Reviews and meta-analysis

A Research Domain Criteria (RDoC) approach to Gambling Disorder: focus on preference-based decision-making and response inhibition

Author

A. Marras¹, N. Makris ²

Affiliations

¹ Department of Neurosciences, Psychology, Drug Research and Child Health (NEUROFARBA), University of Florence, Florence, IT
² Center for Morphometric Analysis, Departments of Psychiatry and Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

Corresponding author

Nikolaos Makris
Center for Morphometric Analysis, Departments of Psychiatry and Neurology,
Massachusetts General Hospital
Harvard Medical School, Boston, MA, USA
E-mail: nikos@cma.mgh.harvard.edu

Abstract

Gambling Disorder (GD) has been recently re-classified in the DSM-5 under the “substance-related and addictive disorders”, in light of its genetic, endophenotypic, and phenotypic resemblances to substance dependence. The clinical phenotype of this population is characterized by unsuccessful efforts to reduce or stop gambling despite negative outcomes, suggestive of aberrant decision-making mechanisms and faulty inhibitory control of gambling impulses that sustain the chronicity and comorbidities of this clinical syndrome. The main symptom clusters are represented by loss of control, craving/withdrawal, and neglect of other areas of life, whereas in a Research Domain Criteria (RDoC) perspective, GD patients exhibit deficits in the domain of “Positive valence systems”, particularly in the “Approach motivation” and “Reward learning” constructs, as well as in the “Cognitive systems”, primarily in the “Cognitive control” construct. In this paper we will focus on the symptomatic cluster of loss of control and we will review the main behavioral manifestations, task performances and corresponding putative neurocircuitries related to the RDoC framework.

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Keywords

Gambling disorder; neurocircuitry; research domain criteria; RDoC; domains

Introduction

Gambling Disorder (GD) is an impulsive-compulsive disorder currently classified as an addictive disorder in the DSM-5 under the “substance-related and addictive disorders” [1]. It is characterized by persistent and recurrent maladaptive patterns of gambling behavior, leading to impaired functioning [1]. The inclusion of GD in the addictive disorder chapter of DSM-5 is motivated by the recognition of its genetic, endophenotypic, and phenotypic resemblances to substance dependence: both disorders show similar comorbidity patterns [2], genetic vulnerabilities, and responses to specific pharmacologic treatments [3].
The hallmark components of the disorder have been proposed to be (a) continued engagement in a behavior despite adverse consequences, (b) diminished self-control over engagement in the behavior, (c) compulsive engagement in the behavior, and (d) an appetitive urge or craving state prior to engaging in the behavior [4,5].
The diagnostic criteria for gambling disorder overlap largely with those for the substance use disorders: the main symptom clusters are represented by loss of control, craving/withdrawal, and neglect of other areas of life [6].
GD has 1-2% prevalence in the general population in Western societies [7,8], and is associated with substance misuses, depression, domestic violence, divorce, crime and suicide [9]. The National Gambling Impact Study Commission estimated that the annual cost for GD is $5 billion (U.S.) per year and an additional $40 billion (U.S.) in lifetime costs for productivity reductions, social service, and creditor losses [10].
Herein, we will focus on the symptom cluster “loss of control” (i.e., unsuccessful efforts to control, cut back, or stop gambling), which appears to be related to deficits in executive functions (namely, diminished response inhibition [11]) and impaired reward-related decision-making [12]. Behavioral manifestations, task performances and corresponding putative neurocircuitries will be reviewed in the context of the Research Domain Criteria (RDoC) framework.

Gambling disorder and the research domain criteria

The National Institute of Mental Health (NIMH) has recently launched the Research Domain Criteria (RDoC) project to overcome the limitations of current classification systems and to develop a framework for research on mental disorders that includes multiple dimensions [13]: behavior, thought patterns, neurobiological measures, and genetics, with a strong focus on neurocircuitries. The RDoC aims at facilitating the incorporation of behavioral neuroscience in the study of psychopathology and at identifying reliable and valid psychological and biological mechanisms and their disruptions, with an eventual goal of understanding how abnormalities in these mechanisms drive psychiatric symptoms [14]. RDoC’s strong focus on neural circuits is evident from the assumption that mental illnesses are conceptualized as brain disorders of brain circuits. Moreover, the RDoC assumes that dysfunctions in neural circuits can/will be identified by tools of neuroscience [13]. Importantly, in the RDoC approach, the behavioral and genetic phenotypes are bridged and integrated through specific brain circuitries, which embody the level of systems biology [15-18].
Neurocircuitries are phenotypic targets of great potential for endophenotypic/biomarker discovery in current neuroimaging clinical research [19]. In a RDoC perspective, GD patients exhibit deficits in the domain of “Positive valence systems”, particularly in the “Approach motivation” and “Reward learning” constructs, as well as in the “Cognitive systems”, more specifically in the “Cognitive control” construct [Figure 1].

