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. Author manuscript; available in PMC: 2026 Feb 26.
Published in final edited form as: Neuropharmacology. 2025 May 17;277:110522. doi: 10.1016/j.neuropharm.2025.110522

Repeated alcohol drinking in mice is associated with bidirectional alterations in corticostriatal coherence

Cherish E Ardinger a, Mitchell D Morningstar b, Christopher C Lapish a,c, David N Linsenbardt b,*
PMCID: PMC12934887  NIHMSID: NIHMS2142990  PMID: 40389153

Abstract

Decreased functional connectivity between the striatum and frontal cortex is observed in individuals with alcohol use disorder (AUD), and predicts the probability of relapse in abstinent individuals with AUD. To further our understanding of how repeated alcohol consumption impacts the corticostriatal circuit, extracellular electrophysiological recordings (local field potentials; LFPs) were gathered from the nucleus accumbens (NAc) and prefrontal cortex (PFC) of C57BL/6J mice voluntarily consuming alcohol or water using the 2-h access ‘drinking-in-the-dark’ (DID) procedure. Following a three-day acclimation period wherein only water access was provided during DID, mice were given 14 consecutive days of access to alcohol. Electrophysiology data was collected throughout the entirety of the final day of acclimation (i.e. water baseline) and the first and final days of alcohol access. We evaluated power and coherence at five frequency bands during bouts of drinking. Surprisingly, we only detected significant changes in power in the NAc; no differences were observed in power in the PFC. Increases in NAc power were detected at the Theta, Beta, and Gamma frequencies. At each of these frequencies, increases were identified on the final alcohol session compared to water baseline. Only at the Theta frequency were increases also detected compared to the first alcohol session. Furthermore, significant increases in Delta coherence were observed on the final alcohol session compared to water baseline, whereas significant decreases in Theta and Beta coherence were identified on both alcohol sessions compared to water baseline. These results provide additional support for alterations in the functional coupling of corticostriatal circuits associated with alcohol consumption and suggest the Theta frequency may be uniquely susceptible to these alterations.

1. Introduction

Alcohol can produce meaningful changes in electroencephalograph (EEG) and local field potential (LFP) power across a range of frequencies (Campanella et al., 2009; Fein and Allen, 2005). Neurophysiological frequency bands can be subdivided into at least five categories in rodents: delta, theta, beta, gamma, and fast gamma. Power in the theta band is increased in those with alcohol use disorder (AUD) compared to controls (Pollock et al., 1992; Mumtaz et al., 2017) as well as in those who report binge drinking (Lopez-Caneda et al., 2017; Affan et al., 2018). Critically, preclinical studies corroborate these findings showing theta involvement in excessive alcohol consumption (McCane et al., 2018; Henricks et al., 2019a, 2019b). Additionally, increases in beta power are prominently observed in those with AUD or those at high risk for AUD (Rangaswamy et al., 2002, 2004), and alterations in delta have also been reported in both sleep (Sharma et al., 2022) and waking conditions (Crane et al., 2023). Together this suggests that EEG and LFP measures can be of high value in the diagnosis and detection of AUD and be of clinical value to target with therapeutics. In the present paper, we specifically identified theta as a frequency band of interest and hypothesized that it would show increases in power and a decrease in coherence – a measure of communication between two brain regions.

To date, numerous neural circuits have been implicated in alcohol consumption (Koob and Volkow, 2010, 2016), and the corticostriatal circuit in particular has been found to undergo functional adaptations that mediate a shift from occasional to higher-risk drinking (Belin et al., 2009; Barker and Taylor, 2014). Specifically, the communication between corticostriatal brain regions has been shown to decrease following alcohol drinking (Courtney et al., 2013; Galandra et al., 2019). For example, corticostriatal functional connectivity is decreased in individuals diagnosed with alcohol use disorder (AUD), and is negatively correlated with time to relapse; i.e. less functional coupling was associated with a higher likelihood of a setback (Camchong et al., 2013). Additionally, recent evidence from a large multi-site collaborative study found that theta coherence, a measure of functional connectivity in the theta band, was a key differentiator of AUD subjects versus controls (Meyers et al., 2021). Combined with the finding that adolescent alcohol exposure is associated with lower cortical theta coherence than control (Ehlers et al., 2020), corticostriatal functional connectivity as measured by theta coherence may be a critical mediator of alcohol use.

