 275.39, p < 0.001). The 4.0 g/kg dose significantly increased NREM bout duration for 3 hr following the injection (ZT 00:00 – 03:00, p ≤ 0.001), while the 2.0 g/kg dose increased NREM bout duration at several of the same time points (ZT 00:00 – 00:30 & 01:00 – 01:30, p ≤ 0.023). The number of NREM bouts was also affected by acute ethanol administration before the LP (Figure 4A, middle column, bottom). There was an overall interaction (Tx x ToD x Photo, F(176, 1350.36) = 1.25, p = 0.019) and a main effect of photoperiod (F(1, 883.20) = 139.86, p < 0.001). The number of NREM bouts was significantly reduced for 1.5 hr. following administration of 4.0 g/kg ethanol (ZT 00:00 – 1:30, p ≤ 0.034), but there was an increased number of NREM bouts in the middle of the DP following the 2.0 g/kg (ZT 18:00 – 19:00, p ≤ 0.049) and 4.0 g/kg dose (ZT 18:30 – 19:00, p = 0.034). For REM bout duration (Figure 4A, right column, top), there was a significant secondary interaction (Tx x Photoperiod, F(4, 931.93) = 7.17, p < 0.001) and main effects of both treatment (F(4, 894.62) = 6.46, p < 0.001) and photoperiod (F(1, 955.69) = 12.48, p < 0.001). The 4.0 g/kg ethanol dose significantly reduced REM bout duration during the LP (p < 0.001) but not the DP (p = 1.00). Similarly, for the number of REM

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bouts (Figure 4A, right column, bottom), there was a secondary interaction (Tx x Photo, F(4, 1048.90) = 7.70, p < 0.001) and a main effect of photoperiod (F(1, 1070.48) = 909.30, p < 0.001). The 4.0 g/kg ethanol dose significantly reduced the number of REM bouts during the LP (p = 0.047) and increased REM bouts during the DP (p = 0.009). For the second phase of the experiment with ethanol administration before the DP, wake bout duration (Figure 4B, left column, top) was not significantly affected by ethanol treatment, similar to the results obtained when ethanol was administered before the LP. In contrast, for the number of wake bouts (Figure 4B, left column, bottom) there was an overall interaction (F(180, 1141.42) = 1.25, p = 0.022) and a main effect of photoperiod (F(1, 728.70) = 171.69, p < 0.001). The 4.0 g/kg dose had biphasic effects on the number of wake bouts, reducing the number of bouts during the first hour after ethanol administration (ZT 12:00 – 1:00, p ≤ 0.002) and significantly increasing wake bout frequency later in the DP (ZT 18:00 – 19:00, 22:30 – 23:00, p ≤ 0.048). There was also a significant reduction in the number of wake bouts following 4.0 g/kg at the transition from the DP to the LP (ZT 23:30 – 00:00, p = 0.017). For NREM bout duration (Figure 4B, middle column, top), there was an overall interaction (Tx x ToD x Photo, F(180, 979.34) = 3.39, p < 0.001) and a main effect of photoperiod (F(1, 453.94) = 6.12, p = 0.014). Relative to saline, the 4.0 g/kg ethanol dose significantly increased the duration of NREM bouts for the first 2 hr after administration (ZT 12:00 – 14:00, p ≤ 0.002) and decreased NREM bout duration during the first 30 min of the LP (ZT 00:00 – 00:30, p = 0.034). The frequency of NREM bouts (Figure 4B, middle column, bottom) was also affected by ethanol administration. There was a significant overall interaction (F(180,1133.32) = 1.24, p = 0.025) and main effects of both treatment (F(4, 669.11) = 3.92, p = 0.004) and photoperiod (F(1, 713.97) = 234.96, p < 0.001). Administration of 4.0 g/kg ethanol significantly increased the number of NREM bouts at several time points across the DP (ZT 14:30 – 15:00, 18:00 – 19:00, and 22:30 – 23:00, p ≤ 0.045). There was also a significant reduction in the number of NREM bouts at the transition between LP and DP (ZT 23:30 – 00:30, p ≤ 0.042). For REM bout duration (Figure 4B, right column, top), there was a significant 3way interaction (Tx x ToD x Photo, F(180, 956.76) = 1.40, p = 0.001) and main effects

17

of treatment (F(4, 596.03) = 5.48, p < 0.001) and photoperiod (F(1, 641.41) = 56.79, p < 0.001). In contrast to some other measures, multiple doses had effects on REM bout duration. Following administration of the lowest dose of ethanol (0.5 g/kg), there was a significant reduction in REM bout duration in the 30 min just before the DP (ZT 23:30 – 00:00, p = 0.029). The 1.0 g/kg dose had effects at more time points across the circadian cycle. During the first 30 min after administration, there was a significant increase in REM bout duration (ZT 12:00 – 12:30, p < 0.001), while REM bouts were shorter across the transition from DP to LP (ZT 23:30 – 00:30, p ≤ 0.046). The 2.0 g/kg dose reduced REM bout duration at a similar time point in the circadian cycle (ZT 00:00 – 1:00, p ≤ 0.040) as did the 4.0 g/kg dose (ZT 00:00 – 00:30, p < 0.001). The 4.0 g/kg dose also reduced REM bout length over 2 hr in the early DP as well (ZT 13:30 – 15:30, p ≤ 0.049). Finally, for the number of REM bouts (Figure 4B, right column bottom), there was an overall interaction (Tx x ToD x Photo, F(180, 1102.45) = 1.79, p < 0.001) and main effects of both treatment (F(4, 842.45) = 8.81, p < 0.001) and photoperiod (F(1, 884.74) = 871.69, p < 0.001). The number of REM bouts was briefly increased shortly after ethanol administration (ZT 12:00 - 12:30, p = 0.002), but following the 4.0 g/kg dose there was a large, delayed increase in the number of REM bouts beginning 1.5 hr after ethanol administration and continuing for 2 hr (ZT 13:00 – 15:00, p ≤ 0.002). Compared to the response to saline injection, there was a slight reduction in the number of REM bouts at the beginning of the LP (ZT 00:00 – 00:03, p = 0.021) and an increased number of bouts later in the LP (ZT 07:30 – 08:00, p = 0.008). While the induction of the DISCO-T state by high dose ethanol reduced the number of wake and NREM bouts shortly after drug administration, this transient effect gave way to an increase in the duration of NREM bouts. In contrast, the modulation of REM sleep architecture was complex, and the valence of the alterations was dictated by the circadian timing of drug administration.

3.4.

