The role of dopamine in inhibitory control in smokers and non-smokers: A pharmacological fMRI study

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Abstract

Contemporary theoretical models of substance dependence posit that deficits in inhibitory control play an important role in substance dependence. The neural network underlying inhibitory control and its association with substance dependence have been widely investigated. However, the pharmacology of inhibitory control is still insufficiently clear. The aims of the current study were twofold. First, we investigated the role of dopamine in inhibitory control and associated brain activation. Second, the proposed link between dopamine and impaired inhibitory control in nicotine dependence was investigated by comparing smokers and non-smoking controls. Haloperidol (2 mg), a dopamine D2/D3 receptor antagonist, and placebo were administered to 25 smokers and 25 non-smoking controls in a double-blind randomized cross-over design while performing a Go/NoGo task during fMRI scanning. Haloperidol reduced NoGo accuracy and associated brain activation in the ACC, right SFG and left IFG, showing that optimal dopamine levels are crucial to effectively implement inhibitory control. In addition, smokers showed behavioral deficits on the Go/NoGo task as well as hypoactivity in the left IFG, right MFG and ACC after placebo, supporting the hypothesis of a hypoactive prefrontal system in smokers. Haloperidol had a stronger impact on prefrontal brain activation in non-smoking controls compared to smokers, which is in line with the inverted ‘U’ curve theory of dopamine and cognitive control. The current findings suggest that altered baseline dopamine levels in addicted individuals may contribute to the often observed reduction in inhibitory control in these populations.

Introduction

Contemporary theoretical models of substance dependence posit that deficits in inhibitory control are of key importance in the development and continuation of substance dependence (Goldstein and Volkow, 2011, Jentsch and Taylor, 1999, Lubman et al., 2004). Deficits in inhibitory control may contribute to the inability to stop taking drugs despite negative consequences and may increase reactivity to substance related cues including attentional bias (Field and Cox, 2008). Inhibitory control is accomplished through a cortical–striatal–thalamic network with feedback loops from sub-cortical regions such as the basal ganglia to prefrontal regions (Feil et al., 2010). The cortical part of the inhibitory control network is mainly right-lateralized and includes the inferior frontal gyrus (IFG), the anterior cingulate gyrus (ACC)/pre-supplementary motor area (pre-SMA) and dorsolateral prefrontal cortex (DLPFC), as well as parietal areas (Aron and Poldrack, 2006, Chambers et al., 2009, Swick et al., 2011). Hypoactivation in prefrontal brain regions has been reported in substance dependent individuals including smokers (De Ruiter et al., 2012, Hester and Garavan, 2004, Kaufman et al., 2003, Li et al., 2009, Nestor et al., 2011). Additionally, hypoactivation in these regions seems to be related to difficulties in controlling substance use in daily life as it was found to be associated with a strong coupling between subjective craving and smoking (Berkman et al., 2011). Although the neural network underlying inhibitory control and its association with substance dependence have been widely investigated, the pharmacology of inhibitory control is an ongoing scientific endeavor. Animal studies suggest that dopamine plays an important role in overall executive functioning. For example, a hallmark study by Brozoski et al., (1979) indicated that dopamine depletion of the monkey prefrontal cortex impaired spatial working memory. In addition, reduced dopamine D2/D3 receptor availability in rats appeared to be associated with elevated impulsivity levels (Dalley et al., 2007). Based on human studies, theorists assume that the relation between dopamine and cognitive control follows an inverted U-shaped curve such that either too low or too high levels of prefrontal dopamine are disadvantageous for cognitive functioning (Cools and D'Esposito, 2011). The inverted U-curve theory further describes a distinct role for dopamine D1 and D2 receptors. Dopamine D1 receptors are mainly expressed in prefrontal regions and appear to be associated with tonic modulation of prefrontal brain activation which is associated with cognitive stability, while dopamine D2 receptors are most prominent in subcortical regions and appear to be associated with implementing flexible behavior. The proposed association between dopamine and cognitive functioning in the inverted U-curve theory is mainly based on studies investigating working memory performance, but it is likely that other cognitive functions depending on prefrontal brain activation are similarly characterized by an inverted U-shaped curve. Recent studies in humans have shown that optimal dopamine levels (i.e., extracellular dopamine and receptor densities) exist for attentional capacity (Finke et al., 2010) and also inhibitory control (Nandam et al., 2011), although these studies are still scarce. It is important to gain more knowledge on how dopamine affects neural networks underlying inhibitory control, to better understand disorders such as substance dependence that are characterized by dysfunctional dopamine systems (Balfour, 2009, Berkman et al., 2011, Diekhof et al., 2008, Franken et al., 2005, Koob and Nestler, 1997, Volkow et al., 2009). For example, reduced dopamine D2 receptor densities in the striatum have been consistently found in substance dependent individuals (Martinez et al., 2004, Volkow et al., 2001, Volkow et al., 2002, Wang et al., 1997) including smokers (Fehr et al., 2008). These reduced dopamine D2 densities have also been linked to reduced metabolism in prefrontal areas (Volkow et al., 1993, Volkow et al., 2001, Volkow et al., 2007). Altogether, it is suggested that alterations in dopaminergic functioning in substance dependent individuals may underlie the observed deficits in inhibitory control as well as hypoactivation in associated prefrontal regions. Increased knowledge concerning the role of dopamine in inhibitory control may contribute to a deeper understanding of dopaminergic medications and the limited efficacy of both dopamine agonists and dopamine antagonists in the treatment of addiction until now (Amato et al., 2007, Elkashef et al., 2005).