Previous research has also shown that neural activity in the prefrontal cortex (PFC) is crucial to encoding reward value (Hernandez and Moorman, 2020; Amarante et al., 2017; Amarante and Laubach, 2020). In the present paper, we are defining PFC as all subregions that receive significant input from the mediodorsal thalamus. These include the infralimbic cortex, prelimbic cortex, anterior cingulate cortex, and supplementary motor area (M2) (Laubach et al., 2018). Theta coherence in the medial PFC was higher when rodents licked a high-value sucrose reward as compared to a low-value reward (Amarante et al., 2017; Amarante and Laubach, 2020). Increases in theta synchrony have been reported between the mPFC and nucleus accumbens (NAc) in alcohol-preferring (P) rats during alcohol drinking. However, less theta synchrony was observed in P rats over the total number of trials (McCane et al., 2018). These results suggest increases in synchrony in the corticostriatal circuit during decision making (i.e. choosing to take a drink); however, the cumulative effect of multiple exposures to alcohol may cause desynchronization over time.

The M2 subregion is included in some definitions of rodent mPFC (Laubach et al., 2018). It serves a critical role in learned, contextual motor behaviors (Kawai et al., 2015), and while it is not necessary for simple, motor actions (Siniscalchi et al., 2016), it is able to exert influence over motor and choice behaviors through its extensive connections with other brain regions (Yang and Kwan, 2021). One prominent connection is with the basal ganglia (Hintiryan et al., 2016; Yang and Kwan, 2021) whose function may be to bias or inhibit learned behaviors (Adam et al., 2022). Pathologically, it is observed that mouse models of compulsive behavior exhibit increased M2 → striatum connectivity (Corbit et al., 2019). To date, however, no studies have focused on M2’s role in alcohol consumption making the present study the first of its kind in this context.

Changes in corticostriatal theta power and coherence play a role in the development of AUD. However, there remains a need to systematically investigate the adaptations within corticostriatal theta neural activity, which are induced by multiple alcohol drinking experiences to better understand how theta oscillations are impacted by sustained alcohol drinking. To begin to answer this question, the current study utilized extracellular electrophysiological recordings collected from the NAc and PFC of mice voluntarily consuming ethanol (alcohol) or water. Drinking bouts were time-locked with electrophysiological recordings, which allowed us to precisely evaluate neural oscillations as a function of drinking behavior. The primary goal of the current study was to identify how corticostriatal theta coherence, a measure of connectivity between brain regions, is influenced by repeated binge drinking. Thus, we evaluated changes in neural activity over many consecutive days of repeated alcohol intake, hypothesizing that theta coherence would decrease following repeated alcohol exposure.

2. Methods

2.1. Subjects

Data were gathered from 14 adult C57BL/6J female (n = 7) and male (n = 7) mice. However, three mice (2 F, 1 M) had off-target placements. These mice were removed from all analyses. This left us with 6 male and 5 female mice for data analysis. Because the group sizes when broken down by sex were small/underpowered, and because no differences between sexes were detected at the behavioral level, all analyses reported here are collapsed on sex. All mice were bred in the AAALAC-approved School of Science vivarium at Indiana University-Purdue University Indianapolis (IUPUI) using breeders supplied directly from Jackson Laboratories. Mice were group-housed with 3–4 same-sex siblings after weaning on postnatal day (PND) 21 in standard Allentown mouse cages (11 × 7 x 5-inch). One week prior to surgery, mice were transferred from the breeding colony to alternate vivarium locations. At the time of this transfer, mice were single-housed in slightly larger (12.5 × 7.5 x 7.5-inch) cages with taller/flat cage tops to prevent implant interference/impacts and were allowed to acclimate for one week prior to surgery on PND 84 (±12 days). Testing began following a one-week recovery period. Mice had ad libitum access to water and rodent chow (LabDiet 5001) at all times except during alcohol DID testing sessions when water was replaced with alcohol. Food remained available during DID. All procedures were approved by the IUPUI School of Science Animal Care and Use Committee and conformed to the Guidelines for the Care and Use of Mammals in Neuroscience and Behavioral Research (National Research Council, 2003).

