Impaired Decision-Making, Higher Impulsivity, and Drug Severity in Substance Dependence and Pathological Gambling.

OBJECTIVES: Substance use disorder is characterized by impaired decision making, impulsivity, and risk taking. Pathological gambling shares many of these characteristics, and having both diagnoses may be associated with greater problems than either diagnosis alone. We investigated whether among substance-dependent individuals, comorbid pathological gambling would be associated with worse decision making, greater impulsivity, risk taking, and drug severity. METHODS: Ninety-six substance-dependent individuals were recruited from a residential treatment program and divided into 1 of the 2 groups depending on whether they met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria for pathological gambling (SDPG, n = 26) or not (SD, n = 70). Ninety-two controls were recruited from the community. Participants completed a decision-making task (modified Iowa Gambling Task), measures of impulsivity (Barratt Impulsivity Scale and Delay Discounting), and risk taking (Balloon Analog Risk Task). Decision making was analyzed using a computational model. We tested for group differences using analysis of covariance or Kruskal-Wallis and appropriate post-hoc tests. RESULTS: The groups differed in decision-making parameters (P < 0.001) and self-reported impulsivity (P < 0.001). All post-hoc comparisons were significant on these measures, and indicated stepwise changes in controls, followed by SD, followed by SDPG, with SDPG performing worse on decision making and being more impulsive. Compared with SD, SDPG had greater drug severity (P < 0.001). No group differences were observed in delay discounting or risk taking. CONCLUSIONS: Compared with individuals with substance dependence without pathological gambling, those with both disorders demonstrated worse decision making and significantly more drug-related symptoms. When evaluating patients with substance dependence, clinicians should consider diagnostic assessments for gambling, as the co-occurrence of both disorders may impact clinical characteristics.

Morphologic changes in the mesolimbic pathway in Parkinson's disease motor subtypes.

BACKGROUND: Parkinson's disease (PD) is a common neurodegenerative disorder associated with gray matter atrophy. Cortical atrophy patterns may further help distinguish between PD motor subtypes. Comparable differences in subcortical volumes have not been found. METHODS: Twenty-one cognitively intact and treated PD patients, including 12 tremor dominant (TD) subtype, Nine postural instability gait dominant (PIGD) subtype, and 20 matched healthy control subjects underwent 3.0 T high-resolution structural MRI scanning. Subcortical volumetric analysis was performed using FreeSurfer and shape analysis was performed with FIRST to assess for differences between PD patients and controls and between PD subtypes. RESULTS: No significant differences in subcortical volumes were found between motor PD subtypes, but comparing grouped PD patients with controls revealed a significant increase in hippocampal volume in PD patients (p = 0.03). A significant shape difference was detected in the right nucleus accumbens (NAcc) between PD and controls and between motor subtypes. Shape differences were driven by positive deviations in the TD subtype. Correlation analysis revealed a trend between hippocampal volume and decreasing MDS-UPDRS (p = 0.06). CONCLUSION: While no significant differences in subcortical volumes between PD motor subtypes were found, increased hippocampal volumes were observed in PD patients compared to controls. Right NAcc shape differences in PD patients were driven by changes in the TD subtype. These unexpected findings may be related to the effects of chronic dopaminergic replacement on the mesolimbic pathway. Further studies are needed to replicate and determine the clinical significance of such morphologic changes.

Temporal profile of fronto-striatal-limbic activity during implicit decisions in drug dependence.

BACKGROUND: Substance dependence is associated with impaired decision-making and altered fronto-striatal-limbic activity. Both greater and lesser brain activity have been reported in drug users compared to controls during decision-making. Inconsistent results might be explained by group differences in the temporal profile of the functional magnetic resonance imaging (fMRI) response. While most previous studies model a canonical hemodynamic response, a finite impulse response (FIR) model measures fMRI signal at discrete time points without assuming a temporal profile. We compared brain activity during decision-making and feedback in substance users and controls using two models: a canonical hemodynamic response function (HRF) and a FIR model. METHODS: 37 substance-dependent individuals (SDI) and 43 controls performed event-related decision-making during fMRI scanning. Brain activity was compared across group using canonical HRF and FIR models. RESULTS: Compared to controls, SDI were impaired at decision-making. The canonical HRF model showed that SDI had significantly greater fronto-striatal-limbic activity during decisions and less activity during feedback than controls. The FIR model confirmed greater activity in SDI during decisions. However, lower activity in SDI during feedback corresponded to a lower post-stimulus undershoot of the hemodynamic response. CONCLUSIONS: Greater activity in fronto-striatal-limbic pathways in SDI compared to controls is consistent with prior work, further supporting the hypothesis that abnormalities in these circuits underlie impaired decision-making. We demonstrate for the first time using FIR analysis that lower activity during feedback may simply reflect the tail end of the hemodynamic response to decision, the post-stimulus undershoot, rather than an actual difference in feedback response.

Reduced neural tracking of prediction error in substance-dependent individuals.

