Emotion Processing and Sociability in GHB
Users
Assessing susceptibility to negative emotional valence in GHB users and non-GHB users using
fMRI
N. Polderman; 5961343
Master thesis Brain & Cognition, Psychology, University of Amsterdam Amsterdam Institute for Addiction Research, Amsterdam Medical Center Supervisors: Marlies Vissers, MSc (UvA) and Dr. Guido van Wingen (AMC) 30 October 2015
________________________________________________________________________________ ABSTRACT
Introduction: GHB, a GABAʙ and GHB agonist, is a highly addictive drug which recidivism rate is twice as high as other drugs. Yet, its underlying addictive mechanisms are unclear. Evidence suggests that GHB leads to depletion of oxytocin systems, as well as depressed GABAergic inhibition, which both cause neuronal excitability in amygdala. As amygdala dysfunction affects emotion processing and sociability, it could be an emotional component maintaining or provoking GHB dependence. Therefore, the aim of the study was to investigate the relationship between GHB and emotion processing and sociability.
Methods: Emotion and social processing was examined in GHB users (n=14) and matched controls (n=10). The depression, anxiety and stress scale (DASS21) was used for subjective measurement of negative emotions. fMRI and the Hariri emotion recognition task were used to study amygdala response to faces with negative emotional valence.
Results: GHB users showed significant more negative emotions, but were not more susceptible to negative face expressions than controls. A non-significant trend towards a linear relationship between quantity of GHB and Anxiety and Stress was found. Accordingly we found a trend indicating that high anxiety and stress is accompanied by susceptibility to negative face expressions in GHB-users.
Conclusion: Results should be interpreted with caution due to small sample size, but alterations in emotion and social processing due to amygdala dysregulation may reflect an addictive emotional component specific to GHB that may contribute to, but is not decisive for, developing GHB dependence.
1 INTRODUCTION
Gamma-hydroxybutyric acid (GHB) is an endogenous substance and is found at low concentrations in the brain. Low doses of GHB increases glutamate levels through GHB receptors (Castelli et al., 2003), while at higher doses GHB binds to GABAʙ receptors and increases GABA release (Andriamampandry et al., 2007; Gobaille et al., 1999). Moreover, GHB influences dopamine release: in low doses it increases dopaminergic cells firing via the GHB receptor, whereas higher doses inhibit dopaminergic firing via GABAʙ receptors (van Amsterdam et al., 2012).
GHB was first developed to serve as an anesthetic in the early 1960s (Laborit, 1964), but due to its negative side effects it is no longer used as an anesthetic. Nowadays GHB is still clinically applied to reduce sleeping problems in narcolepsy (Boscolo-Berto et al., 2012). In addition, since the 1990s GHB became increasingly popular as a recreational drug (Brunt et al., 2014). Feelings enhanced by GHB are euphoria, well-being, relaxation, sociability, enjoyment of dancing, and sexuality (Stein et al., 2010; Korf et al., 2014).
1.1. Characteristics of GHB users
The most problems that occur with GHB seem to have shifted from the party scene in the cities to more rural parts of the Netherlands. In these areas GHB users are more often addicted compared to the recreational users in the cities. The addicted GHB users usually have no day-time activities and/or daily rhythm, have low education levels, often do not work or go to school and are poly-drug users (Voorham & Buitenhuis, 2012; Brunt et al., 2013).
Furthermore, GHB is regularly used to suppress negative feelings. The main reasons why people start using are for better sleeping, forgetting problems, euphoria, sedation, and being more sociable (Voorham & Buitenhuis, 2012; Brunt et al., 2013). In most cases, addiction to GHB is accompanied with psychological disorders. A group of 229 patients treated for GHB addiction reported complaints such as depression, anxiety and stress. Moreover, users often experience problems quitting the use of GHB, and the majority falls back into addiction quickly after their detox period (Dijkstra et al., 2013).
1.2. Effects of GHB on emotion
It is established that GHB quickly causes dependence, which can lead to withdrawal effects such as tremors, insomnia, vomiting and in severe cases hallucinations and delusions (van Noorden et al., 2010). The use of GHB is often continued to avoid these withdrawal effects (Dijkstra et al., 2013). Even after a detoxification period which involves the gradual discontinuation of GHB, the chance of relapsing is high: 44% of the patients in the Netherlands needed a second intervention, twice as much as the average of other illicit drugs (Mol, Wisselink, Kuijpers & Dijkstra, 2014). The study of Dijkstra et al. (2013) indicates that GHB users experience a variety of emotional problems, and it is one of the addictions that accompany the most secondary problems (Mol et al., 2014). This might indicate an emotional component maintaining the addictive effects. It is suggested that acute GHB administration elicits positive emotional and social effects in humans, either indirectly by increasing hormones such as oxytocin, or directly via GHB/GABAʙ receptors. Hence, GHB might be used to suppress negative emotions through its acute positive effect, making people with pre-existing emotional problems more vulnerable. On the other hand, it is also a possibility that discontinuation of GHB use after a profound time of using leads to opposite effects as a result of
alterations in oxytocin or GHB/GABAʙ systems. Nonetheless, both possibilities may explain the high rate of emotional problems accompanying GHB addiction.
1.3. Regulation of amygdala through oxytocin and GABAʙ
For it is suggested that the acute effect of GHB elicits positive emotional and social effects through oxytocin and GABAʙ (Bosch et al., 2015), it is a possibility these effects are regulated via the amygdala. Firstly, the amygdala is important in emotional and social processing; for instance, it regulates negative emotions such as anger and fear, as well as the evaluation of the expression of emotion in others (Ferguson et al., 2001). Both processes contribute to the emotional well-being of a person. People who experience emotional problems are more susceptible for recognizing expressions of anger and fear in others, which is represented by elevated amygdala activity (Hariri, Bookheimer & Mazziotta, 1999). Moreover, the decrease of amygdala responses to stimuli possibly reflects reduced uncertainty about the predictive value of a social stimulus, thereby facilitating social approach behavior (Domes et al., 2007). This indicates that increased amygdala responses can facilitate social avoiding behavior; which again facilitates addiction. Hence, amygdala can either suppress negative emotions through low activity, or elicit them through high activity.