Dose-dependent effects on EEG power spectra

To assess how quantitative features of the EEG were affected by ethanol, independent of alterations in vigilance states, delta, theta, alpha, and gamma power

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spectral bandwidths from both FC and OC derivations were compared across ethanol doses (Figure 5). For measures of delta power obtained after ethanol administration before the LP, there was a significant overall interaction (Tx x ToD x Photo, F(176, 2332.08) = 1.44, p < 0.001) and main effects of both treatment (F(4, 29894) = 3.86, p = 0.004) and photoperiod (F(1, 400.14) = 55.43, p < 0.001). Starting 1 hr after administration, 4.0 g/kg ethanol produced a significant increase in delta power that lasted for 3 hr (ZT 01:00 – 03:00, p ≤ 0.044). There was no effect of ethanol administration before the LP on delta power recorded from the OC derivation. Also, there was no effect on either FC or OC delta power when ethanol was administered before the DP. In contrast to delta power, FC theta oscillations displayed a biphasic response to ethanol administration before the LP (overall interaction, Tx x ToD x Photo, F(176, 1098.02) = 1.33, p = 0.005). The 2.0 g/kg dose produced a transient suppression of theta power beginning 30 min after administration (ZT 00:30 – 01:00, p < 0.050), while the 4.0 g/kg dose reduced theta power throughout the first 2 hr of recording (ZT00:00 – 02:00, p < 0.001). The 4.0 g/kg dose also produced a significant elevation of theta power that lasted for 2 hr starting in the middle of the LP (ZT 05:30 – 07:30, p ≤ 0.033). For OC theta power, there was a significant overall interaction (Tx x ToD x Photo, F(176, 1458.03) = 3.80, p < 0.001) and a main effect of photoperiod (F(1, 53.89) = 426.90, p < 0.001). However, the 4.0 g/kg dose produced only a brief suppression of theta in this recording channel (ZT 01:00 – 01:30, p = 0.041). When ethanol was administered before the DP, there was a more obvious effect to attenuate theta power in the FC, especially by the 2.0 g/kg dose. There was an overall interaction (Tx x ToD x Photo, F(176, 2053.50) = 1.48, p < 0.001) and a main effect of photoperiod (F(1, 307.01) = 8.47, p = 0.004). Following administration of 2.0 g/kg ethanol, theta power was reduced for 1.5 hr (ZT 12:00 – 13:30, p ≤ .030), while the 4.0 g/kg dose decreased theta for 2.5 hr (ZT 12:00 – 14:30, p ≤ 0.001). Ethanol administration before the DP had no effect on OC theta power. Similar to theta oscillations, alpha power was initially suppressed by acute ethanol administration, but this response was followed by elevated alpha power later in the recording. For FC measurements obtained after LP ethanol administration, there 19

was significant overall interaction (Tx x ToD x Photo, F(176, 2247.17) = 4.35, p < 0.001) and a main effect of photoperiod (F(1, 428.15) = 80.96, p < 0.001). The initial effect to reduce FC alpha power was observed during the first hour after administration of the 2.0 g/kg dose (ZT 00:00 – 01:00, p < 0.001) and for 3.5 hr after 4.0 g/kg ethanol (ZT 00:00 – 03:30, p ≤ 0.048). There was a secondary response to the 4.0 g/kg dose that produced increased FC alpha power later in the LP (ZT 06:30 – 07:30, p ≤ 0.025). For alpha power measured from the OC derivation following LP ethanol administration, there was also a significant overall interaction (F(176, 2741.60) = 22.60, p < 0.001) and main effects of both treatment (F(4, 36.30) = 3.93, p = 0.009) and photoperiod (F(1, 128.50) = 184.47, p < 0.001). For 2 hr following the 2.0 g/kg dose, OC alpha power was reduced compared to saline (ZT 00:00 – 02:00, p ≤ 0.004), while 4.0 g/kg ethanol decreased alpha power for the first 4.5 hr of the LP (ZT 00:00 – 04:30, p ≤ 0.016). Again, there was a biphasic response to the highest dose of ethanol characterized by increased alpha power across much of the second half of the LP (ZT 06:30 – 07:30 & 08:00 – 10:00, p ≤ 0.009). This increased alpha power persisted across many time points in the DP (ZT 12:00 – 12:30, 13:00 – 13:30, 15:00 – 16:00, 18:00 – 19:00, and 23:00 - 23:30, p ≤ 0.039). For alpha measures in the FC derivation following ethanol administration before the DP, there was an overall interaction (F(176, 982.73 = 4.97, p < 0.001) and a main effect of photoperiod (F(1, 126.14) = 207.82, p < 0.001). Similar to administration before the LP, ethanol intoxication at the beginning of the DP caused a dose-dependent reduction in FC alpha power. Immediately following the 2.0 g/kg dose, alpha power was reduced for 1.5 hr (ZT 12:00 – 13:30, p ≤ 0.038), and the 4.0 g/kg dose attenuated alpha power for 3.5 hr (ZT 12:00 – 15:30, p ≤ 0.003). Again, there was a biphasic response to 4.0 g/kg ethanol, but the secondary increase in alpha power was significantly different from saline for only a brief time near the middle of the DP (ZT 18:30 – 19:00, p = 0.034). For alpha power in the OC, there was a significant interaction (F(176, 834.4) = 3.44, p < 0.001) and a main effect of photoperiod (F(1, 116.96) = 55.04, p < 0.001). The 2.0 g/kg dose produced a transient suppression of OC alpha during the 30 min immediately after the injection (ZT 12:00 – 12:30, p = 0.042), but the 4.0 g/kg dose reduced alpha power across the first 3 hr of the DP (ZT 12:00 – 15:00, p

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≤ 0.022). Unlike measures of alpha power from the OC after LP ethanol administration, there was no secondary process evident in OC EEG recordings after DP ethanol. Gamma oscillations were sensitive to acute ethanol administration at higher doses (2.0 and 4.0 g/kg). For FC gamma power following LP ethanol administration, there was an overall interaction (Tx x ToD x Photo, F(176, 1336.87) = 2.46, p < 0.001) and main effects of both treatment (F(4, 751.92) = 7.55, p < 0.001) and photoperiod (F(1, 647.89) = 427.15, p < 0.001). The 2.0 g/kg dose decreased gamma power for the first 30 min of the LP (ZT 00:00 – 00:30, p < 0.001), while 4.0 g/kg ethanol administration attenuated FC gamma for 3.5 hr (ZT 00:00 – 03:30, p ≤ 0.018). For OC gamma power, there was an overall interaction (Tx x ToD x Photo, F(176, 1247.69) = 1.68, p < 0.001) and a main effect of photoperiod (F(1, 475.94) = 266.73, p < 0.001). Again, 2.0 g/kg ethanol administration had only a transient effect to reduce gamma power during the first half hour of the LP (ZT 00:00 – 00:30, p < 0.001), and 4.0 g/kg ethanol decreased gamma for the first 3 hr after the injection (ZT 00:00 – 03:00, p ≤ 0.011). For FC gamma power after DP ethanol administration, there was an overall interaction (F(176, 1155.04) = 3.61, p < 0.001) and main effects of both treatment (F(4, 601.78) = 10.40, p < 0.001) and photoperiod (F(1, 647.89) = 427.15, p < 0.001). The 2.0 g/kg dose decreased FC gamma for the first hour after the injection (ZT 12:00 – 13:00, p ≤ 0.007), while the 4.0 g/kg dose reduced gamma power across the first 3.5 hr of the DP (ZT 12:00 – 15:30, p < 0.001). There was a secondary effect to increase gamma power following the 4.0 g/kg dose, but this effect occurred much later in the recording (ZT 23:30 – 00:30, p ≤ 0.038) than the rebound seen in theta and alpha activity. Similar effects were observed for OC gamma, where there was an overall interaction (Tx x ToD x Photo, F(176, 1104.94) = 2.10, p < 0.001) and main effects of both treatment (F(4, 312.88) = 2.43, p = 0.048) and photoperiod (F(1, 375.18) = 89.55, p < 0.001). The 2.0 g/kg ethanol dose reduced OC gamma power for the first half hour of the recording (ZT 12:00 – 12:30, p = 0.001), while the 4.0 g/kg dose reduced OC gamma for 3.5 hr (ZT 12:00 – 15:30, p ≤ 0.014). Additionally, the 4.0 g/kg dose also increased OC gamma during the onset of the LP (ZT 00:00 – 00:30, p = 0.043). Thus, acute ethanol administration had complex effects on EEG power spectra that were dose, time, and