2.2. Surgery

Mice were implanted with custom-built electrodes made from 25 μm tungsten wire (California Fine Wires, Grover Beach, CA) inserted into a silica tubing matrix and then pinned to 16-channel Electrode Interface Boards (EIBs; Neuralynx, Bozeman, MT). Probes were configured such that 8 wires terminated in each of the two targeted brain regions – the M2 subregion of the PFC (A/P: 1.94, M/L: ±1.00, D/V: 1.50) and the core subregion of the NAc (A/P: 1.10, M/L: ±0.80, D/V: 4.25). Anesthesia was induced with isoflourane at 3 % in oxygen, and then maintained at 1–2 % in oxygen during surgery. A subcutaneous injection of Ketoprofen (5 mg/kg, in a volume of 0.1 ml/100g) was administered to reduce post-surgical pain. A sub-dermal injection of Bupivacaine (2.5 mg/mL, 0.05 mL) was administered directly over the incision site prior to exposing and cleaning the skull surface. Next, a unilateral craniotomy was made, electrodes were lowered and secured with dental acrylic, and two ground wires attached to the EIB and affixed with stainless steel screws were placed over the cerebellum. A final head cap was then completed using the same dental acrylic to ensure all components were covered and any burrs were removed. Mice were monitored closely for one-week following surgery, including daily checks for weight, feeding, and signs of distress. Cephazolin (30 mg/kg SC, 3 mg/mL) and/or a topical antibiotic (2 % bacitracin/polymixin) was administered as necessary during this recovery period. During the first 2–3 days of recovery, mice were given LabDiet 5015 mixed with water as a high protein ‘treat’ to encourage post-operative feeding. This treat was available in addition to their standard ad libitum diet, LabDiet 5001. After this one-week recovery period, all mice were at or above presurgery weight and had fully recovered. Local field potentials (LFPs) were then recorded during DID testing (see below).

2.3. Solutions

Alcohol was prepared by diluting 190 proof alcohol from Pharmco, Inc. (Brookfield, CT) to 20 % v/v in tap water. Water for water drinking days was obtained from the same tap as water that was used to dilute the alcohol. Drinking solution was prepared at the beginning of the experiment and stored in a sealed container. This prepared solution was used to fill ball-bearing sipper tubes during DID procedures described below.

2.4. Behavioral electrophysiology recording system

Home cages were located directly beneath overhead frictionless motorized rotary joints that allowed tethered subjects unrestricted movement during recording sessions. Rotary joints were connected to an OpenEphys recording system, which was in turn connected to a data acquisition computer. The acoustics of ball-bearing sipper tubes during drinking bouts were detected using piezo microphones, amplified via a professional audio soundboard, and relayed to an I/O board integrated with the OpenEphys acquisition systems tertiary analog inputs via an HDMI cable. This configuration allowed for precise alignment of bouts to neurophysiology data. The X and Y Cartesian coordinates of mice within the home cage were recorded with AnyMaze tracking software, were then converted to voltage using an AnyMaze digital-to-analog converter, and similarly time-locked with neurophysiology data as drinking bouts.

2.5. Behavioral electrophysiology recording procedures

Mice underwent a common home-cage binge drinking procedure (drinking-in-the-dark, DID; Rhodes et al., 2005) in which standard home cage water bottles are replaced with a single custom-built double ball-bearing sipper tube containing either 20 % alcohol or water 3 h into the dark cycle. The first three days mice were given 2 h of access to water in these tubes. The following 14 days mice were given access to alcohol.

On each testing day, 1 h into the dark cycle, mice were transferred from the colony room to the electrophysiology testing room and given 1.5 h to acclimate in the location where electrophysiology recordings were subsequently collected. Mice were then tethered to the rotary joint 30-min prior to DID session. During this period, home-cage water bottles were replaced with DID ball-bearing sippers, but they always contained water. On days 1–3, immediately following this 30-min period, separate but identical water-containing ball-bearing sippers were swapped with current water sippers, and behavior and electrophysiology were recorded throughout the subsequent 2 h (water) DID session. The first two days served to habituate the animals to the tether, and the final day was used as a baseline to compare to the alcohol sessions. Identical procedures were followed on days 4–17, except sippers containing alcohol were used during the 2 h DID sessions. Fluid volume consumed was recorded daily via the graduations on the custom-built sippers.

