EFFECTS OF AND ACAMPROSATE, AN ALCOHOL USE DISORDER TREATMENT, ON NONHUMAN PRIMATE BEHAVIOR AND MEMORY

BY

CHRISTOPHER A. JOHNSON

A Thesis Submitted to the Graduate Faculty of

WAKE FOREST UNIVERSITY GRADUATE SCHOOL OF ARTS AND SCIENCES

in Partial Fulfillment of the Requirements

for the Degree of

MASTER OF SCIENCE

Neuroscience

May 2019

Winston-Salem, North Carolina

Approved By:

Robert E. Hampson, PhD, Advisor

Joost X. Maier, PhD, Chair

James B. Daunais, PhD

Michael A. Nader, PhD

Terrence R. Stanford, PhD

DEDICATION

Dedicated to my grandparents for supporting my academic journey both spiritually and

financially since my undergraduate career.

ACKNOWLEDGEMENTS

I would like to thank the members of my lab, especially Dr. Rob Hampson, Frances

Miller and Joe Noto for teaching and supporting me during my time in the lab.

TABLE OF CONTENTS

LIST OF ILLUSTRATIONS AND TABLES ...... ii

LIST OF ABBREVIATIONS ...... iii

CHAPTER ONE –...... 1

Abstract...... 2

Introduction...... 3

Conclusion...... 28

CHAPTER TWO –...... 29

Abstract...... 30

Introduction...... 31

Methods...... 32

Results...... 36

Discussion...... 44

i

LIST OF ILLUSTRATIONS AND TABLES

CHAPTER ONE –......

Figure 1...... 9

Figure 2...... 11

Figure 3...... 12

Figure 4...... 15

Figure 5...... 18

Figure 6...... 23

CHAPTER TWO –......

Figure 1...... 37

Figure 2...... 38

Figure 3...... 39

Figure 4...... 41

Figure 5...... 42

Figure 6...... 43

ii

LIST OF ABBREVIATIONS

Acamprosate with alcohol: AA

Attention deficit hyperactivity disorder: ADHD

Alcohol use disorder: AUD

Body mass index: BMI

Blood-oxygen-level dependent imaging: BOLD

Delayed match-to-sample: DMTS

Electroencephalography: EEG

Functional magnetic resonance imaging: fMRI

Focus ring: FR

Gamma-aminobutyric acid: GABA

Gamma-glutamyltransferase: GGT

Intramuscular: IM

Local field potential: LFP

Lateral intraparietal area: LIP

Long-term memory: LTM

Match response: MR

Medial temporal lobe: MTL

Metabotropic (s): mGluR(s)

Non-human primate(s): NHP(s)

N-methyl-D-aspartate: NMDA

Phase-amplitude coupling: PAC

Pre-frontal cortex: PFC

Standard error of the mean: SEM

Sample response: SR

Short-term memory: STM iii

CHAPTER 1: LITERATURE REVIEW

1

ABSTRACT

Alcohol use disorder (AUD) is a major issue facing the population both domestically and abroad. The repeated use of alcohol impairs various behavioral and cognitive functions such as attention and memory and disrupts normal communications between brain regions. These disruptions in communication can occur after single administrations of alcohol and can become permanent through repeated abuse. This disruption in communication negatively affects regions crucial to brain regions underlying working memory and attention, including structures such as the prefrontal cortex, posterior parietal cortex and others. Many are used in the treatment of AUD, with acamprosate being one of the most commonly prescribed drugs. The specific mechanism of acamprosate has not been identified, but it is thought to have an indirect effect on mGluR, NMDA, and possibly GABA A receptors via calcium. This effect is thought to stabilize the hyper- state seen in withdrawal, while possibly reducing the response to alcohol. Acamprosate has been confirmed to be efficacious despite initial disputes of its efficacy through large composite studies. However, the possible behavioral and cognitive effects of acamprosate have not been studied in detail, necessitating further studies that investigate these possible effects.

2

INTRODUCTION

The potential for alcohol abuse will always be extremely high due to it being one of the few drugs of abuse that is sold legally without a prescription as well as its reinforcing and rewarding properties. As of 2015, alcohol is the most prevalent substance of dependence in the world, with over 63.5 million estimated cases 1. The burden caused by alcohol is felt in numerous ways by not only the primary abuser, but others around them as well. Alcohol is one of the three leading factors for global disease burden and 3.8% of all global deaths can be attributed to alcohol in the year 2004, with that number only rising in subsequent years due to increased drinking in females 2,3 .

However, the statistics related to alcohol abuse are far worse due to alcohol’s role in many psychiatric and neuropsychiatric disorders. For instance, the presence of either

AUD or depression in a patient doubles the risk of having the other 4. Other studies have shown similar risk factors that can increase the risk of having AUD such as socioeconomic status, psychiatric and substance abuse disorders, family history, and more 5,6 . Those with bipolar disorder have elevated odds to develop AUD with 2 out of every 5 male patients and 1 out of every 5 female patients with bipolar disorder developing AUD 7. Patients with anxiety disorders and personality disorders also have a high AUD comorbidity rate 8. Given that any one of these disorders greatly affects those around them both physically and psychiatrically, it is clear that AUD has a much larger effect on the world’s population than what is typically estimated.

A clear understanding of each used to treat AUD is needed in order to provide effective treatment to each individual patient. In this study, we sought to investigate the effects of acamprosate, one of the most commonly prescribed drugs in the

3 treatment of AUD. Acamprosate’s efficacy has been proven after many large scale studies, but its possible effects on behavior and memory have not been thoroughly investigated. A non-human primate (NHP) model was used in order to be able to determine the dose-dependent relationship alcohol and acamprosate while simultaneously investigating each dose’s effects on behavior and memory using a complex behavioral assay: the delayed match to sample task (DMTS). The results of this study will provide the basis for future studies to investigate acamprosate’s effects on behavior and memory along with its potential use in treatment of other disorders such as autism, anxiety, and sleep disorders.

DELAYED MATCH-TO-SAMPLE TASK

A robust and well-known method that can be used to assess both attention and memory simultaneously is the delayed match-to-sample task (DMTS). Initially described by B.F. Skinner for use in pigeons 9, the task has evolved and been used in differing ways leading to the present. It has seen use in rodents10,11,12, non-human primates

(NHPs) 13,14,15,16, and humans 17,18,19 . It has been used in the study of a diverse number of diseases, disorders, and drugs including amnesia 20 , ADHD 21 , 22 , cannabis 23,

AUD, and alcohol 24.

The nature of the tasks requires the attentional network to focus on and select the start ring, while the working memory (WM) network is needed to remember images presented. Furthermore, functional magnetic resonance imaging (fMRI) has revealed the

DMTS task to activate regions in the established WM and attentional networks, such as the superior frontal gyrus, prefrontal cortex (PFC) and posterior parietal cortex 25.

Differences in activation were seen in verbal and non-verbal tasks, with larger activation

4 in the left precuneus and right middle frontal gyrus for non-verbal tasks as compared to verbal 25. Knowing the DMTS tasks activates regions in both networks of interest (WM and attentional), the DMTS task could be used as a tool to assess both alcohol and acamprosate’s possible effects on memory and behavior.

NON-HUMAN PRIMATE MODEL

Use of an animal model that provides the greatest translation to humans is needed when assessing disorders such as AUD, which is a social, mental, and behavioral disorder.

In particular, an AUD NHP model may be an optimal choice for this study due to the similarities in behavior and neuroanatomy as compared to other animals 26. A non-human primate model would also allow for experimental manipulation and perhaps improve translatability of the results as compared to a rodent model 27. An extensive amount of studies have used NHPs to study alcohol, which have allowed for universal definitions of dosage (0.25 g/kg per day is the equivalent to one alcoholic drink) and drinking habits

(<2 g/kg per day is considered light drinking, while >3 g/kg per day is considered heavy drinking) 28 . These universal standards are beneficial to this study in two ways: it allows for easy translation to human doses and allows for easier comparison to the multitude of other NHP studies.

ALCOHOL’S EFFECTS ON BEHAVIOR AND MEMORY

Before investigating acamprosate’s possible effects on behavior and memory, it is necessary to assess the effects alcohol has on these measurements. Currently, healthy subjects have no reason to use acamprosate, and patients that are currently approved to use acamprosate will most likely have cognitive functioning similar to those with previous alcohol exposure. A major effect that alcohol has been shown to have is the

5 impairment of response inhibition 29 . In other words, when a movement (decision) has already been made, it is much harder for subjects to stop the intended movement.

Specifically, non-saccadic movements seem to be more difficult to inhibit while saccadic movements may not be as affected by alcohol 30 . Increases in reaction time seen in lower doses of alcohol may be attributed to this phenomena 31 . A decrease in reaction time may only occur during descending blood alcohol concentrations however, which could possibly carry over to the following day during a hangover 32 . Similarly, in a study using rhesus macaques, it was shown that discontinued alcohol use after chronic exposure increased the probability of slower reaction times 33 .

Memory is also affected by alcohol, with some forms of memory being more resilient to alcohol’s effects. Episodic declarative memories are seemingly unimpaired at moderate to lower levels of intoxication 34 . Working memory may also be resilient to alcohol’s effects at lower levels of task difficulty 35 , but that resilience may disappear when tasks with a higher WM load appear 36 . This may be due to alcohol impairing the recruitment of resources needed for tasks with higher difficulty 37 . Another factor that may cause declines in performance for memory tasks is attention to the task. Those who are hungover the day after drinking have been shown to have significantly impaired sustained attention 38,39 . Lack of attention could lead to fewer trials completed in memory tasks, and also worse performance on the task itself if the information that needs to be remembered is not properly attended to.

WORKING MEMORY NEURAL CORRELATES

To fully understand alcohol’s effects on the brain, the circuitry involved must be understood. As previously mentioned, alcohol may affect WM capabilities; WM is the

6 ability to manipulate stored information and is essential in higher-level cognitive functioning. The neural correlates of WM have been studied extensively for this reason.

Initial research performed in NHPs suggested an important role for the pre-frontal cortex

(PFC) 40,41 . Specifically, significant, persistent PFC activity during delay periods of WM tests has been shown, indicating that information is being held until a response is given 42 .

Furthermore, these PFC neurons with persistent activity through the delay period were shown to be directional, meaning they respond heavily to cues from a certain direction and initiate an inhibitory period when cues come from a different direction 43 . Activation of only certain neurons pertaining to certain directions is most likely a way that the brain stores the location of a target stimulus. These neurons also allow for rapid short-term memory storage and turnover; neurons that were activated for a certain direction can be inhibited once another target stimulus appears, allowing the focus to always be on the current target stimulus and not the previous. During the DMTS task used in this study, these neurons are most likely crucial for remembering the target stimulus.

The cingulate gyrus may also help to discriminate between stimuli during WM tasks. In tasks assessing WM such as word-nonword discrimination tasks, the posterior cingulate has been shown to be active during nonword trials 44 . Anterior cingulate activity has also consistently been shown in WM tasks, with activity intensity correlating with better performance and larger WM capacities 45,46 . These studies seem to implicate that the anterior cingulate’s role is one of storing and manipulating information, while the posterior cingulate may be specific to non-word discrimination tasks.

Many NHP studies investigating WM have shown elevated responses in the parietal cortex during tasks that require storage of visual or spatial information 47,48 . A

7 similar study using blood oxygenation level dependent (BOLD) functional MRI imaging revealed the PFC and parietal cortex had the highest level of activity during delay periods of a memory task 49 . When either parietal or prefrontal cortices are inactivated in NHPs, activity of the other between the delay drops by 40% 50 . This suggests that the interactions between the PFC and parietal cortex are essential for the storing and manipulation of information 51 . Overall, these studies suggest that during the DMTS task previously mentioned areas such as the PFC, cingulate gyrus, and the parietal cortex are active during the task.

MULTICOMPONENT WORKING MEMORY MODEL

Previous studies investigating individual processes and singular brain structures involving WM led to more comprehensive theories that acknowledged multiple regions working in tandem. Perhaps the most commonly accepted model of WM was proposed by Baddeley and Hitch in 1974 52 . This model, dubbed the multicomponent working memory model, consists of roughly four components that work in tandem: a central executive, a visuospatial sketchpad, phonological loop, and an episodic buffer 53 . Both the visuospatial sketchpad (visual-spatial memories in the occipital lobe) and phonological loop (verbal memories residing in Broca and Wernicke’s areas) are sensory inputs in the model. The most recent addition to the model, the episodic buffer, is thought to integrate/modulate sensory information from the visuospatial and phonological components. The central executive residing in the prefrontal and anterior cingulate cortices oversees and regulates the processing of information coming from the other components.

8

Figure 1: A depiction of the multicomponent working memory model 54 .

Both long and short term memory are also thought to be involved in the WM process. Initially thought to be a subtype of short term memory (STM), WM is now thought to be more like long term memory (LTM)55 . Typically, STM is defined as memory that is stored for 1-30 seconds, with LTM being information stored for longer than 30 seconds 56 . The rough definition of WM is the storage and manipulation of information used for higher cognitive processing, which by nature implies that information from long term memory can be accessed for WM functions. The PFC, posterior parietal cortex, hippocampus, medial temporal lobe (MTL), and other regions have all been revealed to be active during tasks involving STM and LTM, solidifying the close relationship between these different types of memory 57,58,59,60 .

9

NEURAL NETWORK COMMUNICATIONS

Communication between these regions (prefrontal, parietal, temporal, and occipital) involves a multitude of smaller connections that are inherently designed to communicate efficiently. Understanding which regions within the proposed WM network communicate efficiently with one another allows for further understanding of behavioral impairments seen when these structures are altered via drugs such as acamprosate and alcohol. A common method used to analyze these connections is graph theory, a model used to explain structural and functional properties of systems that can be applied to neural networks. Individual brain regions are dubbed nodes, with the synapses and axonal projections of each region known as edges 61 . Using this sort of analysis, it has been theorized that regions that are spatially close have a higher probability of being connected, while those that are farther away from each other have a lower probability of being connected 62,63,64 . In particular, the prefrontal cortex in macaques seems to have a staggering amount of interconnectivity, with local areas connecting to 94% of the regions in close spatial proximity 64,65 . Distant regions tend to have less connectivity to each other as compared to local regions; this seems to be a purposeful tactic used by the brain to increase communication efficiency. In other words, the less clustered and numerous the connections between long-distance nodes, the greater the communication effiency 61 .