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bandwidth specific, but generally speaking, ethanol increased low frequency power while reducing faster oscillatory components.

3.5.

Acute Ethanol Induces State-Specific Alterations in EEG Power Spectra

The frequency distribution of the EEG changes substantially across vigilance states, so it is possible that ethanol could have differential effects on EEG power spectra depending on the vigilance state. Therefore, the state-specific mean power in delta, theta, alpha, and gamma bandwidths was compared across ethanol doses (Figure 6). State-specific effects are only reported for the FC derivation because there was very little difference between FC and OC channels for these measures.

3.5.1. Delta Acute ethanol administration had opposite effects on delta frequencies when measurements were obtained from wake NREM epochs, and this effect was consistent regardless of whether ethanol was administered before the LP or DP (Figure 6A1 and 6A2). When ethanol was administered before the LP (Figure 6A1), for wake delta power there was an overall interaction (Tx x ToD x Photo, F(176, 1373.88) = 1.93, p ≤ 0.001) and main effects of both treatment (F(4, 1041.31) = 3.69, p = 0.005) and photoperiod (F(1, 1094.45) = 1260.63, p < 0.001). Compared to results following the saline injection, there was a significant transient suppression of wake delta during the first 30 min of the LP (ZT 00:00 – 00:30) following both the 2.0 (p = 0.001) and 4.0 g/kg doses (p < 0.001). Additionally, the 2.0 g/kg dose decreased wake delta toward the middle of the DP (ZT 18:00 – 19:00, p ≤ 0.032), and across the entire recording, the 4.0 g/kg dose significantly reduced wake delta power relative to saline (p = 0.018). For NREM delta power, there was an overall interaction (Tx x ToD x Photo, F(176, 1981.82) = 2.01, p < 0.001) and main effects of both treatment (F(4, 602.42) = 5.08, p < 0.001) and photoperiod (F(1, 673.85) = 666.33, p < 0.001). While the 2.0 g/kg dose significantly increased NREM delta power during the first 30 min of the recording (ZT 00:00 – 00:30, p = 0.001), the 4.0 g/kg dose has biphasic effects. Initially, 4.0 g/kg ethanol suppressed

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NREM delta power (ZT 00:00 – 01:00, p = 0.013), but this effect gave way to a significant enhancement of NREM delta that lasted 3 hr (ZT 01:00 – 04:00, p ≤ 0.040). Overall, the 4.0 g/kg dose increased NREM delta power (vs saline, p = 0.008). For REM delta power, there was an overall interaction (Tx x ToD x Photo, F(176, 1226.15) = 1.39, p = 0.001) and a main effect of photoperiod (F(1, 1172.68) = 778.82, p < 0.001). Starting 30 min after administration, the 4.0 g/kg dose significantly reduced REM delta power for 2 hr (ZT 00:30 – 02:30, p ≤ 0.004), and a little later in the LP, this dose produced a transient increase in REM delta power (ZT 04:00 – 04:30, p = 0.017). Curiously, there was also a slight but significant increase in REM delta power following the 0.5 g/kg dose at this time point (p = 0.027). When ethanol was administered before the DP, there were similar effects on state-specific delta power (Figure 6A2). For wake delta, there was a significant overall interaction (Tx x ToD x Photo, F(176, 1177.24) = 2.26, p < 0.001) and main effects of both treatment (F(4, 814.62) = 3.50, p = 0.008) and photoperiod (F(1, 856.23) = 665.99, p < 0.001). The 2.0 g/kg ethanol dose reduced wake delta power for 30 min after administration (ZT 12:00 – 12:30, p = 0.10), and the 4.0 g/kg dose decreased wake delta for 3 hr (ZT 12:00 – 15:00, p ≤ 0.005). Furthermore, wake delta was enhanced during the transition between the DP and LP following the 4.0 g/kg dose (ZT 23:30 – 01:00, p ≤ 0.036). For NREM delta, there was an overall interaction (Tx x ToD x Photo, F(176, 1111.09) = 1.53, p < 0.001) and main effects of treatment (F(4, 858.95) = 4.21, p = 0.002) and photoperiod (F(1, 898.50) = 432.27, p < 0.001). Starting 30 min after administration of 4.0 g/kg ethanol, NREM delta power was significantly increased for 2.5 hr (ZT 12:30 – 15:00, p ≤ 0.002), and at the transition between LP and DP, this dose significantly reduced delta power (ZT 23:30 – 00:30, p ≤ 0.003). Ethanol administration before the DP did not have a significant effect on REM delta power.

3.5.2. Theta Acute high-dose ethanol administration generally suppressed theta power irrespective of vigilance state or the circadian timing of the dose (Figure 6B1 & 6B2). However, measures obtained from different vigilance states differed with respect to

