The foodcast research image database (FRIDa)

In recent years we have witnessed to an increasing interest in food processing and eating behaviors. This is probably due to several reasons. The biological relevance of food choices, the complexity of the food-rich environment in which we presently live (making food-intake regulation difficult), and the increasing health care cost due to illness associated with food (food hazards, food contamination, and aberrant food39 intake). Despite the importance of the issues and the relevance of this research, comprehensive and validated databases of stimuli are rather limited, outdated, or not available for noncommercial purposes to independent researchers who aim at developing their own research program. The FoodCast Research Image Database (FRIDa) we present here is comprised of 877 images from eight different categories: natural-food (e.g., strawberry), transformed-food (e.g., French fries), rotten-food (e.g., moldy banana), natural-nonfood items (e.g., pinecone), artificial food-related objects (e.g., teacup), artificial objects (e.g., guitar), animals (e.g., camel), and scenes (e.g., airport). FRIDa has been validated on a sample of healthy participants (N=73) on standard variables (e.g., valence, familiarity etc.) as well as on other variables specifically related to food items (e.g., perceived calorie content); it also includes data on the visual features of the stimuli (e.g., brightness, high frequency power etc.). FRIDa is a well-controlled, flexible, validated, and freely available (http://foodcast.sissa.it/neuroscience/) tool for researchers in a wide range of academic fields and industry.