Using fMRI to study regional connectivity during a memory recall task, Geib et al. (2017) mapped memory circuitry using graph theory concepts. Their proposed circuitry seems to confirm high communication efficiency between regions proposed in the multicomponent working memory model; there is a high amount of local node connectivity, and longer but less frequent edges between non-local nodes.

10

Figure 2: Diagram of a hypothesized network for memory maintenance and retrieval.

Five different functional communities (i.e., modules/nodes) were identified from the modularity analysis: occipital/temporal (yellow), fronto-parietal (red), parietal (green), medial temporal (light blue), and subcortical (dark blue). All nodes in the assembly

(depicted as large spheres in Figure 2) showed significantly greater connectivity strength with the left hippocampus (light blue sphere) for remembered as compared to forgotten items (significant connections are depicted as dark lines) 66 .

THE ATTENTIONAL NETWORK AND ALCOHOL

Besides WM, alcohol also impairs attention and by extension the regions responsible for attention; acamprosate also has the potential to affect these regions. The accepted network for visual attention is very similar to the multicomponent working memory model as they both involve many of the same regions, including frontal and parietal areas. The parietal cortex specifically seems to be of great importance for visual attention and is thought to integrate signals from frontal and occipital areas 67 . Integration allows for decisions to be made on resource allocation by processing bottom-up signals from the visual cortex, and top-down signals from the prefrontal areas 67,68,69,70 . When

11 parietal cortex neurons are disrupted via transcranial magnetic stimulation, a drop in performance on an attention task in subjects is seen 70 . In other words, there may be a causal role between parietal neuronal activity and attentional deficits/improvements.

Specific sub-regions may have more influential roles than others within the parietal cortex. Lateral intraparietal area (LIP) neurons have been shown to have larger responses when an image is salient as opposed to stimuli considered to be less salient 68 . The LIP

(along with the superior parietal lobule, frontal eye field, and supplementary eye field) have also been shown to have an increased BOLD response when anticipating a visual stimulus 69 .

Figure 3: Diagram of the hypothesized attentional network. Reciprocal connections between visual, parietal, and prefrontal areas are shown with the parietal cortex integrating signals from both V1 and prefrontal areas. Visual information is sent to the inferior temporal cortex presumably for object recognition purposes 67 . (TEO=area TEO of the inferior temporal cortex).

12

If artificially deactivating parietal region neurons by transcranial magnetic stimulation causes attentional deficits, it is possible that drugs that affect these regions could produce similar deficits. Alcohol use has been shown to specifically lower the intra-network structural connectivity in the intraparietal sulcus and dorsomedial prefrontal cortex, both key components in attentional (and WM) circuits 71 . This would presumably produce an effect similar to deactivating those regions, possibly explaining alcohol’s obstructive effects on attention.

THETA/GAMMA OSCILLATIONS

As previously stated, alcohol impairs cognitive function, including memory and attention. Understanding the mechanisms behind memory encoding and formation is critical to being able to treat the deficits caused by alcohol. Currently, formation and encoding of memories are thought to occur thanks to communication between regions in the WM and attentional circuits in the form of synaptic oscillations. Synaptic oscillations can roughly be defined as rhythmic synaptic activity that occurs at specific frequencies.

Theta (4-8 Hz) and gamma oscillations (30-120 Hz) specifically have been implied in the support and maintenance of memory. Initial interest in gamma oscillations was sparked due to an initial study by Howard et al. (2003) who showed that gamma oscillations were seen to increase linearly with memory load 72 . Structures found to exhibit gamma oscillations during memory encoding include Broca’s area, prefrontal cortex, and the hippocampus among others 73 . Two substructures of the MTL, the rhinal cortex and hippocampus, have been shown to exhibit phase-locked gamma activity during memory tasks that subsequently desynchronizes when the task is complete 74,75 . This suggests that gamma band activity is used to “couple” the two structures during memory encoding, and

13 decouple them once the encoding is complete 74 . This theory of coupling and decoupling extends beyond the MTL and is a vital part of memory formation.

Theta oscillations are also thought to help facilitate communication between regions along with being a key component in the spatial aspect of spatial memory 76 .

During spatial WM tasks, theta oscillations have been shown to modulate firing rate changes in the medial PFC and hippocampus 77,78 . Furthermore, these oscillations are phase-locked between the two regions, and when this synchronous activity is interrupted, performance on memory tasks worsens 79 . Conversely, an increase in theta activity during spatial memory tasks seems to enhance performance 78 . Similar phase-locked theta band activity has been observed in the extrastriate visual cortex during WM tasks 80 . This indicates that theta band activity is most likely a cortical mechanism used to facilitate communication between structures during memory formation. Phase-locked theta activity in the cortex may also be dependent upon the nature of the task, with regions specific to the task being in-sync while other regions unspecific to the task being excluded 80 . For instance, during a visually themed WM task such as the DMTS task, one might expect the prefrontal cortex and occipital lobe to be phase locked, with other irrelevant structures excluded.

THETA/GAMMA COUPLING

While theta and gamma oscillations may have different functions in memory facilitation, theta-gamma coupling became an area of intense study due to many studies observing co-occurrence of theta and gamma frequencies during memory tasks.

Successful theta-gamma coupling is now known to be crucial to encoding and maintaining memories. Hippocampal studies have shown that theta phase oscillations

14 modulate gamma activity81,82,83,84 . Multiple gamma subcycles occur within a theta cycle during coupling 81,82,83,84 , indicating a method of how multiple pieces of information are maintained and transmitted in an ordered fashion.

Figure 4: Example of different gamma subcycles during a theta cycle in rats. Filtered gamma traces (30-50 Hz, blue, or 50-90 Hz, red) and theta filtered local field potential

(LFP) (4-12 Hz, black lines). Traces are aligned to the peak of the theta LFP 81 .

(RUN=Recordings carried out while the animal ran on a linear maze, REM= Recordings during sleep in the animal's home cage that contained at least one REM episode).

Higher phase-amplitude coupling (PAC) between theta and gamma oscillations typically leads to higher success in various memory tasks, including WM tasks 85,86,87,88,89 .

However, it was shown that attention deficit hyperactivity disorder (ADHD) patients with impaired attentional ability exhibited significantly greater than normal PAC 90 . This may suggest that there is a limit to the beneficial effects of PAC, and that once a certain threshold of PAC has been reached, it may be a bane to attentional abilities akin to

15 hyperactivity. Typically, PAC has been observed in areas such as the hippocampus, entorhinal cortex, PFC, and parietal lobe during memory tasks 85,87,91,92 . Depending on the type of task being used to assess memory, other lobes may also exhibit theta-gamma PAC.

Verbal memory tasks have been shown to cause theta-gamma PAC in the temporal lobe 93 , while face recognition tasks show theta-gamma PAC in the occipital lobe 94 . PAC of regions only relevant to a specific task is most likely key for excluding irrelevant information. Increased PAC may be limited to tasks with higher difficulty; Chaieb et al.

(2015) demonstrated that PAC levels increased only when more than one item needed to be remembered, not just one 95 .

Interestingly, although increased PAC between theta and gamma correlate with better performance, an artificial increase in gamma oscillations as compared to normal endogenous levels did not seem to affect WM performance 96 . This would suggest that it is not merely the amplitude of theta or gamma oscillations that facilitates attentional ability and memory formation, but the successful phase locking of the two. A study by

Fell et. al (2003) showed that increased theta-gamma PAC independent of the power of either was a predictor of successful memory formation 75 . Alekseichuk et al. (2016) found that not only does theta-gamma PAC need to occur for memory formation, but the peaks of the cycles need to be in-sync as well 91 . Specifically, induced high frequency gamma cycles occurring at the peaks of theta cycles enhanced memory performance, while gamma cycles occurring at theta troughs did not show a difference in performance 91 .

Those with ADHD also seem to exhibit desynchronized PAC, leading to impaired attentional abilities 97 . These results suggest that this type of peak synchronization during

16

PAC should happen naturally endogenously but are subject to disruption by various drugs and disorders.

While synchronized PAC helps to successfully form memories, unsynchronized

PAC may lead to impaired memory performance. Schizophrenic patients that perform

WM tasks with simultaneous electroencephalography (EEG) show worse performance on

WM tasks compared to healthy controls 98 . EEG results of the study revealed that theta- gamma PAC was impaired in the schizophrenic patients while the control subjects had a positive relationship between accuracy and theta-gamma PAC 98 . Alzheimer’s patients have also been shown to have lower amounts of theta-gamma PAC correlating with worse WM performance 99 . Zhang et al. (2017) has shown that disruption of theta-gamma

PAC via electromagnetic fields impairs performance on WM tasks in mice 100 . Disruption of theta-gamma PAC in humans via transcranial alternating current stimulation specifically designed to cause gamma bursts to couple to theta troughs significantly impaired memory recall 93 . Acamprosate and other drugs have the potential to alter PAC in a similar way.

17

Figure 5: Illustration of summarized results of transcranial alternating current stimulation experiments on theta-gamma PAC. High frequency gamma cycles that occurred during theta wave peaks enhanced PAC and memory performance. High frequency gamma cycles that occurred during theta wave troughs did not enhance memory 91 .

ALCOHOL AND MEDIATION OF PHASE-AMPLITUDE COUPLING

These oscillations in the brain that have proved to be so crucial to memory formation may explain alcohol’s impairment of behavioral functions. Research is scarce on the relation between alcohol and PAC, and more studies are needed to investigate this topic. Resting connectivity in those with AUD has been shown to be altered; specifically, an increase in subject’s theta to gamma ratio was observed 101 . Increases in the theta/gamma ratio may be associated with memory impairment, as shown in subjects with mild cognitive impairment who also had higher theta/gamma ratios 102 . Resting state theta-gamma PAC has been shown to significantly decrease in healthy patients when administered alcohol 103,104 . These results are particularly alarming as they imply that it

18 only takes single administrations of alcohol to impair neural connectivity and function.

Fortunately, it seems to take repeated, excessive alcohol consumption to permanently change resting state connectivity 101 . This may allow drugs such as acamprosate to acutely restore resting state activity back to a normal state.

ACAMPROSATE OVERVIEW

In order to help those with AUD, various pharmaceutical solutions along with behavioral therapies have been vigorously investigated. Multiple approaches to treating

AUD are needed in order to both halt the drinking and to prevent further drinking and craving. Ideally, a drug used to significantly reduce drinking would also rescue effects caused by alcohol, such as tremors and impaired memory and behavior. Acamprosate is one such drug that has potential to restore patient’s behavior and memory, and was developed in Europe in 1989 and approved in the US in 2004 to use to promote abstinence in AUD patients. Among the many drugs prescribed to individuals with AUD, acamprosate is commonly the most highly prescribed 105 . Acamprosate (N-acetyl homotaurine; 3-(acetylamino)-1-propanesulfonic acid calcium salt) is known by its brand name, “Campral” in the United States. A typical dose of acamprosate in the US is 666 mg three times a day, administered orally in the form of two 333 mg tablets 106 . The recommended treatment period is 1 year, with the patient recommended to continue administration even if relapses occur 106 . Treatment regimens vary between countries; for instance, the period of administration recommended in Europe is only 12 months, while

Japan’s recommended period of administration is 24 months 106 . Acamprosate is relatively well tolerated, with its most common side effects related to gastrointestinal irritation (diarrhea, flatulence) 107 . More adverse side effects involving extrapyramidal

19 symptoms have been reported in an elderly patient possibly due to decreased dopamine in the ventral tegmental area 108 . The use of acamprosate is contraindicated in patients with renal deficiency due to acamprosate primarily being excreted via the kidneys 109 .

Acamprosate has also been studied in the treatment of other diseases such as autism 110 and fragile X syndrome 111,112,113 with positive outcomes seen. Studies on acamprosate’s effects on depression also have seen promising results in rodent models 114,115 .

Acamprosate may also have neuroprotective properties. Concurrent administration of acamprosate and alcohol increased the amount of stage III NREM sleep (restful sleep) and decreased the amount of stage 1A NREM sleep (drowsiness) that is normally seen after consuming alcohol 116 . In a mouse model of stroke, acamprosate administration after stroke induction reduced edema, reduced infarct size, and demonstrated neuroprotective properties by preserving neuronal density when compared with controls 117 . Due to acamprosate’s apparent potential in treatment of multiple crippling disorders, insight into its effects on both behavior and memory are imperative. In the present, acamprosate is only approved to treat those with AUD, but if proven to be beneficial to measures such as

WM and attention it may be used to treat a multitude of disorders in the future.

ACAMPROSATE’S EFFICACY ON DRINKING ABSTINENCE

Initial studies after acamprosate’s approval in Europe and the US produced varying results. The first US study evaluating acamprosate showed significantly higher days of abstinence when compared to placebo groups in those with AUD 118. Other studies such as the COMBINE study in the US and the PREDICT study in Germany were both double-blind, placebo controlled randomized trials used to assess the efficacy of various drugs used to treat AUD. Both studies showed results that conflicted with the

20 previously mentioned study, with acamprosate producing a reduction in drinking but being no more significant than the placebo groups in each trial 119,120 . When results were compared by country, the country of origin did not appear to explain the variance between the initial study and the COMBINE/PREDICT studies 121 . A large meta-analysis that followed examined over 6915 patients over 24 double-blind randomized control trials, which revealed acamprosate significantly reduced the risk of drinking and increased abstinence duration compared to placebo trials 122. Questions still linger as to whether acamprosate is reliable enough to use in the treatment of AUD, but the majority of studies seem to now advocate its use.

Identifying the conditions in which acamprosate is most effective has also been the focus of many studies. Commonly, acamprosate is thought to be most effective when patients have the clear goal of abstinence in mind 118,123,124,125. When compared to other pharmacological treatments, acamprosate does well in promoting abstinence, but falters in preventing subjects from further drinking once an initial drink has been consumed 123,125. Other factors seem to influence acamprosate’s efficacy, including weeks of abstinence prior to treatment, body mass index (BMI), mood, and gamma- glutamyltransferase (GGT) levels 126. In general, according to an analysis performed by

Gueorguieva et al. (2015) on patients from the COMBINE study, those who benefit the most from acamprosate are those with a lower amount of time abstinent before acamprosate treatment 126. Additionally, those with low BMI and low to normal GGT also seem to benefit most from treatment. These findings may indicate that those with greater physical health may see the best results when being treated. An adjustment of

21 dosage depending on BMI may also be optimal due to acamprosate’s possible inefficiency at higher BMI levels.

