Neurocomputational mechanisms of food and physical activity decision-making in male adolescents

Abstract

We examined the neurocomputational mechanisms in which male adolescents make food and physical activity decisions and how those processes are influenced by body weight and physical activity levels. After physical activity and dietary assessments, thirty-eight males ages 14-18 completed the behavioral rating and fMRI decision tasks for food and physical activity items. The food and physical activity self-control decisions were significantly correlated with each other. In both, taste- or enjoyment-oriented processes were negatively associated with successful self-control decisions, while health-oriented processes were positively associated. The correlation between taste/enjoyment and healthy attribute ratings predicted actual laboratory food intake and physical activities (2-week activity monitoring). fMRI data showed the decision values of both food and activity are encoded in the ventromedial prefrontal cortex, suggesting both decisions share common reward value-related circuits at the time of choice. Compared to the group with overweight/obese, the group with normal weight showed stronger brain activations in the cognitive control, multisensory integration, and motor control regions during physical activity decisions. For both food and physical activity, self-controlled decisions utilize similar computational and neurobiological mechanisms, which may provide insights into how to promote healthy food and physical activity decisions.

Figure 1

(A) Overview of the study design. (B) Adolescents completed food and activity ratings before fMRI scans. They provided taste and health attributes and overall preference ratings for 60 different food items, and enjoyment and health attributes and overall preference ratings for 60 different activity items. The order of food and activity rating tasks and the order of attribute ratings within each type of task were randomized. (C) fMRI decision task consisted of activity and food decision blocks. Participants completed 6 runs of the decision task and each run included 3 food and 3 physical activity choice blocks (10 decision trials per block). Computer algorithms randomized the order of blocks and the order of trials within the block. For each food and physical activity image, participants entered their decisions using a 4-point scale (“strong no–strong yes” or “strong yes–strong no”; counterbalanced across participants) within 4-s.

Figure 2

(A) Participants’ correlation coefficients of food taste and health ratings and activity enjoyment and health ratings are shown in ascending order of food correlation coefficients. The dotted lines indicate the critical r values at the individual level (± 0.254 at p < 0.05). (B) The correlations between activity enjoyment and health ratings were significantly different between active (ACT) and sedentary (SED) groups. (C) Adolescents’ food decisions were solely predicted by taste ratings, and activity decisions were solely predicted by enjoyment ratings. (D) The food taste beta weights were significantly different between normal weight active (NW ACT) and normal weight sedentary (NW SED) groups, while they were not different between overweight/obese active (OW/OB ACT) and overweight/obese sedentary (OW/OB SED) groups. All error bars denote standard errors. n = 38.

Figure 3

(A) The beta weights of food taste attribute were positively correlated with the beta weights of activity enjoyment attribute. (B) The beta weights of food health attribute were not significantly correlated with the beta weights of activity health attribute. (C) The beta weights of food taste attribute were negatively correlated with the proportions of successful self-control in food decisions. (D) The beta weights of food health attribute were positively correlated with the proportions of successful self-control in food decisions. (E) The beta weights of activity enjoyment attribute were negatively correlated with the proportions of successful self-control in activity decisions. (F) The beta weights of activity health attribute were positively correlated with the proportions of successful self-control in activity decisions. (G) The correlations between food taste and health attribute ratings were negatively associated with the amount of food consumption (kcals) at the ad libitum pizza buffet (M = 1023, SD = 369). (H) The correlations between physical activity enjoyment and health attribute ratings were positively associated with the physical activity level monitor measures of the 2-week assessment period (M = 1866, SD = 418). n = 38.

Figure 4

(A) Both food and physical activity-related decision values were positively correlated with vmPFC activities. (B) OFC showed stronger activity during food choices compared to physical activity choices, while fusiform gyrus showed stronger activity during physical activity choices compared to food choices. All images are threshold at p < 0.05 corrected with cluster size correction.

Figure 5

(A) Weight by activity group interaction effect was found in the pre-SMA. (B) Normal weight group (n = 21) compared to overweight/obesity group (n = 17) showed stronger IFG, motor cortex, and STG activations during activity choices. The images are threshold at p < 0.05 corrected with cluster size correction.