Item

Abstract

Functional magnetic resonance imaging (fMRI) studies require contrast conditions, such as high- vs. low-caloric food items in food-related neuroimaging. Comparing food value signals across reward domains, such as drugs, money, social networks etc., is challenging (e.g. due to difficulties in standardisation or ethical reasons); therefore, different contrast conditions are necessary, e.g. art paintings. Thus, we propose artistic images as a new contrast condition for food-related neuroimaging and other fields of research. This is based on the idea of art as a secondary reward as it elicits similar brain activity patterns compared to primary rewards such as food. We used a deep learning algorithm to merge image styles with input images and thereby create new stimuli based on mundane items with artistic properties. This reduces the dimensionality and complexity of real artwork and makes the art.pics comparable to food pictures. We aim hereby to create an open access database for art stimuli providing normative rating data to be used in experimental contexts.