Secondly, both oxytocin and GABAʙ affects amygdala functioning. Oxytocin, a hormone and neuropeptide that is important for sociability, also mediates anxiety and stress via the amygdala. It is associated with feelings of trust due to the positive effect of oxytocin on stress levels; the more oxytocin, the less stress (Neumann et al., 2000). Moreover, the administration of oxytocin reduces amygdala activity when confronted with angry and fearful faces, and thus also reduces susceptibility to negative stimuli (Domes et al., 2007). If using GHB will heighten oxytocin levels, it might reduce amygdala activity and elicit a positive effect on emotional well-being. Furthermore, GABA acts as the main inhibitory neurotransmitter in the brain and has a key role in inhibiting amygdala activity, again preventing excessive reaction to negative stimuli (Liu et al., 2014). As GHB also functions as a GABAʙ agonist, this too might reduce the susceptibility to negative stimuli. While the acute effects are positive, prolonged use of GHB might lead to alterations in brain processes, perhaps causing lasting amygdala dysregulation and thus eliciting emotional problems. Therefore, either GHB can lead to dysregulation of amygdala making its users susceptible for addiction and emotional problems, or pre-existed amygdala dysregulation can lead to the use of GHB and addiction. Nonetheless, amygdala dysregulation might be the emotional component that explains the high number of relapses.
1.3.1. Pre-existing amygdala dysregulation
As mentioned earlier, it is possible that amygdala dysregulation might be a reason to start using GHB. Namely, it is suggested that alcohol dependence is partly mediated by pro- and antistress peptides in amygdala (alcohol acts on the GABAᴀ receptors, and thus one of the few substances relatively comparable to GHB). These peptides can either reduce anxiety and stress via antistress peptides (for instance, neuropeptide Y), or enhance stress via prostress peptides (for instance, corticotropin-releasing factor). Evidence from human genetics data shows that increased sensitivity to stress may be associated with susceptibility for dependence. Moreover, people with increased sensitivity to stress are likelier to prefer GABAergic substances that increase GABA release, and this craving is reduced by blockade of prostress peptides (Gilpin, Herman & Roberto, 2015). This suggests
that naturally stressed people are more likely to use GHB, increasing the chance of incurring even more stress by affecting amygdala functioning.
1.3.2. Influence of oxytocin on amygdala functioning
Besides pre-existing emotional problems due to amygdala dysregulation, perhaps the effect of GHB on oxytocin also incurs susceptibility to negative emotions. For instance, an animal study on the lasting adverse effects of GHB showed that sociability in rats was impaired for several weeks after GHB use, and the reduced social interaction indicated GHB-withdrawal induced anxiety (Nieuwenhuijzen et al., 2010). It was argued that the emotional deficits after GHB administration were a consequence of neuroadaptations in the brain oxytocin systems. According to McGregor and Bowen (2012), these neuroadaptations might drive drug seeking and behavioral changes due to lower oxytocin levels. Moreover, oxytocin is linked to drug-induced changes in glutamatergic transmission, and GHB affects glutamate in the hippocampal area (van Nieuwenhuijzen, McGregor, Chebib & Hunt, 2014). Hence, it is not unlikely that GHB use influences oxytocin systems and consequently affects emotional and social behavior of GHB users.
1.3.3. Influence of GABAergic disinhibition on amygdala functioning
Finally, another mechanism that may contribute to an emotional addictive component is the consequence of GHB on GABAʙ systems. GABAʙ agonists such as GHB may cause desensitization and poorer functioning of GABAʙ receptors when use is discontinued (Keegan et al., 2015). For instance, it was found that a decrease in GABAergic transmission, i.e. GABAergic disinhibition, occurred during alcohol withdrawal, but only when GABAʙ receptors were affected due to neuroadaptations (Gilpin et al., 2015). Unlike alcohol, GHB alters GABAʙ receptors directly, making it perhaps more accessible for causing neuroadaptations than alcohol. This poorer functioning of GABAʙ receptors leads to facilitation of amygdala activity through GABAergic disinhibition, causing negative effects on emotion and social processing.
Those negative effects on emotion and social processing were examined in animal studies, verifying that GABAergic disinhibition led to neuronal excitability in amygdala and the emergence of fear conditioning and panic-like behavior (Manzanares, Isoardi, Carrer & Molina, 2005; Pérez de la Mora et al., 2007). Moreover, GABAergic disinhibition can be induced by stress (Manzanares et al., 2005; Liu et al., 2014), implying that stress of GHB withdrawal might be an aggravating factor in amygdala dysfunction. It was indeed found that when rats were in ethanol-withdrawal, GABAergic disinhibition occurred due to attenuation or suppression of feedback inhibition caused by blockage of GABAᴀ receptor (Isoardi, Bertotto, Martijena, Molina & Carrer, 2007). Therefore, the use of GHB may have lasting adverse effects on emotional and social processing, decreasing emotional well-being as GHB use is discontinued and subsequently increasing the chance on relapse.
1.4. Research questions and hypotheses
While one might start using GHB as a consequence of emotional problems, its effects on oxytocin and GABAʙ systems might maintain and worsen these problems. As the precise effects of GHB are unknown, it remains unclear whether GHB acts as a more potent drug in causing alterations in emotion and social processes compared to other illicit drugs. Additionally, there is no improvement of emotion recognition and amygdala functioning across time of absence (
Fernández-Serrano et al., 2010; Liu et al., 2014), indicating that the problem will not resolve itself. Therefore, the main question in this study was whether GHB affects emotion processing: are GHB users more susceptible to negative emotions than people who do not use GHB?
