Apparent food selectivity reflects multiple non-food image properties
Three recent publications have reported selective fMRI responses to images of food in the human ventral visual pathway. However, all three studies were based primarily on the Natural Scenes Dataset (NSD), in which high-level categories like food are correlated with other image properties such as the color and size of objects, and the distance of the scene. To test whether the reported food selectivity might reflect these or other correlates of food images rather than (or in addition to) food, we constructed novel stimuli that manipulated these properties on both food and non-food images, and collected data from new subjects in a data-rich design across two experiments pre-registered in OSF. We used a localizer paradigm based on a subset of NSD images to infer the "food component" in new subjects and then measured responses of this component to our new stimuli. In Experiment 1, we found that the food component response magnitude i) had a higher response to color than to greyscale images but showed no interaction between food and color, ii) showed a reduced preference for food over non-food when both were within reaching distance, and most importantly iii) was no higher for food than non-food when both were visually matched and presented as Cutouts on a white background. In Experiment 2, we found that the response of the food component could not be explained by object distance, real-world size, or mid-level visual image statistics. However, the response to non-food images with "gooey" material properties was as high as the response to food. Across both experiments, we consistently found a very low response (at or below fixation baseline) to NSD non-food images, which were predominantly outdoor scenes. Together, our results prompt a revision of prior claims including our own, indicating that the previously reported food component is better characterized as food-biased rather than strictly food-selective, and is driven in part by contextual or material features that are also present in non-food images. Our findings further highlight the importance of supplementing studies based on naturalistic images with experiments that unconfound image properties with carefully designed stimuli.