Selectivity for food in human ventral visual cortex

• Published in: Communications biology Vol. 6; no. 1; pp. 175 - 14
• Main Authors: Jain, Nidhi, Wang, Aria, Henderson, Margaret M., Lin, Ruogu, Prince, Jacob S., Tarr, Michael J., Wehbe, Leila
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 15.02.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 631/378/116/2394; 631/378/116/2395; 631/378/2613/2616; 631/378/2649/1723; Biology; Biomedical and Life Sciences; Brain Mapping - methods; Food; Food selection; Functional magnetic resonance imaging; Humans; Image processing; Life Sciences; Magnetic Resonance Imaging - methods; Pattern Recognition, Visual; Photic Stimulation - methods; Statistical analysis; Visual cortex; Visual Cortex - diagnostic imaging; Visual system
• ISSN: 2399-3642; 2399-3642
• DOI: 10.1038/s42003-023-04546-2

Visual cortex contains regions of selectivity for domains of ecological importance. Food is an evolutionarily critical category whose visual heterogeneity may make the identification of selectivity more challenging. We investigate neural responsiveness to food using natural images combined with large-scale human fMRI. Leveraging the improved sensitivity of modern designs and statistical analyses, we identify two food-selective regions in the ventral visual cortex. Our results are robust across 8 subjects from the Natural Scenes Dataset (NSD), multiple independent image sets and multiple analysis methods. We then test our findings of food selectivity in an fMRI “localizer” using grayscale food images. These independent results confirm the existence of food selectivity in ventral visual cortex and help illuminate why earlier studies may have failed to do so. Our identification of food-selective regions stands alongside prior findings of functional selectivity and adds to our understanding of the organization of knowledge within the human visual system. Neural responsiveness to food images was measured in healthy participants using fMRI, establishing food-selective regions using both data- and hypothesis-driven methods. Further analyses illuminate the organization of food within the visual system.