Limbic and prefrontal brain networks represent distinct information about food hedonics and inhibitory control
Year: 2023
Type: preprint
Abstract: Studies of the neural response to food stimuli are often guided by assumptions about the relevance of particular food properties, and may not address the properties most relevant to participants. We sought to identify those properties and their neural representation, through analyzing the neuroimaging data of 43 participants who viewed images of 36 types of food during functional MRI. We used a data-driven clustering approach based on Representational Similarity Analysis (RSA) that partitioned food-responsive brain regions into two networks, based on their multivariate response to those food images: a Prefrontal network composed of frontoparietal brain regions, and a Limbic network composed of corticolimbic and sub-cortical regions. We performed RSA within these networks using data from a task involving similarity judgements of those same foods, obtained from a large sample of online participants. We identified that the inferred healthfulness or artificiality of those foods was the greatest factor underlying similarity judgments and this property was most strongly represented within the Prefrontal network, suggesting its involvement in the regulation of food consumption. We confirmed this possibility through analysis of a second neuroimaging task, performed by the same participants, which identified that the response to food images in the Prefrontal network was modulated strongly by judgments of the self-control required to resist eating those foods. In contrast, the Limbic network response was primarily modulated by hedonic food judgments. These results suggest that food-related information is distributed across functionally distinct brain networks which act as opponent processes involved in guiding food-related behavior.
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W4383912714