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. Author manuscript; available in PMC: 2020 Jun 1.
Published in final edited form as: CNS Spectr. 2019 Dec;24(6):609–615. doi: 10.1017/S1092852918001645

Abnormalities of Striatal Morphology in Gambling Disorder and At-Risk Gambling

Jon E Grant 1, Masanori Isobe 2,3, Samuel R Chamberlain 2
PMCID: PMC6885013  EMSID: EMS80712  PMID: 30880655

Abstract

Objective

The clinical phenotype of gambling disorder (GD) is suggestive of changes in brain regions involved in reward and impulse suppression, notably the striatum. Studies have yet to characterize striatal morphology (shape) in GD and whether this may be a vulnerability marker. Aims: To characterize morphology of the striatum in those with disordered gambling (At-Risk Gambling and GD) versus controls.

Method

Individuals aged 18–29 years were classified a priori into those with some degree of gambling disorder symptoms (At-Risk Gambling and Gambling Disorder), or controls. Exclusion criteria were current mental disorder (apart from GD), history of brain injury, or taking psychoactive medication within 6 weeks of enrollment. History of any substance use disorder was exclusionary. Participants completed an impulsivity questionnaire and structural brain scan. Group differences in volumes and morphology were characterized in subcortical regions of interest, focusing on the striatum.

Results

32 people with gambling disorder symptoms (14 At-Risk and 18 Gambling Disorder participants) and 22 controls completed the study. Gambling Disorder symptoms were significantly associated with higher impulsivity; and with morphological alterations in bilateral pallidum and left putamen. Localized contraction in the right pallidum strongly correlated with trait impulsivity in those with gambling disorder symptoms.

Conclusions

Morphologic abnormalities of the striatum appear to exist early in the disease trajectory from subsyndromal gambling through to GD, and thus constitute candidate biological vulnerability markers, which may reflect differences in brain development associated with trait impulsivity. Striatal morphology and associated impulsivity might predispose to a range of problematic repetitive behaviors.

Keywords: neuroimaging, gambling, morphology

Introduction

Gambling disorder is a significant public health problem affecting 0.4% to 1% of the US population, also being prevalent in many other countries.1 Understanding the chain of progression from recreational gambling to gambling disorder is vital towards understanding the underlying biological mechanisms (pathogenesis). Comparing people with gambling disorder with those at an increased risk of developing gambling disorder would help to elucidate whether neurobiological aspects of gambling disorder are evident prior to the development of overt pathology or stem from the disorder itself, perhaps even reflecting the harmful effects of recurrent gambling on brain function.

Gambling disorder can be conceptualized from a neurobiological perspective in terms of excessive drive from subcortical regions involved in reward processing coupled with diminished top-down control from prefrontal cortical regions.2,3 Consistent with this perspective, people with gambling disorder often exhibit impairments across a spread of cognitive domains including inhibitory control, working memory, and decision-making.3–6 Extensive translational data implicate sub-cortical structures in these abilities, e.g.7

Functional neuroimaging (fMRI) studies in healthy volunteers have demonstrated that the striatum and pallidum respond to reward and in particular, through dopaminergic signaling, encode reward expectancy (anticipation of reward).8 Such sub-cortical structures are also central to contemporary computational models of decision-making, which in turn stem from human (and translational) data.9,10 Gambling disorder is conceptualized as a Substance Related and Addictive Disorder in DSM-5, and abnormalities of decision-making are central to understanding its symptomatology (e.g. loss of control, craving, escalation of reward-seeking over time, neglect of other areas of life). Reward-related increases in striatal dopamine release have been found in gambling disorder,11 along with a positive correlation between such dopamine release and symptom severity.12 Functional imaging has also found that gambling disorder is typically associated with blunted mesolimbic-prefrontal cortex responses to general rewards, but heightened activation to gambling-related stimuli.13 An fMRI study of gambling disordered adults (n=10) using a monetary reward task, demonstrated that gamblers, compared to controls, exhibited decreased neural activity in the pallidum for decision-making under risk, as opposed to decision under ambiguity, and increased neural activity within the putamen prior to bet choices, as opposed to safe choices.14 A subset of patients with Parkinson’s disease develop impulsive symptoms, including gambling disorder, due to pro-dopaminergic therapy.15 In functional imaging, such impulsive symptoms in Parkinson’s disease were associated with heightened connectivity from the ventral striatum to the putamen and pallidum.16