Theoretically, if GHB users report “being more sociable” as a reason to use GHB (Brunt et al., 2013), while on the other hand GHB use leads to anxiety and stress when discontinued, possible prolonged consequences on emotion processing may reflect an emotional addictive component. We studied emotion processing based on two different aspects; 1) the subjective experience of negative emotions and 2) the susceptibility to negative emotional valence. Therefore, we questioned 1) whether people who use GHB experience more depression, anxiety and stress compared to people who do not use GHB, and 2) whether people who use GHB show higher amygdala activity when confronted with negative emotional expressions compared to those who do not use GHB. Furthermore, we investigated 3) if anxiety and stress, but not depression, in GHB users is related to the quantity of GHB consumption. With this knowledge, eventually more insight is gained into the neural changes induced by GHB. This can be used to establish better treatments, for instance with oxytocin administration (McGregor, Callaghan & Hunt, 2008), stress reducing medication (Gilpin et al., 2015) or GABA restoring agents (Liu et al., 2014).
Based on previous research we hypothesized that 1) GHB users experience more depression, anxiety and stress than non-GHB using subjects. If GHB users score higher than non-GHB users on a questionnaire measuring depression, anxiety and stress, it indicates that GHB users experience more negative emotions. Furthermore, we hypothesized that 2) GHB users show more activity in the amygdala when presented with angry and fearful faces on an emotion-recognition task than people who do not use GHB. If GHB users show elevated amygdala activity when confronted with anxious and/or angry faces compared to non-GHB users, it is an indication that GHB users are more susceptible for negative emotions such as anxiety and stress. Accordingly, it was hypothesized that 3) the quantity of GHB consumption is higher for subjects with high anxiety and stress, but not depression, compared to low anxious and stressed subjects. If the amygdala is the possible origin of an emotional addictive component, the amount of GHB consumption should be specifically related to anxiety and stress. Thus, if there is a linear relationship between amount and duration of GHB used and anxiety and stress, it indicates that the more GHB used the more anxiety and stress subjects experience.
2 METHODS
2.1. Subjects
Our sample existed of a subgroup of a comprehensive study. A total of 28 male subjects were examined, consisting of a group GHB users (N=16) and a matched control group (N=12). Both groups were matched on age, smoking, alcohol use and use of drugs other than GHB. Furthermore, the groups were matched on education since more years of education correlates with better emotion recognition (Fernández-Serrano et al., 2010).
Subjects were recruited via rehabilitation clinics, drugs education platform Unity, through paper and internet advertisement, and using the snow-ball sampling approach. Subjects either received a 50 euro gift card (subjects from clinics) or 50 euro (remaining subjects) for participating.
2.1.1. Inclusion and exclusion criteria
The inclusion of subjects was based on the following criteria: 1) subjects were males with an age of 18-40 years, 2) subjects in the GHB group had a life time prevalence of GHB use of 25 times or more in the last two years and 3) all subjects provided written informed consent to participate to the study. We excluded 1) subjects with epilepsy, 2) subjects that received general anesthesia for a medical intervention in the last two years and 3) subjects suffering from claustrophobia, presence of non-removable metal objects and use of psychotropic medication. Recent and lifetime use of alcohol, ketamine, speed or other drugs was no exclusion criterion, but was registered.
2.2. Material
2.2.1. Tasks and questionnaires
Emotion processing: to examine amygdala activity, each subject was tested on the Hariri
emotion face-recognition task during fMRI (Hariri et al., 2002). In this task, a trial with a target face and two probe faces were presented to the subject (with duration of 5 seconds each trial). One block consisted of six consecutive trials where the target face was either angry or fearful. The subject was instructed to match the emotional expression of the target face to one of the probe faces by pressing the left or the right key on a button box. During the baseline control task, subjects were presented with either vertical or horizontal ovals or circles (with duration of 5 seconds each trial) and instructed to match the shape of the target to one of the probes. Each block of faces and the control task was presented three times in a pseudo randomized order. For each trial the response accuracy and reaction time data was obtained, with a total of 18 trials (three blocks of six trials). By subtracting the “match emotion” condition from the control condition a contrast was obtained which yields robust amygdala activation in normal subjects (Hariri et al., 2000). The task had a total duration of approximately two and a half minutes.
Depression, anxiety and stress: depression and anxiety are disorders that are commonly
accompanied with GHB dependence (Dijkstra et al., 2013). Therefore the DASS21 is administered, which is a 21-item self-report questionnaire designed to measure depression, anxiety and stress. Each domain has seven items with statements, and patients declare how far these statements are applicable for them concerning the past week. Higher scores indicate more severe complaints.
Drug use and addiction: the first module of the Measurement of Addiction for Triage and
Evaluation (MATE 2.1, 1; Schippers, Broekman & Buchholz, 2011) was used to determine the use of drugs in the recent past and during lifetime. Usage and habit was noted by the examiner on a list with names of various drugs and was answered concerning the past thirty days and the quantity per day. Furthermore, information is gathered about lifetime use, the main drug of abuse and the use of nicotine. Since the MATE-1 does not include GHB use, a separate questionnaire is administered to determine the characteristics of GHB use. The questionnaire is based on a modified GHB questionnaire from the GHB monitor study (Dijkstra et al., 2013).
Demographic information: a questionnaire about demographic information was
administered to identify date of birth and education level.
