C06 - Using machine learning to identify multivariate neural determinants of food choice in the human brain
In addition to the basal homeostatic-hedonic control mechanisms described in rodents, higher-level cognitive and socio-habitual factors impact eating behaviour in humans. This is reflected by a stronger recruitment of cortical areas, particularly frontal cortex. How the multiple subcortical and cortical sites interact to determine a human‚Äôs decision to eat is not well understood. This project will combine event-related fMRI with conventional and state-of-the-art machine learning approaches to investigate the neural determinants of immediate food choice and long-term eating behaviour in humans under different homeostatic, sensory-hedonic, cognitive and socio-habitual conditions from a multivariate perspective.