Though striatal brain regions are demonstrably involved in decision-making,8 and functional imaging data have identified altered responses to reward in such regions in gambling disorder,13 direct quantification of structural changes in these regions in patients are lacking. One voxel based morphology (VBM) investigation found that gambling disorder was associated with increased grey matter volumes in the ventral striatum17 (but see18). Another VBM study examining 30 male never-treated gambling patients and 30 controls and showed increased absolute global gray matter volumes in gamblers relative to controls as well as relatively decreased volumes in the left putamen.19

Subcortical structures are difficult to visualize structurally accurately with conventional pipelines due to poor, heterogeneous signal intensities.20 Typical imaging analysis pipelines were designed for analysis of cortex rather than subcortical regions.21,22 Neuroimaging pipelines are now available that enable the sensitive measurement of localized differences in deformations of subcortical structure shapes across groups. This latter approach of examining localized abnormalities in subcortical brain structure (i.e. quantification of local curvature) has the advantage of not relying on arbitrary smoothing extent or tissue classification.20 This innovative modeling approach has been shown to be sensitive to pathologies in other contexts, such as in Alzheimer’s Disease.20

Therefore, the aim of the current study was to examine whether localized morphometric differences of the striatum (caudate, putamen, accumbens, and pallidum) exist in people with gambling disorder symptoms, compared to recreational non-pathologic gambler controls (i.e. those with no gambling disorder symptoms). We hypothesized, based on the above literature, that these regions would show abnormal morphology in those with symptoms, which in turn would correlate with extent of symptoms and impulsivity more broadly.

Method

Subjects

Participants were recruited via media advertisements for anyone who had gambled within the past year. Inclusion criteria were: age 18-29 years (the age limit was set to limit the confounding effects of age), right-handedness, no use of psychotropic medications for the past 6 weeks, and no contraindication to MRI. Participants with current mental disorders (apart from gambling disorder in the gambling disorder group), including any other impulse control disorder, or a lifetime history of psychotic disorder, bipolar disorder or substance use disorder, were excluded. Healthy controls were recruited via media advertisements on the basis of no lifetime or current psychiatric disorders.

The study procedures were carried out in accordance with the ethical standards laid out in the Declaration of Helsinki. The University of Chicago Institutional Review Board approved the study and the consent procedures. After complete description of the study to the subjects, written informed consent was obtained.

Assessments

Demographic variables, including age and gender, were recorded for all participants. Subjects received a psychiatric evaluation, which included the Structured Clinical Interview for Pathological Gambling (SCI-PG)23 adapted for DSM-524. A score of 0 on the SCI-PG designated controls, a score of 1-3 defined a participant as being an at-risk gambler, while a score of 4 or greater was consistent with meeting criteria for gambling disorder.

Clinical measures included: Mini International Neuropsychiatric Inventory (MINI)25, the Eysenck Impulsivity Questionnaire (EIQ)26, and the National Adult Reading Test.27

After completion of the above, participants undertook high-resolution structural imaging using a 3-Tesla (3T) scanner with magnetization-prepared rapid gradient echo (3D-MPRAGE) sequences. The axial three dimensional T1-weighted scans were acquired using the following parameters: repetition time = 2000ms; echo time = 3.0ms; flip angle = 9 degrees; field of view = 256×256; resolution = 1×1×1mm).

Statistical analysis, including neuroimaging processing steps

Group differences in demographic and clinical measures were explored with independent sample t-tests and chi-square tests (p<0.05, uncorrected), using SPSS v24.0.

Imaging pre-processing and data extraction were undertaken on the University of Chicago Midway computing system. We employed the same methodology as with a previous publication by our group.28 T1-weighted images were automatically bias-field corrected and non-linearly registered to the MNI 152 standard space. We employed FMRIB's Integrated Registration and Segmentation Tool (FIRST) implemented in FSL 5.0.9 to automatically segment subcortical structures.20 Segmentation was based on shape models with structural boundaries obtained from 336 manually segmented images, and resulted in a deformable surface mesh of each subcortical structure consisting of vertices. The meshes were reconstructed and filled in MNI space and boundary correction was applied. Then, the segmented images were transformed into original space. All segmented images were visually checked for errors in registration and segmentation.