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duration of these effects, and administration before either the LP or DP also seemed to modulate the duration of ethanol’s immediate effects while also producing a differential response later in the recording (i.e. > 12 hr after injection). Following ethanol administration before the LP (Figure 6B1), for wake theta power there was an overall interaction (Tx x ToD x Photo, F(176, 1384.75) = 2.02, p < 0.001) and main effects of treatment (F(4, 1070.99) = 3.42, p = 0.009) and photoperiod (F(1, 1123.66) = 1545.47, p < 0.001). Both the 2.0 and 4.0 g/kg doses attenuated wake theta power immediately following drug administration for a brief time period (ZT 00:00 – 00:30, p ≤ 0.013). There was also a suppression of wake theta during the DP following the 2.0 g/kg dose (ZT 18:00 – 19:00, p ≤ 0.014). Similarly, NREM theta power was only transiently suppressed by acute ethanol administration. There was overall interaction (Tx x ToD x Photo, F(176, 1985.85) = 1.63, p < 0.001) and a main effect of photoperiod (F(1, 696.05) = 692.19, p < 0.001). The 4.0 g/kg dose decreased NREM theta for the first hour of the LP (ZT 00:00 – 01:00, p < 0.001), and there was an increase in NREM theta power near the middle of the DP following the 2.0 g/kg dose (ZT 18:00 – 19:00, p ≤ 0.032). For ethanol administration before the LP, the longest lasting effects on theta power were observed during REM epochs where there was an overall interaction (Tx x ToD x Photo, F(176, 1210.36) = 1.54, p < 0.001) and a main effect of photoperiod (F(1, 1219.27) = 871.82, p < 0.001). The 4.0 g/kg ethanol dose reduced REM theta power for 2 hr early in the LP (ZT 00:30 – 02:30, p < 0.001), and there was a brief, small increase in REM theta 4 hr after administration of 0.5 g/kg ethanol (ZT 04:00 – 04:30, p = 0.024). Ethanol administration before the DP had notably different effects on theta during wake and REM epochs (Figure 6B2). For wake theta, there was an overall interaction (Tx x ToD x Photo, F(176, 1171.34) = 2.53, p < 0.001) and main effects of both treatment (F(4, 834.85) = 3.83, p = 0.004) and photoperiod (F(1, 876.04) = 1049.54, p < 0.001). Administration of 2.0 g/kg ethanol reduced wake theta power in the first 30 min of the DP (ZT 12:00 – 12:30, p = 0.023), while 4.0 g/kg ethanol administration decreased wake theta for 3 hr (ZT 12:00 – 15:00, p ≤ 0.002). The 4.0 g/kg dose also produced an increase in wake theta over the transition from the DP to the LP (ZT 23:30 – 01:00, p ≤ 0.018) and briefly near the middle of the LP (ZT 04:30 – 05:00, p = 0.027). NREM theta was modulated to a lesser extent than wake theta oscillations. There was

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an overall interaction (Tx x ToD x Photo, F(176, 111.48) = 1.26, p = 0.019) and a main effect of photoperiod (F(1, 916.11) = 503.91, p < 0.001). Following 4.0 g/kg ethanol administration, there was an overall increase in NREM theta power during the DP (p = 0.001), but there was only a brief time point with significantly elevated theta power compared to saline (ZT 18:30 – 19:00, p = 0.018). In contrast, NREM theta was suppressed across the transition from DP to LP following the 4.0 g/kg injection (ZT 23:30 – 00:30, p ≤ 0.007). In contrast to the results from ethanol administration before the LP, there was no effect of ethanol administration before the DP on REM theta power.

3.5.3. Alpha Ethanol’s effects on alpha power (Figure 6C1 & 6C2) were similar to changes in the theta bandwidth. For ethanol administration before the LP (Figure 6C1) there were effects on EEG power spectra in all three vigilance states. For wake alpha, there was an overall interaction (Tx x ToD x Photo, F(176, 1409.93) = 2.11, p < 0.001) and main effects of both treatment (F(4, 1050.70) = 3.79, p = 0.005) and photoperiod (F(1, 1103.76) = 1595.31, p < 0.001). The 2.0 g/kg dose reduced wake alpha during the first 30 min of the recording (ZT 00:00 – 00:30, p < 0.001), while the 4.0 g/kg dose produced a longer lasting attenuation of wake alpha (ZT 00:00 – 01:00, p ≤ 0.031). However, the 2.0 g/kg increased wake alpha at one time during the DP (ZT 16:00 – 16:30, p = 0.034) while decreasing it a little later (ZT 18:00 – 19:00, p ≤ 0.008). Alpha power during NREM epochs was also affected by acute ethanol administration. There was an overall interaction (Tx x ToD x Photo, F(176, 1376.68) = 1.73, p < 0.001) and a main effect of photoperiod (F(1, 1209.50) = 1276.30, p < 0.001). Administration of 4.0 g/kg ethanol attenuated NREM alpha for the first 1.5 hr of the LP (ZT 00:00 – 01:30, p < 0.001). The 2.0 g/kg dose did not have significant effects on NREM alpha during the LP, but it did augment alpha power during the middle of the DP (ZT 18:00 – 19:00, p ≤ 0.024). Compared to wake and NREM, acute ethanol administration had longer lasting effects on REM alpha power. There was an overall interaction (Tx x ToD x Photo, F(176, 1208.18) = 1.54, p < 0.001) and a main effect of photoperiod (F(1, 1222.34) = 727.28, p

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< 0.001). Starting 30 min after drug administration, 4.0 g/kg ethanol significantly reduced REM alpha power for 3 hr (ZT 00:30 – 03:30, p ≤ 0.043). There was a subtle and transient increase in REM alpha following the 0.5 g/kg dose several hours after drug administration (ZT 04:00 – 04:30, p = 0.026), and the 2.0 g/kg dose briefly increased REM alpha during the middle of the DP (ZT 18:00 – 18:30, p = 0.029). When ethanol was administered at the onset of the DP, alpha power during wake epochs was substantially reduced, while effects on NREM alpha were subtle and REM alpha was unaffected (Figure 6C2). For wake alpha, there was an overall interaction (Tx x ToD x Photo, F(176, 1221.66) = 2.41, p < 0.001) and main effects of treatment (F(4, 793.96) = 5.07, p < 0.001) and photoperiod (F(1, 835.79) = 888.13, p < 0.001). Following the 2.0 g/kg dose, there was a brief attenuation of wake alpha (ZT 00:00 – 00:30, p = 0.005), while the 4.0 g/kg dose decreased wake alpha for 3 hr (ZT 12:00 – 15:00, p < 0.001). Additionally, across the transition from the DP to the LP, there was an increase in wake alpha when subjects had received 4.0 g/kg ethanol earlier in the day (ZT 23:30 – 01:00, p ≤ 0.019). Thus, 4.0 g/kg ethanol administration before the DP produced a biphasic response where wake alpha was decreased during the DP (p < 0.001) and increased during the LP (p = 0.013). For NREM alpha, there was an overall interaction (Tx x ToD x Photo, F(176, 1120.61) = 1.27, p = 0.014) and a main effect of photoperiod (F(1, 925.59) = 907.11, p < 0.001). When ethanol was administered before the DP, there was not an immediate effect on NREM alpha power, but there was a transient increase in NREM alpha during the middle of the DP following the 4.0 g/kg dose (ZT 18:30 – 19:00, p = 0.010). Furthermore, this high dose of ethanol reduced NREM alpha over the transition from DP to LP (ZT 23:30 – 00:30, p ≤ 0.008). There was no effect of ethanol on REM alpha power. Thus, the majority of ethanol’s effects on alpha rhythms occurred during wake epochs when ethanol was administered before the DP, while administration before the LP had more pronounced effects on REM alpha.

