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 87 community-recruited regular, but not clinically problematic, gamblers during a binary-choice reinforcement-learning game, to characterize 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 utilize structure when it is available in the reinforcement history of games, potentially increasing their risks of sustaining gambling-related harms.

Keywords::

• computational psychiatry
• impulsivity
• gambling cognitive biases
• predictive control
• reinforcement-learning
• action-selection

Conflicts of interest

Funding sources: This work was supported by the Funding Agency Wellcome Trust under Grant WT088312AIA for T.E.J.B. as a Research Career Development fellowship; and the Funding Agency Wellcome Trust under Grant WT080540MA for L.T.H. to work as a DPhil student on this project

Competing interests: No potential conflict of interest was reported by the authors.

Constraints on publishing

No constraints on publishing were reported by the authors.

Additional information

Notes on contributors

M.S.M. Lim

Matthew S.M. Lim completed this work as part of his doctoral thesis at the University of Oxford.

G. Jocham

Gerhard Jocham is a postdoctoral researcher with Dr Tim Behrens, FMRIB Centre, University of Oxford.

L.T. Hunt

Laurence T. Hunt is a postdoctoral researcher with Dr Tim Behrens, FMRIB Centre, University of Oxford.

T.E.J. Behrens

Tim E.J. Behrens is a Wellcome Trust Fellow and university research lecturer at the Nuffield Department of Clinical Neurosciences, University of Oxford.

R.D. Rogers

Robert D. Rogers is a professor of Cognitive Neuroscience at Bangor University.