A region of interest approach was used for the neuroimaging analyses. Based on literature pertaining to models of decision-making, findings in gambling disorder, and findings in impulse control disorders in Parkinson’s disease (outlined in the introduction), we specifically focused on striatum, defined as putamen, caudate, accumbens, and pallidum. We calculated total intracranial volume (ICV) as the sum volumes of grey matter, white matter and cerebrospinal fluid using FMRIB’s Automated Segmentation Tool (FAST).29 Each subject’s brain scan was skull-stripped with the Brain Extraction Tool and linearly aligned to the MNI152 space, and the inverse of the determinant of the affine transformation matrix computed by the software was multiplied by the ICV size of the template. We adjusted the subcortical volumes by the intracranial volumes (ICV) of each individual.30

Subcortical volumes were compared between those with gambling disorder symptoms (GD+AR) and controls (HC) using t-tests. Values were reported uncorrected for multiple comparisons but were only deemed statistically significant if they withstood Bonferroni correction for the number of comparisons undertaken.

For morphometric analysis, vertex analysis implemented in FIRST (FSL) was employed to compare the shapes of the subcortical structures.20 Negative value of the vertex represented deformation in the inward direction and positive value of a vertex indicated deformation in the outward direction. Curvature abnormalities were identified between those with gambling disorder symptoms (GD+AR) and controls (HC) using ‘Randomise’, a permutation-based non-parametric testing method implemented in FSL with 5000 iterations, which corrects for multiple comparisons and uses Threshold-Free Cluster Enhancement (TFCE) as recommended.31–33 We used the two group comparison because the primary interest was in determining abnormalities in those with gambling disorder symptoms collectively compared to controls. Where significant regions of morphometric abnormalities were found, correlations were explored with the clinical measures (Eysenck scores and SCIGD scores) using Spearman’s rho, with significance set at p<0.05. Correlations were reported uncorrected but were only deemed significant if they withstood Bonferroni correction for the number of correlation analyses undertaken.

Results

Of the 54 participants, 18 had gambling disorder, 14 met criteria for being at-risk gamblers, and 22 were controls. None of the participants had ever sought treatment for gambling behavior. Although the participants had no current mental health issues other than gambling disorder, two were former smokers (only occasionally), and three reported histories of anxiety problems but none met criteria for a previous anxiety disorder.

Demographic and clinical features of the GD, AR, and HC participants are presented in Table 1, where it can be seen that there were no differences for age, gender or IQ. In terms of gambling behavior, the majority of both gambling groups reported casino gambling as their primary form of gambling, with slots and blackjack their preferred games (15 [83.3%] of the gambling disordered participants and 12 [85.7%] of the at-risk). Gambling disorder symptoms were associated with significantly higher impulsiveness on the Eysenck Impulsiveness measure compared to the controls.

Table 1. Demographic and Clinical Comparison of Three Levels of Gambling Behavior (HC = healthy controls; AR = at-risk gamblers; GD = gambling disorder).

(SD) HC AR GD Group-wide Statistic p value
Number [female] 22 [14] 14 [7] 18 [6] 4.316 0.116
Age 30.2 (12.0) 26.5 (2.0) 25.9 (2.7) 1.711 0.191
NART 90.4 (16.1) 89.1 (8.7) 83.4 (8.9) 1.725 0.193
SCI-PG 0 (0) 1.79 (0.80) 6.00 (1.94) 128.657 <0.001
EIQ
   impulsivity 4.67 (3.60)*† 8.92 (4.23)† 10.22 (4.10)* 7.150 0.002
   venturesomeness 8.33 (3.14) 10.21 (3.89) 10.67 (3.89) 2.138 0.131
   empathy 12.58 (2.78) 11.71 (3.67) 14.11 (2.19) 2.836 0.070
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*

p<0.05 post-hoc analysis between HC and GD.

†

p<0.05 post-hoc analysis between HC and AR.