3.5.4. Gamma Gamma oscillations displayed a dose, state, and circadian modulated sensitivity to acute ethanol administration (Figure 6D1 & 6D2). When ethanol was administered

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before the LP (Figure 6D1), there was an overall interaction for wake gamma power (Tx x ToD x Photo, F(176, 1377.78) = 1.93, p < 0.001) and main effects of both treatment (F(4, 1113.32) = 6.34, p < 0.001) and photoperiod (F(1, 1165.40) = 1584.29, p < 0.001). The 2.0 g/kg ethanol dose decreased wake gamma for the first 30 min of the LP (ZT 00:00 – 00:30, p = 0.001), while the 4.0 g/kg dose decreased gamma over the first hour (ZT 00:00 – 01:00, p ≤ 0.035). The 2.0 g/kg dose also reduced wake gamma for 1 hr during the DP (ZT 18:00 – 19:00, p ≤ 0.028). For NREM gamma power, there was an overall interaction (Tx x ToD x Photo, F(176, 1371.38) = 1.56, p < 0.001) and a main effect of photoperiod (F(1, 1188.75) = 968.93, p < 0.001). The 4.0 g/kg ethanol dose reduced NREM gamma power for the first hour of LP (ZT 00:00 – 01:00, p < 0.001) and during the middle of the LP (ZT 04:30 – 05:00, p = 0.027). There was also increased NREM gamma power during the middle of the DP (ZT 18:00 – 19:00, p ≤ 0.032) following the 2.0 g/kg dose. For REM gamma, there was an overall interaction (Tx x ToD x Photo, F(176, 1190.78) = 1.54, p < 0.001) and main effects of both treatment (F(4, 1226.35) = 5.37, p < 0.001) and photoperiod (F(1, 1275.10) = 899.51, p < 0.001). There was a long-lasting attenuation of REM gamma power shortly after administration of the 4.0 g/kg ethanol dose (ZT 00:30 – 04:00, p ≤ 0.019) and again, later in the LP (ZT 07:00 – 07:30, p = 0.024). In contrast, the 0.5 and 1.0 g/kg doses produced a small, brief increase in REM gamma (ZT 04:00 – 04:30, p ≤ 0.024). As noted for alpha and theta power, when ethanol was administered before the DP, most of the effects on gamma oscillations were during wake epochs (Figure 6D2). For wake gamma, there was an overall interaction (Tx x ToD x Photo, F(176, 1176.14) = 2.64, p < 0.001) and main effects of treatment (F(4, 877.17) = 7.36, p < 0.001) and photoperiod (F(1, 917.66) = 928.08, p < 0.001). The 2.0 g/kg dose reduced wake gamma for the first 30 min of the recording (ZT 00:00 – 00:30, p = 0.001), and the 4.0 g/kg dose decreased gamma for 3 hr (ZT 12:00 – 15:00, p < 0.001). The 4.0 g/kg dose also increased wake gamma power over the transition from DP to LP (ZT 23:30 – 01:00, p ≤ 0.033) and later in the LP (ZT 04:30 – 05:00, p = 0.030). For NREM gamma, there was an overall interaction (Tx x ToD x Photo, F(176, 1110.84) = 1.21, p = 0.045) and a main effect of photoperiod (F(1, 896.73) = 690.52, p < 0.001). NREM gamma power was not significantly affected during most of the DP, but there was a decrease during

27

the transition from DP to LP (ZT 23:30 – 00:30, p ≤ 0.007). Gamma oscillations during REM epochs were not significantly affected by ethanol administration before the DP.

3.6.

NMDA antagonism and GABAA activation recapitulates the DISCO-T state induced by high dose Ethanol

Ethanol affects neuronal physiology by altering the function of several molecules (Abrahao et al., 2017), including those involved in glutamatergic and GABAergic synaptic transmission. Ethanol inhibits glutamatergic NMDA receptors (Lovinger et al., 1990) and potentiates GABAergic transmission in several parts of the brain (Ariwodola and Weiner, 2004; Roberto et al., 2003; Zhu and Lovinger, 2006; Zuo et al., 2017). We hypothesized that the anesthetic DISCO-T state, induced by the high dose of ethanol, is associated with ethanol effects on glutamatergic and GABAergic pathways. To attempt to mimic this ethanol effect, we recorded the EEG after systemic administration of an NMDA antagonist (MK801) a GABAA positive allosteric modulator (Diazepam DZ) or the cocktail of both drugs (MK801+DZ cocktail). Neither the NMDA antagonist (MK-801) nor the GABAA agonist (Diazepam DZ) were able to reproduce the DISCO-T state (data not shown). The MK-801+DZ cocktail did not induce a complete anesthetic effect (EMG in Figure 7A), although mice were ataxic upon visual inspection by the experimenter (data not shown). After the cocktail administration, the behavior was also qualitatively different from the 4 g/kg EtOH dose, which induced a complete loss of movement other than breathing. The raw example traces in Figure 7A show the electrophysiological characteristics at different time points after the MK-801 + DZ cocktail. The FC and the OC recordings recapitulate some features of the EEG recordings after 4.0 g/kg ethanol. These characteristics can be observed in the time domain voltage traces illustrated and in the time-frequency periodograms following vehicle and MK801+DZ cocktail (Figure 7B). Relative to the vehicle injection, MK-801+Diazepam substantially altered the shape of the frequency distribution for about 45 min in both FC and OC. The altered state induced by 4.0 g/kg ethanol also lasted for about 45 min, and it was marked by an increase in synchronized EEG oscillations around 5.5 Hz.

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We show the power spectra obtained after 4.0 g/kg of ethanol in Figure 7C to facilitate comparison to Figure 7D that shows the average power spectra obtained during the first hour following the vehicle, MK-801 alone, Diazepam alone, or MK801+Dizepam combined conditions. Note that the combined administration of the NMDA antagonist and GABAA agonist drugs elicited an altered state similar (Figure 7C) to what was observed after 4.0 g/kg ethanol. These data show that MK-801+Diazepam synchronized EEG oscillations around 5.5 Hz, while suppressing other frequencies in a manner similar to the ethanol-induced DISCO-T state.

4. Discussion

This study provides a thorough characterization of acute ethanol dose-dependent effects on sleep and EEG power spectra in C57BL/6J male mice. Ethanol had a narrow dose-response effect on sleep, and only the highest dose (4.0 g/kg) produced consistent, large effects on vigilance states, with the 2.0 g/kg dose having significant, but smaller and more variable effects. A 4.0 g/kg ethanol administration produced a unique, transient state that could not be characterized in terms of canonical sleep-wake states, so we dubbed this novel state DISCO-T to distinguish it from wake, NREM, and REM, which were quantified separately. The administration of 4.0 g/kg of ethanol promoted NREM sleep while reducing wake, but because of the presence of the DISCO-T state early in the recordings, ethanol’s augmentation of NREM was delayed by about 1 hr. While NREM was increased by ethanol administration before either the LP or DP, REM sleep was differentially responsive to the circadian timing of ethanol administration. The changes in vigilance states were associated with an increase in the duration of NREM bouts, indicating that acute ethanol preferentially stabilized the NREM state. EEG power spectra proved more sensitive to ethanol than sleep measures as there were clear effects of ethanol at 2.0 and 4.0 g/kg doses. In general, ethanol promoted delta oscillations and suppressed faster frequencies, but there were clear, differential effects on wake and REM EEG power based on the timing of the ethanol injection.

