Literature DB >> 24893320

Greater striatopallidal adaptive coding during cue-reward learning and food reward habituation predict future weight gain.

Kyle S Burger1, Eric Stice2.   

Abstract

Animal experiments indicate that after repeated pairings of palatable food receipt and cues that predict palatable food receipt, dopamine signaling increases in response to predictive cues, but decreases in response to food receipt. Using functional MRI and mixed effects growth curve models with 35 females (M age=15.5±0.9; M BMI=24.5±5.4) we documented an increase in BOLD response in the caudate (r=.42) during exposure to cues predicting impending milkshake receipt over repeated exposures, demonstrating a direct measure of in vivo cue-reward learning in humans. Further, we observed a simultaneous decrease in putamen (r=-.33) and ventral pallidum (r=-.45) response during milkshake receipt that occurred over repeated exposures, putatively reflecting food reward habitation. We then tested whether cue-reward learning and habituation slopes predicted future weight over 2-year follow-up. Those who exhibited the greatest escalation in ventral pallidum responsivity to cues and the greatest decrease in caudate response to milkshake receipt showed significantly larger increases in BMI (r=.39 and -.69 respectively). Interestingly, cue-reward learning propensity and food reward habituation were not correlated, implying that these factors may constitute qualitatively distinct vulnerability pathways to excess weight gain. These two individual difference factors may provide insight as to why certain people have shown obesity onset in response to the current obesogenic environment in western cultures, whereas others have not.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cue–reward learning; Food reward habituation; Incentive salience; Obesity risk factors; Pavlovian conditioning; fMRI

Mesh:

Year:  2014        PMID: 24893320      PMCID: PMC4142439          DOI: 10.1016/j.neuroimage.2014.05.066

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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