2.2.2. Magnetic Resonance Imaging (MRI)
The scans were performed on a 3.0 T Philips Ingenia MRI scanner (Philips Healthcare, the Netherlands) at the Amsterdam Medical Centre (AMC). A 32-channel head coil was used to acquire
the images. Head movement was minimized by using foam pillows around the heads of subjects. The fMRI images were acquired with the following parameters: repetition time (TR) = 2000 ms; echo time (TE) = 27 ms; field of view (FOV) = 240 mm (RL; AP), 121.8 mm (FH); voxel size = 3 mm (RL; AP); slice thickness = 3 mm; slice gap = 0.3 mm; number of slices = 37; slice orientation = transverse; matrix size = 80 x 78.
2.3. Procedure
Potential subjects were contacted personally and given an information letter. Within two days subjects had to decide whether they wanted to participate or not. After agreement they were screened on inclusion and exclusion criteria and an appointment was made to attend the experiment at the AMC. Before start of the experimental session, all subjects received written information about the protocol and gave informed consent. Subjects were given the opportunity to ask remaining questions about the study. Subsequently the questionnaires were administered in a fixed order. This took approximately 20 minutes. After completion of the questionnaires, subjects were scanned in the MR scanner. Before the subjects started with the task, a high-resolution anatomic image of the brain with contrast between grey matter, white matter and cerebrospinal fluid (CSF) was made (duration was approximately six minutes). The functional MRI scan was made during the execution of the Hariri emotion-recognition task. Stimuli were presented via a projector viewed through a mirror by the subjects in the scanner. The subjects gave feedback by pressing buttons on an MR compatible response box. After completion of the tests subjects received their reward.
2.4. Statistical analyses
Analysis of demographic, drug use and DASS data was performed using a standard statistical package (SPSS, IBM, New York, USA). A Shapiro-Wilk test was performed to control if the data was normally distributed and a Levene’s test to control if the assumption for homogeneity of variances was met. Due to the small sample size and abnormally distributed data, a non-parametric Mann-Whitney U test for small sample sizes and violation of assumptions was used to identify possible differences in drug use and DASS scores between the groups. For education Fisher’s Exact Test for small sample sizes was used to analyze group differences. Linear relationships between age and GHB use, DASS and GHB use, and other illicit drugs that differ significantly between the groups, were analyzed with a regression analysis.
Imaging data was analyzed using Statistical Parametric Mapping software (SPM8, Wellcome Trust Centre for Neuroimaging, London, UK). This included spatial and temporal pre-processing (realignment, co-registration with the structural MRI image and segmentation for normalization to an MNI template), followed by analysis of individual subjects in the context of the General Linear Model, using delta functions convolved with a synthetic hemodynamic response function as regressors.
Next, contrast images were fed into second-level analysis with an independent samples t-test to assess differences between the two groups. Therefore, the contrast emotion recognition minus baseline condition (leaving only activity specific for the emotion recognition condition) was used to detect amygdala response to angry and fearful faces for the GHB-group and the Matched Control (MC) group on the emotion recognition task. To identify significant voxels activated by angry
and fearful faces, a statistical image for the contrast was produced by performing a t-statistic with a threshold of p < 0.05, corrected for multiple comparisons with Familywise Error rate (FWE), subsequently applying an image search mask of the amygdala (from the Automated Anatomical Labeling (AAL) atlas). This was done for 1) GHB-group + MC-group to control whether the task correctly represented amygdala activity and 2) GHB-group > MC-group to detect activity patterns specific to the GHB-group. Exploratory whole brain analysis was performed with a threshold of p < 0.01 (uncorrected), again for GHB-group > MC-group as well for MC-group > GHB-group to detect significant activity for the GHB-group and MC-group, respectively.
Finally, we assessed differences between high vs. low anxiety and stress in GHB subjects. Contrast images (emotion recognition > baseline condition) for high Anxiety and Stress GHB subjects and low Anxiety and Stress GHB subjects were fed into an independent samples t-test. To identify significant voxels activated by angry and fearful faces in the high Anxiety and Stress group, a statistical image for high Anxiety and Stress > low Anxiety and Stress was produced by performing a t-statistic with a threshold of p = 0.01 (uncorrected) and subsequently applied with an image search mask of the amygdala (AAL).
3 RESULTS
3.1. Sample characteristics
Four subjects of the total sample (N=28) had to be excluded, due to incorrect MR scanner parameters (one subject), incorrect data transfer (one subject) and insufficient time to complete the task (two subjects). The remaining subjects (N=24) were assigned to a GHB-group (n=14; age M=27, SD=4.6) and a MC-group (n=10; age M=22, SD=2.7). A linear regression analysis was used to control if there was a relationship between age and GHB use and between age and DASS score. It was found that age was not a significant predictor for GHB use, F(1,12), .237, p = .635, or for total DASS score,
F(1,22), 3.510, p = .074. This establishes that age was not a significant factor in group differences,
although there is a trend in the linear relationship between age and DASS scores, showing higher DASS scores as subjects get older. Fisher’s Exact Test was used to control whether groups differed on education level. This test was used instead of a Chi-Square because 80% of the cells had an expected count less than five, violating assumptions for a Chi-Square. Education did not differ significantly between groups, FET 4.497, p = .325.
We examined group differences in drug use in the past month as well as during the entire lifetime. The data did not met assumptions for normality or equality of variances, which was likely due to the small sample size. Therefore, we used a Mann-Whitney U test to analyze the group differences for the following drugs: alcohol, cannabis, cocaine, stimulants, MDMA and ketamine. Data from one subject on stimulant use was excluded from analysis because the subject reported its use was not recreational. Significant group differences were found for nicotine and stimulants, where GHB-group reported more years used than MC-group. Drug use characteristics and statistics are displayed in Table 1. The GHB-group used GHB for an average of 3 years (SD=3.1), with M=142 ml (SD=489.4) per month and M=12 ml (SD=19) per occasion.