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The DISCO-T state was characterized by a prominent oscillation in the theta bandwidth that differed from both REM and NREM. While rodent REM sleep has a pronounced theta rhythm, there were marked differences between the overall power spectra of REM and DISCO-T epochs, including a shift in the peak of the theta rhythm. Additionally, DISCO-T was characterized by the presence of noticeable muscle tone that further distinguished it from REM. The identification of this state is important, because these epochs were not included as wake, NREM, or REM, and thus, this classification had an important effect on the quantification of canonical states during the first hour following 4.0 g/kg ethanol administration. Because of the presence of the DISCO-T state, the probability of all three states was reduced during the first hour after high-dose ethanol administration. It should also be noted that 4.0 g/kg ethanol produced a net reduction in theta oscillations even at early time points following injection that was separate from the increase in the sharp 5.5 Hz intra-theta component of the EEG. It is generally accepted that sleep is different from anesthesia (Lydic and Baghdoyan, 2005; Tung and Mendelson, 2004). The DISCO-T state, induced by a high dose of ethanol, could be associated with anesthetic effects of ethanol. Ethanol affects neurotransmitters that are also involved with the mechanism of several anesthetic drugs. For example: ethanol enhances GABAergic transmission and inhibit the function of NMDA-type glutamate receptors (for review see Abrahao et al., 2017). Thus, we attempted to reproduce the DISCO-T state with administration of the GABAA receptor positive allosteric modulator diazepam and/or the NMDAR uncompetitive antagonist MK-801. In rodents, MK-801 has been shown to increase hippocampal low-frequency delta power, while disrupting theta oscillations (Dzirasa et al., 2009; Kiss et al., 2013). Increased delta power was also observed after the high dose of ethanol but in our study, this dose also induced an increase in a specific component of the theta frequency. Thus, the administration of MK-801 alone was not able to evoke a change in the power spectrum similar to that induced by high dose ethanol administration. Diazepam has been shown to decrease in theta oscillations (Caudarella et al., 1987; Gottesmann et al., 1998) and increase both beta and gamma oscillations (van Lier et al., 2004; Yamamoto, 1985). It is important to note that these changes may depend on the sleep/wake state (Scheffzük et al., 2013). We did not separate by sleep state as we

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reasoned that the anesthetic effects would interfere with sleep scoring. Diazepam induced an increase in beta and gamma oscillations while decreasing theta oscillation. Although the diazepam effect did not replicate the power spectral changes induced by 4.0 g/kg ethanol, we did observe a peak of activity around 5.5 Hz after diazepam, which is similar to part of what was observed during the ethanol-induced DISCO-T state. Thus, the effects of high dose ethanol are partially, but not completely, recapitulated by either NMDA receptor blockade or GABAA receptor enhancement. The combination of MK-801 and diazepam produced effects that more closely resembled high dose ethanol actions on cortical electrographic activity. This drug combination increased peaks of delta and theta oscillatory activity, an effect similar to that of 4.0 g/kg ethanol. However, it is important to point out that the cocktail effect did not induce the pronounced immobility observed following high dose ethanol administration. After the cocktail, mice were still mobile, although they appeared ataxic and hypolocomotive, and the electrographic correlate of this movement is clearly evident in the EMG recordings (see example in Figure 7). Thus, while alterations in GABAergic and NMDA receptor-mediated transmission may contribute to the high dose ethanol effect, it is likely that other mechanism must be engaged to produce complete immobilization after ethanol. Indeed, ethanol and anesthetics drugs have multiple other common membrane targets such as glycine and nicotinic acetylcholinergic receptors that should be considered in this context. The complex time course of changes in the EEG after 4.0 g/kg ethanol likely involves decreasing brain ethanol concentrations that alleviate the pharmacological mechanisms underlying the DISCO-T effect. Once the DISCO-T state subsided, NREM sleep increased at the expense of wake. A study in rats found a dose-dependent increase in NREM sleep shortly after gastric administration at the beginning of the dark cycle, but at light onset only 3.0 g/kg EtOH caused an increase in NREM sleep (Kubota et al, 2002). In another study with C57BL/6Slac mice, intraperitoneal injection of 3.0 g/kg EtOH at the beginning of the dark cycle decreased the latency to NREM sleep and increased the duration of NREM sleep for 5h (Fang et al., 2017). Ethanol dosedependently increased NREM sleep, which was consistent with decreases in wakefulness (Fang et al., 2017). Thus, ethanol has a dose-dependent effect on 31

vigilance states. In the present study, it is notable that all ethanol doses, besides 4.0 g/kg, did little to NREM or REM sleep probability, suggesting that the ethanol effect on sleep may be non-linear or extremely narrow. However, ethanol had different effects depending on the circadian timing of administration, highlighting that the effects reported here are the result of an interaction between the manipulation (ethanol administration) and the latent state of the organism (circadian phase). The delayed augmentation of NREM after 4.0 g/kg ethanol is supported by stateindependent power spectral results that indicate a delay in the peak of delta power, a hallmark of NREM sleep, which matches the time course of changes in vigilance states. Moreover, the increased delta power is indicative of a cyclostationary, low frequency oscillation that emerged as the initially-enhanced 5.5 Hz theta rhythm subsided. EEG power spectra were also affected by 2.0 g/kg ethanol in a dose-dependent manner. Ethanol dose-dependently induced decreased theta, alpha and gamma oscillations and increased delta power when the complete EEG signal was analyzed. In addition, ethanol effects on the power spectra were similar when the drug was administrated at the beginning of the dark or the light period. Previous studies indicated that during NREM sleep, acute EtOH given at the onset of the light photoperiod induces a suppression of low-frequency bands but no change in high-frequency bands (Fang et al., 2017; Kubota et al., 2002). However, depending on the dose, the classification of the EEG signal within sleep states may be difficult due to anesthesic effect like the DISCO-T state observed in the present study. Ethanol doses between 3.5 and 4.0 g/kg are commonly used for sedation and tolerance tests in mice. These doses induce loss of righting reflex (LORR) which can be measured as a behavioral index of the sedative effects of ethanol. Previous work showed that C57BL/6J mice can recover the righting reflex in 45 to 100 min after the administration of doses between 3.5 and 4.0 g/kg of ethanol (Finn et al., 1990; Alkana et al., 1988; Jury et al., 2017). In our experiments, the DISCO-T lasted for 60 min. Although we could not directly measure the LORR in the mice in which we measured sleep,

the timing of the DISCO-T EEG state indicates a possible association with

LORR.