2.6. Immunohistochemistry

When testing was completed, mice were anesthetized with isoflurane as described in the surgery section above and a stimulus isolator was used to create lesions at the site of each of the wires via sending a 1 mA current through the EIB into each wire for 1 s. Twenty-four hours later mice were transcardially perfused and brains were removed to verify electrode placements. Mice were terminally anesthetized with urethane via intraperitoneal injection at a dose of 1.5 g/kg dissolved in sterile water in a volume of 1.0 mL/kg, and transcardially perfused with isotonic saline followed by 4 % paraformaldehyde (PFA). Brains were removed and placed in PFA for 4 days and then transferred to sucrose solution (30 %) for cryopreservation. Standard slicing and staining procedures using DAPI (Santa Cruz, Cat No: sc-3598) and GFAP (Fisher, Cat No: NBP105198) were followed to determine electrode placement. Placements can be seen in Fig. 1.

Fig. 1. Electrode placements.

Fig. 1.

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Placements for female (red) and male (blue) mice are shown in the PFC (A) and NAc (B). The mouse cartoon was modified from scidraw. io (Tyler and Kravitz, 2020; Paxinos and Franklin, 2007). Placements were determined using Paxinos and Franklin’s Mouse Brain in Stereotaxic Coordinates 3rd edition Atlas. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

2.7. Electrophysiology pre-Processing

Data were imported into MATLAB using open-source MATLAB functions (available on the OpenEphys GitHub page), down sampled to 1000Hz, and normalized via median subtraction to minimize potential impacts of motion artifacts and volume conduction. Prior to pre-processing, excessively noisy channels were identified as those with voltages greater than two standard deviations above the mean of the other channels within a given brain region and removed. Each of five frequency bands were evaluated as follows: Delta (1–4Hz), Theta (4–10Hz), Beta (10–30Hz), Gamma (30–80Hz), and Fast Gamma (80–200Hz).

2.8. Statistics

The primary focus of the current analyses was to assess neural activity associated with alcohol consumption (i.e. drinking bouts), and how this consumption-related activity changed following many alcohol drinking experiences. Bouts were defined identical to Darevsky et al. (2019): three or more licks that occur ≤1 s apart. Bouts were manually identified and curated by reviewing microphone data streams and high-resolution video recordings. LFP data ±4 s around the onset of each bout were extracted from each brain region separately, averaged, and assessed using the MATLAB ‘spectrogram’ function (500 ms window; 450 sample overlap; 1000 Hz sample rate). Coherence of the same bout-aligned LFP epochs was assessed using the MATLAB function ‘wcoherence’.

Data surrounding bouts on final water baseline session (D3), the first alcohol session (D4), and the 14th alcohol session (D17) were extracted for each of the 5 frequency bands (Buzsáki et al., 1983) and then evaluated using repeated measures ANOVAs with Greenhouse-Geisser corrections followed by Tukey’s post-hoc tests. Home cage locomotor activity and fluid consumption were analyzed identically.

3. Results

3.1. Fluid consumption and locomotion

The results of fluid consumption and home cage locomotion can be seen in Fig. 2. We evaluated behavioral results from the 3 days we also evaluated neurophysiology data. We used repeated-measures ANOVAs across all 3 sessions (D3, D4, and D17), for both fluid consumption and home cage locomotion. Unsurprisingly, there were significant differences in fluid consumption as a function of session [F (1.617, 16.17) = 5.787; p = 0.0168] that were driven by larger volumes of water consumed on D3 versus the first alcohol session on D4 (p’s < 0.05; Fig. 2A). No statistically significant differences in locomotion were found [F (1.924, 19.24) = 0.4545; p = 0.6340; Fig. 2B].

Fig. 2. Behavior.

Fig. 2.

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Average intake (A) and locomotor activity (B). Subjects consumed significantly less alcohol on the first alcohol-drinking day (EtOH1) compared to water. * indicates p < 0.05. Circles denote males and squares denote females.

3.2. Power and coherence

Average drinking-bout-associated power during baseline water consumption, the first alcohol consumption session, and the 14th alcohol consumption session can be seen in Fig. 3.

Fig. 3. Power and coherence during fluid consumption.

Fig. 3.

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No statistically significant differences in power were detected in the PFC (A–E). However, significant increases in power were detected in the NAC at the Theta (H), Beta (I), and Gamma (J) frequencies. At each of these frequencies, increases were identified on the final alcohol session (EtOH14) compared to water baseline. Only at the Theta frequency were increases also detected compared to the first alcohol session (EtOH1). Significant increases in Delta coherence were observed on the final alcohol session (EtOH14) compared to water baseline (L), whereas significant decreases in Theta (M) and Beta (N) coherence were identified on both alcohol sessions (EtOH1/14) compared to water baseline. * indicates p < 0.05; ** indicates p < 0.01; *** indicates p < 0.001. Circles denote males and squares denote females.