Figure 1. RDoC domains involved in GD. A) Positive valence systems; B) Cognitive systems. Bold text indicates constructs and subconstructs involved in the symptom cluster “loss of control”. (Adapted from: NIMH RDoC Matrix https://www.nimh.nih.gov/research-priorities/rdoc/constructs/rdoc-matrix.shtml)

Positive valence systems are primarily responsible for responses to motivational situations such as reward seeking, consummatory behavior, and reward/habit learning [20]. The construct of Approach motivation involves “mechanisms/processes that regulate the direction and maintenance of approach behavior influenced by pre-existing tendencies, learning, memory, stimulus characteristics, and deprivation states” (ibidem). Particularly relevant to GD is the subconstruct Reward valuation, which consists of “processes by which the probability and benefits of a prospective outcome are computed and calibrated by reference to external information, social context (e.g., group input, counterfactual comparisons), and/or prior experience. This calibration is influenced by pre-existing biases, learning, memory, stimulus characteristics, and deprivation states. Reward valuation may involve the assignment of incentive salience to stimuli” (ibidem).
Cognitive systems are responsible for various cognitive processes. Specifically, cognitive control “modulates the operation of other cognitive and emotional systems, in the service of goal-directed behavior, when prepotent modes of responding are not adequate to meet the demands of the current context. Additionally, control processes are engaged in the case of novel contexts, where appropriate responses need to be selected from among competing alternatives” [21].

Gambling Disorder domains: behavioral tasks and neurocircuitry

Positive Valence Systems

Approach motivation: preference-based decision-making
In a RDoC perspective, these processes involve an evaluation of costs/benefits and occurr in the context of multiple potential choices being available for decision-making [21].
Changes in reward based decision-making and increases in impulsivity are hallmark features of addiction [22] that has been scarcely studied satisfactorily in GD. Risky decision-making is a core feature of GD: gamblers have a high tolerance toward risk [23,24] and a bias to select short-term over long-term rewards is integral to the syndrome [25]. This bias has been operationalized with the employ of a behavioral measure called delay discounting task [26] (DDT), in which participants choose between pairs of options that yield small, immediate vs. large, delayed rewards. Subjects with substance abuse and behavioral addictions show a tendency to choose small and immediate rewards rather than large and delayed rewards. The Iowa Gambling Task [27] (IGT) has also been employed as a measure of decision-making, since it is considered as the most widely used and ecologically valid measure of decision making in this clinical population. In the IGT, players are given four decks of cards and an endowment of fake money (e.g., $2000) and are instructed to select cards one at a time and try to lose the least amount of money and win the most. GD subjects have shown to perform worse on the IGT and to make more high-risk choices compared to controls, precisely after experiencing wins and losses [28]. During high-risk gambling decisions, fMRI has shown that GD subjects exhibit relatively increased frontal lobe and basal ganglia activation, particularly involving the orbitofrontal cortex (OFC), caudate and amygdala. Increased activation of regions encompassing the extended reward pathway in GD subjects (GDs) during high risk choices suggests that the persistence of GD may be due to the increased salience of immediate and greater potential monetary rewards relative to lower monetary rewards or potential future losses (ibidem). There is also considerable evidence that GDs discount delayed rewards steeper than healthy controls [29]. Neuroimaging research has shown that GD is associated with a shift in the interplay between a prefrontal-parietal control network and a brain network involved in immediate reward consumption [30], and a generally hypoactive reward system [31].
A differential activation of distinguishable neural systems between immediate and delayed choices has been highlighted, with the former driven by the limbic system (including the ventral striatum, medial orbitofrontal cortex (MOFC), medial prefrontal cortex (MPFC), posterior cingulate cortex (PCC), and left posterior hippocampus) and the latter by the lateral prefrontal cortex and associated structures (including the right and left intraparietal cortex (RPar, LPar), right dorsolateral prefrontal cortex (DLPFC), right ventrolateral prefrontal cortex (VLPFC), and right lateral orbitofrontal cortex (LOFC)) [32].
More specifically, there is evidence that the right hemisphere plays an important role in inhibiting impulsive behavior and that the right DLPFC holds a certain role in the process of general decision-making [33]. Although the pathophysiology of GD is not well understood, studies have shown altered brain activity in prefrontal regions (primarily the DLPFC) of GD patients in response to gambling stimuli. Recently, a hypersensitivity to extreme gain-loss ratios of dorsal cortico-striatal network involved in action–outcome contingencies has been shown in gamblers [34].

