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. 2024 Nov 23:20:100574.
doi: 10.1016/j.abrep.2024.100574. eCollection 2024 Dec.

Impact of provoked stress on model-free and model-based reinforcement learning in individuals with alcohol use disorder

Affiliations

Impact of provoked stress on model-free and model-based reinforcement learning in individuals with alcohol use disorder

Florent Wyckmans et al. Addict Behav Rep. .

Abstract

Background: From both clinical and theoretical perspectives, understanding the functionality of evaluative reinforcement learning mechanisms (Model-Free, MF, and Model-Based, MB) under provoked stress, particularly in Alcohol Use Disorder (AUD), is crucial yet underexplored. This study aims to evaluate whether individuals with AUD who do not seek treatment show a greater tendency towards retrospective behaviors (MF) rather than prospective and deliberative simulations (MB) compared to controls. Additionally, it examines the impact of induced social stress on these decision-making processes.

Methods: A cohort comprising 117 participants, including 55 individuals with AUD and 62 controls, was examined. Acute social stress was induced through the socially evaluated cold pressor task (SECPT), followed by engagement in a Two-Step Markov task to assess MB and MF learning tendencies. We measured hypothalamic-pituitary-adrenal axis stress response using salivary cortisol levels.

Results: Both groups showed similar baseline cortisol levels and responses to the SECPT. Our findings indicate that participants with AUD exhibit a reduced reliance on MB strategies compared to those without AUD. Furthermore, stress decreases reliance on MB strategies in healthy participants, but this effect is not observed in those with AUD.

Conclusion: An atypical pattern of stress modulation impacting the balance between MB and MF reinforcement learning was identified in individuals with AUD who are not seeking treatment. Potential explanations for these findings and their clinical implications are explored.

Keywords: Alcohol Use Disorder; Cortisol; Model-Based; Model-Free; Reinforcement Learning; Stress.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Structure of the experiment with all phases and additional measures in chronological order.
Fig. 2
Fig. 2
State transition and reward structure in the two-step RL task.
Fig. 3
Fig. 3
Cortisol and self-reported measures for the group that underwent the cold-pressor task (SECPT) and the Warm-Pressor Task (WPT). Cortisol concentrations are expressed on a logarithmic scale and centered for each subject around its baseline. Graphs show mean values ± SE. P-values of the effect of interaction between time and procedure are reported. * p < 0.05, ** p < 0.01, *** p < 0.001.
Fig. 4
Fig. 4
Effect of the cortisol increase on ω-parameter in AUD and HC. Each continuous score was standardized, and 95% IC is displayed around each regression line.
Fig. 5
Fig. 5
Distribution of the ω-parameter across groups.

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