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A direct comparison between ERP and fMRI measurements of food-related inhibitory control: Implications for BMI status and dietary intake.

Authors :
Carbine KA
Duraccio KM
Kirwan CB
Muncy NM
LeCheminant JD
Larson MJ
Source :
NeuroImage [Neuroimage] 2018 Feb 01; Vol. 166, pp. 335-348. Date of Electronic Publication: 2017 Nov 04.
Publication Year :
2018

Abstract

Obesity and maintaining a healthy diet have important implications for physical and mental health. One factor that may influence diet and obesity is inhibitory control. We tested how N2 and P3 amplitude, event-related potential (ERP) components that reflect inhibitory control, and functional magnetic resonance imaging (fMRI) activity in brain regions associated with inhibitory control differed toward high- and low-calorie food stimuli across BMI status. We also assessed the relationship between neural indices of food-related inhibitory control and laboratory and daily food intake. Fifty-four individuals (17 normal-weight; 18 overweight; 19 individuals with obesity) completed two food-based go/no-go tasks (one with high- and one with low-calorie foods as no-go stimuli), once during ERP data acquisition and once during fMRI data acquisition. After testing, participants were presented with an ad libitum weighed food buffet. Participants also recorded their food intake using the Automated Self-Administered 24-hour Dietary Recall (ASA24) system across four days. Individuals recruited more inhibitory control when withholding responses towards high-compared to low-calorie foods, although this effect was more consistent for N2 than P3 or fMRI assessments. BMI status did not influence food-related inhibitory control. A larger inhibitory response as measured by N2 amplitude was related to increased ASA24 food intake; P3 amplitude and fMRI region of interest activity did not predict ASA24 intake; neither method predicted food intake from the buffet. ERP and fMRI measurements show similar neural responses to food, although N2 amplitude may be somewhat more sensitive in detecting differences between food types and predicting self-reports of food intake.<br /> (Copyright © 2017 Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1095-9572
Volume :
166
Database :
MEDLINE
Journal :
NeuroImage
Publication Type :
Academic Journal
Accession number :
29113942
Full Text :
https://doi.org/10.1016/j.neuroimage.2017.11.008