To the best of our knowledge, only one study employed a dopamine manipulation in substance dependent individuals while measuring inhibitory control (Li et al., 2010). It was shown that the dopamine agonist methylphenidate enhanced inhibitory control compared to placebo in cocaine dependent individuals. The behavioral improvement in inhibitory control was positively associated with activation in the middle frontal gyrus and negatively with activation in the ventromedial prefrontal cortex (Li et al., 2010). Although this study provided valuable insights, a control group consisting of healthy participants was lacking. The aims of the current study were twofold. First, a dopamine manipulation was employed to investigate the role of dopamine in inhibitory control and associated brain activation. Second, the potential link of dopamine with impaired inhibitory control in nicotine dependence was investigated by comparing the effects of dopaminergic manipulation between smokers and non-smoking controls. As part of a larger study (Luijten et al., 2012), participants received placebo and haloperidol in a double-blind randomized cross-over design while performing a Go/NoGo task during fMRI scanning. Haloperidol is a predominant D2/D3 post-synaptic receptor antagonist. As D2 receptors are mainly expressed in subcortical regions (Hall et al., 1994), it can be expected that haloperidol modulates inhibitory control and prefrontal brain functioning via blockade of the indirect basal ganglia pathway in the cortical–thalamic–striatal network underlying inhibitory control. Furthermore, in line with previous studies showing beneficial effects of a dopamine agonist (Li et al., 2010, Nandam et al., 2011), we hypothesized that haloperidol will reduce inhibitory control and associated brain activation. Second, based on the inverted ‘U’ curve theory of dopamine and cognitive control, and reported baseline differences between smokers and controls in dopamine D2 receptor density in subcortical regions, we expected that haloperidol will have differential effects on brain activation associated with inhibitory control in smokers and non-smokers.

Section snippets

Participants

Twenty-five smokers and twenty-five non-smoking controls participated in this study. Data from two non-smokers were discarded due to technical problems during data acquisition and analysis. The final sample consisted of 25 smokers (mean age=22.56 years, SD=2.84, 18 male) and 23 non-smoking controls (mean age=21.74 years, SD=1.82, 14 male). Smokers smoked at least 15 cigarettes per day (M=19.12, SD=3.37; range 15–25) for a duration of at least three years (M=7.20, SD=3.01, range=3–14). The

CO levels and questionnaire data

Smokers had a higher CO breath concentration (in parts per million, Mhaloperidol=6.20, SD=3.39, Mplacebo=6.72, SD=3.50) as compared to non-smoking controls (Mhaloperidol=1.43, SD=0.79, Mplacebo=1.65, SD=0.51), F(1,46)=52.77, p<0.001. CO levels did not differ between medication types for either group, F(1,46)=1.68, ns. Subjective craving in smokers was equal for placebo (M=39.71, SD=11.48) and haloperidol (M=38.08, SD=11.80) conditions F(1,23)=0.44, ns.

Behavioral performance

Accuracy rates revealed a robust main

Discussion

The aim of the current study was to elucidate the role of dopamine in inhibitory control and associated brain activation. In addition, by comparing smokers and non-smokers the potential link between dopamine and reduced inhibitory control in addiction was investigated. The current results confirmed the hypothesis that reduced dopamine levels after haloperidol intake are associated with impairments in inhibitory control. Haloperidol reduced NoGo accuracy rates in both groups, while Go accuracy

Role of funding source

This study was supported by a Grant of the Netherlands Organization for Scientific Research (NWO; VIDI Grant no. 016.08.322). The funding organization had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Contributors

Study designs: IHAF, ML, DJV, RH; data collections: ML, LP (psychiatric screening); data analyses: ML, IMTN, RH, DJV, MS; manuscript writings: ML, IHAF, DJV, RH, MS, IMTN, LP.

Conflicts of interest

The authors have no conflicts of interests regarding the integrity of the reported findings.

Acknowledgment

We would like to thank Esther Spittel for her assistance with data collection and participant recruitment.

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