PFC:

There was no impact of repeated sessions of binge drinking on PFC power in the delta, theta, beta, gamma, and fast gamma frequency bands (p’s > 0.05; Fig. 3A–E).

NAc:

Repeated-measures one-way ANOVA for delta power was non-significant (p > 0.05; Fig. 3F). Repeated-measures one-way ANOVAs for theta power identified significant differences between conditions within the NAC [F (1.963, 19.63) = 6.137; p = 0.0088; Fig. 3H]. Post-hoc testing revealed significantly higher theta power in the NAC on the 14th day of alcohol consumption compared to both water baseline (p = 0.0362) and the first alcohol drinking day (p = 0.0212). Additionally, increased beta power was observed within the NAC [F (1.798, 17.98) = 3.795; p = 0.0461; Fig. 3I]. Post-hoc testing revealed significantly higher beta power in the NAC on the 14th day of alcohol consumption compared to water baseline only (p = 0.0486). Last, increased gamma power was observed in the NAC. Repeated-measures one-way ANOVAs for Gamma power identified significant differences [F (1.501, 15.01) = 4.508; p = 0.0379; Fig. 3J], which post-hoc testing revealed was attributable to significantly higher gamma power in the NAC on the 14th day of alcohol consumption compared to water baseline only (p = 0.0486). No significant differences were observed in fast gamma (Fig. 3K).

PFC-NAC Coherence:

Repeated-measures one-way ANOVA for delta coherence (Fig. 3L) found significant differences between conditions [F (1.342, 13.42) = 6.422; p = 0.0180], which post-hoc testing revealed was driven by differences between the 14th day of alcohol consumption and water baseline (p = 0.0014). Repeated-measures one-way ANOVA for corticostriatal theta coherence (Fig. 3M) found significant differences between conditions [F (1.760, 17.60) = 11.81; p = 0.0008], which post-hoc testing revealed was driven by differences between water baseline and the first (p = 0.0414) and 14th (p = 0.0049) alcohol conditions. Repeated-measures one-way ANOVA for corticostriatal beta coherence (Fig. 3N) found significant differences between conditions [F (1.625, 16.25) = 11.08; p = 0.0015], which post-hoc testing revealed was driven by differences between water baseline and the first (p = 0.0494) and 14th (p = 0.0068) alcohol conditions. No effects were observed on corticostriatal gamma coherence (Fig. 3O) or fast gamma coherence (Fig. 3P).

4. Discussion

The present study was designed to assess the power and coherence of theta in both the PFC and NAc using awake-behaving electrophysiology following repeated alcohol drinking experiences. As hypothesized, we found a significant increase in theta power in the NAc but not PFC. However, we also found significant increases in beta, and gamma power in the NAc but not PFC, as well as significant and bidirectional differences in corticostriatal communication – as measured by coherence. Specifically, we observed increases in delta coherence, but decreases in theta and beta coherence.

General increases in power across multiple frequency bands following extensive alcohol experience have been reported in the literature (Fein and Allen, 2005). This likely reflects a general transition of the brain towards hyperactivity. Additionally, given we evaluated neural function surrounding drinking bouts, increases in activity may reflect alcohol cue hyper-reactivity, which is observed widely in individuals with AUDs (Zeng et al., 2021). Cue-related hyperactivity is observed across the striatum and dlPFC in clinical populations; however, we only observed increases in the power of NAc. Had our PFC electrodes been placed into regions more homologous with human dlPFC function, such as the ACC or dmPFC.

The results of our coherence analyses were mixed. Delta coherence between the PFC and NAc increased over DID sessions, whereas theta and beta coherence decreased. A potential explanation for the decrease in theta and beta coherence is that repeated alcohol drinking may have resulted in a decrease in goal-directed resources needed for drinking-related decisions/movements. For example, a shift in computational resources has been reported following repeated alcohol use from the PFC to NAc as drinking decisions becomes more automated (Barnett et al., 2023; Yamamoto et al., 2015). Importantly, decreases in theta coherence we observed are consistent with observations in humans with alcohol consumption history (see introduction). This supportsthe translatability of our findings and suggests that reversal of ethanol-induced functional plasticity may be an effective therapeutic strategy for AUD. Deltacoherence has not been as explicitly studied as theta or beta in the context of drug seeking. However, its increase may indeed be related to increased drug seeking or craving (Ngbokoli et al., 2023).

