Characterization of a food image stimulus set for the study of multi-attribute decision-making

Abstract

Everyday decisions are generally made between options that vary on multiple different attributes. These might vary from basic biological attributes (e.g. caloric density of a food) to higher-order attributes like healthiness or aesthetic appeal. There is a long tradition of studying the processes involved in explicitly multi-attribute decisions, with information presented in a table, for example. However, most naturalistic choices require attribute information to be identified from the stimulus during evaluation or value comparison. Well-characterized stimulus sets are needed to support behavioral and neuroscience research on this topic. Here we present a set of 200 food images suited to the study of multi-attribute value-based decision-making. The set includes food items likely to appeal to those accustomed to North American and European diets, varying widely on the subjective attributes of visual-aesthetic appeal (“beauty”), tastiness and healthiness, as rated by healthy young Canadian participants (N=30-67). The images have also been characterized on objective characteristics relevant to food decision-making, including caloric density, macronutrient content and visual salience. We provide all attribute data by image and show the extent to which attributes are correlated across the stimulus set. We hope this stimulus set will accelerate progress in the study of naturalistic, value-based decision-making.