Higher motivation and pleasure scores predict more reliance on model-free decision making.

Decision making is driven by factors such as motivation, pleasure, and cognitive skill. The current study evaluates how these factors are related to decision making in a community population. In recent years, work in the field of reinforcement learning has identified two main pathways that drive decision making: model-based and model-free learning. Model-free learning updates action values retrospectively, after a reward is received. In contrast, model-based learning updates action values prospectively, by weighing contextual factors, the overall structure of the situation, and reward received. The current study utilizes a two-stage decision-making task to assess the relative contribution of model-free versus model-based learning in relation to measures that assess motivation, pleasure, and cognition in a community sample (n = 127). Generalized linear mixed-effect models showed that individuals high in motivation and pleasure had significantly greater reliance on model-free decision making (p = 0.0267). In contrast, individuals with better working memory, as measured by a running span task, had significantly greater reliance on model-based learning (p = 0.0003). These findings provide evidence that individual differences in motivation and cognition are associated with reliance on particular learning pathways. It has been suggested that lower levels of motivation, pleasure, and cognition in various forms of psychopathology (e.g., depression) can impair decision making. Our results show these relationships transcend clinical contexts. Specifically, these findings suggest that individuals who experience low motivation and pleasure may be less sensitive to immediate rewards, and that working memory capacity is highly relevant to model-based learning.