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We used the intraperitoneal (i.p.) injection route of administration to facilitate the administration of ethanol in these mice that were tethered to a cable for the sleep recordings. Chen et al. (2013) observed no significant difference between blood ethanol concentration in mice after administration of 1.12 g/kg ethanol via i.p. or gavage, suggesting that equivalent amounts of ethanol are absorbed and cleared at similar rates. On the other hand, Livy et al. (2003) observed that i.p. injection of 3.8 g/kg ethanol induced slightly higher blood ethanol concentration than gavage administration of the same dose. Thus, at least for the dose of 4.0 g/kg, our results are associated with higher blood ethanol concentration than those that would likely be observed after gavage administration. In addition, we did not perform blood ethanol measurements in the mice used for sleep analysis, as the handling and stress of these measurements would disrupt sleep and EEG recordings. Previous studies in C57Bl6J mice indicate that systemic injection ranging from 1 g/kg to 4 g/kg ethanol doses lead to an average peak of blood concentrations between 120 mg/dL and 360 mg/dL, respectively (Chen et al 2013; Livy et al., 2003). Different aspects could contribute to the ethanol effects on polysomnography. For example, mice are likely to experience hypothermia after ethanol administration. Previous studies have shown that 4.0 g/kg ethanol can induce a small decrease in rectal and brain temperature (Benjanian et al., 1991; Finn et al., 1994), but this decrease persists for more than 2 hours, which is longer than the duration of the DISCO-T. While it is possible that DISCO-T is a secondary effect to hypothermia, mice were likely also hypothermic during the subsequent deep NREM state, which has different polysomnographic features. In addition, we did not observe the DISCO-T state following the 2 g/kg ethanol dose, which may also induce some degree of hypothermia. With regard to the possibility of shivering, while there was some slight activity in the EMG during the DISCO-T state (see figure 2A), this activity appeared to too low in amplitude to be a vigorous shivering response. Also note there is a total absence of activity in the subsequent slow-wave rich NREM state. In addition, the magnitude of the theta oscillation in DISCO-T seems to be inversely related to the magnitude of EMG, and this is opposite of what you would expect if DISCO-T EEG phenomena were due to

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shivering. Overall, our findings indicate that the DISCO-T state is not a response to hypothermia. Ethanol effects on brain activity are of great interest to understand neuroadaptation and behavioral changes induced by this drug of abuse. Although we did not observe strong effects of ethanol at low doses, this does not mean that brain functions would not be disrupted either during or after sleep by these subtle low dose effects. Furthermore, chronic administration at these low doses could induce changes of sleep and anesthetic properties of this drug. Thus, future studies should focus on the changes in EEG recordings during and after chronic ethanol exposure. In addition, the DISCO-T state induced by high dose ethanol has considerable translational importance. Acute ethanol toxicity is a significant societal problem (Hingson et al., 2017; Vonghia et al., 2008). Adolescents, for example, have been using ethanol at extreme binge levels (Patrick et al., 2013), defined by NIAAA as 4 doses of alcohol for women and 5 doses of alcohol for man during 2 hours. This pattern of drinking is considered one type of Alcohol Use Disorder (AUD) in the DSMV. In addition, severe toxicity can be observed when people combine ethanol with anesthetic drugs (Mihic and Harris, 2017). Indeed, rapid, high-dose ethanol consumption results in death due to respiratory depression that can number over 1000 per year in the USA, and a coma-like state can also be induced (Yoon et al., 2003). Other effects of high-dose alcohol consumption, including memory “blackouts” could also be related to a DISCO-T-type state (Wetherill and Fromme, 2016). Understanding the neural basis of the extreme soporific effects of high dose ethanol may aid in treating acute toxicity.

5. Acknowledgements

The authors declare no conflicts of financial interest.

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Legends

Figure 1: Experimental Design for alcohol dose-response studies with sleep measures. Inset shows birds-eye-view schematic of electrode placement on skull. Note that electrodes were placed ipsilateral on either the left or right side. As shown in the diagram, subjects were exposed to one of five patterns of alcohol administration in a latin square design. Baseline measures were collected before each round of the latin square following a saline injection. Within the latin square, alcohol doses were administered once every 48 hr. The white rectangles in the diagram indicate days where no injection was administered, while colored rectangles indicate days where alcohol was administered. The dose of alcohol given on a particular day is color-coded according to the key listed on the figure. Habituation refers to habituation to the recording environment, including being tethered to the non-motorized commutator.

Figure 2: An anesthetic dose of alcohol induces an altered state with distinct electrographic features from NREM. A, Example polysomnography and hypnograms from the same subject following saline and 4.0 g/kg alcohol administration. Color-coded hypnograms denote wake in red, NREM in blue, REM in green, and an altered state (termed DISCO-T) that was induced by alcohol in magenta. A, top: 6 hr segment of sleep-wake activity aligned to EEG from FC and OC derivations and the EMG voltage trace. Expanded views show 30 sec segments of normal wake and NREM states. A, bottom: 6 hr segment of sleep-wake activity from the same subject following i.p. administration of 4 g/kg given just before the beginning of recording. Again, voltage traces from two EEG channels and EMG are aligned to the colorcoded hypnogram. This dose of alcohol induces behavioral signs of anesthesia within 5 min of administration. During the first 45 min of the recording, there was a notable synchronized oscillation around 5.5 Hz (see panel B) that is visibly present in the time domain waveforms from both FC and OC derivations. At this time there was also a gradual increase in EMG tone that, combined with the robust 5.5 Hz oscillation, rendered a polysomnographic pattern inconsistent with NREM sleep. At later time points in the anesthetic bout, an EEG pattern consistent with NREM sleep emerged, albeit with robust slow-wave activity. This secondary response is consistent with effects of clinically used anesthetics like benzodiazepines and barbiturates. B, Plots of time-frequency domain power spectral analysis of FC and OC EEG signals over 6 hr following administration of saline, 2.0 g/kg, and 4.0 g/kg alcohol. These data are from the same subject as the data in panel A. The heat maps shows absolute power (µV2)

