Relation of neural response to palatable food tastes and images to future weight gain: Using bootstrap sampling to examine replicability of neuroimaging findings
- PMID: 30144570
- PMCID: PMC6197913
- DOI: 10.1016/j.neuroimage.2018.08.035
Relation of neural response to palatable food tastes and images to future weight gain: Using bootstrap sampling to examine replicability of neuroimaging findings
Abstract
Because understanding neural vulnerability factors that predict future weight gain may guide the design of more effective obesity prevention programs and treatments, we tested whether neural response to palatable food tastes and images predicted future weight gain. We recruited 135 initially healthy weight adolescents, to reduce the possibility that a history of overeating affected neural responsivity, had them complete fMRI paradigms examining neural response to tastes of milkshakes that varied in fat and sugar content and images of palatable foods, and assessed BMI annually over a 3-year follow-up. We used a novel bootstrapping analytic approach to investigate the replicability of the fMRI findings. Whole-brain analyses indicated that lower response in the pre-supplemental motor area to high-fat/low-sugar milkshake taste predicted future BMI gain in the full sample and in 5 out of the 10 bootstrap samples. Elevated response in the precentral gyrus/Rolandic operculum to images of appetizing foods predicted future BMI gain in the full sample and in 4 out of the 10 bootstrap samples. Other peaks that emerged in the full sample did not replicate in most of the bootstrap samples, suggesting they were not reliable. Region of interest analyses did not replicate the predictive effects of peaks reported in past papers that used similar paradigms, including the evidence that TaqIA polymorphism moderated the relation of striatal response to palatable food tastes to future weight gain. Results suggest that lower responsivity of a region implicated in motor processing in response to palatable taste was associated with greater BMI gain over time, and further that bootstrap sampling may be useful for estimating the replicability of findings that emerge from whole brain analyses or regions of interest analyses with the full sample.
Copyright © 2018 Elsevier Inc. All rights reserved.
Conflict of interest statement
All authors report no conflict of interest with respect to the content of this paper.
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