December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
Representation of naturalistic food categories in the human brain
Author Affiliations & Notes
  • Jason Avery
    Laboratory of Brain and Cognition, National Institute of Mental Health
  • Madeline Carrington
    Laboratory of Brain and Cognition, National Institute of Mental Health
  • Alexander Liu
    Laboratory of Brain and Cognition, National Institute of Mental Health
  • Alex Martin
    Laboratory of Brain and Cognition, National Institute of Mental Health
  • Footnotes
    Acknowledgements  This study was supported by the Intramural Research Program of the NIMH/NIH: ZIA MH002588
Journal of Vision December 2022, Vol.22, 3426. doi:https://doi.org/10.1167/jov.22.14.3426
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      Jason Avery, Madeline Carrington, Alexander Liu, Alex Martin; Representation of naturalistic food categories in the human brain. Journal of Vision 2022;22(14):3426. https://doi.org/10.1167/jov.22.14.3426.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Studies of the neural response to food pictures have identified responses in food-associated regions, such as the insula, amygdala, and orbitofrontal cortex. However, beyond this domain-specific response, little is known about how finer-grained food categories are represented in the brain. Specifically, are brain responses to food pictures driven more by objective measures of food qualities or by subjective estimates of those qualities? To address this question, we asked 487 participants on Amazon Mechanical Turk to perform an “odd-one-out” triplet task to generate a quantitative measure of the similarity of 36 food images with varying known levels of fat and sugar. We used the data from this task to generate a similarity matrix of these foods, which we then analyzed using Principal Components Analysis and K-means clustering, to identify subjective categories of these foods. Using these emergent categories and a Representational Similarity Analysis approach, we analyzed the neuroimaging data of 61 healthy subjects who viewed pictures of these foods and non-food objects during fMRI. PCA of the online data indicated most of the variance was related to participants’ estimates of how processed the foods were and their sugar content, rather than objective measures of fat, sugar, or caloric content. K-means clustering of this data revealed five emergent food groupings: sweets, fats, starches, fruits, and vegetables. Multivariate hemodynamic responses to food pictures reflected this category structure – and not objective nutritional content – in food-responsive ROIs in the brain, as pattern similarity was significantly greater within vs. between categories in the mid-insula, OFC, amygdala, and ventral striatum. A searchlight analysis also reflected this food-category structure in the responses of bilateral regions of the ventral occipito-temporal cortex. These results reveal a fine-grained representation of food categories in the brain that corresponds more to subjective assessments of food qualities, than to objective food properties.

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