Acamprosate’s efficacy on drinking reduction may be limited to a short-term timespan. Recent studies have suggested that acamprosate’s effects may be explained in part by an increase in extracellular dopamine. Application of acamprosate into the nucleus accumbens revealed increases in extracellular dopamine thought to be caused by acamprosate’s interaction with NMDA receptors 127. A similar increase in dopamine levels in the accumbens and ventral tegmental area was seen but was shown to be abolished when antagonists to and nicotinic acetylcholine receptors were applied 128. Along with the elevation of extracellular dopamine, acamprosate was shown to reduce the amount of dopamine produced by alcohol intake 128. The elevation of dopamine produced by acamprosate along with the reduction of the dopaminergic response to alcohol is one of the major proposed mechanisms behind acamprosate’s efficacy in abstinence promotion. However, tolerance to this effect has been demonstrated in rat models. Chau et al (2018) measured alcohol induced dopamine levels in the nucleus accumbens of naïve rats, rats pretreated with acamprosate for 2 days, and rats that were pretreated with acamprosate for 10 days. Rats that were pretreated with acamprosate for 10 days showed elevated dopamine in response to alcohol during acamprosate administration, an effect that acamprosate was thought to nullify 129. These data implies a tolerance to acamprosate may be developed overtime.

22

Figure 6: Treatment with acamprosate produces the expected reduction in alcohol intake followed by a reduction in effect (top). This corresponds to an inability of acamprosate to reduce the dopaminergic response to alcohol (bottom) 129.

ACAMPROSATE, BEHAVIOR AND MEMORY

Previous studies have investigated acamprosate’s effects on behavior and memory with conflicting results. Healthy male subjects receiving acute administration of acamprosate performed worse on a free recall task meant to assess long-term memory 130 .

Healthy volunteers (both male and female) that received acamprosate administration for 7 days before testing also recalled fewer words on a free recall task, but showed increased recall speed during a word recognition task 116 . In contrast, in patients with schizophrenia and comorbid AUD, acamprosate did not impair participants in verbal recall or attentional tasks 131 . These conflicting results may be due to the difference in participants, as those diagnosed with both schizophrenia and AUD are known to have significant cognitive dysfunction 132 . However, schizophrenia and AUD comorbidity may be the best

23 model available from studies at this moment, as comorbidity of the two does not have an additive effect on cognition 133 . Furthermore, the differences in impairment of behavior and memory between those with only schizophrenia or only AUD appear to be minimal 133 .

Pietrzak et al. (2005) have investigated the effects of acamprosate and alcohol on the EEG of rabbits, but did not assess behavior. The results of their study reveal acamprosate had a multitude of effects, including a marked decrease in the theta frequency compared to baseline in the frontal cortex. Alcohol significantly decreased both theta and gamma frequencies, and this effect was only exacerbated when acamprosate was co-administered 134 . However, this study was limited in that it only assessed frequencies 15 and 60 minutes after administration of each drug. In order to gain a better understanding of the possible effects of acamprosate on memory, a study that simultaneously assesses behavior and memory while acquiring EEG after administration is warranted. This would allow for greater understanding of the effects that acamprosate and alcohol have on cognition through the alterations of brain frequencies. A study using these methods is a future direction that could follow the study in Chapter 2.

PHARMACOKINETICS OF ACAMPROSATE

Acamprosate is known to have a half-life of ~30-32 hours when administered orally, and ~3 hours when administered via intravenous infusion 135 . Bioavailability of acamprosate is poor in humans (11% from the gastrointestinal tract) and rodents (20%), which explains the need for the relatively large doses 109. Absorption of the drug is very slow, reaching maximal concentrations ~6.3 hours after oral administration 135,136 .

24

Naltrexone, another commonly used drug to combat AUD, increases absorption of acamprosate by 33% when coadministered 137 . Absorption is decreased when coadministered with food 135 . Acamprosate has been shown to have no pharmacokinetic interactions with other drugs prescribed for the treatment of AUD (disulfiram, diazepam, nordiazepam, naltrexone) 138 . Acamprosate is not protein bound and is excreted completely unchanged in urine 110 . No sign of liver or hepatic dysfunction have been shown in clinical trials 139 .

PHARMACODYNAMICS OF ACAMPROSATE

There has been much debate as to acamprosate’s mechanism of action at receptors.

Discovering and understanding this mechanism is crucial to understanding the behavioral effects being evaluated in this study. Initial investigations indicated that acamprosate

140 may be a direct agonist of γ-aminobutyric acid type A (GABA A) and an antagonist to

141 N-methyl-D-aspartate (NMDA) receptors . Blockade of both NMDA and GABA A receptors abolishes any effect of acamprosate on action potentials, seemingly confirming the role of acamprosate on both receptors, but leaving the mechanism of action in question 142. Acamprosate was specifically shown to modulate GABA transmission in rat models, increasing GABA uptake in specific cortical areas such as the hippocampus and

143 thalamus, and the subcortical striatum . When a GABA A antagonist was applied, this

142,144 effect was inhibited, leading to the theory of direct GABA A interaction by acamprosate. Acamprosate was also shown to not alter responses to GABA in neocortical neurons 145 . These results suggest that acamprosate’s effects may be indirectly mediated by some other mechanism.

25

Initial in vitro patch clamp studies in hippocampal neurons also suggested possible antagonism of NMDA receptors by acamprosate 141,146 . When compared to other known NMDA receptor antagonists in cultured hippocampal neurons, acamprosate was shown to have a very weak antagonism in comparison, which still allowed for modulation

147 of NMDA receptors regardless . Similar to GABA A receptors, the effects on NMDA receptors may be region specific, with modulation of synaptic potentials seen in the mesencephalon 148 , but not in the cerebellum or striatum 149 . A possible benefit of acamprosate’s theorized antagonism of NMDA receptors is the reduction of alcohol withdrawal induced seizures. Other NMDA receptor antagonists such as have been shown to reduce withdrawal related seizures and epileptic onsets in rodent models,150,151,152 making it theoretically possible the same effect could be seen when acamprosate is used. A study by Farook et al. (1990) found that acamprosate did indeed reduce alcohol withdrawal related convulsions in a mouse model 153. A hyper- glutamatergic state is seen after cessation of alcohol, causing the withdrawal effects seen after abuse 154,155 . Acamprosate has been shown to normalize this hyper-glutamatergic state by its proposed antagonism of NMDA and possibly mGluR receptors 155,156 .

Acamprosate may also antagonize metabotropic glutamate receptors (mGluRs), specifically mGlu1 and mGlu5. It was observed that is involved in alcohol dependence and withdrawal, and that the increase in glutamic acid that is released upon withdrawal is reduced by acamprosate 157 . This led to the theory that acamprosate may be antagonistic to mGluRs, particularly mGlu5. This seemed to be confirmed when it was observed that acamprosate blocked the neurotoxic effects of trans-ACPD, a known mGluR1 and mGluR5 agonist 158 . Tests of mGlu5 receptor antagonists including

26 acamprosate have been shown to reduce mGlu5 modulated anxiety-like behavior in rats, further supporting acamprosate’s action on mGlu5 receptors 139 . In a similar test of acamprosate’s efficacy in depression, it was found that acamprosate improved responses in mice using the tail suspension test; however, this effect was nullified when CDPPB, a positive of NMDA and mGlu5 receptors was applied 140 .

The exact method of acamprosate on these receptors is unknown; however, a prominent emerging theory is that acamprosate’s effects are due to indirect action on receptors that is mediated by calcium. It was initially thought that the N-acetyl homotaurine component of acamprosate’s chemical makeup was the active component, but when sodium (Na-AOTA) is substituted for calcium (Ca-AOTA), no reduction in self-administration was seen in a rat model 159 . When calcium (Ca-AOTA) was reinstated, rats began reducing the amount of self-administrated alcohol consistent with the expected effect of acamprosate 159 . To definitively test acamprosate’s effects on specific receptors, a study by Reilly et al. (2008) injected Xenopus oocytes with cDNAs or cRNAs that encoded for mGlu1, mGlu5, GABA A, and M1 muscarinic receptors along with subunits of voltage-gated Na + channels 160. Using electrophysiological recordings, acamprosate was applied at various clinical doses to each receptor subtype to measure the possible effects on each. None of the receptors acamprosate had been thought to act on responded to acamprosate alone, further suggesting an indirect mechanism of action 160. A similar study performed by Spanagel et al. (2014) seems to confirm these results. Using Xenopus laevis oocytes, acamprosate was shown to have no effect on NMDA and mGlu5 receptor activity when compared to known antagonists of each receptor 161 . Furthermore, when a

27 combination of Na-AOTA with calcium chloride was used to substitute acamprosate (Ca-

AOTA), a reduction in drinking was seen in rats comparable to acamprosate 161.

CONCLUSION

The following study sought to answer the question of the effects acamprosate may have on behavior and memory. Use of a NHP model to answer this question will prove beneficial in that it most likely offers improved translatability compared to other animal models. The dose response curve shown in this study might also help in selecting a potentially faciliatory dose to use in treatment of other diseases and disorders other than

AUD. Four doses of acamprosate were tested in the DMTS task without the presence of alcohol. The NHP was then subjected to the DMTS task after alcohol self-administration.

This was followed by acamprosate administration with alcohol. Based on previous literature, the hypothesis for the study was that acamprosate would produce mild impairment on memory performance, specifically percentage correct on the DMTS task.

A slight decrease in response time due to lack of attention was also expected. This is due to the few studies in healthy human patients that showed impairment in memory recall tasks when given acamprosate, albeit with somewhat conflicting results.

28

CHAPTER 2:

EFFECTS OF ALCOHOL AND ACAMPROSATE, AN ALCOHOL USE DISORDER

TREATMENT, ON NONHUMAN PRIMATE BEHAVIOR AND MEMORY

Johnson CA 1; Daunais JB 1; Porrino LJ 1; Deadwyler SA 1; Hampson RE 1

1Wake Forest School of Medicine, Winston-Salem, NC, USA

[Support contributed by: NIH grant DA06634]

The authors declare no competing financial interests

29

ABSTRACT

Acamprosate is one of many drugs prescribed to individuals with alcohol use disorder (AUD) meant to prevent a patient from drinking once they have decided to stop.

The potential effects of this drug on cognition and attention have not been studied in depth. Due to acamprosate being investigated for the treatment of other major disorders

(anxiety, depression, and more), insight into these potential effects will prove crucial in the future. To assess these effects, we subjected a male non-human primate (NHP; rhesus macaque) to a delayed match to sample task (DMTS) while exposed to alcohol alone, acamprosate alone, or a combination of both alcohol and acamprosate. Results of alcohol exposure showed a detrimental effect on attention, but seemingly did not affect working memory (WM) ability evidenced by no differences seen in average percent correct between groups in the DMTS task. Acamprosate administration revealed varying results, with a lower dose facilitating behavioral and memory measures and a moderate dose having the opposite effect. When administered after alcohol consumption, acamprosate improved attentional ability but was unable to restore other measures, indicating that acamprosate may only be faciliatory at lower doses after a patient has been detoxified of alcohol.

30

INTRODUCTION

Alcohol use disorder (AUD) is a major burden on society and will continue to be for the foreseeable future. Globally, alcohol was the seventh leading risk factor for deaths and disability-adjusted life years as of 2016 162 . In the 15-49 age groups, alcohol is the leading risk factor in both previously mentioned categories 162 . Additionally, it is estimated that 27% of global alcohol use is unreported, intensifying an already extremely burdensome problem 163 .

Alcohol’s effects on the brain have been subject to intense study, with cognition being a common area of focus. Severe impairment has been shown in a wide variety of cognitive tasks ranging from simple stimulus identification to sustained attention, verbal memory, WM, psychomotor speed, and more 164,165,166 . Individuals who experience hangovers caused by excessive drinking also have been shown to have decreased reaction times and accuracy on simple tasks such as judging whether one number is greater than the other 167 . Furthermore, alcohol can worsen cognitive deficits seen by other factors such as stress 168 . Alcohol’s impairing effects have even been compared to effects seen after hippocampal lesions 169 . These effects may be enduring in those that have a long history of abuse, even those that have abstained for a long period of time 170 . Thus, the importance of promoting abstinence in those with AUD cannot be understated.

Treatment of AUD typically consists of psychosocial interventions combined with drug treatment personalized to each individual patient. This approach has been proven to be cost effective and to produce better patient outcomes 171,172 . Acamprosate, known by the brand name “Campral” in the US, is one such drug used in treatment of AUD.

Developed in Europe in 1989 and approved by the FDA in 2004, acamprosate is now one

31 of the most commonly prescribed drugs for AUD in the US 105 . The drug is relatively well tolerated, with the most common side effects seen being flatulence and diarrhea 107 .

The most positive outcomes when taking acamprosate are seen in patients with the clear goal of abstinence 173 . Those with healthy BMI and gamma-glutamyltransferase (GGT) levels may also see increased benefits from taking acamprosate 126. Acamprosate has

140,142,144 141 158 been shown to have an effect on GABA A , NMDA , and mGluR receptors , although the exact mechanism has not yet been clearly identified. Recent studies point towards an indirect effect on these receptors mediated by calcium levels 160,161 .

Research into acamprosate’s effects on behavior and memory is scarce with mixed results 116,131,132 , emphasizing the need for more examination of this topic. Based on previous literature, the hypothesis was that higher individual doses of acamprosate tested would cause a reduction in working memory performance exemplified by a lower amount of correct trials on the DMTS task, while moderate to lower doses were expected to produce no change in DMTS task performance. When administered after alcohol, acamprosate was not expected to improve any impairment seen by alcohol in the DMTS task due to its abstinence promoting effects also disappearing once alcohol has been consumed.

Results of the following study reveal acamprosate may be faciliatory on measures such as WM and attention at lower doses, and possibly detrimental at moderate to higher doses. The effects of alcohol in this study shows the resilience of WM and impairment of attentional abilities, which seems to agree with previous literature. When administered after being exposed to alcohol, acamprosate seemingly improved attentional abilities, but seemed to worsen WM performance. The results of these experiments provide

32 groundwork for future studies on acamprosate’s behavioral effects related to behavior and memory.