Reward learning
The similarity between GD and substance abuse has been repeatedly hypothesized on the basis of large overlaps between addictive manifestations of both disorders. Recently, an interesting contribution to a broader understanding of the neurocognitive features of GD, hypothesized a loss of willpower to resist gambling, deriving from a pathological usurpation of mechanisms of learning that under normal circumstances serve to shape survival behaviors related to the pursuit of rewards and the cues that predict them [35]. This mechanism has been shown to be related with reward-based cognitive inflexibility, presumably resulting from an aberrant reward-based learning and observed as some kind of continuous gambling even in the face of increasing losses [36].
On a neurobiological perspective, reward-based cognitive inflexibility, has been associated with the orbitofrontal cortex (OFC – [37]), the ventral prefrontal cortex (vPFC – [38]), the ventrolateral prefrontal cortex (vl-PFC – [39]) and is facilitated by dopaminergic activity in the ventral regions of the striatum [37, 38].

Cognitive Control

Response inhibition
Response inhibition refers the ability to suppress behaviors that are inappropriate, unsafe, or no longer required [40]. Recent findings suggest that the ability to suppress automatic responses could be critical to gambling addictive behavior [35]. Whereas the increased sensitization toward gambling-related cues appears to be related to a hyperactivity of impulsive processes that may explain gamblers’ motivation to seek out relevant reward [35], the unsuccessful efforts to reduce or stop gambling despite negative outcomes [41-43] are thought to depend on a dysregulation of the so-called “reflective system”, and specifically, a faulty inhibitory control, responsible for inadequate efforts to control (or cut back or stop) gambling (ibidem).
Inhibitory control has been usually assessed with behavioral measures such as the Stop Signal Task (SST [44]), in which subjects perform a choice reaction task, and, on a random selection of the trials, an auditory stop signal instructs subjects to withhold their response, or Go/No-Go tasks, which require people to make manual responses to rapidly presented visual or auditory cues (i.e., ‘Go’ stimuli), but to withhold responses in the presence of a different cue (‘No-Go’ stimuli) [45].
Deficits in behavioral and cognitive control constitute a symptom dimension associated with diminished response inhibition in experimental tasks. Impaired response inhibition performance (i.e. prolonged latency of motor response inhibition) has been previously highlighted in pathological gambling by using the stop-signal task and the go/no-go paradigm (for a review, see [35]) and recent contributions highlight the correlation between deficits in response inhibition and gambling severity [46-47].
Recent neuroimaging research suggests that response inhibition may depend on a fronto-basal-ganglia circuit, including the inferior frontal gyrus (IFG), the pre-supplementary motor area (pre-SMA) and the subthalamic nucleus (STN) and striatum [48]. Both right IFG and pre-SMA

activation appear to be associated with successful stop trials. However, whereas right IFG contributes to response inhibition and not to monitoring performance or adjusting behavior, the pre-SMA seem to be involved in monitoring or resolving the conflict between the opposing task demands in the stop-signal paradigm. Also, fMRI studies showed inhibition-related activation in basal ganglia, including the STN and striatum and lesions to the basal ganglia impaired stop performance for both humans and rodents (ibidem).

