Prefrontal Electrophysiological Biomarkers and Mechanism-Based Drug Effects in a Rat Model of Alcohol Addiction

Prefrontal Electrophysiological Biomarkers and Mechanism-Based Drug Effects in a Rat Model of Alcohol Addiction | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Prefrontal Electrophysiological Biomarkers and Mechanism-Based Drug Effects in a Rat Model of Alcohol Addiction Bettina Habelt, Dzmitry Afanasenkau, Cindy Schwarz, Kevin Domanegg, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3905152/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Dec, 2024 Read the published version in Translational Psychiatry → Version 1 posted 10 You are reading this latest preprint version Abstract Current treatments for alcohol use disorder (AUD) show large heterogeneity in response and thus limited effectiveness and high relapse rates. A precision medicine approach with biomarkers responsive to new treatments is warranted to overcome this limitation. Promising biomarkers relate to prefrontal control mechanisms that are severely disturbed in AUD. This results in reduced inhibitory control of compulsive behavior and, eventually, relapse. We reasoned here that prefrontal dysfunction, which underlies vulnerability to relapse, is evidenced by altered neuroelectric signatures and should be restored by pharmacological interventions that specifically target prefrontal dysfunction. To test this, we applied our recently developed biocompatible neuroprosthesis to measure prefrontal neural function in a well-established rat model of alcohol addiction and relapse. We monitored neural oscillations and event-related potentials in awake alcohol-dependent rats during abstinence and following treatment with psilocybin or LY379268, agonists of the serotonin 2A receptor (5-HT 2A R) and the metabotropic glutamate receptor 2 (mGluR2), that are known to reduce prefrontal dysfunction and relapse. Electrophysiological impairments in alcohol-dependent rats are reduced amplitudes of P1N1 and N1P2 components and attenuated event-related oscillatory activity. Psilocybin and LY379268 were able to restore these impairments. Furthermore, alcohol-dependent animals displayed a dominance in higher beta frequencies indicative of a state of hyperarousal that is prone to relapse, which particularly psilocybin was able to counteract. In summary, we provide prefrontal markers indicative of relapse and treatment response, especially for psychedelic drugs. Health sciences/Biomarkers Biological sciences/Neuroscience Figures Figure 1 Figure 2 Figure 3 Introduction Substance use disorders are a severe health issue worldwide. With more than three million deaths each year, the highest impact is attributed to the abuse of alcohol [1, 2]. Treatment options for alcohol use disorder (AUD) include pharmacological interventions (e.g. acamprosate and naltrexone) and psychotherapy (e.g. cognitive behavioural therapy). However, there is a considerable heterogeneity in response to these treatments, thus limiting their effectiveness, and the vast majority of patients suffer from relapse [3, 4]. A wealth of theoretical and empirical evidence thus strongly supports efforts towards a precision medicine approach with adequate biomarkers to identify and target pathophysiological mechanisms that will likely respond best to a given treatment [5, 6]. Potential biomarkers of clinical state and treatment responsiveness include electrophysiological brain activity measures of neural oscillations and event-related potentials (ERPs) that represent the neural basis of sensory information processing and higher-order cognitive abilities such as attention, working memory, decision making and behavioural control – prefrontal functions that are strongly disturbed in AUD [7, 8]. Resting-state neural oscillations describe a continuous, rhythmic and repetitive electrical activity generated spontaneously by temporally and spatially synchronised neurons and reflect a rather fundamental brain state [9, 10]. Brain oscillations are subdivided into different frequency bands, most commonly delta (1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–30 Hz) and gamma (> 30 Hz) [11]. Chronic alcohol consumption increases oscillatory power within all frequency bands, but most prominently in the beta band [12–16]. Higher-frequency beta activity has been associated with a state of hyperarousal and increased relapse probability [12]. In contrast, event-related oscillations (ERO) refer to time-frequency measurements in response to motor, sensory or cognitive events [17]. When tested for executive functioning during Go/NoGo tasks, AUD patients display reduced ERO power in the delta, theta and alpha range in response to NoGo stimuli [18, 19] indicating impaired behavioural inhibition and cognitive control. Disturbed impulse control has also been related to beta oscillations, which are dominant in sensorimotor functioning and display a reduced power in binge drinkers during NoGo task conditions [20]. Superposition and phase synchronisation of EROs further determine the formation of ERP components [17, 21]. These stimulus-evoked voltage deflections are time-locked local positive or negative maxima within a continuously recorded electroencephalogram. They are commonly named according to their polarity (P = positive, N = negative) and time (in ms post-stimulus) or order of appearance [22]. Alcohol consumption reduces amplitudes and/or increases latencies of multiple ERP components, pointing to alterations of the entire information processing system [23, 24]. Increased salience of alcohol-related cues in combination with a lack of inhibitory resources are the central neurocognitive mechanisms underlying relapse, with the P3 being the most reliable ERP component to predict relapse risk and treatment success [25–27]. It is recognized that the described cognitive impairments and limited behavioural control observed in AUD relate to disturbances primarily within prefrontocortical networks [28, 29]. Thus, the present study builds on the assumption that (i) aberrant neuroelectric signatures in AUD represent impaired prefrontal function that underlies vulnerability to relapse, and (ii) pharmacological interventions which address such a vulnerable state can restore altered electrophysiological activity. We previously developed an electrocorticographic (ECoG) interface [30] tailored to capture prefrontal ERP and neural oscillations and we here applied this new technology to a well-established animal model for alcohol addiction and relapse behavior. In this model rats are subjected to long-term voluntary alcohol consumption in a four-bottle procedure, repeatedly interrupted with abstinence periods. The re-presentation of alcohol following deprivation induces relapse-like drinking - a temporary increase in alcohol intake over baseline drinking referred to as the alcohol-deprivation effect (ADE) [31]. The development of compulsive drinking behavior is further characterized by insensitivity to taste adulteration with quinine, a loss of circadian drinking patterns, and a shift towards drinking highly concentrated alcohol solutions to rapidly increase blood alcohol concentrations and achieve intoxication during a relapse situation. In addition, alcohol-dependent rats that derive from this model show tolerance and physical as well as anxiety-related withdrawal symptoms [32–34]. The ADE model has been utilised in various preclinical and translational alcohol studies and has helped identify new treatment targets with good predictive validity [32, 35]. After assessing prefrontal electrophysiological signatures in the ADE rat model, we tested two drug treatments that we expected to interfere with prefrontal dysfunction and relapse behaviour. One of the therapeutic targets is the metabotropic glutamate receptor 2 (mGluR2) which is a key regulator of glutamate release. Prefrontal mGluR2 expression and function is strongly diminished in animal models of alcohol addiction and in severe AUD case [36, 37]. Consequently, it has been proposed to use, mGluR2 agonists such as LY379268 to counteract this diminished prefrontal function providing preclinical evidence of its potential to attenuate alcohol-seeking and relapse-like behaviour [37–41]. Recently, we demonstrated that virally restoring normal prefrontal mGluR2 levels is able to prevent cognitive impairment and craving in alcohol-dependent rats and that the normalisation of mGluR2 is also possible via a single administration of the psychedelic agent psilocybin which ultimately reduced relapse-like behavior [37]. Psilocybin seems promising in treating AUD since a recent clinical trial using psilocybin in combination with psychotherapy demonstrated a significant reduction of heavy drinking days in AUD patients [42]. The behavioural and therapeutic effects of psilocybin are primarily attributed to the activation of the serotonin 2A receptor (5-HT 2A R) [43] and its modulation by other pathways including the physical interaction with the mGluR2 [36]. Both, mGluR2 and 5-HT 2A R are enriched in prefrontal areas. This supports our hypothesis that their activation can restore altered ERPs and neural oscillations in alcohol-dependent rats, thereby improving cognitive functioning and reducing the risk of relapse. Materials and Methods Animals All investigations within this project have been approved by the institutional ethics commissions of TU Dresden and the Central Institute of Mental Health, Mannheim and the regional authorities of the federated states of Saxony (Landesdirektion Sachsen) and Baden-Württemberg (Regierungspräsidium Karlsruhe). Experiments were performed in accordance with the guidelines of the Directive 2010/63/EU on the protection of animals used for scientific purposes of the European Commission with great attention to avoid suffering and to reduce number of animals used [44]. We used male Wistar rats from the breeding colony at the CIMH. Rats were housed in single cages (Makrolon®, Type III, Tecniplast Deutschland GmbH) on sawdust bedding (Ssniff - Bedding 3/4 S, Altrogge) with Bed-r'Nest material (Datesand Ltd.). Pelleted food (V1534-300, ssniff Spezialdiäten GmbH) and water were available ad libitum. Housing rooms were temperature (20–22°C) and humidity (40–55%) controlled with a 12 h automatic light-dark cycle (lights on at 6.00 am). Long-term alcohol consumption with repeated deprivation periods Following two weeks of habituation to the animal room, rats were given ad libitum access to ethanol (VWR International GmbH) solutions of 5%, 10%, and 20% (v/v) besides tap water. Concurrent access to several alcohol concentrations has been shown to increase the magnitude and duration of the ADE [31, 32]. The positions of bottles were changed weekly. After eight weeks of continuous alcohol availability, bottles with alcohol solution were removed from the cages and reintroduced after a deprivation period of two weeks. Phases of free access to alcohol and deprivation subsequently alternated randomly with variable durations of drinking between 4–6 weeks and deprivation lasting 2–3 weeks, aiming to prevent habituation and behavioural adjustment. The long-term alcohol exposure procedure, including all drinking and deprivation phases, continued over 13 months. During the final two-week period of alcohol deprivation, animals (n = 10) were