Neural signature of the Food Craving Questionnaire (FCQ)-Trait. (1st December 2016)

• Record Type: Journal Article
• Authors: Ulrich, Martin; Steigleder, Leon; Grön, Georg
• Is Part Of: Appetite. Volume 107(2016)
• Page Start: 303
• Page End: 310
• Publication Date: 2016-12-01
• Subjects: Food -- Craving -- Ventral striatum -- Caudate nucleus -- Nucleus accumbens -- fMRI; Food habits -- Periodicals; Appetite -- Periodicals; Appetite disorders -- Periodicals; Electronic journals; 306.4613
• DOI: 10.1016/j.appet.2016.08.012
• Languages: English
• ISSNs: 0195-6663

Abstract

Abstract: The Trait and State versions of the Food Craving Questionnaire (FCQ) have been used in numerous behavioral and physiological eating studies. However, the neurobiological signature of the FCQ has not been reported yet. In the present study, 20 healthy male participants performed a food/non-food discrimination task during functional magnetic resonance imaging (fMRI). We investigated where in the brain greater activation upon high-caloric minus low-caloric food cues correlated with participants' scores on the German version of the FCQ-Trait, with the FCQ-State total scores included as a covariate, and vice versa. It was also tested whether individual subscales would map onto distinguishable neural correlates. Significant positive correlations with total scores on the FCQ-Trait were evident in several bilateral loci of the striatum, and in the right middle/lateral orbitofrontal cortex (OFC). Correlations with scores on the FCQ-Trait subscales Reinforcement and Hunger were found for subsets of voxels within the ventral striatum, whereas the FCQ-Trait subscales Intentions/Lack of control and Thoughts/Guilt mapped onto right OFC. There were no significant correlations between calorie-sensitive brain activation and scores on the FCQ-State when including the total scores on the FCQ-Trait as a covariate. Present findings show that the trait version of the FCQ associates with neural correlates known to be involved in coding motivational salience, detecting and estimating reward value, and representing information of expected outcomes.