Brain Circuitry underlying behavioral deficits in gambling disorder

The pre-SMA, which is located in the dorsomedial frontal cortex anterior to the leg representation of the primary motor cortex, has been suggested to be involved in cognitive control and impulsive choice reduction because of its role in updating or change of action plans, switching between tasks, and switching between rules linking stimuli to responses (see e.g., [49-62]). Moreover, the pre-SMA and the SMA both contain neurons encoding motivation to perform specific movements. The strength of this motivational signal reflects the amount of reward that is expected to follow from the action and, therefore, encodes an action value signal. These cortical centers are strongly innervated by the mesocorticolimbic system, including the ventral tegmental area (VTA), a dopaminergic system considered to be most at risk in addiction disorders, which is critical in mediating the hedonic impact of gambling and attributing incentive salience to reward-related gambling stimuli. Neurobiologically, dopamine deficiency seems to play a major role in pathological gambling and dorsal, ventral prefrontal cortex, SMA, pre-SMA as well as nucleus accumbens (NAc), Figure 2: Diagram of the dorsal and ventral prefrontal circuitry central to pre-SMA and SMA stimulation. Abbreviations: ACC: anterior cingulate cortex; BA: Brodmann’s area; FEF: frontal eye fields; IFG: inferior frontal gyrus; MFG: middle frontal gyrus; MPFC: medial prefrontal cortex; NAc: nucleus accumbens septi; OFC: orbitofrontal cortex; SMA: supplementary motor area; SN: substantia nigra; VTA: ventral tegmental area.
amygdala and hippocampus are connected and directly affected by the mesocorticolimbic network. Importantly, the gray matter centers in this network are interconnected via medium range and local frontal lobe connections and two principal long range fiber tracts, namely the cingulum bundle (CB) and the medial forebrain bundle (MFB). A simplified diagram of the dorsal and ventral prefrontal circuitry central to pre-SMA and SMA stimulation is shown in Figure 1.The anterior cingulate cortex (ACC, BA 24) is interconnected with the SMA (BA 6) and pre-SMA (BA 6) and higher-order association prefrontal cortices while at the same time receives inputs and innervates brainstem areas, the ventral striatum, the amygdala and hippocampal formation [63]. Its unique structural connectivity enables the integration of autonomic, affective, cognitive and motor information making the prefrontal-congulate circuitry a major player in cognitive and motor control [64]. Current structural and functional neuroimaging enables us to study the circuitry of the premotor areas in vivo (see e.g., [65-66]). A simplified diagram of the dorsal and ventral prefrontal circuitry central to pre-SMA and SMA stimulation is shown in Figure 2.

Figure 2: Diagram of the dorsal and ventral prefrontal circuitry central to pre-SMA and SMA  stimulation. Abbreviations: ACC: anterior cingulate cortex; BA: Brodmann’s area; FEF: frontal eye fields; IFG: inferior frontal gyrus; MFG: middle frontal gyrus; MPFC: medial prefrontal cortex; NAc: nucleus accumbens septi; OFC: orbitofrontal cortex; SMA: supplementary motor area; SN: substantia nigra; VTA: ventral tegmental area.

Conclusions

The inclusion of GD in the “substance related and addictive disorders” chapter of DSM-5 recognizes the disorder as a prototypical behavioral addiction, characterized by symptom clusters of loss of control, craving/withdrawal, and neglect of other areas of life. Nevertheless, the paucity of neuroimaging, genetic and translational data on GD results in a still scarce understanding of the neurobiological underpinnings of the disorder. This would be crucial to the development of targeted medications, given that, despite its prevalence and impact, there are no medications with indications for treating GD and to date; no drug has an indication approval from the FDA [67]. The adoption of a RDoC approach facilitates the identification of the neurobiological factors underlying the disorder by breaking up a complex psychiatric disorder into its components and domains and identifying the corresponding constructs and subconstructs, thus rendering the process more tangible and experimentally addressable. Importantly, RDoC constructs relate to biological and behavioral measures and may also help in identifying endophenotypes for the disorder. Therefore, recent research in GD is focusing on the identification of the neurobiological underpinnings of most employed behavioral tasks related to decision making and response inhibition (e.g. Iowa Gambling Task, Delayed Discounting Task, Stop Signal Task), to identify the neural correlates of the disorder’s symptomatologic clusters and domains. Herein, we focused on the symptom cluster “loss of control” (i.e., unsuccessful efforts to control, cut back, or stop gambling), which appears to be mainly related to impaired reward-related decision-making and deficits in executive functions. These deficits are associated with the RDoC domains of Positive Valence Systems (and its constructs of Approach motivation and Reward learning) and Cognitive Control (mainly its construct Response inhibition) respectively. Consistent with the RDoC matrix, deficits in preference-based decision-making have been identified in GD with the utilization of the IGT, revealing an involvement of numerous brain areas such as the striatum, amygdala, and OFC. Evidence regarding aberrant reward learning mechanisms are less robust, nevertheless they were hypothesized to be related with reward-based cognitive inflexibility and associated with an involvement of the OFC and ventral striatum, as highlighted in the RDoC matrix. Lastly, deficits in Cognitive control and particularly in the subconstruct of response inhibition have been identified in the disorder, using the SST and the Go/No-Go task, revealing the involvement of a fronto-striatal circuit and of the pre-supplementary motor area (pre-SMA). Further research is needed to expand our knowledge regarding the constructs of the disorder and how they correlate with the clinical presentation of the disorder as well as with the abnormalities at a neurocircuits level of explanation.

Conflict of Interest: The authors declare no conflict of interest.

Doi

https://doi.org/10.30435/ABA.01.2019.06

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