MATERIALS AND METHODS

NON-HUMAN PRIMATE

This study was conducted in an adult, male rhesus macaque ( macaca mulatta ), age 13. The monkey had a lengthy history of performing the DMTS task for five days a week for several years before this study. As part of a separate pilot study that examined the impact of low, moderate and heavy alcohol consumption on resting state brain function, the monkey consumed escalating doses of alcohol (0.25,0.75 and 1.5 g/kg) for roughly 2 months at each dose in the two years prior to this study. The NHP was water restricted based on weight prior to and during this study to encourage participation in the task.

DELAYED MATCH-TO-SAMPLE TASK

The NHP was tested on a delayed match-to-sample task (Figure 1). The task was performed five days a week with or without drug. Sitting in a primate chair, the NHP was placed in an operant box in view of a display screen after having a UV-fluorescent wristband placed onto the right hand. The attached wristband allowed for hand movement tracking via a 15 W UV lamp and an LCD camera placed above the animal.

Computers connected to the cameras allow for the NHP’s hand movements to be displayed as a cursor on the task display screen.

To begin the task, the cursor is placed in a central circle (start signal) after which an image is subsequently presented in one of eight different positions on the display screen (sample presentation). In order advance from the sample presentation phase, the

33

NHP had to hover the cursor over the presented image (sample response). Following the sample response (SR), a variable delay of 5-30s during which the display screen was blank. After the end of the delay, 2-5 images were presented in separate spatial locations on the screen (match phase), one of which was the image presented in the sample presentation phase. The NHP was then required to place the cursor on one of the presented images (match response). A correct response resulted in a reward (juice presented through a tube positioned before beginning the task), while an incorrect response led to a blank screen without any juice reward. The NHP performed the task for a varying amount of trials depending on performance and time. The task was completed each day once the NHP completed either 100 trials or 90 minutes of the task. Baseline performance measures were collected on a daily basis for 30 days prior to alcohol consumption for this study. DMTS performance occurred during morning sessions.

Alcohol consumption (1.0 g/kg or 4 drinks/day equivalent) occurred immediately following task performance in order to avoid the effects of alcohol intoxication on task performance.

For the purposes of analysis, individual trials were broken down into high cognitive load groups. High cognitive load is defined as a delay between sample and match phase of 20 seconds or more, with greater than four images displayed during the match phase of the task. Insufficient low load trials occurred due to the randomness of the delay period and number of images presented in the match phase which prevented any low cognitive load trial analysis.

All animal procedures were reviewed and approved by the Institutional Animal

Care and Use Committee of Wake Forest University, in accordance with U.S.

34

Department of Agriculture, International Association for the Assessment and

Accreditation of Laboratory Animal Care, and National Institutes of Health guidelines.

DRUG PREPARATION AND ADMINISTRATION

ACAMPROSATE

Acamprosate was administered via intramuscular injection (IM) 30 minutes before performing the DMTS task to allow the drug to take effect. Dosages tested were

0.5, 0.75, 1.0, and 2.6 mg/kg. Each of the four dosages were tested twice. The drug was weighed out and dissolved in sufficient sterile water to produce a 10 mg/kg stock solution.

After stock preparation, it was filter sterilized and injected through a .22µm syringe filter into a capped sterile vial. Each dose was injected into the quadriceps muscle of the NHP.

Due to a higher injection volume during the highest tested dose (2.6 mg/kg), two injections were necessary and were given on opposite muscles.

ALCOHOL

The monkey had access to alcohol (1.0 g/kg) for the duration of the study.

Alcohol was provided after completion of the DMTS task via a bottle placed on the

NHP’s cage. The alcohol was mixed with juice to encourage drinking, and a supplementary bottle of 100 ml of water was given in tandem in order to prevent excess dehydration. Consumption of the alcohol was confirmed each day by observation of the

NHP throughout the day after presentation of the bottle containing the alcohol. During testing of the alcohol and acamprosate with alcohol, the NHP received alcohol seven days of the week for two weeks.

35

ACAMPROSATE AND ALCOHOL

The NHP received acamprosate and alcohol in the same fashion as when they were administered separately. Acamprosate (0.75 mg/kg) was injected IM 30 minutes before beginning the DMTS task. Alcohol administration began the day before coadministration with acamprosate to allow the effects of alcohol to take place before acamprosate administration. During days of task performance, alcohol was provided after completion of the DMTS task (1.0 g/kg). Consumption of the alcohol was confirmed each day by observation of the NHP and the volume throughout the day after presentation of the bottle containing the alcohol.

STATISTICAL ANALYSES

To interpret the collected data, both descriptive statistics and statistical conclusion methods were used. The normality of the data distributions was assessed using the

Shapiro-Wilk test. A one way analysis of variance (ANOVA) was used to assess possible differences between parametric groups, followed by the Student-Newman-Keuls

Method for post hoc pairwise comparison. Groups that failed the initial ANOVA were not subject to any post hoc comparisons.

Possible differences between non-parametric groups were assessed using the

Kruskal-Wallis ANOVA on Ranks Test when k > 2 groups. In order to analyze the differences in high cognitive load trials between groups, individual means for each dose and load were obtained, then compared using the Kruskal-Wallis test (ex: 0.5 mg/kg high load match percentage correct vs 0.75 mg/kg high load percentage correct, etc). Those groups were then subject to post hoc analyses. Dunn’s Method was used as a non-

36 parametric pairwise comparison to assess contrasts in group means. For all statistical assessments, α=0.05 was the maximum accepted value for type I error.

RESULTS

ALCOHOL

The effects of 1.0 g/kg alcohol on DMTS performance measures were assessed prior to co-administration of acamprosate (Figure 4). Alcohol was consumed daily for seven days/wk for 14 days. Alcohol (1.0 g/kg) did not significantly alter average SR latency, MR latency, or percentage correct in the DMTS task when compared to control trials. However, alcohol did cause significant increases in average FR latency (p=0.026) and significant decreases in average number of trials performed (M=47.2 trials, p=0.003) compared to the control (M=88.3 trials).

ACAMPROSATE

Differing dose dependent effects were seen on DMTS task parameters due to acamprosate administration (Figure 2). The 0.75 mg/kg dose was significantly lower than all other doses on average in SR latency (p=<0.001 vs. 1 mg/kg and control, p=0.001 vs. 0.5 mg/kg, p=0.002 vs. 2.6 mg/kg). No other significant differences were seen in the

SR latency measure. For match response (MR) latency, the 0.75 mg/kg dose

(SEM=0.212) was significantly better than 1.0 mg/kg (p=<0.001) and control (p<0.001) groups but was not significantly different from 0.5 mg/kg and 2.6 mg/kg averages. The

1.0 mg/kg group was significantly worse in MR latency than all other groups including control (p=<0.001 for all comparisons). For focus ring (FR) latency, the 0.75 mg/kg dose

(SEM=2.804) was significantly better than all other doses, including control (p=<0.001

37 when compared to 1.0 mg/kg, 2.6 mg/kg, and control, p=0.029 when compared to 0.5 mg/kg). In contrast, the 1.0 mg/kg dose (SEM=7.172) was significantly worse than all other doses including the control group for mean FR latency (p=<0.001 for all comparisons). No differences were seen in mean percentage correct between doses and control. Analysis of cognitive load revealed little differences between doses (Figure 3).

There were no significant differences between mean MR latencies or percentage correct for high cognitive load.

Figure 1: An example of a single delayed match-to-sample trial. The task requires the participant to hover over a focus ring in order to have the sample image presented. The sample image then disappears and is followed by a delay period once the participant hovers over the image. Then, the participant is required to select the previously presented image for the response to be correct.

38

Figure 2: Results of the DMTS task for individual doses of acamprosate compared to control trials. (A): SR Latency: 0.75 mg/kg dose of acamprosate (SEM=0.480) is significantly faster than all other groups (p=<0.002 for all comparisons). No other differences were seen. (B): MR Latency: 0.75 mg/kg dose of acamprosate (SEM=0.212) performed significantly better than 1.0 mg/kg and control groups (p=<0.001 and p=0.011 respectively). 1.0 mg/kg dose (SEM=2.455) performed significantly worse than all other groups (p=<0.001 for all comparisons). (C): FR Latency: 0.75 mg/kg (SEM=2.804) dose was significantly better than all other groups (p=0.029 vs 0.5 mg/kg dose, p=<0.001 for all other comparisons). 1 mg/kg dose (SEM=7.172) was significantly worse than all

39 other groups (p=<0.001 for all comparisons). (D): Mean Percentage Correct: 0.75 mg/kg dose (SEM=0.032) performed better than 1.0 mg/kg dose (SEM=0.047) (p=0.046). No other significant differences were seen. (DMTS=delayed match-to-sample, SR=sample response, MR=match response, FR=focus ring, SEM=standard error of mean).

Figure 3: Results of the DMTS task for acamprosate doses separated by high cognitive load compared to combined averages (mean ± SEM). (A): No significant differences were seen in high cognitive load MR latencies. (B): Average 1.0 mg/kg latencies were significantly higher than all other groups. 0.75 mg/kg latencies were significantly lower only when compared to 1 mg/kg and control groups. No other differences were seen. (C):

40

No significant differences between mean percentage correct groups were seen for high load trials. (D): No differences were seen in overall mean percentage correct between doses and control. (High cognitive load= >20 second delays and >4 images, DMTS= delayed match-to-sample task, MR=match response, SEM=standard error of the mean).

ACAMPROSATE AND ALCOHOL

Next, we examined the effects of acamprosate when administered after alcohol consumption (AA) to control and alcohol trials (Figure 4). The 0.75 mg/kg dose of acamprosate was chosen to use with the alcohol due to the results of the individual doses suggesting the 0.75 mg/kg dose was the most faciliatory among the doses tested. No significant effects were seen on SR latencies or MR latencies. A decline in mean percentage correct (p=<0.001) was seen in AA trials (SEM=0.028) vs control trials

(SEM=0.017). While there was no significant difference between SR latencies, an inverse trend can be seen between SR latency and percentage correct. A significant effect on FR latency (p=0.026) was seen between control trials (SEM=2.247) and alcohol trials (SEM=7.960). There was no significant difference in FR latency between control trials and AA trials (SEM=5.537). When broken down to high cognitive load, there were no significant differences for either percentage correct or MR latencies (Figure 5). When comparing the average number of trials performed for alcohol and AA sessions, no significant differences were found. However, an upward trend in number of trials can be seen from the week of alcohol sessions to the week of AA sessions (Figure 6).

41

Figure 4: Results of the DMTS task for control, alcohol, and acamprosate and alcohol trials (mean ± SEM). (A): The 0.75 mg/kg dose of acamprosate was significantly faster on average than other groups (p=<0.001). (B): The 0.75 mg/kg dose of acamprosate was significantly faster on average than other groups (p=<0.001). (C): A significant increase on mean FR latency was seen in alcohol trials compared to control (p=0.026). There was no significant difference between AA and control trials. (D): AA trials were significantly worse on average than control trials (p=<0.001). No significant differences were seen between mean alcohol and control trials. (AA=acamprosate with alcohol,

42

DMTS=delayed match-to-sample, FR=focus ring, MR=match response, SR=sample response, SEM=standard error of the mean).

Figure 5: Results of the DMTS task separated by high cognitive load compared to combined averages (mean ± SEM). (A): The 0.75 mg/kg dose of acamprosate was significantly faster on average than other groups (p=<0.001). (B): The 0.75 mg/kg dose of acamprosate was significantly faster on average than other groups (p=<0.001). (C):

There were no differences seen in mean percentage correct high load groups. (D): AA trials were significantly worse overall on average than control trials (p=<0.001). (High

43 cognitive load= >20 second delays and >4 images, DMTS=delayed match-to-sample task,

SEM=standard error of the mean).

Figure 6: Number of trials performed in the DMTS task throughout the testing of alcohol and AA groups. Alcohol administration (1.0 g/kg) began a day before the alcohol administration period (black dots), and continued throughout the acamprosate (0.75 mg/kg) and alcohol (1.0 g/kg) administration period (red dots). Average number of trials was not significantly different between the alcohol (M=47.2) and AA groups (M=52.3).

(DMTS=delayed match-to-sample, AA= acamprosate with alcohol).

44

DISCUSSION

This study provides novel results of acamprosate’s dose-dependent effects on cognition in a NHP model of alcohol self-administration. The results shown in this study suggest that acamprosate may be faciliatory on measures such as WM and attention at lower doses, and possibly detrimental at moderate to higher doses. The detrimental effects of alcohol on attentional abilities were also demonstrated in this study. When administered after alcohol consumption, acamprosate seemingly improved attentional abilities, but seemed to worsen WM performance.

The effects of alcohol demonstrated in this study used a 1.0 g/kg (4 drinks a day) dose, which is considered light drinking by NHP standards 28 . Focus ring latency (the time it takes the NHP to begin each DMTS trial) was the only measure significantly impaired when compared to control trials. Perhaps unsurprisingly, overall WM performance (MR latency, mean percentage correct on the DMTS task) seemed to be more resilient to alcohol’s effects. This aligns with previous studies that have shown that

WM is more resistant to alcohol’s effects than other types of memory 35,36 . These results also agree with previous studies that have shown impairments in sustained attention due to alcohol 38,39 .

Further breakdown of these results between high cognitive load and overall results also indicate no difference between control, alcohol, and AA groups. This seems to agree with previous neuroimaging studies that have shown activation of areas such as the PFC increases with higher WM loads, indicating a higher level of allocated resources for harder tasks 175,176 . As previously shown, however, communication between these

45 areas via theta-gamma oscillations are likely impaired by alcohol 101,102 . The dosage of alcohol used in this study (1.0 g/kg=4 drinks/day) is considered light drinking, which seems to be enough to impair measures such as attention. However, it may take higher doses to impair WM performance at higher cognitive loads.

The current results of these tests show that a lower dose of acamprosate may improve attentional abilities, reaction time, and WM capabilities. In contrast, moderate to higher doses may impair these measures. When compared to previous studies, these results partially agree with results in healthy patients that show a reduction in WM performance, but an increase in reaction time 116,130 . In contrast, these results conflict with results from a study in patients with comorbid AUD and schizophrenia showing no impairment in WM or other measures using a higher dose of acamprosate 131 . This may be due to the fact that those with schizophrenia are known to already have cognitive impairment 132 . However, this study was limited in that each dose was tested twice in one subject, limiting the conclusions that can be made from these results. Further confirmation of these results is needed, but if proven reliable, this study may have certain clinical implications. Mainly, if a patient experiences cognitive impairment at the standard doses of acamprosate, a switch to a lower dose may remedy those impairments while also serving its original purpose of maintaining abstinence. This may or may not be possible depending on a patient’s cravings, as the highest dose tested in this study (2.6 mg/kg, which is roughly equivalent to 0.2168 g) is still not equivalent to the most commonly used single dose in humans (.666 g given three times daily). Also, these results seem to agree with the growing notion in clinical medicine that highly individualized treatment plans for each patient are necessary and can be significantly

46 beneficial to patients 177 . Furthermore, this study suggests that these lower doses may be ideal for use in studies experimenting with acamprosate to treat other disorders such as anxiety and depression due to its possible faciliatory effects.

