Neurobiomarkers of Real-World Dietary Success
Loading...
Authors
Parsons, John-Dennis
Date
Type
thesis
Language
eng
Keyword
dietary decision-making , functional magnetic resonance imaging (fMRI) , neuroanatomy and neural function , body mass index (BMI) , baseline and regulatory food choices
Alternative Title
Abstract
Why do some people regularly eat healthy foods, while many others suffer poor health outcomes due to maladaptive dietary choices? Empirical work suggests that functional and structural properties of the brain contain meaningful information about a person's ability to align their dietary behaviours with higher health goals. In previous magnetic resonance imaging (MRI) studies, brain structure and function in two regions of prefrontal cortex (PFC) were linked to individual differences in 'dietary success' in laboratory food tasks (Han et al., 2018; Schmidt et al., 2018; Tusche and Hutcherson, 2018). These regions were dorsolateral prefrontal cortex (dlPFC) and ventromedial prefrontal cortex (vmPFC). Both regions have long been known to play a role in food choices (Hare et al., 2009; 2011) by influencing valuation and self-control processes during dietary decision-making (Motoki and Suzuki, 2020). Function and structure in dlPFC and vmPFC are indicators of people's choice behaviour in laboratory food tasks, and so are construed as 'neurobiomarkers' of dietary success. But to what extent can these neurobiomarkers predict real-world dieting outcomes, and which are the strongest predictors? In the current study, we tested whether brain function and structure in these 'dietary success' regions could predict a proxy measure of successful dietary behaviour, namely body mass index (BMI). In a novel approach, we estimated subjects' BMI scores in an out-of-sample predictive analysis. In a single model, we combined neural activity and cortical thickness in dlPFC and vmPFC and tested the relationship between these neurobiomarkers and subjects' BMI scores. We found that the best prediction of BMI relied exclusively on neural activity in dlPFC and vmPFC. Moreover, the prediction was strongest when subjects made natural, autonomous food choices without any task-imposed goals or considerations. These results shed new light on how brain function and structure related to food choices in the laboratory can extend to predict BMI, an outcome of real-world dietary behaviour.
Description
Citation
Publisher
License
Queen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canada
ProQuest PhD and Master's Theses International Dissemination Agreement
Intellectual Property Guidelines at Queen's University
Copying and Preserving Your Thesis
This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.
Attribution-NonCommercial-ShareAlike 3.0 United States
ProQuest PhD and Master's Theses International Dissemination Agreement
Intellectual Property Guidelines at Queen's University
Copying and Preserving Your Thesis
This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.
Attribution-NonCommercial-ShareAlike 3.0 United States