habituated to the recording set-up and underwent surgery to implant the neuroprosthetic device (Fig. 1 a). Ten alcohol-naïve control animals underwent the same procedure [30]. Manufacturing and implantation of neuroprosthetic interfaces The procedures to fabricate, characterise and implant the used neuroprosthetics have been described in detail before [30, 45, 46]. Briefly, micro-EcoG interfaces were produced by an additive manufacturing approach using the 3D bioprinter 3DDiscovery ™ Evolution (regenHU Ltd.). The devices consisted of soft silicone for the base (DOWSIL™ SE 1700, Dow Inc., Midland, USA) and isolating (SE 734, Dow Inc., Midland, USA) layers embedding a 3 × 3 electrode array of conductive platinum ink (chemPUR). The electrode interconnects were attached to stainless steel microwires (∅: 0.23 mm, 7SS-2T, Science Products GmbH) soldiered to a plug-in connector (BKL 10120653, BKL-Electronic Kreimendahl GmbH). An additional microwire was fixed to a microscrew drilled into the skull during surgery and served as a reference electrode. Implantation was performed under subcutaneous (s.c.) anaesthesia (fentanyl (0.005 mg/kg, Hameln Pharma), midazolam (2 mg/kg, Ratiopharm), medetomidine hydrochloride (0.135 mg/kg, Orion Pharma) in a stereotactic surgery involving trepanation of the skull (∅ 6.0 mm, 330205486001060, Meisinger) to position the devices epidurally on the prefrontal cortex with the frontal electrode row located at 3.2 mm anterior to bregma. External parts of the implant were fixed to the skull using dental cement (Paladur, Kulzer GmbH), and the wound was sutured. After completion of the surgery, anaesthesia was antagonised (s.c., naloxone hydrochloride (0.12 mg/kg, Inresa Arzneimittel GmbH), flumazenil (0.2 mg/kg), atipamezolhydrochloride (0.75 mg/kg, Orion Pharma). Animals received meloxicam (1 mg/kg, s.c., Boehringer Ingelheim Vetmedica GmbH) as an analgesic right after surgery and the following day. Electrocorticography recording and acute pharmacological modulation of neural activity ECoG recordings without any further interventions were implemented three days after the animals had undergone surgery. Recordings were performed at a sampling rate of 3 kHz using the Intan RHD2000 USB interface system cable connected to the implant plug-in module. The initial recording measured a state of abstinence in alcohol dependent rats compared to matched alcohol-naïve rats. Recordings were performed within an electrically shielded and sound-insulated audiometry booth where one animal at a time was placed in a rodent sling (Lomir Biomedical Inc.) to reduce movement artefacts. To record auditory event-related activity, sound stimuli were presented through a stereo loudspeaker located at a distance of 40 cm and an angle of 45° centrally above the animal's head. Auditory stimuli have been generated using the Psychophysics Toolbox (Version 3) for Matlab (Version R2019b, The Mathworks Inc.) and were composed of frequent (standards: 50 ms, 1 kHz, 70 dB sound pressure level (SPL), 87% of trials) and rare (deviants: 50 ms, 2 kHz, 80 dB SPL, 13% of trials) sinusoidal sounds with 5-ms onset/offset ramps, presented in 6 blocks of 5 min with 1 s interstimulus interval. Deviant sounds have been interspersed with at least one standard tone to avoid successive occurrences. On day 6 and 9 after initial recordings, alcohol-dependent rats randomly received intraperitoneal (i.p.) injections of psilocybin (2.5 mg/kg, 3-[2-(dimethylamino) ethyl]-1H-indol-4-yl] dihydrogen phosphate (purity 99.7%) obtained from the University of Chemistry and Technology Prague, Czech Republic, dissolved in Ampuwa (Braun Melsungen AG) or LY379268 (1 mg/kg, 1 R ,4 R ,5 S ,6 R )-4-Amino-2-oxabicyclo[3.1.0]hexane-4,6-dicarboxylic acid, Tocris Bioscience) each 30 min before recording. Respective dosing was chosen based on previously published data that demonstrated efficacy in reducing alcohol relapse [37, 41]. To capture drug-induced changes in resting-state neural activity, we performed continuous 5-minute recordings right before administering psilocybin or LY379268, and directly after the auditory oddball paradigm described above. Pre- and post-application recordings were approximately one hour apart. Event-related potentials and oscillatory activity Data processing was performed using the EEGLAB toolbox [47] (Version 2019.1) for Matlab. Following offline filtering using a 0.1–45 Hz bandpass finite impulse response filter (Kaiser windowed, Kaiser β = 5.65, filter length 54330 points), data were segmented in epochs between − 100 and 700 ms relative to stimulus onset separately for standard and deviant sounds and baseline-corrected using the pre-stimulus interval between − 100 ms to 0 ms. Artefacts and noisy channels were identified and excluded based on a delta criterion of 500 µV and visual confirmation before averaging epochs for single subjects and over all animals (grand average). As neural responses to the frequent standard sounds rarely displayed pronounced amplitudes, indicating habituation effects due to the high repetition rate [48], subsequent analysis was performed on the difference curves (deviant-minus-standard responses). ERP peak latencies were detected within the following time intervals confirmed by visual inspection: P1: 20–70 ms, N1: 35–120 ms, P2: 60–260 ms, N2: 100–320 ms, P3: 130–600 ms. The amplitudes of the ERP components were calculated as peak-to-peak amplitudes (P1N1, N1P2, P2N2, N2P3). Oscillatory power in the delta (1–4 Hz), theta (4–8 Hz), alpha (8–12 Hz), beta (12–30 Hz) and gamma (30–45 Hz) bands was determined by applying the function pop_newtimef.m in EEGLAB based on a Fast Fourier transform using 400 datapoints and a pad ratio of 64. The resulting event-related spectral perturbation (ERSP) was calculated as decibels (dB) ( ≙ 10*log 10 (µV 2 /Hz)). Resting-state neural oscillations Data were initially bandpass filtered, as described above, and segmented into 2 s-epochs with 50% overlap. Following the exclusion of bad epochs (δ = 500 µV, confirmed by visual inspection), we applied the EEGLAB function pop_spectopo.m to determine channel spectra based on the Welch method. The resulting power spectral density (PSD) in the 1–45 Hz frequency range was calculated as dB. Statistics Statistical analyses were conducted using SPSS® (Version 28, IBM Corp.) and R (Version 4.2.3, R Foundation for Statistical Computing). Differences in ERPs (peak latencies, amplitudes) and EROs (bandpower (ERSP), latency and frequency of max. power within each frequency band and over the whole frequency range) induced by psilocybin and LY379268 were examined by applying within-subjects repeated measures analysis of variance (rmANOVA) with factors treatment and channel. Multiple comparisons were adjusted using the Sidak correction. Likewise, rmANOVA was applied to analyse resting-state oscillatory activity (PSD) before vs. after administration of psilocybin and LY379268. Neural parameters of alcohol- and drug-naïve controls were compared with those of long-term alcohol consumers and each pharmacological intervention by applying a between-subjects ANOVA with factors treatment and channel and Sidak adjustment for multiple comparisons. To explore the potential impact of individual alcohol consumption patterns and susceptibility to the ADE on designated neural parameters, we performed Spearman correlation analyses using the averaged amounts of alcohol (g/kg body weight) consumed by each rat per day during the last week of a drinking phase (= baseline consumption, BL) and on the first day following periods of abstinence (= Alcohol Deprivation Effect (ADE)) as well as relapse intensities (difference of ADE and previous BL). Partial Spearman correlation was performed to relate alcohol consumption patterns with the neural activity following pharmacotreatments, controlling for neural activity without drug administration. Results Impact of long-term alcohol consumption on neural activity Alcohol consumption patterns throughout the experimental timeline are illustrated in Fig. 1 b. Mean baseline total alcohol intake (g/kg/day ± standard deviation (SD)) was 3.43 ± 0.54, with rats consuming 1.02 ± 0.54 of 5%, 1.25 ± 0.45 of 10% and 1.16 ± 0.40 of the 20% alcohol solution, respectively. Following deprivation, animals displayed increased consumption of all alcohol concentrations compared to baseline drinking (5%: 1.58 ± 0.60, p = 0.006; 10%: 1.49 ± 0.47, p = 0.11; 20%: 1.59 ± 0.58, p = 0.034, Total: 4.66 ± 0.64, p = < 0.001, two-sided paired t-tests) revealing a pronounced ADE. Neurophysiological data revealed a significant effect of long-term alcohol consumption for most neural parameters (Fig. 2 ) with reduced ERP amplitudes of P1N1 and N1P2 components in alcohol-dependent rats, thus also resulting in earlier peaking of N1 and P2 components compared to naïve controls (Figs. 2 a-c, Table S1 ). In contrast, P2N2 amplitudes were enhanced following long-term alcohol consumption, while N2P3 amplitudes remained similar to controls. Furthermore, alcohol-dependent animals displayed reduced and later peaking ERO activities within delta, theta, alpha and beta bands and over the whole frequency range (Figs. 2 d-f, Table S1 ). Only in the gamma range long-term alcohol consumption induced an increased oscillatory power. We further observed an elevated activity within higher beta frequency ranges in alcohol-dependent animals while low beta frequencies dominated in naïve controls (Figs. 2 g; Table S1 ). Statistical analyses did not yield an effect of channel location or channel × treatment interaction for any of the parameters. Concerning alcohol consumption patterns, P1N1 and N1P2 amplitudes and oscillatory activities of the whole frequency range displayed a strong positive correlation with relapse intensity to 10% alcohol and a moderate positive correlation to baseline consumption of 20% alcohol. In addition, gamma band activity revealed a strong negative correlation with baseline consumption of 10% alcohol (Fig. 3 a, Table S2). Correlation analyses of resting-state oscillatory activities with alcohol consumption before substance application most consistently revealed moderate to strong positive correlations with consumption of 20% alcohol at baseline and after abstinence. This relation was also observed for delta, theta and alpha waves, with total alcohol relapse intensity primarily attributed again to 20% alcohol. In addition, gamma activity displayed a moderate negative correlation with post-deprivation consumption of 5% alcohol (Fig. 3 b, Table S3). Pharmacological modulation of neural activity in alcohol-dependent rats After successfully investigating the electrophysiological changes in alcohol-dependent rats, we wanted to examine whether pharmacological interventions counteract these neuropathological changes. We previously demonstrated that pharmacotreatment with psilocybin and LY379268 reduces alcohol intake following abstinence thereby significantly counteracting the ADE (Fig. 1 c) [41, 49]. We build upon this work and investigated the neurophysiological effects induced by acute psilocybin and LY379268. Psilocybin Following an acute application of 2.5 mg/kg psilocybin in alcohol-detoxified rats, we observed a partial decrease in resting-state oscillatory activities, predominantly in delta and theta bands, with no effect of channel location