TY  - JOUR
A1  - Wyckmans, Florent
A1  - Otto, A. Ross
A1  - Sebold, Miriam Hannah
A1  - Daw, Nathaniel
A1  - Bechara, Antoine
A1  - Saeremans, Mélanie
A1  - Kornreich, Charles
A1  - Chatard, Armand
A1  - Jaafari, Nemat
A1  - Noël, Xavier
T1  - Reduced model-based decision-making in gambling disorder
JF  - Scientific reports
N2  - Compulsive behaviors (e.g., addiction) can be viewed as an aberrant decision process where inflexible reactions automatically evoked by stimuli (habit) take control over decision making to the detriment of a more flexible (goal-oriented) behavioral learning system. These behaviors are thought to arise from learning algorithms known as "model-based" and "model-free" reinforcement learning. Gambling disorder, a form of addiction without the confound of neurotoxic effects of drugs, showed impaired goal-directed control but the way in which problem gamblers (PG) orchestrate model-based and model-free strategies has not been evaluated. Forty-nine PG and 33 healthy participants (CP) completed a two-step sequential choice task for which model-based and model-free learning have distinct and identifiable trial-by-trial learning signatures. The influence of common psychopathological comorbidities on those two forms of learning were investigated. PG showed impaired model-based learning, particularly after unrewarded outcomes. In addition, PG exhibited faster reaction times than CP following unrewarded decisions. Troubled mood, higher impulsivity (i.e., positive and negative urgency) and current and chronic stress reported via questionnaires did not account for those results. These findings demonstrate specific reinforcement learning and decision-making deficits in behavioral addiction that advances our understanding and may be important dimensions for designing effective interventions.
Y1  - 2019
U6  - https://doi.org/10.1038/s41598-019-56161-z
SN  - 2045-2322
VL  - 9
PB  - Nature Publ. Group
CY  - London
ER  -