In order to control for possible confounding effects due to significant group differences in years used for nicotine and stimulants, a linear regression analysis was performed to determine whether there was a relationship with total DASS score. Results show that there was no relationship
between stimulants (years used) and total DASS score, F(1,21), .007, p = .936. However, nicotine (years used) did show a linear relationship with DASS score, F(1,22), 12.374, p = .002; the higher the DASS scores, the more years subjects were smoking. Accordingly, it is possible that nicotine use affected depression, anxiety and stress levels, or vice versa.
Table 1. The Mean and Standard Deviations for Drug Use Characteristics for GHB-group and MC-group
GHB-group MC-group statistics
M SD M SD U Z
Use per month
Alcohol (glasses) 72 43 68 51 62 -.469 Nicotine (cigarettes) 234 188 73 100 38.5 -1.847 Cannabis (joints) 5 7 21 31 97.5 1.619 Cocaine (mg.) 771 1119 600 1350 49.6 -1.341 Stimulants (mg.) 529 199 903 684 59.5 -.343 MDMA (mg.) 99 240 170 141 103 2.032 Ketamine (mg.) 346 748 660 1558 69 -.064 Years used** Alcohol 1.5 3 0.7 1.9 62.5 -.491 Nicotine* 7.5 5.9 2 2.9 31.5* -2.318* Cannabis 3.5 4.6 3 3.1 65 -.295 Cocaine 0.2 0.5 0 0.1 57 -1.072 Stimulants* 0.6 0.2 0.1 0 32* -2.267* MDMA 0.5 1.2 0.2 0.3 62.5 -.463 Ketamine 0.1 0.3 0.1 0.2 62.5 -.677 Note. * Significant at p < .05
Note 2. ** Alcohol: number of years > 28 glasses per week; nicotine: number of years daily smoking; other: number of
years weekly use
3.2. Amygdala response to negative emotional valence
In order to check whether the emotion recognition task elicited amygdala activity in subjects when confronted with negative emotional valence, functional imaging data from both groups were analyzed using an independent samples t-test (for contrast emotion recognition > baseline condition). Subsequently, a statistical image was formed by collapsing both groups (at p < .05 FWE corrected, image mask: amygdala (AAL)). This showed significant activity in both left (t = 6.63, p = .000) and right amygdala (t = 7.48, p = .000). The MNI-space coordinates for right amygdala were x= 24, y= -6, z= -16 and coordinates for left amygdala were x= -20, y= -8, z= -16. These coordinates are consistent with previous findings using the Hariri emotion-recognition task (Hariri et al., 2000; Hariri et al., 2002). This confirms that the task is a reliable tool for detecting amygdala activity, and allowed us to use it for analyzing group differences in amygdala reaction to angry and fearful faces between GHB-group and MC-group.
3.3. Group differences in susceptibility to negative emotional valence 3.3.1. Depression, anxiety and stress scale
To determine if GHB users had more complaints of depression, anxiety and stress than non-GHB users, the scores on each subscale of the DASS, namely; Depression (DEP), Anxiety (ANX), Stress
(STR) as well as ANX and STR combined (ANX+STR) and the total DASS scores (DAS), were compared between the GHB-group and MC-group. Due to our small sample size and violation of assumptions, the Mann-Whitney U test was used to analyze the data. A one-tailed test was performed as we expected that the GHB-group scored higher than the MC-group on all scales. Significant outliers were removed from subscales DEP (2 subjects), STR (1 subject) and ANX+STR (2 subjects).
We found that the scores of GHB-group subjects were not significantly higher than MC-group subjects on ANX, U = 53, Z = -1.021, p = .171, r = -.21, nor on STR, U = 51.5, Z = -.858, p = .205,
r = -.18. Thus, GHB users did not have more anxiety or stress than non-GHB users, which was against
our expectations. Nonetheless, a trend was found for Anxiety and Stress; GHB-group subjects had higher scores than MC-group subjects, U = 36, Z = -1.607, p = .061, r = -.34. A similar trend was found for Depression, again with higher scores in GHB-group than in MC-group, U = 35, Z = -1.598, p = .063,
r = -.34. Although not significant at a confidence interval of α = 0.05, effect size r was between 0.3
and 0.5 for both scales, reflecting a medium sized effect. This was relatively high given the small sample size. These results were in accordance with our expectations and confirm that GHB users experience more anxiety and stress, as well as more depression, than non-GHB users. Finally, results showed that GHB-group subjects scored significantly higher on DAS compared to MC-group subjects,
U = 41, Z = -1.704, p = .048, r = -.35. Again, a medium sized effect was found. Thus, GHB users also
showed more depression, anxiety and stress together than subjects in the MC-group, which confirmed our expectations that GHB users experience more emotional problems compared to non-GHB users. Table 2 shows the mean scores and standard deviations for non-GHB-group and MC-group on the DASS and its subscales.
Table 2. Mean Scores and Standard Deviations on Subscales and Total DASS for GHB-group and MC-group
GHB-group MC-group M SD n M SD n DEP 5.85 1.42 13 2.67 1.05 9 ANX 4.14 0.99 14 2.60 0.9 10 STR 7.85 2.04 13 3.8 1.13 10 ANX + STR 10.67 1.99 12 6.4 1.26 10 DAS 20.29 3.7 14 11.6 3.25 10
3.3.2. Emotion recognition task
In order to examine if GHB users and non-GHB users differed in amygdala response to negative emotional valence, we examined whether the GHB-group had more amygdala activity when confronted with angry and fearful faces compared to MC-group. To this end, functional imaging data from MC-group was subtracted from GHB-group functional imaging data (GHB-group > MC-group; at
p < .005 uncorrected, mask image: amygdala (AAL)), leaving only brain activity specific for
GHB-group. However, unlike expectations, no significant voxels were found, indicating that there was no difference in amygdala response to negative emotional valence between GHB users and non-GHB users.