or channel × treatment interaction (Fig. 2 h-i, upper panels, Table S4). Bandpowers after vs. before drug administration were positively correlated with moderate to strong effect sizes (Table S5). Correlation with alcohol consumption revealed most consistently a moderate, negative correlation of post-administration resting-state bandpowers with total alcohol consumption after abstinence and corresponding relapse intensity and a moderate, positive correlation of theta, alpha, beta and gamma band activities with baseline consumption of 20% alcohol (Fig. 3 B, Table S6). After administration of psilocybin, ERPs of alcohol-dependent rats revealed increased amplitudes of P1N1, N1P2 and N2P3 amplitudes (Figs. 2 a-b, Table S7). The manifestation of these ERPs was similar to those observed in naïve rats and even showed slightly higher and earlier peaking amplitudes (Figs. 2 a-b, Table S8). In contrast to resting-state oscillations, EROs displayed elevated bandpowers over the whole frequency range (Figs. 2 d-e, Table S7). We additionally observed a shift from maximum beta powers to lower frequency ranges after administering psilocybin (Figs. 2 d,g, Table S7). Compared to naïve controls, ERO activity differed predominantly in the gamma frequency range, revealing increased and earlier peaking bandpowers (Figs. 2 e-f, Table S8). Correlation analyses of event-related activity following psilocybin administration vs. initial recordings without drug application revealed a moderate negative correlation for P2N2 amplitudes, while all other ERPs and EROs were positively correlated with varying effect sizes (Table S9). Regarding alcohol consumption patterns, we observed a positive correlation between post-administration ERPs and EROs and drinking amounts of 20% alcohol at baseline and following deprivation and a negative correlation with total baseline alcohol intake and consumption of 5% alcohol following abstinence (Fig. 3 c, Table S10). LY379268 The administration of 1 mg/kg LY379268 induced a decrease in resting-state oscillatory activity within all frequency bands and at all electrode sites with medium to large effect sizes (Fig. 2 h-i, bottom panels, Table S11). Bandpowers after vs. before drug application were positively correlated (Table S12), whereas the correlation of post-administration bandpowers with alcohol consumption patterns displayed only a weak connection overall (Fig. 3 d, Table S13). Following administration of LY379268, ERPs revealed increased P1N1 and decreased P2N2 amplitudes (Figs. 2 a-b; Table S14) and an elevated ERO activity (Figs. 2 d-e; Table S14). As with psilocybin, beta frequencies dominated at lower frequency ranges compared to the non-treated condition (Fig. 2 g, Table S14). Compared to naïve controls, ERP amplitudes were in the same range (Figs. 2 a-b, Table S15), while EROs displayed an increased and earlier peaking gamma activity under the influence of LY379268 (Fig. 2 g, Table S15). Event-related activity following LY379268 administration displayed weak positive correlations with initial recordings without drug application (Table S16) and also weaker connections to alcohol consumption patterns than those recorded under the influence of psilocybin, but indicates a similar negative relation to total alcohol intake at baseline and specifically with the relapse intensity to 20% alcohol in case of the P2N2 component (Fig. 2 d, Table S17). Discussion In the present study, we used an established animal model of compulsive alcohol consumption and relapse behaviour and a new neuroprosthetic interface to record, modulate and classify potential electrophysiological biomarkers to reveal i) neuroelectric changes in the prefrontal cortex in alcohol-dependent rats and ii) their reversal via application of the psychedelic psilocybin and the mGluR2 agonist LY379268. Alcohol-dependent rats displayed reduced ERP amplitudes of P1N1 and N1P2 components and decreased and later peaking ERO activity within delta, theta, alpha and beta frequency bands, indicating deficiencies in sensory gating and early attentive filtering [17, 19, 50]. However, in the gamma range, chronic alcohol intake induced an increased oscillatory power, which has been related to enhanced extracellular glutamate concentrations [51, 52]. We further observed a dominance within higher beta frequency ranges in alcohol-dependent rats compared to naïve controls with maximum band powers in low beta frequencies. In patients with AUD, abnormal frontal high beta and gamma activities have been associated with an impaired working memory system and deficient top-down processing known to provoke reduced executive control and inhibition [53, 54] underlying relapse behaviour. Manifestation of ERPs and EROs showed a diametrically opposite correlation with baseline drinking compared to the relapse-like increase in alcohol consumption following abstinence, suggesting that relapse-like drinking and baseline alcohol consumption are controlled through different neural mechanism. Disturbed sensory gating, as reflected by P1N1 and N1P2 deficiencies, has been correlated with perceptual aberrations and the proneness to develop psychotic symptoms [55]. Acute application of psilocybin increased amplitudes of P1N1 and N1P2 components in our alcohol-dependent rats and elevated corresponding bandpowers over the whole frequency range. In addition, we show that psilocybin shifted maximum beta powers from mid/high beta ranges, associated with stress, anxiety and paranoia, to lower frequencies that reflect conscious focusing [56]. Psilocybin treatment in alcohol-dependent rats even pushed neural processing compared to naïve controls, as revealed by elevated P1N1 amplitudes and accelerated peak latencies of most ERP components and increased and earlier peaking gamma bandpowers. Gamma oscillations have been linked to mechanisms of synaptic plasticity and supposedly reflect the coordinated activity of neuronal assemblies supporting cognitive functioning, including memory formation, effective learning and focused attention [57]. Thus, psilocybin might facilitate these processes by strengthening gamma activity. Mental sharpness and cognitive control might be additionally supported by the psilocybin-induced increase in oscillatory activity within lower frequency ranges of delta, theta and alpha bands that are related to relaxation, mindfulness and creativity [56]. Synchronisation of these low frequency bands supposedly predicts P1N1 latency and amplitude and contributes to forming the P3 component [17, 21]. Both pharmacological treatments clearly augmented event-related neural activity restoring a pronounced P1-N1-P2 complex comparable to naïve controls that directly disembogued into the P3 component rather than forming a marked N2. A marked N2P2 component was a distinct feature of untreated alcohol-dependent rats. Higher N2 amplitudes have been related to increased task difficulty and effort necessary to inhibit behaviour as in NoGo responses [58]. An elevated N2 component in alcohol-dependent rats might, therefore, indicate an inappropriate activation of mental resources not necessary for the simple passive listening task applied here, while a small N2 might further emphasise the facilitation of sensory information processing in response to both applied pharmacological interventions. Finally, and in line with previous preclinical studies, psilocybin and LY379268 had a soothing effect on resting-state neural activity in our alcohol-dependent rats, though this effect was not as pronounced as previously seen in healthy rats [59, 60]. 5-HT 2A R and mGluR2 have been shown to physiologically interact antagonistically to ensure correct glutamate exocytosis [61]. Therefore, it seems surprising that in this study, we found similar effects of the administration of psilocybin and LY379268 on electrophysiological brain activity. One possible explanation might be the aforementioned dysfunction of mGluR2 often observed in patients with AUD. In addition, a recent study in mice displaying deficiencies in auditory ERO activity confirmed the beneficial effect of LY379268 [62]. Further experiments should consider the co-administration of these two compounds as well as the administration of mGluR2 and 5-HT 2A R antagonists in combination with psilocybin and LY379268, respectively. These results will help to deepen our understanding of the receptor-receptor crosstalk and its effects on brain activity. Correlation analysis further revealed that the changes induced by pharmacological treatment in resting-state and event-related activity depend on both individual neural activity states without drug application and alcohol consumption patterns. Interestingly, the effect of both pharmacological treatments on ERPs and EROs was more pronounced the lower the alcohol intake had been. However, these findings were restricted to low and moderately concentrated alcohol solutions, while psilocybin-induced enhancements of neural activity were positively correlated with the consumption of 20% alcohol. Differential neuronal activity as measured here through our neuroprosthetic interface might, therefore, reflect both individual alcohol consumption habits and responsiveness to drug application, an imperative to optimized individualized treatment strategies. Conclusion Here, we have employed a custom-made ECoG interface to acquire neurophysiological impairments induced by chronic alcohol use and to monitor their restoration to mechanism-based pharmacological interventions. The chosen electrophysiological parameters have been related to the onset and persistence of clinical symptoms and may predict the clinical trajectory in individual patients. In conjunction with the ADE rat model, which mimics key characteristics of AUD-related pathophysiology and behavioural deficits, this approach provides a powerful translational toolbox showcased by investigating the effects of administering psilocybin and LY379268 which ultimately support recent suggestions of a 5-HT 2A R-mGluR2-based approach to therapeutically target AUD. Declarations Acknowledgement We acknowledge use of the Microstructure Facility of the BIOTEC at TU Dresden (partly funded by the State of Saxony and the European Fund for Regional Development – EFRE (100344812)) for implant fabrication. We thank Kristin Wogan for her excellent technical support. Funding This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 518530049 (NB), the European Research Council (804005; IntegraBrain) (IRM), Volkswagen Foundation (Freigeist 91690) (IRM), Bundesministerium für Bildung und Forschung (BMBF) funded ERA-NET Psi-Alc (FKZ: 01EW1908) (RS, MWM), SysMedSUDs (FKZ: 01ZX1909A) (RS), DZPG (RS), DFG – Project-ID: ME 5279/3-1 (MWM), DFG – Project-ID 402170461- TRR 265 (RS, MWM). Author contributions Conceptualisation: BH, MWM, NB. Methodology: BH, MWM, DA, NB. Software: BH, DA. Validation: BH. Formal analysis: BH. Investigation: BH, CS. Resources: MWM, IRM, NB. Data Curation: BH. Visualisation: BH, NB. Writing - original draft: BH, NB. Writing - review & editing: BH, DA, CS, KD, MK, CW, IRM, RS, MWM, RS. Supervision: MWM, IRM, NB. Project administration: BH, MWM, KD, MK, NB. Funding acquisition: RS, MWM, IRM, CW, NB. All authors read and approved the article's final version and agreed on all aspects of the work. Availability of data and materials All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Ethics approval The animal study was reviewed and approved by the institutional ethics commissions of TU Dresden and the Central Institute of Mental Health (CIMH) Mannheim, and the regional authorities of the federated states of Saxony (Landesdirektion Sachsen) and Baden-Württemberg (Regierungspräsidium Karlsruhe). Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. References Degenhardt L, Charlson F, Ferrari A, Santomauro D, Erskine H, Mantilla-Herrara A, et al. 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Percentage of Heavy Drinking Days Following Psilocybin-Assisted Psychotherapy vs Placebo in the Treatment of Adult Patients With Alcohol Use Disorder: A Randomized Clinical Trial. JAMA Psychiatry. 2022;79:953. Nichols DE. Psychedelics. Pharmacol Rev. 2016;68:264–355. Spanagel R. Ten Points to Improve Reproducibility and Translation of Animal Research. Front Behav Neurosci. 2022;16:869511. Afanasenkau D, Kalinina D, Lyakhovetskii V, Tondera C, Gorsky O, Moosavi S, et al. Rapid prototyping of soft bioelectronic implants for use as neuromuscular interfaces. Nat Biomed Eng. 2020;4:1010–22. Athanasiadis M, Pak A, Afanasenkau D, Minev IR. Direct Writing of Elastic Fibers with Optical, Electrical, and Microfluidic Functionality. Adv Mater Technol. 2019;4:1800659. Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods. 2004;134:9–21. Johnson A, Yonovitz A. Habituation of Auditory Evoked Potentials: The Dynamics of Waveform Morphology. Australian and New Zealand Journal of Audiology. 2007;29:77–88. Meinhardt MW, Güngör C, Skorodumov I, Mertens LJ, Spanagel R. Psilocybin and LSD have no long-lasting effects in an animal model of alcohol relapse. Neuropsychopharmacol. 2020;45:1316–22. Lijffijt M, Lane SD, Meier SL, Boutros NN, Burroughs S, Steinberg JL, et al. P50, N100, and P200 sensory gating: Relationships with behavioral inhibition, attention, and working memory. Psychophysiology. 2009;46:1059–68. Hong LE, Summerfelt A, Buchanan RW, O’Donnell P, Thaker GK, Weiler MA, et al. Gamma and Delta Neural Oscillations and Association with Clinical Symptoms under Subanesthetic Ketamine. Neuropsychopharmacol. 2010;35:632–40. Lally N, Mullins PG, Roberts MV, Price D, Gruber T, Haenschel C. Glutamatergic correlates of gamma-band oscillatory activity during cognition: A concurrent ER-MRS and EEG study. NeuroImage. 2014;85:823–33. Rangaswamy M, Porjesz B. Understanding alcohol use disorders with neuroelectrophysiology. In: Handbook of Clinical Neurology. Elsevier; 2014. p. 383–414. Dousset C, Kajosch H, Ingels A, Schröder E, Kornreich C, Campanella S. Preventing relapse in alcohol disorder with EEG-neurofeedback as a neuromodulation technique: A review and new insights regarding its application. Addictive Behaviors. 2020;106:106391. Gooding DC, Gjini K, Burroughs SA, Boutros NN. The association between psychosis proneness and sensory gating in cocaine-dependent patients and healthy controls. Psychiatry Research. 2013;210:1092–100. Abhang PA, Gawali BW, Mehrotra SC. Technical Aspects of Brain Rhythms and Speech Parameters. In: Introduction to EEG- and Speech-Based Emotion Recognition. Elsevier; 2016. p. 51–79. Kucewicz MT, Berry BM, Kremen V, Brinkmann BH, Sperling MR, Jobst BC, et al. Dissecting gamma frequency activity during human memory processing. Brain. 2017;140:1337–50. Patel SH, Azzam PN. Characterization of N200 and P300: Selected Studies of the Event-Related Potential. Int J Med Sci. 2005;:147–54. Vejmola Č, Tylš F, Piorecká V, Koudelka V, Kadeřábek L, Novák T, et al. Psilocin, LSD, mescaline, and DOB all induce broadband desynchronization of EEG and disconnection in rats with robust translational validity. Transl Psychiatry. 2021;11:506. Jones NC, Reddy M, Anderson P, Salzberg MR, O’Brien TJ, Pinault D. Acute administration of typical and atypical antipsychotics reduces EEG gamma power, but only the preclinical compound LY379268 reduces the ketamine-induced rise in gamma power. Int J Neuropsychopharm. 2012;15:657–68. Olivero G, Grilli M, Vergassola M, Bonfiglio T, Padolecchia C, Garrone B, et al. 5-HT2A-mGlu2/3 receptor complex in rat spinal cord glutamatergic nerve endings: A 5-HT2A to mGlu2/3 signalling to amplify presynaptic mechanism of auto-control of glutamate exocytosis. Neuropharmacology. 2018;133:429–39. Dormann O-D, Schuelert N, Rosenbrock H. Effects of the mGlu2/3 receptor agonist LY379268 on two models of disturbed auditory evoked brain oscillations in mice. Transl Psychiatry. 2023;13:150. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3905152","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":273903108,"identity":"0a4b1529-7678-4f4d-8e23-0fea22d146e7","order_by":0,"name":"Bettina Habelt","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Bettina","middleName":"","lastName":"Habelt","suffix":""},{"id":273903109,"identity":"993518a1-c3d9-406f-94ea-90cc404448bc","order_by":1,"name":"Dzmitry Afanasenkau","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Dzmitry","middleName":"","lastName":"Afanasenkau","suffix":""},{"id":273903110,"identity":"6686ebe8-771a-42ac-a252-1e0b145e10b5","order_by":2,"name":"Cindy Schwarz","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Cindy","middleName":"","lastName":"Schwarz","suffix":""},{"id":273903111,"identity":"0935590f-b03d-4497-a093-37ea426f1cb0","order_by":3,"name":"Kevin Domanegg","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Kevin","middleName":"","lastName":"Domanegg","suffix":""},{"id":273903112,"identity":"92917558-12ce-4420-97aa-10ecf5d66c83","order_by":4,"name":"Martin Kuchar","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Martin","middleName":"","lastName":"Kuchar","suffix":""},{"id":273903113,"identity":"d12092b2-f998-4c57-a1e3-5f21ca564085","order_by":5,"name":"Carsten Werner","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Carsten","middleName":"","lastName":"Werner","suffix":""},{"id":273903114,"identity":"4efd021c-da10-4e5a-801a-f04c80512c7b","order_by":6,"name":"Ivan R. 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Alcohol consumption phases were initially 8 weeks and then between 4 – 6 weeks, interspersed with deprivation periods of 2 – 3 weeks. Following the final (8\u003csup\u003eth\u003c/sup\u003e) alcohol-drinking cycle, rats were habituated to the recording set-up and underwent stereotactic surgery to implant the neuroprosthetic interface. Alcohol-detoxified animals underwent electrocorticographic (ECoG) recordings during a two-tone auditory oddball paradigm initially without any further interventions, while subsequent recording sessions were performed following administration of psilocybin or LY379268 in a randomised order. \u003cstrong\u003eb)\u003c/strong\u003e Alcohol consumption patterns throughout the experimental timeline. Data are presented as daily means ± standard error of the mean of pure EtOH in g per kg over all animals during the last week of a drinking phase (baselines, BL) and on the first day following periods of abstinence (i.e. Alcohol Deprivation Effect (ADE)).\u003cstrong\u003e c)\u003c/strong\u003e Drug treatment with psilocybin und LY379268 was chosen based on previously published data that demonstrated efficacy in reducing relapse-like drinking behaviour [41, 49].\u003c/p\u003e","description":"","filename":"Fig110.png","url":"https://assets-eu.researchsquare.com/files/rs-3905152/v1/8ff5e61c30d1eced6f7270c8.png"},{"id":51485827,"identity":"a108a6bb-01e5-42ea-b022-8bdae9542a40","added_by":"auto","created_at":"2024-02-22 12:44:08","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":189847,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImpact of chronic alcohol consumption and administration of psilocybin and LY379268 on prefrontal electrophysiological activity. a)\u003c/strong\u003e Representative grand average deviant-minus-standard auditory event-related potential (ERP) difference curves at the frontocentral (FC) electrode.\u003cstrong\u003e b)\u003c/strong\u003e Peak-to-peak amplitudes of P1N1, N1P2, P2N2 and N2P3 components. \u003cstrong\u003ec)\u003c/strong\u003e ERP peak latencies of P1, N1, P2, N2 and P3 components.\u003cstrong\u003e d) \u003c/strong\u003eGrand average deviant-minus-standard event-related oscillatory (ERO) activity at the FC channel. Data is given as event-related spectral perturbation (ERSP) in decibels (dB).\u003cstrong\u003e e)\u003c/strong\u003e Maximum ERO activity (as ERSP in dB) within delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-30 Hz) and gamma (\u0026gt; 30 Hz) frequency bands and over the whole frequency range.\u003cstrong\u003ef)\u003c/strong\u003e Latencies of maximum ERO activity within delta, theta, alpha, beta and gamma bands and over the whole frequency range.\u003cstrong\u003e g)\u003c/strong\u003e Frequencies of maximum ERO activity within delta, theta, alpha, beta and gamma bands and over the whole frequency range.\u003cstrong\u003e h)\u003c/strong\u003e Grand average resting-state neural activity of alcohol-dependent animals before and ca. one h after application of psilocybin or LY379268 as means over all channels ± SD. Data is given as power spectral density (PSD) in dB.\u003cstrong\u003e i)\u003c/strong\u003eResting-state neural activity (as PSD in dB) within delta, theta, alpha, beta and gamma bands before and after administration of psilocybin or LY379268.\u003cstrong\u003e \u003c/strong\u003eGraphs illustrated in black: alcohol- and drug-naive controls (n = 10), red: alcohol-dependent animals (n = 10), green: alcohol-dependent animals that received a single dose of psilocybin, blue: alcohol-dependent animals that received a single dose of LY379268. Panels \u003cstrong\u003eb-c\u003c/strong\u003e, \u003cstrong\u003ee-g,\u003c/strong\u003e and\u003cstrong\u003e i\u003c/strong\u003e display data points for all channels of all rats and as mean barplots ± 95 % confidence interval. Asterisks indicate significant differences between interventions with *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Fig210.png","url":"https://assets-eu.researchsquare.com/files/rs-3905152/v1/8a01938529e3598c454fa1e0.png"},{"id":51485828,"identity":"c4f5048a-ce0d-4e43-8cee-43602c480b3a","added_by":"auto","created_at":"2024-02-22 12:44:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":50403,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation of electrophysiological activity with alcohol consumption. a)\u003c/strong\u003e Spearman correlation of ERP amplitudes and ERO activity (as event-related spectral perturbation, ERSP) and \u003cstrong\u003eb) \u003c/strong\u003eresting-state oscillatory activity (as power spectral density, PSD) with alcohol consumption in alcohol-dependent animals before pharmacological interventions. Partial Spearman correlation of event-related (ERP amplitudes, ERSP) and resting-state activity (PSD) with alcohol consumption following administration of \u003cstrong\u003ec)\u003c/strong\u003e Psilocybin or \u003cstrong\u003ed)\u003c/strong\u003e LY379268, controlled for neural activity acquired under drug-free conditions as given in a) and b).Electrophysiological activity data used as means over all channels. Alcohol consumption patterns are given as means over the whole experimental period corresponding to baseline (BL) drinking during the last week of a drinking phase, the first day following periods of