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Peer-reviewed journal article

Top-down expectation effects of food labels on motivation

Joost WegmaniD, Ilke van Loon, Paul A.M. SmeetsiD, Roshan CoolsiD, Esther AartsiD

Abstract

When we buy our food, the information on the package informs us about the properties of the product, such as its taste and healthiness. These beliefs can influence the processing of food rewards and impact decision making beyond objective sensory properties. However, no studies, within or beyond the food domain, have assessed how written information, such as food labels, affect implicit motivation to obtain rewards, even though choices in daily life might be strongly driven by implicit motivational biases. We investigated how written information affects implicit motivation to obtain food rewards. We used food labels (high- and low-calorie), associated with an identical lemonade, to study motivation for food rewards during fMRI. In a joystick task, hungry participants (N=31) were instructed to make fast approach or avoid movements to earn the cued drinks. Behaviorally, we found a general approach bias, which was stronger for the drink that was most preferred during a subsequent choice test, i.e. the one labeled as low-calorie. This behavioral effect was accompanied by increased BOLD signal in the sensorimotor cortex during the response phase of the task for the preferred, low-calorie drink compared with the non-preferred, high-calorie drink. During the anticipation phase, the non-preferred, high-calorie drink label elicited stronger fMRI signal in the right ventral anterior insula, a region associated with aversion and taste intensity, than the preferred, low-calorie label. Together, these data suggest that high-calorie labeling can increase avoidance of drinks and reduce neural activity in brain regions associated with motor control. In conclusion, we show effects of food labeling on fMRI responses during anticipation and subsequent motivated action and on behavior, in the absence of objective taste differences, demonstrating the influence of written information on implicit biases. These findings contribute to our understanding of implicit biases in real-life eating behavior.

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