OBJECTIVE: Substance-dependent individuals make poor decisions on the Iowa Gambling Task, a reward-related decision-making task that involves risk and uncertainty. Task performance depends on several factors, including how sensitive individuals are to feedback and how well they learn based on such feedback. A physiological signal that guides decision making based on feedback is prediction error. The authors investigated whether disruptions in the neural systems underlying prediction error processing in substance-dependent individuals could account for decision-making performance on a modified Iowa Gambling Task. METHODS: Thirty-two substance-dependent individuals and 30 healthy comparison subjects played a modified version of the Iowa Gambling Task during MR scanning. Trial-to-trial behavior and functional MRI (fMRI) blood-oxygen-level-dependent (BOLD) signal were analyzed using a computational model of prediction error based on internal expectancies. The authors investigated how well BOLD signal tracked prediction error in the striatum and the orbitofrontal cortex as well as over the whole brain in patients relative to comparison subjects. RESULTS: Compared with healthy subjects, substance-dependent patients were less sensitive to loss compared with gain, made less consistent choices, and performed worse on the modified Iowa Gambling Task. The ventral striatum and medial orbitofrontal cortex did not track prediction error as strongly in patients as in healthy subjects. CONCLUSIONS: Weaker tracking of prediction error in substance-dependent relative to healthy individuals suggests that altered frontal-striatal error learning signals may underlie decision-making impairments in drug abusers. Computational fMRI may help bridge the knowledge gap between physiology and behavior to inform research aimed at substance abuse treatment.

Sex modulates approach systems and impulsivity in substance dependence.

BACKGROUND: Personality traits such as pathological engagement in approach behaviors, high levels of impulsivity and heightened negative affect are consistently observed in substance dependent individuals (SDI). The clinical course of addiction has been shown to differ between sexes. For example, women increase their rates of consumption of some drugs of abuse more quickly than men. Despite the potential influence of personality and sex on features of addiction, few studies have investigated the interaction of these factors in substance dependence. METHODS: Fifty-one SDI (26 males, 25 females) and 66 controls (41 males, 25 females) completed the Behavioral Inhibition/Behavioral Activation System (BIS/BAS) Scales, the Barratt Impulsiveness Scale, and the Positive and Negative Affect Schedule (PANAS-X). Data were analyzed with 2×2 ANCOVAs testing for main effects of group, sex and group by sex interactions, adjusting for education level. RESULTS: Significant group by sex interactions were observed for BAS scores [F(1,116)=7.03, p<.01] and Barratt Motor Impulsiveness [F(1,116)=6.11, p<.02] with female SDI showing the highest approach tendencies and impulsivity followed by male SDI, male controls, and finally female controls. SDI scored higher on negative affect [F(1,116)=25.23, p<.001] than controls. Behavioral Inhibition System scores were higher in women than men [F(1,116)=14.03, p<.001]. CONCLUSION: Higher BAS and motor impulsivity in SDI women relative to SDI men and control women suggest that personality traits that have been previously associated with drug use may be modulated by sex. These factors may contribute to differences in the disease course observed in male compared to female drug users.

Resting-state activity in the left executive control network is associated with behavioral approach and is increased in substance dependence.

BACKGROUND: Individuals with drug addictions report increased willingness to approach rewards. Approach behaviors are thought to involve executive control processes and are more strongly represented in the left compared to right prefrontal cortex. A direct link between approach tendencies and left hemisphere activity has not been shown in the resting brain. We hypothesized that compared to controls, substance dependent individuals (SDI) would have greater left hemisphere activity in the left executive control network (ECN) at rest. METHODS: Twenty-five SDI and 25 controls completed a Behavioral Inhibition System/Behavioral Activation System (BIS/BAS) questionnaire and underwent a resting-state fMRI scan. Group independent component analysis was performed. We used template matching to identify the left and right ECN separately and compared the corresponding components across groups. Across group, BAS scores were correlated with signal fluctuations in the left ECN and BIS scores with right ECN. RESULTS: BAS scores were higher in SDI compared to controls (p<.003) and correlated with signal fluctuation in the left ECN. SDI showed significantly more activity than controls in the left prefrontal cortex of the left ECN. Conversely, SDI showed less activity than controls in the right prefrontal cortex of the right ECN. CONCLUSIONS: Results from this study suggest that approach tendencies are related to the left ECN, even during rest. Higher resting-state signal in the left ECN may play a role in heightened approach tendencies that contribute to drug-seeking behavior.

Negative reinforcement learning is affected in substance dependence.

BACKGROUND: Negative reinforcement results in behavior to escape or avoid an aversive outcome. Withdrawal symptoms are purported to be negative reinforcers in perpetuating substance dependence, but little is known about negative reinforcement learning in this population. The purpose of this study was to examine reinforcement learning in substance dependent individuals (SDI), with an emphasis on assessing negative reinforcement learning. We modified the Iowa Gambling Task to separately assess positive and negative reinforcement. We hypothesized that SDI would show differences in negative reinforcement learning compared to controls and we investigated whether learning differed as a function of the relative magnitude or frequency of the reinforcer. METHODS: Thirty subjects dependent on psychostimulants were compared with 28 community controls on a decision making task that manipulated outcome frequencies and magnitudes and required an action to avoid a negative outcome. RESULTS: SDI did not learn to avoid negative outcomes to the same degree as controls. This difference was driven by the magnitude, not the frequency, of negative feedback. In contrast, approach behaviors in response to positive reinforcement were similar in both groups. CONCLUSIONS: Our findings are consistent with a specific deficit in negative reinforcement learning in SDI. SDI were relatively insensitive to the magnitude, not frequency, of loss. If this generalizes to drug-related stimuli, it suggests that repeated episodes of withdrawal may drive relapse more than the severity of a single episode.