abstinence (i.e. Alcohol Deprivation Effect (ADE)) and relapse intensities (difference of ADE and previous BL). Rho: Spearman’s correlation coefficient with rho ≥ 0.1 = weak, ≥ 0.4 = moderate, ≥ 0.7 = strong, ≥ 0.9 = very strong correlation. Asterisks indicate significant results with *\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Fig311.png","url":"https://assets-eu.researchsquare.com/files/rs-3905152/v1/0ce7080887b6b636400ee00d.png"},{"id":70743942,"identity":"6d2f8ff7-3735-4f71-9970-9a2c06ede9b2","added_by":"auto","created_at":"2024-12-06 08:09:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":964742,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3905152/v1/3768da04-8b7f-49ca-9b5e-af9012b1d479.pdf"},{"id":51485829,"identity":"ba3bb77d-9947-4e40-aaf6-85871f2a4d0b","added_by":"auto","created_at":"2024-02-22 12:44:08","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":118567,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"SupplTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-3905152/v1/d65f9a2b97c3401cf758a3a5.docx"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"Prefrontal Electrophysiological Biomarkers and Mechanism-Based Drug Effects in a Rat Model of Alcohol Addiction","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSubstance use disorders are a severe health issue worldwide. With more than three million deaths each year, the highest impact is attributed to the abuse of alcohol [1, 2]. Treatment options for alcohol use disorder (AUD) include pharmacological interventions (e.g. acamprosate and naltrexone) and psychotherapy (e.g. cognitive behavioural therapy). However, there is a considerable heterogeneity in response to these treatments, thus limiting their effectiveness, and the vast majority of patients suffer from relapse [3, 4]. A wealth of theoretical and empirical evidence thus strongly supports efforts towards a precision medicine approach with adequate biomarkers to identify and target pathophysiological mechanisms that will likely respond best to a given treatment [5, 6]. Potential biomarkers of clinical state and treatment responsiveness include electrophysiological brain activity measures of neural oscillations and event-related potentials (ERPs) that represent the neural basis of sensory information processing and higher-order cognitive abilities such as attention, working memory, decision making and behavioural control \u0026ndash; prefrontal functions that are strongly disturbed in AUD [7, 8].\u003c/p\u003e \u003cp\u003eResting-state neural oscillations describe a continuous, rhythmic and repetitive electrical activity generated spontaneously by temporally and spatially synchronised neurons and reflect a rather fundamental brain state [9, 10]. Brain oscillations are subdivided into different frequency bands, most commonly delta (1\u0026ndash;4 Hz), theta (4\u0026ndash;8 Hz), alpha (8\u0026ndash;12 Hz), beta (12\u0026ndash;30 Hz) and gamma (\u0026gt;\u0026thinsp;30 Hz) [11]. Chronic alcohol consumption increases oscillatory power within all frequency bands, but most prominently in the beta band [12\u0026ndash;16]. Higher-frequency beta activity has been associated with a state of hyperarousal and increased relapse probability [12].\u003c/p\u003e \u003cp\u003eIn contrast, event-related oscillations (ERO) refer to time-frequency measurements in response to motor, sensory or cognitive events [17]. When tested for executive functioning during Go/NoGo tasks, AUD patients display reduced ERO power in the delta, theta and alpha range in response to NoGo stimuli [18, 19] indicating impaired behavioural inhibition and cognitive control. Disturbed impulse control has also been related to beta oscillations, which are dominant in sensorimotor functioning and display a reduced power in binge drinkers during NoGo task conditions [20]. Superposition and phase synchronisation of EROs further determine the formation of ERP components [17, 21]. These stimulus-evoked voltage deflections are time-locked local positive or negative maxima within a continuously recorded electroencephalogram. They are commonly named according to their polarity (P\u0026thinsp;=\u0026thinsp;positive, N\u0026thinsp;=\u0026thinsp;negative) and time (in ms post-stimulus) or order of appearance [22]. Alcohol consumption reduces amplitudes and/or increases latencies of multiple ERP components, pointing to alterations of the entire information processing system [23, 24]. Increased salience of alcohol-related cues in combination with a lack of inhibitory resources are the central neurocognitive mechanisms underlying relapse, with the P3 being the most reliable ERP component to predict relapse risk and treatment success [25\u0026ndash;27].\u003c/p\u003e \u003cp\u003eIt is recognized that the described cognitive impairments and limited behavioural control observed in AUD relate to disturbances primarily within prefrontocortical networks [28, 29]. Thus, the present study builds on the assumption that (i) aberrant neuroelectric signatures in AUD represent impaired prefrontal function that underlies vulnerability to relapse, and (ii) pharmacological interventions which address such a vulnerable state can restore altered electrophysiological activity.\u003c/p\u003e \u003cp\u003eWe previously developed an electrocorticographic (ECoG) interface [30] tailored to capture prefrontal ERP and neural oscillations and we here applied this new technology to a well-established animal model for alcohol addiction and relapse behavior. In this model rats are subjected to long-term voluntary alcohol consumption in a four-bottle procedure, repeatedly interrupted with abstinence periods. The re-presentation of alcohol following deprivation induces relapse-like drinking - a temporary increase in alcohol intake over baseline drinking referred to as the alcohol-deprivation effect (ADE) [31]. The development of compulsive drinking behavior is further characterized by insensitivity to taste adulteration with quinine, a loss of circadian drinking patterns, and a shift towards drinking highly concentrated alcohol solutions to rapidly increase blood alcohol concentrations and achieve intoxication during a relapse situation. In addition, alcohol-dependent rats that derive from this model show tolerance and physical as well as anxiety-related withdrawal symptoms [32\u0026ndash;34]. The ADE model has been utilised in various preclinical and translational alcohol studies and has helped identify new treatment targets with good predictive validity [32, 35].\u003c/p\u003e \u003cp\u003eAfter assessing prefrontal electrophysiological signatures in the ADE rat model, we tested two drug treatments that we expected to interfere with prefrontal dysfunction and relapse behaviour. One of the therapeutic targets is the metabotropic glutamate receptor 2 (mGluR2) which is a key regulator of glutamate release. Prefrontal mGluR2 expression and function is strongly diminished in animal models of alcohol addiction and in severe AUD case [36, 37]. Consequently, it has been proposed to use, mGluR2 agonists such as LY379268 to counteract this diminished prefrontal function providing preclinical evidence of its potential to attenuate alcohol-seeking and relapse-like behaviour [37\u0026ndash;41]. Recently, we demonstrated that virally restoring normal prefrontal mGluR2 levels is able to prevent cognitive impairment and craving in alcohol-dependent rats and that the normalisation of mGluR2 is also possible via a single administration of the psychedelic agent psilocybin which ultimately reduced relapse-like behavior [37]. Psilocybin seems promising in treating AUD since a recent clinical trial using psilocybin in combination with psychotherapy demonstrated a significant reduction of heavy drinking days in AUD patients [42]. The behavioural and therapeutic effects of psilocybin are primarily attributed to the activation of the serotonin 2A receptor (5-HT\u003csub\u003e2A\u003c/sub\u003eR) [43] and its modulation by other pathways including the physical interaction with the mGluR2 [36]. Both, mGluR2 and 5-HT\u003csub\u003e2A\u003c/sub\u003eR are enriched in prefrontal areas. This supports our hypothesis that their activation can restore altered ERPs and neural oscillations in alcohol-dependent rats, thereby improving cognitive functioning and reducing the risk of relapse.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnimals\u003c/h2\u003e \u003cp\u003e All investigations within this project have been approved by the institutional ethics commissions of TU Dresden and the Central Institute of Mental Health, Mannheim and the regional authorities of the federated states of Saxony (Landesdirektion Sachsen) and Baden-W\u0026uuml;rttemberg (Regierungspr\u0026auml;sidium Karlsruhe). Experiments were performed in accordance with the guidelines of the Directive 2010/63/EU on the protection of animals used for scientific purposes of the European Commission with great attention to avoid suffering and to reduce number of animals used [44].\u003c/p\u003e \u003cp\u003eWe used male Wistar rats from the breeding colony at the CIMH. Rats were housed in single cages (Makrolon\u0026reg;, Type III, Tecniplast Deutschland GmbH) on sawdust bedding (Ssniff - Bedding 3/4 S, Altrogge) with Bed-r'Nest material (Datesand Ltd.). Pelleted food (V1534-300, ssniff Spezialdi\u0026auml;ten GmbH) and water were available ad libitum. Housing rooms were temperature (20\u0026ndash;22\u0026deg;C) and humidity (40\u0026ndash;55%) controlled with a 12 h automatic light-dark cycle (lights on at 6.00 am).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eLong-term alcohol consumption with repeated deprivation periods\u003c/h2\u003e \u003cp\u003eFollowing two weeks of habituation to the animal room, rats were given ad libitum access to ethanol (VWR International GmbH) solutions of 5%, 10%, and 20% (v/v) besides tap water. Concurrent access to several alcohol concentrations has been shown to increase the magnitude and duration of the ADE [31, 32]. The positions of bottles were changed weekly. After eight weeks of continuous alcohol availability, bottles with alcohol solution were removed from the cages and reintroduced after a deprivation period of two weeks. Phases of free access to alcohol and deprivation subsequently alternated randomly with variable durations of drinking between 4\u0026ndash;6 weeks and deprivation lasting 2\u0026ndash;3 weeks, aiming to prevent habituation and behavioural adjustment.\u003c/p\u003e \u003cp\u003eThe long-term alcohol exposure procedure, including all drinking and deprivation phases, continued over 13 months. During the final two-week period of alcohol deprivation, animals (n\u0026thinsp;=\u0026thinsp;10) were habituated to the recording set-up and underwent surgery to implant the neuroprosthetic device (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Ten alcohol-na\u0026iuml;ve control animals underwent the same procedure [30].