Group Differences in Subcortical Volumes and Morphology

Table 2 provides group volumetric differences. There were no statistically significant group differences for volumes in the ROIs of interest.

Table 2. Volumetric analysis (HC = healthy controls; AR = at-risk gamblers; GD = gambling disorder). There were no significant group differences with Bonferroni correction.

(SD) HC GD+AR t value Uncorrected p value
GMV 582670 (59003) 580662 (61470) 0.120 0.905
WMV 507871 (59601) 506506 (72851) 0.073 0.942
ICV 1395966 (131429) 1396334 (165300) 0.009 0.993
Lt NAcc 0.400 (0.088) 0.460 (0.120) 1.981 0.053
Lt Caudate 2.613 (0.325) 2.639 (0.350) 0.275 0.784
Lt Pallidum 1.296 (0.135) 1.374 (0.256) 1.307 0.197
Lt Putamen 3.949 (0.553) 4.164 (0.485) 1.509 0.137
Rt NAcc 0.317 (0.080) 0.305 (0.099) 0.474 0.637
Rt Caudate 2.639 (0.336) 2.686 (0.331) 0.505 0.616
Rt Pallidum 1.341 (0.118) 1.449 (0.163) 2.649 0.011
Rt Putamen 3.818 (0.521) 3.993 (0.431) 1.345 0.185
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GMV: gray matter volume, WMV: white matter volume, ICV: intracranial volume, NAcc: Nucleus Accumbens. Values in brackets are standard deviations.

Several significant morphometric abnormalities were associated with subsyndromal and clinical gambling disorder, compared to controls. Specifically, localized morphometric abnormalities were found in the bilateral pallidum and left putamen (Figure 1; FDR p<0.05). In post hoc t-tests using extracted cluster means, at-risk gamblers did not differ significantly from gambling disorder participants for curvature in the identified abnormal significant clusters (all p>0.10).

Figure 1.

Figure 1

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Morphological abnormalities in disordered gamblers, compared to controls. Blue indicates significant excess inward curvature, and red indicates significant excess outward curvature, in the gambling disorder symptom group versus controls (permuted p<0.05, corrected). Top row: left pallidum; middle row: right pallidum; bottom row: left putamen.

Relationship between morphology and clinical measures

In terms of clinical correlates, the morphological shape of the right pallidum demonstrated a significant correlation with the impulsivity subscale score of the EIQ across all participants pooled; this was due to a significant correlation in those with gambling disorder symptoms but not in the healthy controls (see Figure 2). No significant correlation was found with the severity of gambling symptoms.

Figure 2.

Figure 2

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Correlation between right pallidum mean curvature (vertex value) in cluster of group difference and impulsivity on the Eysenck Impulsivity Questionnaire (EIQ). The correlation was significant with all subjects pooled, and in the combined GD+AR group (r=0.45, p<0.001) but not in the controls (r=0.03, p>0.3).

Discussion

This study investigated subcortical morphology in individuals with gambling disorder symptoms compared to controls who gamble but had no pathologic symptoms. This approach stemmed from our goal to evaluate morphological abnormalities of subcortical structures common to those with any degree of gambling disorder symptoms versus those with none; since such differences may inform understanding of vulnerability markers and differences in brain development predisposing these and other impulsive psychiatric problems. Partly consistent with our a priori hypothesis, we identified morphologic abnormalities of pallidum and putamen in those with gambling disorder symptoms. The morphological abnormalities in the right pallidum correlated highly significantly with impulsivity scores on the Eysenck Impulsivity Questionnaire, across all study participants. Contrary to expectation, morphology in these structures did not correlate significantly with symptom severity in those with gambling disorder symptoms. We conclude that abnormalities of striatal morphology, specifically involving the pallidum, are associated with trait impulsivity and thus may predispose to gambling disorder and potentially other impulsive symptomatologies.