Previous experiments have shown that NMDA receptor activation along with

AMPA modulated mGluR activity facilitate memory performance, including high load trials 178,179 . Acamprosate is known to be an antagonist to both NMDA and mGlu

139,141,158 142,144 receptors , while also being a possible agonist to GABA A receptors .

Antagonistic activity at NMDA and mGlu receptors would be expected to not improve performance on high load trials. Analysis of high cognitive load trials between individual acamprosate doses revealed that no individual dose was particularly faciliatory on high load trials. This not only agrees with the previously mentioned studies 178,179 , but also suggests that the faciliatory effects seen at lower doses of acamprosate are due to the agonism of GABA A receptors.

Administration of acamprosate after a history of alcohol consumption revealed that acamprosate may not be able to improve the performance deficits caused by alcohol.

The dose of acamprosate (0.75 mg/kg) used in tandem with alcohol was chosen due to the faciliatory effects seen when administered alone. However, this dose was seemingly unable to produce the same effects when administered after alcohol exposure. Results showed a marked improvement in sustained attention, no improvement in SR or MR latencies, and worse WM performance. An inverse trend between SR latency and percentage correct can be seen (Figure 4). This may indicate a deficit in procedural memory of the NHP that tracks the current phase of the task. Due to this, reaction times may worsen, leading to decreased WM performance.

47

Previous literature suggests that acamprosate is not efficacious in preventing drinking once a single drink has already been consumed 123,125 . This agrees with results from this study, where acamprosate did not deter drinking when administered after alcohol. The same logic may apply to behavioral abilities; once alcohol has been consumed, acamprosate may no longer have the potential to restore those abilities as shown by the results of this study. The improvement in FR latency may be attributed to acamprosate’s ability to improve withdrawal symptoms by normalizing the hyper- glutamatergic state seen in withdrawal 155,156 , making it easier for subjects to focus.

Conversely, these results may indicate acamprosate exacerbates alcohol’s effects on response inhibition. Alcohol has been shown to reduce the ability of subjects to stop intended movements once a decision has been made; 29,30,31 this may lead to an improvement in reaction time but could be detrimental to making a correct decision.

Examination of the average number of trials performed through the testing period revealed no significant differences between alcohol and AA groups. However, an upward trend in the number of trials performed each day was seen during the week of acamprosate administration with alcohol. This could possibly indicate a gradual restoration of attentional abilities that might occur with additional testing over time and warrants further examination.

Overall, our results appear to be consistent with previous literature concerning alcohol and acamprosate. Impairment in attentional ability resulted from alcohol consumption, but WM seemed more resistant to its effects. Also, acamprosate may exacerbate alcohol’s effects on response inhibition, exemplified by a decrease in FR latency along with a decrease in WM performance. Novel results from this study points

48 toward lower doses of acamprosate being faciliatory, and mid to higher doses possibly impairing, but only without co-consumption of alcohol.

Future directions of this study will seek to confirm these results by testing these doses for a longer period of time in a larger group of NHPs. Intermediate doses between the 1.0 and 2.6 mg/kg doses would also be necessary to confirm that moderate doses of acamprosate are the most impairing. Simultaneous EEG recording during behavioral tasks would allow for comparison of theta-gamma coupling to behavioral data. Results in this study suggest that acamprosate may worsen the possible effects of alcohol on theta/gamma coupling when administered when alcohol has already been consumed.

However, it may improve theta/gamma coupling when used in a detoxified subject. A drug such as naltrexone may be administered alongside alcohol consumption to see if it would prove more efficacious than acamprosate at rescuing WM abilities.

49

REFERENCES

1: Peacock, A., Leung, J., Larney, S., College, S., Hickman, M., Rehm, J., . . .

Degenhardt, L. (2018). Global statistics on alcohol, tobacco and illicit drug use: 2017 status report. Addiction, 113(10), 1905-1926. Doi:10.1111/add.14234

2: Lim, S. S., Vos, T., Flaxman, A. D., Danaei, G., Shibuya, K., … Ezzati, M. (2012). A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: A systematic analysis for the Global

Burden of Disease Study 2010. Lancet, 380(9859), 2224-2260. doi:10.1016/S0140-

6736(12)61766-8

3: Rehm, J., Mathers, C., Popova, S., Thavorncharoensap, M., Teerawattananon, Y., &

Patra, J. (2009). Global burden of disease and injury and economic cost attributable to alcohol use and alcohol-use disorders. The Lancet, 373(9682), 2223-2233. doi:10.1016/s0140-6736(09)60746-7

4: Boden, J. M., & Fergusson, D. M. (2011). Alcohol and depression. Addiction, 106(5),

906-914. doi:10.1111/j.1360-0443.2010.03351.x

5: Hasin, D. S., Stinson, F. S., Ogburn, E., & Grant, B. F. (2007). Prevalence, Correlates,

Disability, and Comorbidity of DSM-IV Alcohol Abuse and Dependence in the United

States. Archives of General Psychiatry, 64(7), 830. doi:10.1001/archpsyc.64.7.830

6: Paljärvi, T., Koskenvuo, M., Poikolainen, K., Kauhanen, J., Sillanmäki, L., & Mäkelä,

P. (2009). Binge drinking and depressive symptoms: A 5-year population-based cohort study. Addiction, 104(7), 1168-1178. doi:10.1111/j.1360-0443.2009.02577.x

50

7: Naglich, A., Adinoff, B., & Brown, E. S. (2017). Pharmacological Treatment of

Bipolar Disorder with Comorbid Alcohol Use Disorder. CNS Drugs, 31(8), 665-674. doi:10.1007/s40263-017-0449-5

8: Wiener, C. D., Moreira, F. P., Zago, A., Souza, L. M., Branco, J. C., Oliveira, J. F., . . .

Oses, J. P. (2017). Mood disorder, anxiety, and suicide risk among subjects with alcohol abuse and/or dependence: A population-based study. Revista Brasileira De Psiquiatria,

40(1), 1-5. doi:10.1590/1516-4446-2016-2170

9: Skinner, B. F. (1950). Are theories of learning necessary? Psychological Review, 57(4),

193-216. doi:10.1037/h0054367

10: Hampson, R. E., Heyser, C. J., & Deadwyler, S. A. (1993). Hippocampal cell firing correlates of delayed-match-to-sample performance in the rat. Behavioral Neuroscience,

107(5), 715-739. doi:10.1037/0735-7044.107.5.715

11: Lee, K. A., Preston, A. J., Wise, T. B., & Templer, V. L. (2018). Testing for

Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats.

Journal of Visualized Experiments, (136). doi:10.3791/57489

12: Templer, V. L., Lee, K. A., & Preston, A. J. (2017). Rats know when they remember:

Transfer of metacognitive responding across odor-based delayed match-to-sample tests.

Animal Cognition, 20(5), 891-906. doi:10.1007/s10071-017-1109-3

13: Fuster, J. M., Bauer, R. H., & Jervey, J. P. (1985). Functional interactions between inferotemporal and prefrontal cortex in a cognitive task. Brain Research, 330(2), 299-307. doi:10.1016/0006-8993(85)90689-4

14: Moody, S. L., Wise, S. P., Pellegrino, G. D., & Zipser, D. (1998). A Model That

Accounts for Activity in Primate Frontal Cortex during a Delayed Matching-to-Sample

51

Task. The Journal of Neuroscience, 18(1), 399-410. doi:10.1523/jneurosci.18-01-

00399.1998

15: Opris, I., Barborica, A., & Ferrera, V. P. (2003). Comparison of performance on memory-guided saccade and delayed spatial match-to-sample tasks in monkeys. Vision

Research, 43(3), 321-332. doi:10.1016/s0042-6989(02)00418-2

16: Song, D., Opris, I., Chan, R. H., Marmarelis, V. Z., Hampson, R. E., Deadwyler, S.

A., & Berger, T. W. (2012). Functional connectivity between Layer 2/3 and Layer 5 neurons in prefrontal cortex of nonhuman primates during a delayed match-to-sample task. 2012 Annual International Conference of the IEEE Engineering in Medicine and

Biology Society. doi:10.1109/embc.2012.6346485

17: Lamar, M., Yousem, D. M., & Resnick, S. M. (2004). Age differences in orbitofrontal activation: An fMRI investigation of delayed match and nonmatch to sample. NeuroImage, 21(4), 1368-1376. doi:10.1016/j.neuroimage.2003.11.018

18: Olsen, R. K., Nichols, E. A., Chen, J., Hunt, J. F., Glover, G. H., Gabrieli, J. D., &

Wagner, A. D. (2009). Performance-Related Sustained and Anticipatory Activity in

Human Medial Temporal Lobe during Delayed Match-to-Sample. Journal of

Neuroscience, 29(38), 11880-11890. doi:10.1523/jneurosci.2245-09.2009

19: Kropotov, J. D., & Ponomarev, V. A. (2015). Differentiation of neuronal operations in latent components of event-related potentials in delayed match-to-sample tasks.

Psychophysiology, 52(6), 826-838. doi:10.1111/psyp.12410

20: Holdstock, J., Shaw, C., & Aggleton, J. (1995). The performance of amnesic subjects on tests of delayed matching-to-sample and delayed matching-to-position.

Neuropsychologia, 33(12), 1583-1596. doi:10.1016/0028-3932(95)00145-x

52

21: Matthews, N., Vance, A., Cummins, T. D., Wagner, J., Connolly, A., Yamada, J., . . .

Bellgrove, M. A. (2012). The COMT Val158 allele is associated with impaired delayed- match-to-sample performance in ADHD. Behavioral and Brain Functions, 8(1), 25. doi:10.1186/1744-9081-8-25

22: Lencz, T., Bilder, R. M., Turkel, E., Goldman, R. S., Robinson, D., Kane, J. M., &

Lieberman, J. A. (2003). Impairments in Perceptual Competency and Maintenance on a

Visual Delayed Match-to-Sample Test in First-Episode Schizophrenia. Archives of

General Psychiatry, 60(3), 238. doi:10.1001/archpsyc.60.3.238

23: Lane, S. D., Cherek, D. R., Lieving, L. M., & Tcheremissine, O. V. (2005).

Marijuana Effects On Human Forgetting Functions. Journal of the Experimental Analysis of Behavior, 83(1), 67-83. doi:10.1901/jeab.2005.22-04

24: Oscar-Berman, M., & Bonner, R. T. (1985). Matching- and delayed matching-to- sample performance as measures of visual processing, selective attention, and memory in aging and alcoholic individuals. Neuropsychologia, 23(5), 639-651. doi:10.1016/0028-

3932(85)90065-x

25: Daniel, T. A., Katz, J. S., & Robinson, J. L. (2016). Delayed match-to-sample in working memory: A BrainMap meta-analysis. Biological Psychology, 120, 10-20. doi:10.1016/j.biopsycho.2016.07.015

26: Barr, C. S., & Goldman, D. (2006). Non-human primate models of inheritance vulnerability to alcohol use disorders. Addiction Biology, 11(3-4), 374-385. doi:10.1111/j.1369-1600.2005.00034.x

53

27: Wallace, T. L., Ballard, T. M., & Glavis-Bloom, C. (2015). Animal Paradigms to

Assess Cognition with Translation to Humans. Cognitive Enhancement Handbook of

Experimental , 27-57. doi:10.1007/978-3-319-16522-6_2

28: Grant, K. A., & Bennett, A. J. (2003). Advances in nonhuman primate alcohol abuse and alcoholism research. Pharmacology & Therapeutics, 100(3), 235-255. doi:10.1016/j.pharmthera.2003.08.004

29: Marczinski, C. A. (2017). How Actions Taken (or Not) Influence Inhibitory Control and Perceived Impairment Under Alcohol. PsycEXTRA Dataset. doi:10.1037/e512472017-001

30: Campbell, A. E., Chambers, C. D., Allen, C. P., Hedge, C., & Sumner, P. (2017).

Impairment of manual but not saccadic response inhibition following acute alcohol intoxication. Drug and Alcohol Dependence, 181, 242-254. doi:10.1016/j.drugalcdep.2017.08.022

31: Hernández, O. H., & Vogel-Sprott, M. (2010). Alcohol Slows the Brain Potential

Associated With Cognitive Reaction Time to an Omitted Stimulus*. Journal of Studies on Alcohol and Drugs, 71(2), 268-277. doi:10.15288/jsad.2010.71.268

32: Bartholow, B. D., Fleming, K. A., Wood, P. K., Cowan, N., Saults, J. S., Altamirano,

L., . . . Sher, K. J. (2018). Alcohol effects on response inhibition: Variability across tasks and individuals. Experimental and Clinical Psychopharmacology, 26(3), 251-267. doi:10.1037/pha0000190

33: Wright, M. J., Vandewater, S. A., & Taffe, M. A. (2013). The influence of acute and chronic alcohol consumption on response time distribution in adolescent rhesus macaques.

Neuropharmacology, 70, 12-18. doi:10.1016/j.neuropharm.2013.01.003

54

34: Hagsand, A. V., Hjelmsäter, E. R., Granhag, P. A., Fahlke, C., & Gordh, A. S. (2016).

Witnesses stumbling down memory lane: The effects of alcohol intoxication, retention interval, and repeated interviewing. Memory, 25(4), 531-543. doi:10.1080/09658211.2016.1191652

35: Vinader-Caerols, C., Talk, A., Montañés, A., Duque, A., & Monleón, S. (2017).

Differential Effects of Alcohol on Memory Performance in Adolescent Men and Women with a Binge Drinking History. Alcohol and Alcoholism, 52(5), 610-616. doi:10.1093/alcalc/agx040

36: Wesley, M. J., Lile, J. A., Fillmore, M. T., & Porrino, L. J. (2017).