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eManufacturing and implantation of neuroprosthetic interfaces\u003c/h2\u003e \u003cp\u003eThe procedures to fabricate, characterise and implant the used neuroprosthetics have been described in detail before [30, 45, 46]. Briefly, micro-EcoG interfaces were produced by an additive manufacturing approach using the 3D bioprinter 3DDiscovery\u003csup\u003e\u0026trade;\u003c/sup\u003e Evolution (regenHU Ltd.). The devices consisted of soft silicone for the base (DOWSIL\u0026trade; SE 1700, Dow Inc., Midland, USA) and isolating (SE 734, Dow Inc., Midland, USA) layers embedding a 3 \u0026times; 3 electrode array of conductive platinum ink (chemPUR). The electrode interconnects were attached to stainless steel microwires (\u0026empty;: 0.23 mm, 7SS-2T, Science Products GmbH) soldiered to a plug-in connector (BKL 10120653, BKL-Electronic Kreimendahl GmbH). An additional microwire was fixed to a microscrew drilled into the skull during surgery and served as a reference electrode. Implantation was performed under subcutaneous (s.c.) anaesthesia (fentanyl (0.005 mg/kg, Hameln Pharma), midazolam (2 mg/kg, Ratiopharm), medetomidine hydrochloride (0.135 mg/kg, Orion Pharma) in a stereotactic surgery involving trepanation of the skull (\u0026empty; 6.0 mm, 330205486001060, Meisinger) to position the devices epidurally on the prefrontal cortex with the frontal electrode row located at 3.2 mm anterior to bregma. External parts of the implant were fixed to the skull using dental cement (Paladur, Kulzer GmbH), and the wound was sutured. After completion of the surgery, anaesthesia was antagonised (s.c., naloxone hydrochloride (0.12 mg/kg, Inresa Arzneimittel GmbH), flumazenil (0.2 mg/kg), atipamezolhydrochloride (0.75 mg/kg, Orion Pharma). Animals received meloxicam (1 mg/kg, s.c., Boehringer Ingelheim Vetmedica GmbH) as an analgesic right after surgery and the following day.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eElectrocorticography recording and acute pharmacological modulation of neural activity\u003c/h2\u003e \u003cp\u003eECoG recordings without any further interventions were implemented three days after the animals had undergone surgery. Recordings were performed at a sampling rate of 3 kHz using the Intan RHD2000 USB interface system cable connected to the implant plug-in module. The initial recording measured a state of abstinence in alcohol dependent rats compared to matched alcohol-na\u0026iuml;ve rats.\u003c/p\u003e \u003cp\u003eRecordings were performed within an electrically shielded and sound-insulated audiometry booth where one animal at a time was placed in a rodent sling (Lomir Biomedical Inc.) to reduce movement artefacts. To record auditory event-related activity, sound stimuli were presented through a stereo loudspeaker located at a distance of 40 cm and an angle of 45\u0026deg; centrally above the animal's head. Auditory stimuli have been generated using the Psychophysics Toolbox (Version 3) for Matlab (Version R2019b, The Mathworks Inc.) and were composed of frequent (standards: 50 ms, 1 kHz, 70 dB sound pressure level (SPL), 87% of trials) and rare (deviants: 50 ms, 2 kHz, 80 dB SPL, 13% of trials) sinusoidal sounds with 5-ms onset/offset ramps, presented in 6 blocks of 5 min with 1 s interstimulus interval. Deviant sounds have been interspersed with at least one standard tone to avoid successive occurrences.\u003c/p\u003e \u003cp\u003eOn day 6 and 9 after initial recordings, alcohol-dependent rats randomly received intraperitoneal (i.p.) injections of psilocybin (2.5 mg/kg, 3-[2-(dimethylamino) ethyl]-1H-indol-4-yl] dihydrogen phosphate (purity 99.7%) obtained from the University of Chemistry and Technology Prague, Czech Republic, dissolved in Ampuwa (Braun Melsungen AG) or LY379268 (1 mg/kg, 1\u003cem\u003eR\u003c/em\u003e,4\u003cem\u003eR\u003c/em\u003e,5\u003cem\u003eS\u003c/em\u003e,6\u003cem\u003eR\u003c/em\u003e)-4-Amino-2-oxabicyclo[3.1.0]hexane-4,6-dicarboxylic acid, Tocris Bioscience) each 30 min before recording. Respective dosing was chosen based on previously published data that demonstrated efficacy in reducing alcohol relapse [37, 41].\u003c/p\u003e \u003cp\u003eTo capture drug-induced changes in resting-state neural activity, we performed continuous 5-minute recordings right before administering psilocybin or LY379268, and directly after the auditory oddball paradigm described above. Pre- and post-application recordings were approximately one hour apart.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eEvent-related potentials and oscillatory activity\u003c/h2\u003e \u003cp\u003eData processing was performed using the EEGLAB toolbox [47] (Version 2019.1) for Matlab. Following offline filtering using a 0.1\u0026ndash;45 Hz bandpass finite impulse response filter (Kaiser windowed, Kaiser β\u0026thinsp;=\u0026thinsp;5.65, filter length 54330 points), data were segmented in epochs between \u0026minus;\u0026thinsp;100 and 700 ms relative to stimulus onset separately for standard and deviant sounds and baseline-corrected using the pre-stimulus interval between \u0026minus;\u0026thinsp;100 ms to 0 ms. Artefacts and noisy channels were identified and excluded based on a delta criterion of 500 \u0026micro;V and visual confirmation before averaging epochs for single subjects and over all animals (grand average). As neural responses to the frequent standard sounds rarely displayed pronounced amplitudes, indicating habituation effects due to the high repetition rate [48], subsequent analysis was performed on the difference curves (deviant-minus-standard responses). ERP peak latencies were detected within the following time intervals confirmed by visual inspection: P1: 20\u0026ndash;70 ms, N1: 35\u0026ndash;120 ms, P2: 60\u0026ndash;260 ms, N2: 100\u0026ndash;320 ms, P3: 130\u0026ndash;600 ms. The amplitudes of the ERP components were calculated as peak-to-peak amplitudes (P1N1, N1P2, P2N2, N2P3).\u003c/p\u003e \u003cp\u003eOscillatory power in the delta (1\u0026ndash;4 Hz), theta (4\u0026ndash;8 Hz), alpha (8\u0026ndash;12 Hz), beta (12\u0026ndash;30 Hz) and gamma (30\u0026ndash;45 Hz) bands was determined by applying the function pop_newtimef.m in EEGLAB based on a Fast Fourier transform using 400 datapoints and a pad ratio of 64. The resulting event-related spectral perturbation (ERSP) was calculated as decibels (dB) (\u0026thinsp;≙\u0026thinsp;10*log\u003csub\u003e10\u003c/sub\u003e (\u0026micro;V\u003csup\u003e2\u003c/sup\u003e/Hz)).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eResting-state neural oscillations\u003c/h2\u003e \u003cp\u003eData were initially bandpass filtered, as described above, and segmented into 2 s-epochs with 50% overlap. Following the exclusion of bad epochs (δ\u0026thinsp;=\u0026thinsp;500 \u0026micro;V, confirmed by visual inspection), we applied the EEGLAB function pop_spectopo.m to determine channel spectra based on the Welch method. The resulting power spectral density (PSD) in the 1\u0026ndash;45 Hz frequency range was calculated as dB.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistics\u003c/h2\u003e \u003cp\u003eStatistical analyses were conducted using SPSS\u0026reg; (Version 28, IBM Corp.) and R (Version 4.2.3, R Foundation for Statistical Computing). Differences in ERPs (peak latencies, amplitudes) and EROs (bandpower (ERSP), latency and frequency of max. power within each frequency band and over the whole frequency range) induced by psilocybin and LY379268 were examined by applying within-subjects repeated measures analysis of variance (rmANOVA) with factors treatment and channel. Multiple comparisons were adjusted using the Sidak correction. Likewise, rmANOVA was applied to analyse resting-state oscillatory activity (PSD) before vs. after administration of psilocybin and LY379268.\u003c/p\u003e \u003cp\u003eNeural parameters of alcohol- and drug-na\u0026iuml;ve controls were compared with those of long-term alcohol consumers and each pharmacological intervention by applying a between-subjects ANOVA with factors treatment and channel and Sidak adjustment for multiple comparisons.\u003c/p\u003e \u003cp\u003eTo explore the potential impact of individual alcohol consumption patterns and susceptibility to the ADE on designated neural parameters, we performed Spearman correlation analyses using the averaged amounts of alcohol (g/kg body weight) consumed by each rat per day during the last week of a drinking phase (=\u0026thinsp;baseline consumption, BL) and on the first day following periods of abstinence (=\u0026thinsp;Alcohol Deprivation Effect (ADE)) as well as relapse intensities (difference of ADE and previous BL). \u003cem\u003ePartial\u003c/em\u003e Spearman correlation was performed to relate alcohol consumption patterns with the neural activity following pharmacotreatments, controlling for neural activity without drug administration.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eImpact of long-term alcohol consumption on neural activity\u003c/h2\u003e \u003cp\u003eAlcohol consumption patterns throughout the experimental timeline are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb. Mean baseline total alcohol intake (g/kg/day\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD)) was 3.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54, with rats consuming 1.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54 of 5%, 1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.45 of 10% and 1.16\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40 of the 20% alcohol solution, respectively. Following deprivation, animals displayed increased consumption of all alcohol concentrations compared to baseline drinking (5%: 1.58\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006; 10%: 1.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.11; 20%: 1.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.58, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.034, Total: 4.66\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001, two-sided paired t-tests) revealing a pronounced ADE.\u003c/p\u003e \u003cp\u003eNeurophysiological data revealed a significant effect of long-term alcohol consumption for most neural parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) with reduced ERP amplitudes of P1N1 and N1P2 components in alcohol-dependent rats, thus also resulting in earlier peaking of N1 and P2 components compared to na\u0026iuml;ve controls (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-c, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). In contrast, P2N2 amplitudes were enhanced following long-term alcohol consumption, while N2P3 amplitudes remained similar to controls. Furthermore, alcohol-dependent animals displayed reduced and later peaking ERO activities within delta, theta, alpha and beta bands and over the whole frequency range (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed-f, Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Only in the gamma range long-term alcohol consumption induced an increased oscillatory power. We further observed an elevated activity within higher beta frequency ranges in alcohol-dependent animals while low beta frequencies dominated in na\u0026iuml;ve controls (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg; Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). Statistical analyses did not yield an effect of channel location or channel \u0026times; treatment interaction for any of the parameters.