Associative learning and high-level cognitive processes in the control of food-related behaviors

Abstract

We are under constant pressure to make decisions about what, when, and how much to eat. Under these circumstances, the interactions among associative learning, rule-based learning, and cognitive control are critical to predict our food-related behaviors. This selective review summarizes some of the key findings from the last years to provide an introductory overview of the interplay of these constructs in the food context. Evidence from inhibitory-control training suggests that understanding of fundamental associative processes may be a relevant prerequisite for gaining insight into high-level cognitive control. Moreover, investigating associative processes in executive-control paradigms will lead not only to the discovery of novel food-related learning phenomena, but it will also be the central challenge for the next generation of behavior-change interventions targeting disordered eating.