Neurophysiological capacity in a working memory task differentiates dependent from nondependent heavy drinkers and controls. Drug and Alcohol Dependence, 175, 24-35. doi:10.1016/j.drugalcdep.2017.01.029

37: Looby, A., Norton-Baker, M., & Russell, T. D. (2018). Interactive effects of baseline executive functioning and working memory depletion on alcohol use among heavy drinking young adults. Experimental and Clinical Psychopharmacology, 26(4), 341-346. doi:10.1037/pha0000205

38: Mckinney, A., Coyle, K., Penning, R., & Verster, J. C. (2012). Next day effects of naturalistic alcohol consumption on tasks of attention. Human Psychopharmacology:

Clinical and Experimental,27(6), 587-594. doi:10.1002/hup.2268

39: Rohsenow, D. J., Howland, J., Arnedt, J. T., Almeida, A. B., Greece, J., Minsky,

S., . . . Sales, S. (2010). Intoxication with bourbon versus vodka: Effects on hangover, sleep, and next-day neurocognitive performance in young adults. Alcohol Clin Exp Res,

1(34), 3rd ser., 509-518. doi:10.1111/j.1530-0277.2009.01116.x.

55

40: Funahashi, S., Bruce, C. J., & Goldman-Rakic, P. S. (1989). Mnemonic coding of visual space in the monkeys dorsolateral prefrontal cortex. Journal of Neurophysiology,

61(2), 331-349. doi:10.1152/jn.1989.61.2.331

41: Miller, E. K., Erickson, C. A., & Desimone, R. (1996). Neural Mechanisms of Visual

Working Memory in Prefrontal Cortex of the Macaque. The Journal of Neuroscience,

16(16), 5154-5167. doi:10.1523/jneurosci.16-16-05154.1996

42: Fuster, J. M., & Alexander, G. E. (1971). Neuron Activity Related to Short-Term

Memory. Science, 173(3997), 652-654. doi:10.1126/science.173.3997.652

43: Funahashi, S., Bruce, C. J., & Goldman-Rakic, P. S. (1989). Mnemonic coding of visual space in the monkeys dorsolateral prefrontal cortex. Journal of Neurophysiology,

61(2), 331-349. doi:10.1152/jn.1989.61.2.331

44: Perrachione, T. K., Ghosh, S. S., Ostrovskaya, I., Gabrieli, J. D., & Kovelman, I.

(2017). Phonological Working Memory for Words and Nonwords in Cerebral Cortex.

Journal of Speech Language and Hearing Research, 60(7), 1959. doi:10.1044/2017_jslhr- l-15-0446

45: Chein, J. M., Moore, A. B., & Conway, A. R. (2011). Domain-general mechanisms of complex working memory span. NeuroImage, 54(1), 550-559. doi:10.1016/j.neuroimage.2010.07.067

46: Osaka, M., Osaka, N., Kondo, H., Morishita, M., Fukuyama, H., Aso, T., & Shibasaki,

H. (2003). The neural basis of individual differences in working memory capacity: An fMRI study. NeuroImage, 18(3), 789-797. doi:10.1016/s1053-8119(02)00032-0

56

47: Ferrera, V., Rudolph, K., & Maunsell, J. (1994). Responses of neurons in the parietal and temporal visual pathways during a motion task. The Journal of Neuroscience, 14(10),

6171-6186. doi:10.1523/jneurosci.14-10-06171.1994

48: Chafee, M. V., & Goldman-Rakic, P. S. (2000). Inactivation of Parietal and

Prefrontal Cortex Reveals Interdependence of Neural Activity During Memory-Guided

Saccades. Journal of Neurophysiology, 83(3), 1550-1566. doi:10.1152/jn.2000.83.3.1550

49: Mendoza-Halliday, D., Torres, S., & Martinez-Trujillo, J. C. (2014). Sharp emergence of feature-selective sustained activity along the dorsal visual pathway. Nature

Neuroscience, 17(9), 1255-1262. doi:10.1038/nn.3785

50: Pessoa, L., Gutierrez, E., Bandettini, P. A., & Ungerleider, L. (2001). Neural correlates of visual working memory: BOLD predicts task performance. NeuroImage,

13(6), 720. doi:10.1016/s1053-8119(01)92063-4

51: Chafee, M. V., & Goldman-Rakic, P. S. (2000). Inactivation of Parietal and

Prefrontal Cortex Reveals Interdependence of Neural Activity During Memory-Guided

Saccades. Journal of Neurophysiology, 83(3), 1550-1566. doi:10.1152/jn.2000.83.3.1550

52: Baddeley, A. D., & Hitch, G. (1974). Working Memory. Psychology of Learning and

Motivation, 47-89. doi:10.1016/s0079-7421(08)60452-1

53: Baddeley, A. (2000). The episodic buffer: A new component of working memory?

Trends in Cognitive Sciences, 4(11), 417-423. doi:10.1016/s1364-6613(00)01538-2

54: Chai, W. J., Hamid, A. I., & Abdullah, J. M. (2018). Working Memory From the

Psychological and Neurosciences Perspectives: A Review. Frontiers in Psychology, 9. doi:10.3389/fpsyg.2018.00401

57

55: Cowan, N. (2008). What are the differences between long-term, short-term, and working memory? Progress in Brain Research Essence of Memory, 323-338. doi:10.1016/s0079-6123(07)00020-9

56: Atkinson, R. C., & Shiffrin, R. M. (1971). The Control Processes of Short-Term

Memory. Scientific American, 225(2), 82-90. doi:10.1038/scientificamerican0871-82

57: Ranganath, C. (2006). Working memory for visual objects: Complementary roles of inferior temporal, medial temporal, and prefrontal cortex. Neuroscience, 139(1), 277-289. doi:10.1016/j.neuroscience.2005.06.092

58: Postle, B. (2006). Working memory as an emergent property of the mind and brain.

Neuroscience, 139(1), 23-38. doi:10.1016/j.neuroscience.2005.06.005

59: Liu, Z., Grady, C., & Moscovitch, M. (2018). The effect of prior knowledge on post- encoding brain connectivity and its relation to subsequent memory. NeuroImage, 167,

211-223. doi:10.1016/j.neuroimage.2017.11.032

60: Nee, D. E., & Jonides, J. (2008). Neural correlates of access to short-term memory.

Proceedings of the National Academy of Sciences, 105(37), 14228-14233. doi:10.1073/pnas.0802081105

61: Bullmore, E., & Sporns, O. (2009). Complex brain networks: Graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience, 10(3), 186-

198. doi:10.1038/nrn2575

62: Hellwig, B. (2000). A quantitative analysis of the local connectivity between pyramidal neurons in layers 2/3 of the rat visual cortex. Biological Cybernetics, 82(2),

111-121. doi:10.1007/pl00007964

58

63: Braitenberg, V., & Schüz, A. (1998). Statistics and Geometry of Neuronal

Connectivity. doi:10.1007/978-3-662-03733-1

64: Averbeck, B. B., & Seo, M. (2008). The Statistical Neuroanatomy of Frontal

Networks in the Macaque. PLoS Computational Biology, 4(4). doi:10.1371/journal.pcbi.1000050

65: Friedman, H., & Goldman-Rakic, P. (1994). Coactivation of prefrontal cortex and inferior parietal cortex in working memory tasks revealed by 2DG functional mapping in the rhesus monkey. The Journal of Neuroscience, 14(5), 2775-2788. doi:10.1523/jneurosci.14-05-02775.1994

66: Geib, B. R., Stanley, M. L., Dennis, N. A., Woldorff, M. G., & Cabeza, R. (2017).

From hippocampus to whole-brain: The role of integrative processing in episodic memory retrieval. Human Brain Mapping, 38(4), 2242-2259. doi:10.1002/hbm.23518

67: Desimone, R. (1995). Neural Mechanisms of Selective Visual Attention. Annual

Review of Neuroscience, 18(1), 193-222. doi:10.1146/annurev.neuro.18.1.193

68: Bisley, J. W., & Goldberg, M. E. (2010). Attention, Intention, and Priority in the

Parietal Lobe. Annual Review of Neuroscience, 33(1), 1-21. doi:10.1146/annurev-neuro-

060909-152823

69: Buschman, T., & Kastner, S. (2015). From Behavior to Neural Dynamics: An

Integrated Theory of Attention. Neuron, 88(1), 127-144. doi:10.1016/j.neuron.2015.09.017

70: Jigo, M., Gong, M., & Liu, T. (2018). Neural Determinants of Task Performance during Feature-Based Attention in Human Cortex. Eneuro, 5(1). doi:10.1523/eneuro.0375-17.2018

59

71: Kim, S., Im, S., Lee, J., & Lee, S. (2017). Disrupted Control Network Connectivity in Abstinent Patients with Alcohol Dependence. Psychiatry Investigation, 14(3), 325. doi:10.4306/pi.2017.14.3.325

72: Howard, M. W. (2003). Gamma Oscillations Correlate with Working Memory Load in Humans. Cerebral Cortex, 13(12), 1369-1374. doi:10.1093/cercor/bhg084

73: Mainy, N., Kahane, P., Minotti, L., Hoffmann, D., Bertrand, O., & Lachaux, J. (2006).

Neural correlates of consolidation in working memory. Human Brain Mapping, 28(3),

183-193. doi:10.1002/hbm.20264

74: Fell, J., Klaver, P., Lehnertz, K., Grunwald, T., Schaller, C., Elger, C. E., &

Fernández, G. (2001). Human memory formation is accompanied by rhinal–hippocampal coupling and decoupling. Nature Neuroscience, 4(12), 1259-1264. doi:10.1038/nn759

75: Fell, J., Klaver, P., Elfadil, H., Schaller, C., Elger, C. E., & Fernández, G. (2003).

Rhinal-hippocampal theta coherence during declarative memory formation: Interaction with gamma synchronization? European Journal of Neuroscience, 17(5), 1082-1088. doi:10.1046/j.1460-9568.2003.02522.x

76: Düzel, E., Penny, W. D., & Burgess, N. (2010). Brain oscillations and memory.

Current Opinion in Neurobiology, 20(2), 143-149. doi:10.1016/j.conb.2010.01.004

77: Hyman, J. M., Zilli, E. A., Paley, A. M., & Hasselmo, M. E. (2005). Medial prefrontal cortex cells show dynamic modulation with the hippocampal theta rhythm dependent on behavior. Hippocampus, 15(6), 739-749. doi:10.1002/hipo.20106

78: Jones, M. W., & Wilson, M. A. (2005). Theta Rhythms Coordinate Hippocampal–

Prefrontal Interactions in a Spatial Memory Task. PLoS Biology, 3(12). doi:10.1371/journal.pbio.0030402

60

79: Siapas, A. G., Lubenov, E. V., & Wilson, M. A. (2005). Prefrontal Phase Locking to

Hippocampal Theta Oscillations. Neuron, 46(1), 141-151. doi:10.1016/j.neuron.2005.02.028

80: Lee, H., Simpson, G. V., Logothetis, N. K., & Rainer, G. (2005). Phase Locking of

Single Neuron Activity to Theta Oscillations during Working Memory in Monkey

Extrastriate Visual Cortex. Neuron, 45(1), 147-156. doi:10.1016/j.neuron.2004.12.025

81:Belluscio, M. A., Mizuseki, K., Schmidt, R., Kempter, R., & Buzsaki, G. (2012).

Cross-Frequency Phase-Phase Coupling between Theta and Gamma Oscillations in the

Hippocampus. Journal of Neuroscience, 32(2), 423-435. doi:10.1523/jneurosci.4122-

11.2012

82: Heusser, A. C., Poeppel, D., Ezzyat, Y., & Davachi, L. (2016). Episodic sequence memory is supported by a theta–gamma phase code. Nature Neuroscience, 19(10), 1374-

1380. doi:10.1038/nn.4374

83: Lisman, J., & Jensen, O. (2013). The Theta-Gamma Neural Code. Neuron, 77(6),

1002-1016. doi:10.1016/j.neuron.2013.03.007

84: Rajji, T. K., Zomorrodi, R., Barr, M. S., Blumberger, D. M., Mulsant, B. H., &

Daskalakis, Z. J. (2016). Ordering Information in Working Memory and Modulation of

Gamma by Theta Oscillations in Humans. Cerebral Cortex. doi:10.1093/cercor/bhv326

85: Köster, M., Finger, H., Graetz, S., Kater, M., & Gruber, T. (2018). Theta-gamma coupling binds visual perceptual features in an associative memory task. Scientific

Reports, 8(1). doi:10.1038/s41598-018-35812-7

86: Köster, M., Martens, U., & Gruber, T. (2018). Memory entrainment by visually evoked theta-gamma coupling. doi:10.1101/191189

61

87: Köster, M., Friese, U., Schöne, B., Trujillo-Barreto, N., & Gruber, T. (2014). Theta– gamma coupling during episodic retrieval in the human EEG. Brain Research, 1577, 57-

68. doi:10.1016/j.brainres.2014.06.028

88: Daume, J., Gruber, T., Engel, A. K., & Friese, U. (2017). Phase-Amplitude Coupling and Long-Range Phase Synchronization Reveal Frontotemporal Interactions during

Visual Working Memory. The Journal of Neuroscience, 37(2), 313-322. doi:10.1523/jneurosci.2130-16.2017

89: Osipova, D., Takashima, A., Oostenveld, R., Fernandez, G., Maris, E., & Jensen, O.

(2006). Theta and Gamma Oscillations Predict Encoding and Retrieval of Declarative

Memory. Journal of Neuroscience, 26(28), 7523-7531. doi:10.1523/jneurosci.1948-

06.2006

90: Kim, J. W., Lee, J., Kim, H., Lee, Y. S., & Min, K. J. (2015). Relationship between theta-phase gamma-amplitude coupling and attention-deficit/hyperactivity behavior in children. Neuroscience Letters, 590, 12-17. doi:10.1016/j.neulet.2015.01.068

91: Alekseichuk, I., Turi, Z., Amador De Lara, G., Antal, A., & Paulus, W. (2016).

Spatial Working Memory in Humans Depends on Theta and High Gamma

Synchronization in the Prefrontal Cortex. Current Biology, 26(12), 1513-1521. doi:10.1016/j.cub.2016.04.035

92: Colgin, L. L. (2015). Theta–gamma coupling in the entorhinal–hippocampal system.

Current Opinion in Neurobiology, 31, 45-50. doi:10.1016/j.conb.2014.08.001

93: Lara, G. A., Alekseichuk, I., Turi, Z., Lehr, A., Antal, A., & Paulus, W. (2018).