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eConcerning alcohol consumption patterns, P1N1 and N1P2 amplitudes and oscillatory activities of the whole frequency range displayed a strong positive correlation with relapse intensity to 10% alcohol and a moderate positive correlation to baseline consumption of 20% alcohol. In addition, gamma band activity revealed a strong negative correlation with baseline consumption of 10% alcohol (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, Table S2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eCorrelation analyses of resting-state oscillatory activities with alcohol consumption before substance application most consistently revealed moderate to strong positive correlations with consumption of 20% alcohol at baseline and after abstinence. This relation was also observed for delta, theta and alpha waves, with total alcohol relapse intensity primarily attributed again to 20% alcohol. In addition, gamma activity displayed a moderate negative correlation with post-deprivation consumption of 5% alcohol (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, Table S3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePharmacological modulation of neural activity in alcohol-dependent rats\u003c/h2\u003e \u003cp\u003eAfter successfully investigating the electrophysiological changes in alcohol-dependent rats, we wanted to examine whether pharmacological interventions counteract these neuropathological changes. We previously demonstrated that pharmacotreatment with psilocybin and LY379268 reduces alcohol intake following abstinence thereby significantly counteracting the ADE (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec) [41, 49]. We build upon this work and investigated the neurophysiological effects induced by acute psilocybin and LY379268.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePsilocybin\u003c/h2\u003e \u003cp\u003eFollowing an acute application of 2.5 mg/kg psilocybin in alcohol-detoxified rats, we observed a partial decrease in resting-state oscillatory activities, predominantly in delta and theta bands, with no effect of channel location or channel \u0026times; treatment interaction (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eh-i, upper panels, Table S4). Bandpowers after vs. before drug administration were positively correlated with moderate to strong effect sizes (Table S5). Correlation with alcohol consumption revealed most consistently a moderate, negative correlation of post-administration resting-state bandpowers with total alcohol consumption after abstinence and corresponding relapse intensity and a moderate, positive correlation of theta, alpha, beta and gamma band activities with baseline consumption of 20% alcohol (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, Table S6).\u003c/p\u003e \u003cp\u003eAfter administration of psilocybin, ERPs of alcohol-dependent rats revealed increased amplitudes of P1N1, N1P2 and N2P3 amplitudes (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-b, Table S7). The manifestation of these ERPs was similar to those observed in na\u0026iuml;ve rats and even showed slightly higher and earlier peaking amplitudes (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-b, Table S8). In contrast to resting-state oscillations, EROs displayed elevated bandpowers over the whole frequency range (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed-e, Table S7). We additionally observed a shift from maximum beta powers to lower frequency ranges after administering psilocybin (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed,g, Table S7). Compared to na\u0026iuml;ve controls, ERO activity differed predominantly in the gamma frequency range, revealing increased and earlier peaking bandpowers (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee-f, Table S8). Correlation analyses of event-related activity following psilocybin administration vs. initial recordings without drug application revealed a moderate negative correlation for P2N2 amplitudes, while all other ERPs and EROs were positively correlated with varying effect sizes (Table S9). Regarding alcohol consumption patterns, we observed a positive correlation between post-administration ERPs and EROs and drinking amounts of 20% alcohol at baseline and following deprivation and a negative correlation with total baseline alcohol intake and consumption of 5% alcohol following abstinence (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, Table S10).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eLY379268\u003c/h2\u003e \u003cp\u003eThe administration of 1 mg/kg LY379268 induced a decrease in resting-state oscillatory activity within all frequency bands and at all electrode sites with medium to large effect sizes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eh-i, bottom panels, Table S11). Bandpowers after vs. before drug application were positively correlated (Table S12), whereas the correlation of post-administration bandpowers with alcohol consumption patterns displayed only a weak connection overall (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ed, Table S13).\u003c/p\u003e \u003cp\u003eFollowing administration of LY379268, ERPs revealed increased P1N1 and decreased P2N2 amplitudes (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-b; Table S14) and an elevated ERO activity (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed-e; Table S14). As with psilocybin, beta frequencies dominated at lower frequency ranges compared to the non-treated condition (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg, Table S14). Compared to na\u0026iuml;ve controls, ERP amplitudes were in the same range (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-b, Table S15), while EROs displayed an increased and earlier peaking gamma activity under the influence of LY379268 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eg, Table S15). Event-related activity following LY379268 administration displayed weak positive correlations with initial recordings without drug application (Table S16) and also weaker connections to alcohol consumption patterns than those recorded under the influence of psilocybin, but indicates a similar negative relation to total alcohol intake at baseline and specifically with the relapse intensity to 20% alcohol in case of the P2N2 component (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed, Table S17).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the present study, we used an established animal model of compulsive alcohol consumption and relapse behaviour and a new neuroprosthetic interface to record, modulate and classify potential electrophysiological biomarkers to reveal i) neuroelectric changes in the prefrontal cortex in alcohol-dependent rats and ii) their reversal via application of the psychedelic psilocybin and the mGluR2 agonist LY379268.\u003c/p\u003e \u003cp\u003eAlcohol-dependent rats displayed reduced ERP amplitudes of P1N1 and N1P2 components and decreased and later peaking ERO activity within delta, theta, alpha and beta frequency bands, indicating deficiencies in sensory gating and early attentive filtering [17, 19, 50]. However, in the gamma range, chronic alcohol intake induced an increased oscillatory power, which has been related to enhanced extracellular glutamate concentrations [51, 52]. We further observed a dominance within higher beta frequency ranges in alcohol-dependent rats compared to na\u0026iuml;ve controls with maximum band powers in low beta frequencies. In patients with AUD, abnormal frontal high beta and gamma activities have been associated with an impaired working memory system and deficient top-down processing known to provoke reduced executive control and inhibition [53, 54] underlying relapse behaviour. Manifestation of ERPs and EROs showed a diametrically opposite correlation with baseline drinking compared to the relapse-like increase in alcohol consumption following abstinence, suggesting that relapse-like drinking and baseline alcohol consumption are controlled through different neural mechanism.\u003c/p\u003e \u003cp\u003eDisturbed sensory gating, as reflected by P1N1 and N1P2 deficiencies, has been correlated with perceptual aberrations and the proneness to develop psychotic symptoms [55]. Acute application of psilocybin increased amplitudes of P1N1 and N1P2 components in our alcohol-dependent rats and elevated corresponding bandpowers over the whole frequency range. In addition, we show that psilocybin shifted maximum beta powers from mid/high beta ranges, associated with stress, anxiety and paranoia, to lower frequencies that reflect conscious focusing [56]. Psilocybin treatment in alcohol-dependent rats even pushed neural processing compared to na\u0026iuml;ve controls, as revealed by elevated P1N1 amplitudes and accelerated peak latencies of most ERP components and increased and earlier peaking gamma bandpowers. Gamma oscillations have been linked to mechanisms of synaptic plasticity and supposedly reflect the coordinated activity of neuronal assemblies supporting cognitive functioning, including memory formation, effective learning and focused attention [57]. Thus, psilocybin might facilitate these processes by strengthening gamma activity. Mental sharpness and cognitive control might be additionally supported by the psilocybin-induced increase in oscillatory activity within lower frequency ranges of delta, theta and alpha bands that are related to relaxation, mindfulness and creativity [56]. Synchronisation of these low frequency bands supposedly predicts P1N1 latency and amplitude and contributes to forming the P3 component [17, 21].\u003c/p\u003e \u003cp\u003eBoth pharmacological treatments clearly augmented event-related neural activity restoring a pronounced P1-N1-P2 complex comparable to na\u0026iuml;ve controls that directly disembogued into the P3 component rather than forming a marked N2. A marked N2P2 component was a distinct feature of untreated alcohol-dependent rats. Higher N2 amplitudes have been related to increased task difficulty and effort necessary to inhibit behaviour as in NoGo responses [58]. An elevated N2 component in alcohol-dependent rats might, therefore, indicate an inappropriate activation of mental resources not necessary for the simple passive listening task applied here, while a small N2 might further emphasise the facilitation of sensory information processing in response to both applied pharmacological interventions.\u003c/p\u003e \u003cp\u003eFinally, and in line with previous preclinical studies, psilocybin and LY379268 had a soothing effect on resting-state neural activity in our alcohol-dependent rats, though this effect was not as pronounced as previously seen in healthy rats [59, 60].\u003c/p\u003e \u003cp\u003e5-HT\u003csub\u003e2A\u003c/sub\u003eR and mGluR2 have been shown to physiologically interact antagonistically to ensure correct glutamate exocytosis [61]. Therefore, it seems surprising that in this study, we found similar effects of the administration of psilocybin and LY379268 on electrophysiological brain activity. One possible explanation might be the aforementioned dysfunction of mGluR2 often observed in patients with AUD. In addition, a recent study in mice displaying deficiencies in auditory ERO activity confirmed the beneficial effect of LY379268 [62]. Further experiments should consider the co-administration of these two compounds as well as the administration of mGluR2 and 5-HT\u003csub\u003e2A\u003c/sub\u003eR antagonists in combination with psilocybin and LY379268, respectively. These results will help to deepen our understanding of the receptor-receptor crosstalk and its effects on brain activity.