Impulsivity and predictive control are associated with suboptimal action-selection and action-value learning in regular gamblers

Abstract

Heightened impulsivity and cognitive biases are risk factors for gambling problems. However, little is known about precisely how these factors increase the risks of gambling-related harm in vulnerable individuals. Here, we modelled the behaviour of eighty-seven community-recruited regular, but not clinically problematic, gamblers during a binary-choice reinforcement-learning game, to characterise the relationships between impulsivity, cognitive biases, and the capacity to make optimal action selections and learn about action-values. Impulsive gamblers showed diminished use of an optimal (Bayesian-derived) probability estimate when selecting between candidate actions, and showed slower learning rates and enhanced non-linear probability weighting while learning action values. Critically, gamblers who believed that it is possible to predict winning outcomes (as 'predictive control') failed to use the game's reinforcement history to guide their action selections. Extensive evidence attests to the ease with which gamblers can erroneously perceive structure in the reinforcement history of games when there is none. Our findings demonstrate that the generic and specific risk factors of impulsivity and cognitive biases can interfere with the capacity of some gamblers to utilise structure when it is available in the reinforcement history of games, potentially increasing their risks of sustaining gambling-related harms.