Perturbation of theta-gamma coupling at the temporal lobe hinders verbal declarative memory. Brain Stimulation, 11(3), 509-517. doi:10.1016/j.brs.2017.12.007

62

94: Sato, W., Kochiyama, T., Uono, S., Matsuda, K., Usui, K., Inoue, Y., & Toichi, M.

(2014). Rapid, high-frequency, and theta-coupled gamma oscillations in the inferior occipital gyrus during face processing. Cortex, 60, 52-68. doi:10.1016/j.cortex.2014.02.024

95: Chaieb, L., Leszczynski, M., Axmacher, N., Höhne, M., Elger, C. E., & Fell, J.

(2015). Theta-gamma phase-phase coupling during working memory maintenance in the human hippocampus. Cognitive Neuroscience, 6(4), 149-157. doi:10.1080/17588928.2015.1058254

96: Pahor, A., & Jaušovec, N. (2018). The Effects of Theta and Gamma tACS on

Working Memory and Electrophysiology. Frontiers in Human Neuroscience, 11. doi:10.3389/fnhum.2017.00651

97: Kim, J. W., Kim, B., Lee, J., Na, C., Kee, B. S., Min, K. J., . . . Lee, Y. S. (2016).

Desynchronization of Theta-Phase Gamma-Amplitude Coupling during a Mental

Arithmetic Task in Children with Attention Deficit/Hyperactivity Disorder. Plos One,

11(3). doi:10.1371/journal.pone.0145288

98: Barr, M. S., Rajji, T. K., Zomorrodi, R., Radhu, N., George, T. P., Blumberger, D. M.,

& Daskalakis, Z. J. (2017). Impaired theta-gamma coupling during working memory performance in schizophrenia. Schizophrenia Research, 189, 104-110. doi:10.1016/j.schres.2017.01.044

99: Goodman, M. S., Kumar, S., Zomorrodi, R., Ghazala, Z., Cheam, A. S., Barr, M.

S., . . . Rajji, T. K. (2018). Theta-Gamma Coupling and Working Memory in Alzheimer’s

Dementia and Mild Cognitive Impairment. Frontiers in Aging Neuroscience, 10. doi:10.3389/fnagi.2018.00101

63

100: Zhang, Y., Zhang, Y., Yu, H., Yang, Y., Li, W., & Qian, Z. (2017). Theta-gamma coupling in hippocampus during working memory deficits induced by low frequency electromagnetic field exposure. Physiology & Behavior, 179, 135-142. doi:10.1016/j.physbeh.2017.05.033

101: Park, S. M., Lee, J. Y., Kim, Y. J., Lee, J., Jung, H. Y., Sohn, B. K., . . . Choi, J.

(2017). Neural connectivity in Internet gaming disorder and alcohol use disorder: A resting-state EEG coherence study. Scientific Reports, 7(1). doi:10.1038/s41598-017-

01419-7

102: Moretti, D., Fracassi, C., Pievani, M., Geroldi, C., Binetti, G., Zanetti, O., . . .

Frisoni, G. (2009). Increase of theta/gamma ratio is associated with memory impairment.

Clinical Neurophysiology, 120(2), 295-303. doi:10.1016/j.clinph.2008.11.012

103: Lee, J., & Yun, K. (2013). Alcohol Reduces Cross-Frequency Theta-Phase Gamma-

Amplitude Coupling in Resting Electroencephalography. Alcoholism: Clinical and

Experimental Research, 38(3), 770-776. doi:10.1111/acer.12310

104: Loheswaran, G., Barr, M. S., Zomorrodi, R., Rajji, T. K., Blumberger, D. M., Foll,

B. L., & Daskalakis, Z. J. (2017). Impairment of Neuroplasticity in the Dorsolateral

Prefrontal Cortex by Alcohol. Scientific Reports, 7(1). doi:10.1038/s41598-017-04764-9

105: Mark, T. L., Kassed, C. A., Vandivort-Warren, R., Levit, K. R., & Kranzler, H. R.

(2009). Alcohol and dependence medications: Prescription trends, overall and by physician specialty. Drug and Alcohol Dependence, 99(1-3), 345-349. doi:10.1016/j.drugalcdep.2008.07.018

106: Plosker, G. L. (2015). Acamprosate: A Review of Its Use in Alcohol Dependence.

Drugs, 75(11), 1255-1268. doi:10.1007/s40265-015-0423-9

64

107: Acamprosate. (n.d.). Retrieved January 28, 2019, from https://www.addictioncenter.com/alcohol/acamprosate/

108: Woo, J., & Rim, H. (2014). Acamprosate-induced Extrapyramidal Symptoms in an

Elderly Patient with Alcohol Dependence. Clinical Psychopharmacology and

Neuroscience, 12(2), 166-168. doi:10.9758/cpn.2014.12.2.166

109: Kufahl, P. R., Watterson, L. R., & Olive, M. F. (2014). The development of acamprosate as a treatment against alcohol relapse. Expert Opinion on Drug Discovery,

9(11), 1355-1369. doi:10.1517/17460441.2014.960840

110: Erickson, C. A., Early, M., Stigler, K. A., Wink, L. K., Mullett, J. E., & Mcdougle,

C. J. (2011). An Open-Label Naturalistic Pilot Study of Acamprosate in Youth with

Autistic Disorder. Journal of Child and Adolescent Psychopharmacology, 21(6), 565-569. doi:10.1089/cap.2011.0034

111: Schaefer, T. L., Davenport, M. H., Grainger, L. M., Robinson, C. K., Earnheart, A.

T., Stegman, M. S., . . . Erickson, C. A. (2017). Acamprosate in a mouse model of fragile

X syndrome: Modulation of spontaneous cortical activity, ERK1/2 activation, locomotor behavior, and anxiety. Journal of Neurodevelopmental Disorders, 9(1). doi:10.1186/s11689-017-9184-y

112: Erickson, C. A., Ray, B., Maloney, B., Wink, L. K., Bowers, K., Schaefer, T. L., . . .

Lahiri, D. K. (2014). Impact of acamprosate on plasma amyloid-β precursor protein in youth: A pilot analysis in fragile X syndrome-associated and idiopathic autism spectrum disorder suggests a pharmacodynamic protein marker. Journal of Psychiatric Research,

59, 220-228. doi:10.1016/j.jpsychires.2014.07.011

65

113: Gross, C., Hoffmann, A., Bassell, G. J., & Berry-Kravis, E. M. (2015). Therapeutic

Strategies in Fragile X Syndrome: From Bench to Bedside and Back. Neurotherapeutics,

12(3), 584-608. doi:10.1007/s13311-015-0355-9

114: Kotlinska, J., & Bochenski, M. (2008). The influence of various glutamate receptors antagonists on anxiety-like effect of ethanol withdrawal in a plus-maze test in rats.

115: Pałucha-Poniewiera, A., & Pilc, A. (2012). Involvement of mGlu5 and NMDA receptors in the antidepressant-like effect of acamprosate in the tail suspension test.

Progress in Neuro-Psychopharmacology and Biological Psychiatry, 39(1), 102-106. doi:10.1016/j.pnpbp.2012.05.015European Journal of Pharmacology, 598(1-3), 57-63. doi:10.1016/j.ejphar.2008.09.026

116: Koob, G. F., Mason, B. J., Witte, P. D., Littleton, J., & Siggins, G. R. (2002).

Potential Neuroprotective Effects of Acamprosate. Alcoholism: Clinical and

Experimental Research, 26(4), 586-592. doi:10.1097/00000374-200204000-00021

117: Doeppner, T. R., Pehlke, J. R., Kaltwasser, B., Schlechter, J., Kilic, E., Bähr, M., &

Hermann, D. M. (2015). The Indirect NMDAR Antagonist Acamprosate Induces

Postischemic Neurologic Recovery Associated with Sustained Neuroprotection and

Neuroregeneration. Journal of Cerebral Blood Flow & Metabolism, 35(12), 2089-2097. doi:10.1038/jcbfm.2015.179

118: Mason, B., Goodman, A., Chabac, S., & Lehert, P. (2006). Effect of oral acamprosate on abstinence in patients with alcohol dependence in a double-blind, placebo-controlled trial: The role of patient motivation. Journal of Psychiatric Research,

40(5), 383-393. doi:10.1016/j.jpsychires.2006.02.002

66

119: Anton, R.F., O’Malley, S.S,… Williams, L.D. (2007). Combined Pharmacotherapies and Behavioral Interventions for Alcohol Dependence: The COMBINE Study: A

Randomized Controlled Trial. Yearbook of Psychiatry and Applied Mental Health, 2007,

95-96. doi:10.1016/s0084-3970(08)70391-8

120: Mann, K., Lemenager, T., Hoffmann, S., Reinhard, I., Hermann, D., Batra, A., . . .

Anton, R. F. (2012). Results of a double-blind, placebo-controlled pharmacotherapy trial in alcoholism conducted in Germany and comparison with the US COMBINE study.

Addiction Biology, 18(6), 937-946. doi:10.1111/adb.12012

121: Donoghue, K., Elzerbi, C., Saunders, R., Whittington, C., Pilling, S., & Drummond,

C. (2015). The efficacy of acamprosate and naltrexone in the treatment of alcohol dependence, Europe versus the rest of the world: A meta-analysis. Addiction, 110(6),

920-930. doi:10.1111/add.12875

122: Rösner, S., Hackl-Herrwerth, A., Leucht, S., Lehert, P., Vecchi, S., & Soyka, M.

(2010). Acamprosate for alcohol dependence. Cochrane Database of Systematic Reviews. doi:10.1002/14651858.cd004332.pub2

123: Rösner, S., Leucht, S., Lehert, P., & Soyka, M. (2007). Acamprosate supports abstinence, Naltrexone prevents excessive drinking: Evidence from a meta-analysis with unreported outcomes. Journal of Psychopharmacology, 22(1), 11-23. doi:10.1177/0269881107078308

124: Roos, C. R., Mann, K., & Witkiewitz, K. (2016). Reward and relief dimensions of temptation to drink: Construct validity and role in predicting differential benefit from acamprosate and naltrexone. Addiction Biology, 22(6), 1528-1539. doi:10.1111/adb.12427

67

125: Maisel, N. C., Blodgett, J. C., Wilbourne, P. L., Humphreys, K., & Finney, J. W.

(2012). Meta-analysis of naltrexone and acamprosate for treating alcohol use disorders:

When are these medications most helpful? Addiction, 108(2), 275-293. doi:10.1111/j.1360-0443.2012.04054.x

126: Gueorguieva, R., Wu, R., Tsai, W., O’Connor, P. G., Fucito, L., Zhang, H., &

O’Malley, S. S. (2015). An analysis of moderators in the COMBINE study: Identifying subgroups of patients who benefit from acamprosate. European

Neuropsychopharmacology, 25(10), 1586-1599. doi:10.1016/j.euroneuro.2015.06.006

127: Cano-Cebrián, M. J., Zornoza-Sabina, T., Guerri, C., Polache, A., & Granero, L.

(2003). Local acamprosate modulates dopamine release in the rat nucleus accumbens through NMDA receptors: An in vivo microdialysis study. Naunyn-Schmiedebergs

Archives of Pharmacology, 367(2), 119-125. doi:10.1007/s00210-002-0674-3

128: Chau, P., Stomberg, R., Fagerberg, A., Soderpalm, B., & Ericson, M. (2010).

Glycine Receptors Involved in Acamprosate’s Modulation of Accumbal Dopamine

Levels: An In Vivo Microdialysis Study. Alcoholism: Clinical and Experimental

Research, 34(1), 32-38. doi:10.1111/j.1530-0277.2009.01062.x

129: Chau, P., Lidö, H. H., Söderpalm, B., & Ericson, M. (2018). Acamprosates ethanol intake-reducing effect is associated with its ability to increase dopamine. Pharmacology

Biochemistry and Behavior, 175, 101-107. doi:10.1016/j.pbb.2018.09.009

130: Schneider, U., Wohlfarth, K., Schulze-Bonhage, A., Haacker, T., Müller-Vahl, K. R.,

Zedler, M., . . . Emrich, H. M. (1999). Effects of acamprosate on memory in healthy young subjects. Journal of Studies on Alcohol, 60(2), 172-175. doi:10.15288/jsa.1999.60.172

68

131: Ralevski, E., Obrien, E., Jane, J. S., Dean, E., Dwan, R., & Petrakis, I. (2011).

Effects of Acamprosate on Cognition in a Treatment Study of Patients With

Schizophrenia Spectrum Disorders and Comorbid Alcohol Dependence. The Journal of

Nervous and Mental Disease, 199(7), 499-505. doi:10.1097/nmd.0b013e3182214297

132: Allen, D. N., Goldstein, G., & Aldarondo, F. (1999). Neurocognitive dysfunction in patients diagnosed with schizophrenia and alcoholism. Neuropsychology, 13(1), 62-68. doi:10.1037/0894-4105.13.1.62

133: Nixon, S. J., Hallford, H., & Tivis, R. D. (1996). Neurocognitive function in alcoholic, schizophrenic, and dually diagnosed patients. Psychiatry Research, 64(1), 35-

45. doi:10.1016/0165-1781(96)02911-3

134: Pietrzak, B., & Czarnecka, E. (2005). Effect of the combined administration of ethanol and acamprosate on rabbit EEG. Pharmacol Rep, 57(1), 61-69.

135: Saivin, S., Hulot, T., Chabac, S., Potgieter, A., Durbin, P., & Houin, G. (1998).

Clinical Pharmacokinetics of Acamprosate. Clinical Pharmacokinetics, 35(5), 331-345. doi:10.2165/00003088-199835050-00001

136: Zornoza, T., Cano-Cebrián, M. J., Hipólito, L., Granero, L., & Polache, A. (2006).

