Do inherent preferences interfere with the associative learning of food values?

Cognitive and behavioral flexibility is crucial for adapting to changing environments. Studies probing this often use monetary rewards; however, food valuation is evolutionary and reflects strong, heterogeneous preferences beyond nutritional content. These inherent – rather than learned or calorically assumed – values motivate food choices in healthy individuals and may critically drive disordered eating behavior. Prior work suggests that such values can be changed, yet very little is known about the flexibility of this process. We designed a novel probabilistic reversal-learning task in which participants predict associations between personally salient food stimuli and point outcomes. Inherent subjective values were estimated from pre-task ratings of 65 food items. The task utilized 4 food stimuli that each participant (a) strongly disliked, (b) disliked, (c) liked, and (d) strongly liked. In Congruent blocks, participants’ subjective value ratings align with outcomes; in Incongruent blocks, this relationship is reversed, requiring flexible updating of food-value associations. We will use model-free and model-based approaches to probe differences in food-value learning, as reflected in participants’ outcome predictions, between Congruent and Incongruent conditions.