Contingency learning in alcohol dependence and pathological gambling: learning and unlearning reward contingencies.

BACKGROUND

Patients with alcohol dependence (AD) and pathological gambling (PG) are characterized by dysfunctional reward processing and their ability to adapt to alterations of reward contingencies is impaired. However, most neurocognitive tasks investigating reward processing involve a complex mix of elements, such as working memory, immediate and delayed rewards, and risk-taking. As a consequence, it is not clear whether contingency learning is altered in AD or PG. Therefore, the current study aimed to examine performance in a deterministic contingency learning task, investigating discrimination, reversal, and extinction learning.

METHODS

Thirty-three alcohol-dependent patients (ADs), 28 pathological gamblers (PGs), and 18 healthy controls (HCs) performed a contingency learning task in which they learned stimulus-reward associations that were first reversed and later extinguished while receiving deterministic feedback throughout. Accumulated points, number of perseverative errors and trials required to reach a criterion in each learning phase were compared between groups using nonparametric Kruskal-Wallis rank-sum tests. Regression analyses were performed to compare learning curves.

RESULTS

PGs and ADs did not differ from HCs in discrimination learning, reversal learning, or extinction learning, on the nonparametric tests. Regression analyses, however, showed differences in the initial speed of learning: PGs were significantly faster in discrimination learning compared to ADs, and both PGs and ADs learned slower than HCs in the reversal learning and extinction phases of the task.

CONCLUSIONS

Learning rates for reversal and extinction were slower for the alcohol-dependent group and PG group compared to HCs, suggesting that reversing and extinguishing learned contingencies require more effort in ADs and PGs. This implicates a diminished flexibility to overcome previously learned contingencies.