Nevertheless, whole brain analysis for GHB-group functional imaging data (obtained with GHB-group > MC-group; at p < .01 uncorrected) showed an uncorrected significant activity on cluster level in the right superior frontal gyrus (rSFG) with MNI-space coordinates x= 6, y= 42, z= 54 (K = 839,
multiple comparisons, though it still represented a trend. Moreover, given the small sample size, this unpredicted activity in the rSFG is a notable result since this activity is higher for GHB-group than MC-group, perhaps representing a relationship with GHB use. In the discussion we evaluate possible explanations for this effect. Figure 1 shows the observed activity and statistics for the whole brain analysis. Concluding, the significant activity found in the rSFG might represent a process specific for GHB users.
Finally, a whole brain analysis for the functional imaging data from MC-group was performed, by subtracting GHB-group data from MC-group data (MC-group > GHB-group; at p < .01 uncorrected), which showed no significant voxels or trends after FWE corrections. This was conform expectations. Thus, non-GHB users did not differ in brain activity from GHB users when confronted with negative emotional valence.
Figure 1. Observed activity with threshold p < .01 uncorrected (p = .096 FWE corrected) in the right Superior Frontal Gyrus (rSFG) given by the contrast Emotion Recognition minus Baseline Condition for GHB-group > MC-group.
MNI-space coordinates were x= 6, y= 42, z= 54 with a cluster size of 839 voxels. 3.4 Linear relationships between GHB use and stress and anxiety
Given the possibility that stress and anxiety are consequences of amygdala dysregulation (Ferguson et al., 2001), the fact that we found a trend regarding higher Anxiety and Stress scores for the GHB-group is an interesting finding. It is not unlikely that the amount and duration of GHB use affects amygdala functioning, resulting in higher anxiety and stress. Therefore, in order to examine the existence of a relationship between the quantity of GHB use and the experience of anxiety and stress, we used a linear regression analysis to analyze total ml GHB per month and years using GHB (GHBtotal) and Anxiety and Stress scores. In order to compare GHBmonth and GHByear, data was transformed to a Z-score because the values did not have the same dimension.
Results showed a trend towards a linear relationship between GHBtotal and ANX+STR scores, F(2,21), 2.798, p = .084. This was according our expectations and showed that the more and longer GHB was used, the higher anxiety and stress levels were. In order to investigate whether this relationship is specific for anxiety and stress only, or if depression also showed a relationship with the quantity of GHB use, we analyzed the linear relationship between GHBtotal and DAS scores. Conversely, there was no longer a significant relationship, F(2,21), 1.631, p = .219, suggesting that anxiety and stress are specifically related to the amount and duration of GHB use, and not depression.
3.5. Amygdala activity in high anxiety and stress GHB users
Since we found that higher anxiety and stress showed a possible relationship with GHB use, while on the other hand no significant amygdala reaction to negative emotional valence was found in GHB users, it is a possibility that amygdala dysregulation only exists in GHB users with high anxiety and stress. The amount and duration of GHB use showed a relationship with anxiety and stress, potentially suggesting that this is reflected in amygdala functioning. Therefore, we examined whether subjects with high anxiety and stress showed more amygdala activity when confronted with negative emotional valence compared to subjects with low anxiety y and stress.
The subjects from GHB-group were divided in a high Anxiety and Stress group (ANX+STR score > 9; n=8), and a low Anxiety and Stress group (ANX+STR score < 9; n=6). The functional imaging data of low ANX+STR group was subtracted from function imaging data of high ANX+STR group to identify significant voxels specific for the high ANX+STR group (high ANX+STR group > low ANX+STR group; at p < .01 uncorrected, mask image: amygdala (AAL)). Results showed a trend towards activity in both left amygdala (t = 3.52, p = .055 FWE corrected; x = -22, y = -8, z = -12 (MNI-space)) and right amygdala (t = 3.39, p = .072 FWE corrected; x = 22, y = -4, z = -12 (MNI-space)). These results confirm that GHB users with high anxiety and stress showed higher amygdala activity when confronted with negative emotional valence than GHB users with low anxiety and stress, which was in accordance with our expectations. Figure 2 shows the observed amygdala activity and statistics for high Anxiety and Stress in GHB-group subjects.
Figure 2. Observed activity with threshold at p < .01 uncorrected in left Amygdala (p = .055, FWE corrected, t = 3.52) and right Amygdala (p = .072, FWE corrected, t = 3.39) given by the contrast Emotion Recognition > Baseline Condition for GHB-group high ANX+STR > low ANX+STR.
MNI-space coordinates for left Amygdala were x = -22, y = -8, z = -12; MNI-space coordinates for right Amygdala were x = 22, y = -4, z = -12.
4 DISCUSSION
In this study we investigated if GHB users were more susceptible to negative emotions compared to people who did not use GHB. We investigated two different aspects of emotion processing; 1) the subjective experience of negative emotions (depression, anxiety and stress), and 2) susceptibility to faces with negative emotional valence on the basis of amygdala functioning. Results showed that neither anxiety nor stress alone was higher for GHB users; though when those scores were combined we found a trend that GHB users had more anxiety and stress than non-GHB users. Moreover, we found a trend showing that GHB users experience more depression. Also, GHB users reported significantly more anxiety, stress and depression combined than non-GHB users.
These findings suggest that GHB use is related to more emotional problems, which is in line with our expectations. Finally, we found that anxiety and stress, but not depression, anxiety and stress together, showed a relationship with the amount and duration of GHB use. This was in line with our expectations and perhaps represents a relationship between quantity of GHB consumption and amygdala functioning, as anxiety and stress, and not depression, is mediated via amygdala.
However, imaging data showed that GHB users did not differ in amygdala response to negative emotional valence compared to non-GHB users, suggesting that GHB users were not more susceptible to negative emotional valence than non-GHB users. Since we did found that GHB users had more anxiety and stress, not finding any differences in amygdala functioning was highly unexpected. Nonetheless, we established that GHB users who experienced the most anxiety and stress showed higher amygdala activity when confronted with negative emotional valence compared to GHB users who experienced lower anxiety and stress. This suggests that GHB users with high anxiety and stress are more susceptible to negative emotional valence. Nevertheless, no conclusive assumptions can be made due to insufficient sample size.