\u003c/p\u003e \u003cp\u003eCorrelation analysis further revealed that the changes induced by pharmacological treatment in resting-state and event-related activity depend on both individual neural activity states without drug application and alcohol consumption patterns. Interestingly, the effect of both pharmacological treatments on ERPs and EROs was more pronounced the lower the alcohol intake had been. However, these findings were restricted to low and moderately concentrated alcohol solutions, while psilocybin-induced enhancements of neural activity were positively correlated with the consumption of 20% alcohol. Differential neuronal activity as measured here through our neuroprosthetic interface might, therefore, reflect both individual alcohol consumption habits and responsiveness to drug application, an imperative to optimized individualized treatment strategies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eHere, we have employed a custom-made ECoG interface to acquire neurophysiological impairments induced by chronic alcohol use and to monitor their restoration to mechanism-based pharmacological interventions. The chosen electrophysiological parameters have been related to the onset and persistence of clinical symptoms and may predict the clinical trajectory in individual patients. In conjunction with the ADE rat model, which mimics key characteristics of AUD-related pathophysiology and behavioural deficits, this approach provides a powerful translational toolbox showcased by investigating the effects of administering psilocybin and LY379268 which ultimately support recent suggestions of a 5-HT\u003csub\u003e2A\u003c/sub\u003eR-mGluR2-based approach to therapeutically target AUD.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgement\u003c/p\u003e\n\u003cp\u003eWe acknowledge use of the Microstructure Facility of the BIOTEC at TU Dresden (partly funded by the State of Saxony and the European Fund for Regional Development \u0026ndash; EFRE (100344812)) for implant fabrication. We thank Kristin Wogan for her excellent technical support.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) \u0026ndash; Project-ID 518530049 (NB), the European Research Council (804005; IntegraBrain) (IRM), Volkswagen Foundation (Freigeist 91690) (IRM), Bundesministerium f\u0026uuml;r Bildung und Forschung (BMBF) funded ERA-NET Psi-Alc (FKZ: 01EW1908) (RS, MWM), SysMedSUDs (FKZ: 01ZX1909A) (RS), DZPG (RS), DFG \u0026ndash; Project-ID: ME 5279/3-1 (MWM), DFG \u0026ndash; Project-ID 402170461- TRR 265 (RS, MWM).\u003c/p\u003e\n\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eConceptualisation: BH, MWM, NB.\u0026nbsp;Methodology: BH, MWM, DA, NB. Software: BH, DA. Validation: BH.\u0026nbsp;Formal analysis: BH. Investigation: BH, CS. Resources: MWM, IRM, NB. Data Curation: BH. Visualisation: BH, NB. Writing - original draft: BH, NB. Writing - review \u0026amp; editing: BH, DA, CS, KD, MK, CW, IRM, RS, MWM, RS. Supervision: MWM, IRM, NB. Project administration: BH, MWM, KD, MK, NB. Funding acquisition: RS, MWM, IRM, CW, NB. All authors read and approved the article\u0026apos;s final version and agreed on all aspects of the work.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eAll data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.\u003c/p\u003e\n\u003cp\u003eEthics approval\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe animal study was reviewed and approved by the institutional ethics commissions of TU Dresden and the Central Institute of Mental Health (CIMH) Mannheim, and the regional authorities of the federated states of Saxony (Landesdirektion Sachsen) and Baden-W\u0026uuml;rttemberg (Regierungspr\u0026auml;sidium Karlsruhe).\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003e\u003cspan\u003eDegenhardt L, Charlson F, Ferrari A, Santomauro D, Erskine H, Mantilla-Herrara A, et al. 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Neuropsychopharmacol. 2020;45:1316\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eLijffijt M, Lane SD, Meier SL, Boutros NN, Burroughs S, Steinberg JL, et al. P50, N100, and P200 sensory gating: Relationships with behavioral inhibition, attention, and working memory. Psychophysiology. 2009;46:1059\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eHong LE, Summerfelt A, Buchanan RW, O\u0026rsquo;Donnell P, Thaker GK, Weiler MA, et al. Gamma and Delta Neural Oscillations and Association with Clinical Symptoms under Subanesthetic Ketamine. Neuropsychopharmacol. 2010;35:632\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eLally N, Mullins PG, Roberts MV, Price D, Gruber T, Haenschel C. Glutamatergic correlates of gamma-band oscillatory activity during cognition: A concurrent ER-MRS and EEG study. 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Technical Aspects of Brain Rhythms and Speech Parameters. In: Introduction to EEG- and Speech-Based Emotion Recognition. Elsevier; 2016. p. 51\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eKucewicz MT, Berry BM, Kremen V, Brinkmann BH, Sperling MR, Jobst BC, et al. Dissecting gamma frequency activity during human memory processing. Brain. 2017;140:1337\u0026ndash;50.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003ePatel SH, Azzam PN. Characterization of N200 and P300: Selected Studies of the Event-Related Potential. Int J Med Sci. 2005;:147\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eVejmola Č, Tyl\u0026scaron; F, Pioreck\u0026aacute; V, Koudelka V, Kadeř\u0026aacute;bek L, Nov\u0026aacute;k T, et al. Psilocin, LSD, mescaline, and DOB all induce broadband desynchronization of EEG and disconnection in rats with robust translational validity. Transl Psychiatry. 2021;11:506.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eJones NC, Reddy M, Anderson P, Salzberg MR, O\u0026rsquo;Brien TJ, Pinault D. Acute administration of typical and atypical antipsychotics reduces EEG gamma power, but only the preclinical compound LY379268 reduces the ketamine-induced rise in gamma power. Int J Neuropsychopharm. 2012;15:657\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eOlivero G, Grilli M, Vergassola M, Bonfiglio T, Padolecchia C, Garrone B, et al. 5-HT2A-mGlu2/3 receptor complex in rat spinal cord glutamatergic nerve endings: A 5-HT2A to mGlu2/3 signalling to amplify presynaptic mechanism of auto-control of glutamate exocytosis. Neuropharmacology. 2018;133:429\u0026ndash;39.\u003c/span\u003e\u003c/li\u003e\n \u003cli\u003e\u003cspan\u003eDormann O-D, Schuelert N, Rosenbrock H. Effects of the mGlu2/3 receptor agonist LY379268 on two models of disturbed auditory evoked brain oscillations in mice. Transl Psychiatry. 2023;13:150.\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"translational-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tp","sideBox":"Learn more about [Translational Psychiatry](http://www.nature.com/tp/)","snPcode":"41398","submissionUrl":"https://mts-tp.nature.com/cgi-bin/main.plex","title":"Translational Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-3905152/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3905152/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCurrent treatments for alcohol use disorder (AUD) show large heterogeneity in response and thus limited effectiveness and high relapse rates. A precision medicine approach with biomarkers responsive to new treatments is warranted to overcome this limitation. Promising biomarkers relate to prefrontal control mechanisms that are severely disturbed in AUD. This results in reduced inhibitory control of compulsive behavior and, eventually, relapse. We reasoned here that prefrontal dysfunction, which underlies vulnerability to relapse, is evidenced by altered neuroelectric signatures and should be restored by pharmacological interventions that specifically target prefrontal dysfunction. To test this, we applied our recently developed biocompatible neuroprosthesis to measure prefrontal neural function in a well-established rat model of alcohol addiction and relapse. We monitored neural oscillations and event-related potentials in awake alcohol-dependent rats during abstinence and following treatment with psilocybin or LY379268, agonists of the serotonin 2A receptor (5-HT\u003csub\u003e2A\u003c/sub\u003eR) and the metabotropic glutamate receptor 2 (mGluR2), that are known to reduce prefrontal dysfunction and relapse. Electrophysiological impairments in alcohol-dependent rats are reduced amplitudes of P1N1 and N1P2 components and attenuated event-related oscillatory activity. Psilocybin and LY379268 were able to restore these impairments. Furthermore, alcohol-dependent animals displayed a dominance in higher beta frequencies indicative of a state of hyperarousal that is prone to relapse, which particularly psilocybin was able to counteract. In summary, we provide prefrontal markers indicative of relapse and treatment response, especially for psychedelic drugs.\u003c/p\u003e","manuscriptTitle":"Prefrontal Electrophysiological Biomarkers and Mechanism-Based Drug Effects in a Rat Model of Alcohol Addiction","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-22 12:44:03","doi":"10.21203/rs.3.rs-3905152/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2024-03-28T15:29:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-03-25T11:33:05+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-03-08T22:47:06+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-03-08T12:00:59+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-02-26T19:01:50+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2024-02-20T15:13:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-31T10:46:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Translational Psychiatry","date":"2024-01-30T14:24:28+00:00","index":"","fulltext":""},{"type":"checksFailed","content":"","date":"2024-01-29T11:35:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-28T08:31:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"translational-psychiatry","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"tp","sideBox":"Learn more about [Translational Psychiatry](http://www.nature.com/tp/)","snPcode":"41398","submissionUrl":"https://mts-tp.nature.com/cgi-bin/main.plex","title":"Translational Psychiatry","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"23c9ccf6-ad52-4214-b2f0-23bdf478d7ae","owner":[],"postedDate":"February 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":28869081,"name":"Health sciences/Biomarkers"},{"id":28869082,"name":"Biological sciences/Neuroscience"}],"tags":[],"updatedAt":"2024-12-06T08:09:25+00:00","versionOfRecord":{"articleIdentity":"rs-3905152","link":"https://doi.org/10.1038/s41398-024-03189-z","journal":{"identity":"translational-psychiatry","isVorOnly":false,"title":"Translational Psychiatry"},"publishedOn":"2024-12-05 05:00:00","publishedOnDateReadable":"December 5th, 2024"},"versionCreatedAt":"2024-02-22 12:44:03","video":"","vorDoi":"10.1038/s41398-024-03189-z","vorDoiUrl":"https://doi.org/10.1038/s41398-024-03189-z","workflowStages":[]},"version":"v1","identity":"rs-3905152","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3905152","identity":"rs-3905152","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}