Integration of homeostatic signaling and food reward processing in the human brain

Abstract

Background: Food intake is guided by homeostatic needs and by the reward value of food, yet the exact relation between the two remains unclear. The aim of this study was to investigate the influence of different metabolic states and hormonal satiety signaling on responses in neural reward networks.

Methods: Twenty-three healthy participants underwent functional magnetic resonance imaging while performing a task distinguishing between the anticipation and the receipt of either food- or monetary-related reward. Every participant was scanned twice in a counterbalanced fashion, both during a fasted state (after 24 hours fasting) and satiety. A functional connectivity analysis was performed to investigate the influence of satiety signaling on activation in neural reward networks. Blood samples were collected to assess hormonal satiety signaling.

Results: Fasting was associated with sensitization of the striatal reward system to the anticipation of food reward irrespective of reward magnitude. Furthermore, during satiety, individual ghrelin levels were associated with increased neural processing during the expectation of food-related reward.

Conclusions: Our findings show that physiological hunger stimulates food consumption by specifically increasing neural processing during the expectation (i.e., incentive salience) but not the receipt of food-related reward. In addition, these findings suggest that ghrelin signaling influences hedonic-driven food intake by increasing neural reactivity during the expectation of food-related reward. These results provide insights into the neurobiological underpinnings of motivational processing and hedonic evaluation of food reward.

Trial registration: ClinicalTrials.gov NCT03081585.

Funding: This work was supported by the German Competence Network on Obesity, which is funded by the German Federal Ministry of Education and Research (FKZ 01GI1122E).

Keywords: Neuroscience.

Conflict of interest statement

Conflict of interest: The authors have declared that no conflict of interest exists.

Figures

Figure 1. Incentive delay task.

At the beginning of each trial, participants were presented with a cue depicting the amount of money (monetary incentive delay task) or snack points (SP; food incentive delay task) to be won. A circle with two horizontal lines represented 1 EUR or 10 SP, a circle with one line represented 0.2 EUR or 2 SP, and an empty circle represented 0 EUR or 0 SP. After a delay period, participants had to react by pressing a left or right button according to the position of the triangle. During the feedback phase, participants were informed about the amount won during the respective trial. Immediately after the fMRI scan, participants received the amount of money won and were able to choose snacks from a basket according to the amount of SP won.

Figure 2. Neural activation during the expectation and receipt of food reward is differentially related to satiety status.

(A) During the expectation of food-related reward, percentage signal change extracted from the right and left ventral striatum was influenced by reward level (F(1,22) = 13.17, P < 0.001, F(1,22) = 12.1, P < 0.001, respectively, n = 23) as well as satiety state (F(1,22) = 5.09, P = 0.034, F(1,22) = 6.78, P = 0.016, respectively, n = 23). We observed no interaction between reward level and satiety state (all P values > 0.35). (B) During the receipt of food-related reward, percentage signal change extracted from the right, left, and medial orbitofrontal cortex was influenced by reward level (F(1,22) = 6.36, P = 0.004, F(1,22) = 8.66, P = 0.001, F(1,22) = 4.83, P = 0.013, respectively, n = 23) but not by satiety state (all P values > 0.2, n = 23). We observed no interaction between reward level and satiety state (all P values > 0.17). Repeated-measures ANOVAs were used for the statistical analysis. In box-and-whisker plots, horizontal bars indicate the medians, boxes indicate 25th to 75th percentiles, and whiskers indicate 10th and 90th percentiles.

Figure 3. Neural activation during monetary reward processing.

(A) During the expectation of monetary-related reward, percentage signal change extracted from the right and left ventral striatum was influenced by reward level (F(1,21) = 21.47, P < 0.001, F(1,21) = 28.06, P < 0.001, n = 22, respectively) but not by satiety state (all P values > 0.47, n = 23). We observed no interaction between reward level and satiety state (all P values > 0.47, n = 23). (B) During the receipt of food-related reward, percentage signal change extracted from the right and left orbitofrontal cortex was neither influenced by reward level nor by satiety state (all P values > 0.09, n = 23). Activity in the medial orbitofrontal cortex was influence by reward level (F(1,21) = 12.36, P < 0.001, n = 23) but not by satiety state (P = 0.81, n = 23). We observed an interaction effect between reward level and satiety state in the medial orbitofrontal cortex (F(2,42) = 4.26, P = 0.021, n = 23) but the right or left orbitofrontal cortex (all P values > 0.34, n = 23). Repeated-measures ANOVAs were used for the statistical analysis. In box-and-whisker plots, horizontal bars indicate the medians, boxes indicate 25th to 75th percentiles, and whiskers indicate 10th and 90th percentiles.

Figure 4. Interaction analyses during the expectation of reward.

The top row shows the percentage signal change extracted from the left VS during the expectation of food-related reward and monetary-related reward during the fasted state (red line with circles) and the sated state (black line with squares) divided according to reward level (as indicated on the x axis). The bottom row shows the signal change extracted from the right VS during the expectation of food- and monetary-related reward during different satiety states. Error bars indicate SEM.

Figure 5. Interaction analyses during the receipt of reward.

The top row shows the percentage signal change extracted from the left OFC during the receipt of food-related reward and monetary-related reward during the fasted state (red line with circles) and the sated state (black line with squares) divided according to reward level (as indicated on the x axis). The middle row shows the signal change extracted from the right OFC during the receipt of food- and monetary-related reward during different satiety states. The bottom row shows the signal change extracted from the medial OFC during the receipt of food- and monetary-related reward during different satiety states. Error bars indicate SEM.

Figure 6. Neural food reward processing is related to hormonal satiety parameters and lifetime maximal weight.

(A) Percentage signal change of BOLD activation extracted from the right ventral striatum during the expectation of food-related reward (high reward: 10 snack points) when satiated was positively related to ghrelin total values (Pearson r(11) = 0.611, P = 0.027, 2-tailed correlation, n = 13). (B) Percentage signal change of BOLD activation extracted from the left ventral striatum during the expectation of a food-related reward (high reward: 10 snack points) during the fasted state was negatively related to lifetime maximal weight (r(21) = –0.433, P = 0.039, 2-tailed correlation, n = 23).

Figure 7. Anatomical brain reward mask.

Anatomical mask used to identify the reward network from the group independent component analysis. The mask contained the bilateral caudatus, putamen, thalamus, anterior cingulate cortex, and medial orbitofrontal cortex. The mask was created using the Wake Forest University PickAtlas, and all regions were taken from the Automated Anatomical Labeling atlas.

Figure 8. Reward component derived from the group independent component analysis.

The brain reward network obtained using a spatial group independent component analysis and subsequent spatial correlation with an a priori defined structural mask of relevant brain reward regions (correlation with the template mask, r = 0.341). The obtained component was included in a random-effect analysis using a 1-sample t test, with age and BMI as covariates of no interest (n = 23). The statistical map was thresholded at a cluster-defining threshold of P < 0.001 uncorrected (cluster size k > 10). We observed significant clusters of activation at a family-wise error corrected cluster level threshold of P < 0.05 in the bilateral striatum, posterior cingulate cortex, inferior parietal cortex, lingual gyrus, inferior and superior frontal gyrus, precuneus, medial and lateral orbitofrontal cortex, occipital cortex, and the postcentral gyrus. We observed no results when comparing component activity between metabolic states using a 2-sample t test with age and BMI as covariates of no interest.