The rodent PFC and NAc are heterogenous structures that each contain subdivisions with differences in anatomy (e.g. afferent/effect projections) and biochemistry (e.g. neurotransmitters, receptors). In the current study, PFC electrodes were primarily in the M2 region, which send projections to the NAc (Li et al., 2018). To our knowledge, this is the first assessment of this specific projection in a rodent model of voluntary alcohol consumption. The M2 subregion exhibits extensive connectivity with the striatum, and in models of compulsive behavior this connectivity is enhanced (Corbit et al., 2019; Hintiryan et al., 2016; Yang and Kwan, 2021). Furthermore, its role in contextual, learned motor behaviors suggests it has an extensive role in higher order executive functions (Kawai et al., 2015). Together, this suggests that reducing M2 → striatal connectivity may be a promising means of ameliorating compulsive alcohol drinking. However, this prefrontal subregion is understudied in the context of addiction, and further studies are needed to better contextualize the present findings. Nonetheless, projections from more dorsomedial PFC subregions (prelimbic and anterior cingulate cortex) to the NAc core have been shown to be of particular importance in drug-seeking models (Stefanik et al., 2013; McGlinchey et al., 2016), including for alcohol as evidenced by reductions in cue-evoked oscillations (McCane et al., 2018; Linsenbardt et al., 2019; Linsenbardt and Lapish, 2015; Timme et al., 2022).

An important next step in this line of research will be to determine the potential causality of our observations, for example, by evaluating the impact of experimental manipulations of theta coherence on alcohol consumption. To this end, a recent study in individuals with AUDs demonstrated that transcranial magnetic theta burst stimulation in the medial PFC led to a 3-fold increase in the probability of maintaining sobriety than those who received sham treatment (McCalley et al., 2023). Thus, we are currently well positioned to use the model described here to validate these types of promising clinical observations as well as to identify novel intervention strategies using neural populations-specific manipulations.

Despite all the interesting observations just discussed, there are several important caveats worth discussing. First, an important limitation of the current study is the lack of a sucrose/saccharin control group for novelty. A relationship between novelty seeking and AUD is well-described (Flagel et al., 2014; Manzo et al., 2014; Wingo et al., 2016). Studies have shown that licking sucrose tends to produce increases in both theta power (Wingerden et al., 2010) and theta coherence (Amarante et al., 2017; Amarante and Laubach, 2020, Horst and Laubach, 2013), suggesting that our day 1 coherence results may not be specific to alcohol. Future work along the lines of the current study should include a sucrose/saccharin control to assess the impact of novelty on theta oscillations. Second, we were surprised not to observe differences in alcohol intake between sexes, given female mice typically consume more EtOH than males. However, we believe this may be due to reactivity differences to the minor restraint stress necessary to connect our headstages (Becker et al., 2011). An additional limitation is the usage of coherence values as a proxy of functional connectivity. While LFPs allow for spatially constrained measurements of emergent electrical activity, specific bands of those LFPs may emerge from other brain regions (Carmichael et al., 2017). Future studies of this circuit will include single unit spiking activity in order to ameliorate this potential concern (Morningstar et al., 2020).

In summary, the current findings provide further support for decreased corticostriatal theta/beta synchrony and increased corticostriatal theta/beta power as biomarkers of alcohol drinking and/or AUD. Furthermore, these data provide novel evidence that alcohol-drinking experience may also be associated with increases in delta power/synchrony. Combined these data provide additional support for corticostriatal circuits as important modulators of alcohol drinking experience that may serve as targets for treating AUDs.

Acknowledgments

This work was supported in part by grant #s: AA025120, the New Mexico Alcohol Research Center P50-AA022534, AA007462, AA023786, and the Indiana Alcohol Research Center P60-AA007611.

Footnotes

CRediT authorship contribution statement

Cherish E. Ardinger: Writing – review & editing, Writing – original draft, Visualization, Validation, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Mitchell D. Morningstar: Writing – review & editing, Visualization, Validation, Investigation, Formal analysis, Data curation. Christopher C. Lapish: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis. David N. Linsenbardt: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.

Declaration of competing interest

None.

Data availability

Data will be made available on request.

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Data Availability Statement

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