Risk Factors for Addiction and Their Association with Model-Based Behavioral Control

Abstract

Addiction shows familial aggregation and previous endophenotype research suggests that healthy relatives of addicted individuals share altered behavioral and cognitive characteristics with individuals suffering from addiction. In this study we asked whether impairments in behavioral control proposed for addiction, namely a shift from goal-directed, model-based toward habitual, model-free control, extends toward an unaffected sample (n = 20) of adult children of alcohol-dependent fathers as compared to a sample without any personal or family history of alcohol addiction (n = 17). Using a sequential decision-making task designed to investigate model-free and model-based control combined with a computational modeling analysis, we did not find any evidence for altered behavioral control in individuals with a positive family history of alcohol addiction. Independent of family history of alcohol dependence, we however observed that the interaction of two different risk factors of addiction, namely impulsivity and cognitive capacities, predicts the balance of model-free and model-based behavioral control. Post-hoc tests showed a positive association of model-based behavior with cognitive capacity in the lower, but not in the higher impulsive group of the original sample. In an independent sample of particularly high- vs. low-impulsive individuals, we confirmed the interaction effect of cognitive capacities and high vs. low impulsivity on model-based control. In the confirmation sample, a positive association of omega with cognitive capacity was observed in highly impulsive individuals, but not in low impulsive individuals. Due to the moderate sample size of the study, further investigation of the association of risk factors for addiction with model-based behavior in larger sample sizes is warranted.

Keywords: addiction; alcohol; cognitive capacity; decision-making; family history; impulsivity; instrumental control; risk.

Figure 1

Task and Raw Data Results. (A) Exemplary trial sequence. At each stage, subjects made a choice (maximum decision time 2 s) between two stimuli presented: two gray boxes at the first stage and two pairs of differently colored boxes at the second stage. After this choice the respective stimulus was framed in red, moved to the top of the screen and remained there for 1.5 s. before the subject entered the second stage, where another choice had to be made. Reward was delivered after the second-stage choice. (B) First and second stage choices were linked via a fixed transition probability: each first-stage choice led to one pair of the second-stage stimuli with a probability of 70% (C). Stay-switch behavior at the first-stage of the task was analyzed as a function of reward and state in the previous trial. These stay probabilities were subjected to repeated-measures ANOVAs with reward and state as within-subject factors and group as a between-subject factor. We observed a significant main effect of reward (F = 23.66, p < 0.001) and reward × state interaction (F = 43.83, p < 0.001); no significant main effect of state (F = 0.95, p = 0.34) and no significant reward × group (F = 0.38, p = 0.54), state × group (F = 1.85, p = 0.18) or reward × state × group (F = 0.57, p = 0.46) interactions could be observed.

Figure 2

Density function of BIS-11 values in the original sample and the confirmation sample. The different distributions are due to differences in recruitment strategy: in the confirmation sample, participants were specifically chosen based on particularly low vs. high values on the BIS-11 (Deserno et al., 2015a).

Figure 3

Model-based behavior and cognitive capacity. (A) Association of model-based behavior (as given by the parameter omega) with cognitive capacity (Z-score of fluid intelligence) in the lower, but not in the higher impulsive group of the original sample. (B) In the confirmation sample, a positive association of omega with cognitive capacity was found in the high-impulsive subgroup. In the original sample, high and low impulsive groups were defined based on a median split. In the confirmation sample, groups were defined by sampling from the upper and lower ends of the BIS-11 range in a larger sample (n = 452) according to their particularly high vs. low values in the BIS-11 (Deserno et al., 2015a).

Figure 4

Post-hoc tests with cognitive subdomains. (A) In the original sample, omega correlates positively with TMT B in the low impulsivity group. (B) In the confirmation sample, omega correlates positively with DSST scores in the high impulsivity group. In the original sample, high- and low-impulsive groups were defined based on a median split. In the confirmation sample, groups were defined by sampling from the upper and lower ends of the BIS-11 range in a larger sample (n = 452) according to their particularly high vs. low values in the BIS-11 (Deserno et al., 2015a). We plot z-transformed scores of the cognitive test scores.