The striatum encodes reward via dopaminergic signaling,8 and aberrant functional connectivity between such structures has been found in impulse control problems in Parkinson’s disease, perhaps arising from pro-dopaminergic therapy.16 The current data enhance existing neurobiological models of gambling disorder,13 but also extend beyond these models by suggesting that pallidum abnormalities in particular may be a vulnerability marker associated more broadly with impulsive tendencies (measured here using the Eysenck questionnaire), rather than necessarily only to disordered gambling per se. Neural responses in the pallidum have been shown to be specific to high reward levels occurring in the context of increasing reward.10 Thus, the pallidum may play a key role in the pathophysiology of gambling disorder, and this may offer some explanation for what we see clinically in problem gamblers, that is the inability to control the behavior despite the negative consequences.34,35 Our results suggest that pallidum curvature abnormalities are more related to the extent of trait impulsivity rather than gambling disorder symptoms in particular. In preclinical work, a subset of pallidum neurons has been found to respond selectively in situations requiring the sudden cancellation of impulsive actions.36 Thus we suggest that morphological abnormalities (versus controls) in the pallidum might contribute to (or correlate with) impulsive traits, which in turn may predispose towards a range of problematic behaviors including disordered gambling.

These findings are interesting when placed also in the context of imaging results in the field of substance addiction, which are pertinent given that gambling disorder is now regarded as a Substance Related and Addictive Disorder in DSM-5. For example, bilateral gross symmetric lesions of the pallidum have been associated with heroin intoxication37 and lesions of the pallidum have been found in 5–10% of heroin addicted individuals post-mortem.38 More recently, widespread grey matter reductions in the pallidum (in addition to other areas) have been found in adults receiving methadone maintenance treatment for opioid use disorder.39

This study has several positive features, notably that it is the first imaging study of subcortical structures in adults with varying levels of gambling severity, and entailed examination not only of volumes but also of shapes (localized curvature) of implicated structures. Of course, we examined only localized morphometric differences of the striatum, and therefore whole brain analyses may have resulted in additional findings. We focused on the striatum for several reasons including relative lack of data on this region in gambling disorder; its likely involvement in reward and habit learning; and the relatively recent development of suitable analysis pipelines for interrogating these relatively small, hard-to-visualize structures. We also focused on these regions to reduce multiple comparisons that are hard to mitigate with relatively small sample sizes. The subjects were free from current psychiatric comorbidities and psychotropic medications. Several limitations, however, should be considered. The sample size may have limited statistical power to detect more subtle differences between the groups (i.e. group differences with small effect sizes). Larger samples in future studies would also help to rule out false positives. Also, the lack of correlation between curvature abnormalities and gambling disorder severity could reflect the smaller sample size for this correlational analysis, compared to the correlational analysis for impulsiveness, which was measurable along a continuum across all participants. We selected subjects who were not taking psychotropic medications and who were free from comorbid psychiatric conditions, including nicotine dependence and substance use. It therefore remains to be seen whether the findings generalize to gambling disorder more widely, as the condition is often comorbid with other disorders.

In summary, the current study identified morphologic abnormalities of the pallidum and putamen in people with gambling disorder symptoms (at-risk gambling and Gambling Disorder), compared to recreational gamblers without any pathologic symptoms. The right pallidum abnormality bore a particularly strong relationship with trait impulsiveness on the Eysenck impulsivity questionnaire, rather than with gambling disorder severity. We suggest that pallidum morphology and associated impulsivity might predispose to a range of problematic repetitive behaviors including gambling; and that these differences observed in people with gambling disorder symptoms may reflect abnormalities of longitudinal brain development related to impulsivity.

Acknowledgments

Disclosure information:

Samuel Chamberlain has the following disclosures:

This research was supported by a Center of Excellence in Gambling Research grant to Dr. Grant from the National Center for Responsible Gaming and a Wellcome Trust Clinical Fellowship to Dr. Chamberlain (110049/Z/15/Z).

Dr. Chamberlain consults for Cambridge Cognition, Shire, and Promentis. There are no competing financial interests in relation to this work.

Jon Grant has the following disclosures:

Dr. Grant has received research grants from American Foundation for Suicide Prevention, TLC Foundation, and Takeda Pharmaceuticals. Dr. Grant receives yearly compensation from Springer Publishing for acting as Editor-in-Chief of the Journal of Gambling Studies and has received royalties from Oxford University Press, American Psychiatric Publishing, Inc., Norton Press, and McGraw Hill.

Masanori Isobe has nothing to disclose.

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