Neurocomputational Mechanisms of Self-Control in Dietary Choices: A Value-Based Decision-Making Perspective

ABSTRACT:

Why do some individuals reliably succeed at self-control while others struggle — especially in the face of tempting choices? In this talk, I present a series of studies combining behavioral computational modeling with functional and structural MRI data to investigate the neural mechanisms supporting cognitive regulation across different goals and choice contexts. Our findings challenge traditional views of self-control as the inhibition of prepotent hedonic impulses or the direct modulation of integrative value signals in core valuation regions such as the ventromedial prefrontal cortex (vmPFC). Instead, our results highlight the critical role of flexible, goal-consistent representations of choice attributes, encoded in regions like the dorsolateral prefrontal cortex (DLPFC), which reliably predict regulatory success.

Extending beyond localized brain activity, we also examine individual differences in self-control using a novel gradient-based framework that captures large-scale patterns of neural organization. This whole-brain approach reveals how self-regulation may depend on stable modes of brain activation that minimize the need for context-specific reconfiguration of large-scale activation patterns.

Together, these findings provide new insights into the neural architecture of dietary self-control and goal-directed behavior more broadly — suggesting that successful regulators may rely on flexible, goal-dependent representations of choice-relevant attributes and large-scale brain states that efficiently support flexible decision-making across domains.

ABOUT THE SPEAKER:

Prof. Anita Tusche is an Associate Professor of Psychology at Queen’s University and Director of the Queen’s Neuroeconomics Lab. Her research combines neuroscience, psychology, and behavioural economics to explore the neural mechanisms of social decision-making, including empathy, altruism, and consumer behaviour. Using tools like fMRI and machine learning, she investigates how cognitive and emotional processes shape choices and individual differences