Besides the results concerning our research questions, we also found an unexpected effect. Imaging data showed a trend of heightened activity in the right superior frontal gyrus (rSFG) as a reaction to negative emotional valence for GHB users, though not for non-GHB users. While this effect was no longer significant after FWE correction, it still showed a notable trend in activity compared to other regions, given de small sample size and lack of data. We will address this issue later in the discussion. Finally, a very important issue is the fact that the study was critically underpowered. Due to inclusion difficulties not enough subjects were examined to draw definitive conclusions. We will therefore interpret our results with caution.
4.1. Amygdala dysfunction as emotional addictive component
As the amygdala is important for processing and regulating physiologic and behavioral responses to fearful, stressful and drug-related stimuli (Gilpin et al., 2015), we expected a difference in amygdala activity between GHB users and non-GHB users, reflecting a higher susceptibility for negative emotional valence. As we did not find heightened amygdala response to negative emotional valence for all GHB users, but merely for GHB users with high anxiety and stress, it is an option that just anxiety and stress is related with amygdala functioning regardless of GHB use, and that GHB itself does not alter amygdala regulation. But since the higher amygdala response to negative emotional valence and therefore the higher susceptibility to negative emotions were only present in GHB users, it still might depict a function as an emotional component responsible for the high rate of recidivism.
Moreover, since we found a relationship between anxiety, stress and quantity of GHB used, it may indicate a relationship with the amygdala. For instance, it possibly reflects that either a) the quantity of GHB-use affects anxiety and stress (perhaps through consequences of GHB on amygdala functioning through oxytocin depletion or GABAergic disinhibition); or that anxiety and stress reflects vulnerability for GHB use (perhaps due to pre-existing amygdala dysregulation). Nonetheless, in case of GHB withdrawal it is quite possible that amygdala functioning represents an emotional component in GHB addiction and relapse.
The positive emotional and social acute effects of GHB (Bosch et al., 2015) make it a risky drug for anxious and stressed persons, whom may already be vulnerable to eventual adverse effects
of GHB use on emotion processing. It is speculated that when people experience a lot of stress, they tend to prefer substances that enhances GABA (Gilpin et al., 2015). However, excessive use of GABA agonists can eventually leads to facilitation and less GABAergic inhibition over amygdala and thus enhancing the susceptibility for negative emotions (Manzanares, et al., 2005; Pérez de la Mora et al., 2007). Besides the use of GABA agonists, stress and withdrawal can also attenuate or suppress GABA inhibition over amygdala (Isoardi et al., 2007). Hence, it is not unlikely that pre-existing amygdala dysregulation increases the chances of developing a GHB addiction. On the contrary, the subjects in our study were mainly recreational GHB users who still showed higher susceptibility to negative emotional valence, suggesting that it is not a decisive factor in developing GHB dependence. Further research should focus on examining if these findings are generalizable to persons with GHB dependence, and subsequently whether interventions targeting the amygdala act positively on the process of staying sober.
4.2. Evaluation of superior frontal gyrus activity
The unexpected finding of activity in the right superior frontal gyrus (SFG) may be related to GHB use, as there is evidence indicating a connection between right SFG, amygdala functioning and emotion regulation. In the literature right SFG is often described as an important brain region for emotional self-regulation (Frank et al., 2014), rapid inhibitory control (Floden & Stuss, 2006) and enhanced selective attention towards expressions of anger (Smith, Balkwill, Vartanian & Goel, 2015). The activation of right SFG is also associated with the down-regulation of arousal and reappraising emotional impact, while on the other hand, no activation of amygdala occurs during the down-regulation of arousal (Beauregard, Levesque & Bourgouin, 2001; Falquez et al., 2014). This is possibly attributed to the ability to willfully modulate the intensity and direction of emotional response (Frank et al., 2014). Thus, perhaps (recreational) GHB users process negative emotional valence in a more cognitive fashion compared to non-GHB users.
A more cognitive manner of emotion processing may have positive effects on emotional well-being. Researchers suggested that activity in the right SFG may be related with reductions in social anxiety after cognitive-behavioral therapy, as the subjects were less sensitive to social criticism (Goldin et al., 2014). Moreover, in healthy subjects stronger activation in the right SFG correlated with higher fear intensity ratings (Labudda, Mertens, Steinkroeger, Bien & Woermann, 2014), implying that the right SFG reacts stronger to negative stimuli. This may be a positive function, as it helps processing negative stimuli through a network between amygdala and prefrontal cortex. This is interesting; as it was mooted that prefrontal cortex and amygdala connectivity could decrease as a result of stress and GABAergic disinhibition (Gilpin et al., 2015). In this case, the activity in the right SFG may first of all indicate connectivity, as well as a mechanism positively affecting emotion and social processing. Further research could investigate whether its functions as a factor in the vulnerability for development of GHB dependence, as our findings may be distorted due to the small sample size.
Nonetheless, also contradictory findings have been reported. In a study concerning relatives of subjects with bipolar disorder, they found lower activity in the right SFG when presented with negative images, suggesting that actually lower activity in right SFG reflects resilience to negative emotion processing (Sepede et al., 2015). Although the differences in interpretation of the function
of right SFG, it most likely has a cognitive and controlling effect over emotional and social stimuli with negative valence.
4.3. Limitations and further research
One of the most prominent limitations of the current study is the small sample size, which was ensued by being underpowered, abnormally distributed data, more noticeable outliers and limited options to analyze the data. Therefore, the results need to be interpreted with caution.