Evidence of a flip-flop phenomenon in acamprosate pharmacokinetics: An in vivo study in rats. Biopharmaceutics & Drug Disposition, 27(7), 305-311. doi:10.1002/bdd.513

137: Mason, B. (2002). A Pharmacokinetic and Pharmacodynamic Drug Interaction

Study of Acamprosate and Naltrexone. Neuropsychopharmacology, 27(4), 596-606. doi:10.1016/s0893-133x(02)00368-8

69

138: Kalk, N. J., & Lingford-Hughes, A. R. (2014). The clinical pharmacology of acamprosate. British Journal of Clinical Pharmacology, 77(2), 315-323. doi:10.1111/bcp.12070

139: Rosenthal, R. N., Gage, A., Perhach, J. L., & Goodman, A. M. (2008). Acamprosate:

Safety and Tolerability in the Treatment of Alcohol Dependence. Journal of Addiction

Medicine, 2(1), 40-50. doi:10.1097/adm.0b013e31816319fd

140: Boismare, F., Daoust, M., Moore, N., Saligaut, C., Lhuintre, J., Chretien, P., &

Durlach, J. (1984). A homotaurine derivative reduces the voluntary intake of ethanol by rats: Are cerebral GABA receptors involved? Pharmacology Biochemistry and Behavior,

21(5), 787-789. doi:10.1016/s0091-3057(84)80020-9

141: Berton, F., Francesconi, W. G., Madamba, S. G., Zieglgansberger, W., & Siggins, G.

R. (1998). Acamprosate Enhances N-Methyl-D-Apartate Receptor-Mediated

Neurotransmission But Inhibits Presynaptic GABAB Receptors in Nucleus Accumbens

Neurons. Alcoholism: Clinical and Experimental Research, 22(1), 183-191. doi:10.1111/j.1530-0277.1998.tb03636.x

142: Pierrefiche, O., Daoust, M., & Naassila, M. (2004). Biphasic effect of acamprosate on NMDA but not on GABAA receptors in spontaneous rhythmic activity from the isolated neonatal rat respiratory network. Neuropharmacology, 47(1), 35-45. doi:10.1016/j.neuropharm.2004.03.004

143: Daoust, M., Legrand, E., Gewiss, M., Heidbreder, C., Dewitte, P., Tran, G., &

Durbin, P. (1992). Acamprosate modulates synaptosomal GABA transmission in chronically alcoholised rats. Pharmacology Biochemistry and Behavior, 41(4), 669-674. doi:10.1016/0091-3057(92)90210-7

70

144: Boismare, F., Daoust, M., Moore, N., Saligaut, C., Lhuintre, J., & Flipo, J. L. (1986).

Which Gaba receptors are involved in the voluntary ethanol intake by rats? Alcohol

Alcoholism, 21.

145: Zeise, M. L., Kasparov, S., Capogna, M., & Zieglgänsberger, W. (1993).

Acamprosate (calciumacetylhomotaurinate) decreases postsynaptic potentials in the rat neocortex: Possible involvement of excitatory amino acid receptors. European Journal of

Pharmacology, 231 (1), 47-52. doi:10.1016/0014-2999(93)90682-8

146: Madamba, S. G., Schweitzer, P., Zieglgansberger, W., & Siggins, G. R. (1996).

Acamprosate (Calcium Acetylhomotaurinate) Enhances the N-Methyl-d-Aspartate

Component of Excitatory Neurotransmission in Rat Hippocampal CA1 Neurons In Vitro.

Alcoholism: Clinical and Experimental Research, 20(4), 651-658. doi:10.1111/j.1530-

0277.1996.tb01667.x

147: Rammes, G., Mahal, B., Putzke, J., Parsons, C., Spielmanns, P., Pestel, E., . . .

Schadrack, J. (2001). The anti-craving compound acamprosate acts as a weak NMDA- , but modulates NMDA-receptor subunit expression similar to and MK-801. Neuropharmacology, 40(6), 749-760. doi:10.1016/s0028-

3908(01)00008-9

148: Allgaier, C., Franke, H., Sobottka, H., & Scheibler, P. (2000). Acamprosate inhibits

Ca2 influx mediated by NMDA receptors and voltage-sensitive Ca2 channels in cultured rat mesencephalic neurones. Naunyn-Schmiedebergs Archives of Pharmacology, 362(4-

5), 440-443. doi:10.1007/s002100000285

71

149: Popp, R., & Lovinger, D. M. (2000). Interaction of acamprosate with ethanol and on NMDA receptors in primary cultured neurons. European Journal of

Pharmacology, 394 (2-3), 221-231. doi:10.1016/s0014-2999(00)00195-3

150: Grant, K. A., Valverius, P., Hudspith, M., & Tabakoff, B. (1990). Ethanol withdrawal seizures and the NMDA receptor complex. European Journal of

Pharmacology, 176(3), 289-296. doi:10.1016/0014-2999(90)90022-x

151: Kotlinska, J., Biala, G., Rafalski, P., Bochenski, M., & Danysz, W. (2004). Effect of neramexane on ethanol dependence and reinforcement. European Journal of

Pharmacology, 503(1-3), 95-98. doi:10.1016/j.ejphar.2004.09.036

152: Rothan, H. A., Amini, E., Faraj, F. L., Golpich, M., Teoh, T. C., Gholami, K., &

Yusof, R. (2017). NMDA receptor antagonism with novel indolyl, 2-(1,1-Dimethyl-1,3- dihydro-benzo[e]indol-2-ylidene)-malonaldehyde, reduces seizures duration in a rat model of epilepsy. Scientific Reports, 7(1). doi:10.1038/srep45540

153: Farook, J. M., Krazem, A., Lewis, B., Morrell, D. J., Littleton, J. M., & Barron, S.

(2008). Acamprosate attenuates the handling induced convulsions during alcohol withdrawal in Swiss Webster mice. Physiology & Behavior, 95(1-2), 267-270. doi:10.1016/j.physbeh.2008.05.020

154: Tsai, G., Gastfriend, D. R., & Coyle, T. J. (1995). The glutamatergic basis of human alcoholism. American Journal of Psychiatry, 152(3), 332-340. doi:10.1176/ajp.152.3.332

155: Spanagel, R., Pendyala, G., Abarca, C., Zghoul, T., Sanchis-Segura, C., Magnone,

M. C., . . . Albrecht, U. (2005). Erratum: The clock gene Per2 influences the glutamatergic system and modulates alcohol consumption. Nature Medicine, 11(2), 233-

233. doi:10.1038/nm0205-233c

72

156: Dahchour, A., Witte, P. D., Bolo, N., Nédélec, J., Muzet, M., Durbin, P., & Macher,

J. (1998). Central effects of acamprosate: Part 1. Acamprosate blocks the glutamate increase in the nucleus accumbens microdialysate in ethanol withdrawn rats. Psychiatry

Research: Neuroimaging, 82(2), 107-114. doi:10.1016/s0925-4927(98)00016-x

157: Witte, P. D., Littleton, J., Parot, P., & Koob, G. (2005). Neuroprotective and

Abstinence-Promoting Effects of Acamprosate. CNS Drugs, 19(6), 517-537. doi:10.2165/00023210-200519060-00004

158: Kiefer, F., & Mann, K. (2010). Acamprosate: How, Where, and for Whom Does it

Work? Mechanism of Action, Treatment Targets, and Individualized Therapy. Current

Pharmaceutical Design, 16(19), 2098-2102. doi:10.2174/138161210791516341

159: Mason, B. J., & Heyser, C. J. (2009). The neurobiology, clinical efficacy and safety of acamprosate in the treatment of alcohol dependence. Expert Opinion on Drug Safety,

9(1), 177-188. doi:10.1517/14740330903512943

160: Reilly, M. T., Lobo, I. A., Mccracken, L. M., Borghese, C. M., Gong, D., Horishita,

T., & Harris, R. A. (2008). Effects of Acamprosate on Neuronal Receptors and Ion

Channels Expressed in Xenopus Oocytes. Alcoholism: Clinical and Experimental

Research, 32(2), 188-196. doi:10.1111/j.1530-0277.2007.00569.x

161: Spanagel, R., Vengeliene, V., Jandeleit, B., Fischer, W., Grindstaff, K., Zhang,

X., . . . Kiefer, F. (2014). Acamprosate Produces Its Anti-Relapse Effects Via Calcium.

Neuropsychopharmacology, 39(4), 783-791. doi:10.1038/npp.2013.264

162: Degenhardt, L., Charlson, F., Ferrari, A., Santomauro, D., Erskine, H., Mantilla-

Herrara, A., . . . Vos, T. (2018). The global burden of disease attributable to alcohol and drug use in 195 countries and territories, 1990–2016: A systematic analysis for the Global

73

Burden of Disease Study 2016. The Lancet Psychiatry, 5(12), 987-1012. doi:10.1016/s2215-0366(18)30337-7

163: Probst, C., Manthey, J., Merey, A., Rylett, M., & Rehm, J. (2018). Unrecorded alcohol use: A global modelling study based on nominal group assessments and survey data. Addiction, 113(7), 1231-1241. doi:10.1111/add.14173

164: Cash, C., Peacock, A., Barrington, H., Sinnett, N., & Bruno, R. (2015). Detecting impairment: Sensitive cognitive measures of dose-related acute alcohol intoxication.

Journal of Psychopharmacology, 29(4), 436-446. doi:10.1177/0269881115570080

165: Sánchez-Cubillo, I., Periáñez, J., Adrover-Roig, D., Rodríguez-Sánchez, J., Ríos-

Lago, M., Tirapu, J., & Barceló, F. (2009). Construct validity of the Trail Making Test:

Role of task-switching, working memory, inhibition/interference control, and visuomotor abilities. Journal of the International Neuropsychological Society, 15(03), 438. doi:10.1017/s1355617709090626

166: Shokri-Kojori, E., Tomasi, D., Wiers, C. E., Wang, G., & Volkow, N. D. (2016).

Alcohol affects brain functional connectivity and its coupling with behavior: Greater effects in male heavy drinkers. Molecular Psychiatry, 22(8), 1185-1195. doi:10.1038/mp.2016.25

167: Grange, J. A., Stephens, R., Jones, K., & Owen, L. (2015). The Effect of Alcohol

Hangover on Choice Response Time. SSRN Electronic Journal. doi:10.2139/ssrn.2690770

168: Rajput, P., Jangra, A., Kwatra, M., Mishra, A., & Lahkar, M. (2017). Alcohol aggravates stress-induced cognitive deficits and hippocampal neurotoxicity: Protective

74 effect of melatonin. Biomedicine & Pharmacotherapy, 91, 457-466. doi:10.1016/j.biopha.2017.04.077

169: Hoffmann, S. E., & Matthews, D. B. (2001). Ethanol-Induced Impairments in

Spatial Working Memory Are Not Due to Deficits in Learning. Alcoholism: Clinical and

Experimental Research, 25(6), 856-861. doi:10.1097/00000374-200106000-00011

170: Nowakowska-Domagała, K., Jabłkowska-Górecka, K., Mokros, Ł, Koprowicz, J., &

Pietras, T. (2017). Differences in the verbal fluency, working memory and executive functions in alcoholics: Short-term vs. long-term abstainers. Psychiatry Research, 249, 1-

8. doi:10.1016/j.psychres.2016.12.034

171: Peacock, A., Eastwood, B., Jones, A., Millar, T., Horgan, P., Knight, J., . . . Marsden,

J. (2018). Effectiveness of community psychosocial and pharmacological treatments for alcohol use disorder: A national observational cohort study in England. Drug and Alcohol

Dependence, 186, 60-67. doi:10.1016/j.drugalcdep.2018.01.019

172: Chisholm, D., Moro, D., Bertram, M., Pretorius, C., Gmel, G., Shield, K., & Rehm,

J. (2018). Are the “Best Buys” for Alcohol Control Still Valid? An Update on the

Comparative Cost-Effectiveness of Alcohol Control Strategies at the Global Level.

Journal of Studies on Alcohol and Drugs, 79(4), 514-522. doi:10.15288/jsad.2018.79.514

173: Koeter, M. W., Brink, W. V., & Lehert, P. (2010). Effect of early and late compliance on the effectiveness of acamprosate in the treatment of alcohol dependence.

Journal of Substance Abuse Treatment, 39(3), 218-226. doi:10.1016/j.jsat.2010.06.002

174: Fuster, J., Willey, T., Riley, D., & Ashford, J. (1982). Effects of ethanol on visual evoked responses in monkeys performing a memory task. Electroencephalography and

Clinical Neurophysiology, 53(6), 621-633. doi:10.1016/0013-4694(82)90138-9

75

175: D'Esposito, M. (2007). From cognitive to neural models of working memory. Philos

Trans R Soc Lond B Biol Sci, 29;362(1481), 761-762. doi:10.1098/rstb.2007.2086

176: Charlet, K., Beck, A., Jorde, A., Wimmer, L., Vollstädt-Klein, S., Gallinat, J., . . .

Heinz, A. (2013). Increased neural activity during high working memory load predicts low relapse risk in alcohol dependence. Addiction Biology, 19(3), 402-414. doi:10.1111/adb.12103

177: Fatovich, D. M. (2016). The inverted U curve and emergency medicine:

Overdiagnosis and the law of unintended consequences. Emergency Medicine Australasia,

28(4), 480-482. doi:10.1111/1742-6723.12588

178: Porrino, L. J., Daunais, J. B., Rogers, G. A., Hampson, R. E., & Deadwyler, S. A.

(2005). Facilitation of Task Performance and Removal of the Effects of Sleep

Deprivation by an (CX717) in Nonhuman Primates. PLoS Biology, 3(9). doi:10.1371/journal.pbio.0030299

179: Hampson, R. E., España, R. A., Rogers, G. A., Porrino, L. J., & Deadwyler, S. A.

(2008). Mechanisms underlying cognitive enhancement and reversal of cognitive deficits in nonhuman primates by the ampakine CX717. Psychopharmacology, 202(1-3), 355-369. doi:10.1007/s00213-008-1360-z

76

Christopher A. Johnson Permanent Address: 730 Walnut Forest Rd, Apt C. Winston-Salem, NC 27103

(815) 715-3370 EDUCATION

GRADUATE: Wake Forest University School of Medicine August 2017-May 2019 Master of Science - Neuroscience

UNDERGRADUATE: University of Illinois at Urbana-Champaign August 2010-May 2014 Bachelor of Science - Psychology

RELATED ACTIVITIES Animal Lab Work Worked with rat and non-human primates in a lab setting during graduate work. Presentations/Community Outreach Presented posters at the annual Society for Neuroscience conferences (2017/2018). Presented neuroscience topics to the community at various public outlets. Scientific Writing Prepared writing for posters, theses, and scientific papers.

RESEARCH INTERESTS

Brain-computer interfaces (BCIs), Neurorehabilitation, EEG, Neurodiagnostics

PROFESSIONAL WORK EXPERIENCE

Biotronic Neuronetwork/Nuvasive Clinical Services

Neurophysiologist/Intraoperative Neuromonitoring January 2015-May 2017

CERTIFICATIONS

CNIM Certified 2016-2017

77