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with frequency resolution of 0.25 Hz and temporal resolution of 5 min. Note the distinct high intensity band around 5.5 Hz during the first part of the recording when there is a suppression of other frequencies. Also, note the robust increase in power of low frequency oscllations that emerges when the 5.5 Hz rhythm subsides. C, Summary data from all subjects comparing power spectra from the first hour of recordings among epochs of wake, NREM, REM, and the Drug-Induced State with a Characteristic Oscillation in the Theta Band (DISCO-T) state. Wake, NREM, and REM power spectra represent the average of spectra obtained from all epochs of the respective state within the first hour of recording following saline injection (region delineated by red, blue, and green arrows between FC and OC graphs under saline in panel B). In contrast, the DISCO-T spectrum represents the average of all epochs of this state that were detected within the first hour of recording following the 4 g/kg alcohol injection (region denoted by magenta arrow in 4 g/kg plots in panel B). Note that the DISCO-T spectrum does not correspond to spectra for wake, NREM, or REM. D, Summary data from all subjects showing state-independent averages of power spectra from all epochs within the first hour of recording following injection of either saline, 2.0, or 4.0 g/kg alcohol. Note the attenuation of frequencies above 6 Hz and the substantial increase in power at 5.5 Hz following the 4.0 g/kg dose. A & B, time domain indicated in zeitgeber time (ZT) with respect to the onset of the light photoperiod. C & D, thin lines show averages of power spectra during 1st hr after injection from individual subjects. The thick lines denote the group mean. Figure 3: Only an anesthetic dose of alcohol altered sleep-wake states by increasing NREM soon after administration while suppressing wake and REM. A, State probabilities as a function of zeitgeber time (ZT). From left to right, plots depict the effect of increasing ethanol dose on vigilance states. Downward facing arrowheads illustrate the time of drug administration. The top row of graphs show results from experiments where ethanol was administered at the onset of the light cycle (ZT 00:00), and results from experiments where ethanol was administered prior to the dark cycle on the bottom row. The DISCO-T state is shown in magenta but was only observed following the 4.0 g/kg dose of ethanol. B, Ethanol dose-response effect on each vigilance state. Downward facing arrowheads depict the time of drug administration. The top row shows data from ethanol administration at the onset of the light cycle (ZT 00:00), and results from experiments with ethanol administration at the beginning of the dark phase (ZT 12:00) are shown on the bottom row. Vertical colored hashed lines and nongray shaded regions highlight timepoints when Bonferroni-corrected pair-wise comparisons with vehicle found significant (p < 0.05) effects of ethanol on the probability of occurrence of each

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respective vigilance state. Significant differences for a particular dose are indicated by the corresponding color of the hashed line and shading. The DISCO-T state is not represented in this panel B because it was only observed following the 4.0 g/kg ethanol dose and because it lasted only about 1 hr. Dose-specific effects on sleep are color coded by the shading. In all plots, gray shaded background denotes the dark cycle (ZT12:00 to 23:59), and solid lines superimposed on shaded regions depict the group mean with the shaded regions representing the standard error of the mean.

Figure 4: High dose alcohol stabilizes NREM sleep while fragmenting REM. A, Vigilance state architecture results for experiments with ethanol administration at the onset of the light cycle (ZT00:00) (n = 16). B, vigilance state architecture results for experiments where ethanol was administered at the onset of the dark cycle (ZT12:00) (n = 13). In both panels, the top row represents the duration of vigilance state bouts on a logarithmic scale, and the bottom row shows the number of bouts of each vigilance state with respect to time. In all plots, the gray shaded background depicts the dark phase. The vertical colored hashed lines and shaded regions highlight timepoints when Bonferroni-corrected pair-wise comparisons with vehicle found significant (p < 0.05) effects of ethanol on the probability of occurrence of each respective vigilance state. Significant differences for a particular dose are indicated by the corresponding color of the hashed line and shading. The DISCO-T state is not represented in this panel B because it was only observed following the 4.0 g/kg ethanol dose and because it lasted only about 1 hr. Solid lines superimposed on shaded regions depict the group mean with the shaded regions representing the standard error of the mean.

Figure 5: Alcohol produces complex alterations in power spectral bandwidths associated with sleep. Left side shows results for experiments with ethanol administration at the onset of the light cycle (ZT00:00) (n = 16). Right side shows results for experiments where ethanol was administered at the onset of the dark cycle (ZT12:00) (n = 13). Figures depict the effect of varying doses of ethanol, the time of day of administration, and the electrode location on integrated power in canonical EEG power spectral bandwidths over a 4 hr period. Columns labelled with FC represent data obtained from the frontal electrode location, and columns labelled with OC represent data obtained from the occipital location. In all plots, the gray shaded background depicts the dark phase. The vertical colored hashed lines and non-gray shaded regions highlight timepoints when Bonferroni-corrected pair-wise comparisons with vehicle found significant (p < 0.05) effects of ethanol on the power observed in each bandwidth.

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Significant differences for a particular dose are indicated by the corresponding color of the hashed line and shading. Solid lines superimposed on shaded regions depict the group mean with the shaded regions representing the standard error of the mean.

Figure 6: Alcohol produces state-specific changes in the frequency composition of EEG that is regulated by circadian phase. A1, Integrated delta power for experiments with ethanol administration at the onset of the light phase (ZT00:00) (n = 16). A2, Integrated delta power for experiments with ethanol administration at the onset of the dark phase (ZT12:00) (n = 13). B1, Integrated theta power for experiments with ethanol administration at ZT00:00. B2, Integrated theta power for experiments with ethanol administration at ZT12:00. C1, Integrated alpha power for experiments with ethanol administration at ZT00:00. C2, Integrated alpha power for experiments with ethanol administration at ZT12:00. D1, Integrated gamma power for experiments with ethanol administration at ZT00:00. D2, Integrated gamma power for experiments with ethanol administration at ZT12:00. In all plots, the gray shaded background depicts the dark phase. The vertical colored hashed lines and non-gray shaded regions highlight timepoints when Bonferroni-corrected pair-wise comparisons with vehicle found significant (p < 0.05) effects of ethanol on the power observed in each bandwidth. Significant differences for a particular dose are indicated by the corresponding color of the hashed line and shading. Solid lines superimposed on shaded regions depict the group mean with the shaded regions representing the standard error of the mean. Figure 7: NMDA antagonism and GABAA activation recapitulates aspects of the DISCO-T high dose ethanol-induced state. A, Example polysomnography after administration of the MK-801+DZ cocktail. The cocktail did not induce a complete anesthetic effect. Details show raw example traces of the electrophysiological characteristics at different time points after the cocktail. B, Time domain voltage traces illustrated in the time-frequency periodograms following vehicle and MK801+DZ cocktail. Relative to the vehicle injection, MK-801+DZ substantially altered the shape of the frequency distribution for about 45 min in both FC and OC. The altered state induced by 4.0 g/kg ethanol also lasted for about 45 min and it was marked by an increase in synchronized EEG oscillations around 5.5 Hz. C, Power spectra obtained after 4.0 g/kg of ethanol during Wake, NREM and DISCO-T (Altered) states. D, Average power spectra obtained during the first hour following the vehicle, only MK-801, only Diazepam, or MK-801+Dizepam cocktail. Note that the combined administration of the NMDA antagonist and GABAA agonist drugs elicited an altered state similar to what was observed after 4.0 g/kg ethanol.

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Dose-dependent alcohol effects on electroencephalogram: sedation/anesthesia is qualitatively distinct from sleep

Authors: Karina P Abrahao, PhD1*; Matthew J Pava, PhD2* and David M Lovinger, PhD**

Author Contributions Section

All authors were involved in the design of the project. KPA and MJP were responsible for performing the experiments. MJP did the statistical analysis of the data. All authors discussed the results and wrote the manuscript.

1

Present address: Assistant Professor, Departamento de Psicobiologia, Universidade Federal de São Paulo, Campus São Paulo, SP, Brazil. Email: [email protected]

2

Present address: Arlington, VA, USA. Email: [email protected]

1

The authors declare no competing interests or conflicts of financial interest.