Other limitations included the characteristics of our sample; subjects were mainly well-educated, with the majority having college education experience or higher. This may not correctly reflect the group of problematic GHB users. High education is also associated with better emotion recognition, while lower educated persons often experience more problems (Fernández-Serrano et al., 2010). Furthermore, the majority of our subjects were recreational GHB and drug users. Firstly, it is a possibility that those users do not use enough GHB to suffer from potential GHB-induced alterations of brain processes. Also, since there was only one subject with a history of GHB dependence, we could not investigate the role of addiction on emotion processing. Finally, as GHB-induced coma is often experienced by users, we could not examine these consequences since we did not have enough subjects that experienced coma. Therefore, alterations in brain processes as a result from GHB-induced coma remain unclear.
Further research would need to entail more GHB dependent subjects; only then the possible consequences specifically related to addiction and withdrawal can be assessed. Since GHB dependence often is accompanied by a high rate of GHB-induced comas (Dutch & Austin, 2012), the consequences of coma need to be investigated. Since it is known that comas affect cognitive functioning (Perouansky & Hemmings, 2009), it may also contribute to factors that could increase the chance of relapse.
To establish the role of the amygdala as possible emotional component in GHB dependence, more research should be conducted concerning emotion and social processing and regulation. As the precise working of GHB on a molecular level largely remains unknown, it also remains unclear how GHB affects the brain differently than other GABA enhancing substances. For instance, longitudinal research might show whether GHB use leads to amygdala dysfunction, or if amygdala dysfunction leads to GHB use. Moreover, direct measurement of cortisone or oxytocin levels could be measured, to establish whether GHB users physically show more stress, and if oxytocin levels are lower than non-GHB users. If there are differences, it could also contribute to the emotional problems reported by GHB users. When the processes underlying GHB addiction are clearer, more effective therapeutic interventions could be developed.
4.3.1. Therapeutic interventions
As we found a trend that GHB users experience more negative emotions than non-GHB users, it could reflect vulnerability in developing addiction. If more is known about the consequences of GHB use on the brain, and specifically the consequences on emotion and social processing, more targeted therapeutic interventions can be investigated to reduce emotional problems. Recently, more and more interest is expressed in the therapeutic effects of oxytocin because of its positive effects on sociability anxiety and stress (Domes et al., 2007). Since social anxiety in GHB withdrawal is likely a consequence of the depletion of oxytocin systems (Nieuwenhuijzen et al., 2010),treatment
with oxytocin could have positive effects on withdrawal symptoms. For instance, McGregor et al. (2008) discusses the high probability of long lasting social dysfunction as a result of oxytocin depletion in animals, which can be reversed by oxytocin administration.
Firstly, oxytocin directly prevents actions of alcohol on the brain by targeting GABAᴀ receptors in rats, decreasing alcohol-induced GABAergic activity which may be relevant for treating intoxication (Bowen et al., 2015). Additional research to the effect of oxytocin on GABAʙ is desirable. Secondly, rats which received oxytocin administration in their adolescence showed less anxiety-like behavior and more social interactions than non-treated rats. Moreover, the rats treated with oxytocin consumed less alcohol than non-treated rats when they had unlimited access to alcohol and water, and administration of oxytocin instantly decreased alcohol intake (Bowen, Carson, Spiro, Arnold & McGregor, 2011). These findings show that oxytocin depletion may function as vulnerability factor that may provoke GHB use, but also that treatment may reduce the intake of GHB.
Besides positive effects of oxytocin in rats, several studies have assessed the therapeutic use of oxytocin in humans through the use of an intranasal spray. These studies are mainly concerning its pro-social effects in general, but few imply that oxytocin also has a positive effect on substance abuse. While oxytocin has a rewarding effect on the brain, oxytocin itself does not seem to act addictive. Nonetheless, additional research is necessary as most studies involved small samples (Striepens, Kendrick, Maier, & Hurlemann, 2011). Also, for an extensive review about the therapeutic effects, see Striepens et al. (2011).
Finally, some possible directions for development of other therapeutic interventions can include the reduction of stress. As GABAergic disinhibition affects amygdala functioning as a consequence of stress, this might lead to vulnerability for GHB dependence, as well as stress from withdrawal may lead to relapse (Manzanares et al., 2005; Isoardi et al., 2007). In their study, Liu et al. (2014) mentioned the use of the drug metyrapone, which prevents facilitation of GABA inhibition from stress. Therefore, it could stabilize withdrawal effects. Furthermore, as prostress peptides such as CRF in amygdala may increase the craving to consume GABAergic substances, this craving could be reduced by blocking receptors that bind with prostress peptides (Gilpin et al., 2015). If additional research to prostress receptor blockade confirms a reduction in craving to GABAergic substances, this may greatly reduce the number of relapses.
4.4. Conclusion
It is clear that GHB dependence is accompanied by emotional problems, and that the recidivism rate is higher compared to other drug dependencies (Mol et al., 2014). This raised the question whether there was an emotional component maintaining addictive behavior. In the literature it was suggested that the amygdala may be the origin of the emergence of emotional problems, as it modulates anxiety and stress, as well as the susceptibility to negative emotions in others, affecting sociability (Hariri et al., 1999; Ferguson et al., 2001). Our findings, despite the small sample size, indeed indicate more negative emotions in GHB users, and GHB users who experience the most negative emotions were also more susceptible for expressions of negative emotions in others. Moreover, there was relationship between the quantity of GHB consumed and the experience of anxiety and stress. Therefore, the addictive emotional component may comprise alterations in emotion and social processing due to amygdala dysregulation, resulting in higher
susceptibility for negative emotions. As these effects were found mainly in recreational users, it probably is not a decisive factor, but it may be a contributing factor. Nonetheless, there seem to be a few promising possibilities for the development of therapeutic interventions, which may target either the cause of the emotional problems, or prevent relapse after detoxification.
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