Effects of Processed Foods on Brain Reward Circuitry and Food Cue Learning

Effects of Processed Foods on Brain Reward Circuitry and Food Cue Learning

Examine if ultra-processed (UP) foods are more effective in activating reward, attention, and memory brain regions and in promoting food cue learning than minimally-processed foods. Assess individual differences in neurobehavioral responses to UP foods.

Obesity is the second leading cause of premature death. Consumption of ultra-processed foods is theorized to be a key cause of obesity. Ultra-processed foods are formulations of cheap industrial sources of dietary energy and nutrients plus additives such as fat, sugar, and flavors that enhance acceptability of the foods.

A cross-over experiment with overweight adults found that ad lib access to an ultra-processed diet for 2-weeks resulted in increased caloric intake (508 kcal/day) and more weight gain versus ad lib access to a minimally-processed diet matched for presented calories, energy density, macronutrients, sugar, sodium, and fiber. The fact that ad lib access to ultra-processed foods resulted in a large increase in caloric intake and weight gain implies that ultra-processed foods may more effectively activate brain regions implicated in reward processing, attention/salience, and memory that influence eating behavior.

However, no brain imaging study has experimentally tested whether ultra-processed foods are more effective in activating brain regions implicated in reward, attention, and memory than minimally-processed foods or experimentally investigated the relative role of the elevated caloric density versus the flavor enhancers of ultra-processed foods in driving greater activation of these brain regions. Preliminary data showed that tastes of ultra-processed high-calorie chocolate milkshake produced greater activation in regions implicated in reward valuation (caudate, nucleus accumbens), attention/salience (precuneus), and memory retrieval (medial temporal gyrus, dorsomedial prefrontal cortex) than tastes of ultra-processed low-calorie chocolate milkshake.

The investigators propose to evaluate the efficacy of ultra-processed foods to activate reward, attention, and memory regions compared to minimally-processed foods, investigate the relative role of the higher caloric content versus the flavor additives/enhancers of ultra-processed foods to engage this circuitry using a 2 x 2 experimental design, test whether ultra-processed foods are more effective in increasing the incentive salience of food cues than minimally-processed foods, which is important because elevated reward region response to food cues/images increases risk for excess weight gain, and test whether individuals who show the greatest responsivity of reward, attention, and memory regions to ultra-processed foods and stronger food reward cue learning are at risk for greater ad lib intake of ultra-processed foods and future body fat gain.

Aim 1: Test the hypothesis that tastes, anticipated tastes, and images of ultra-processed foods activate reward, attention, and memory brain regions more than tastes, anticipated tastes, and images of minimally-processed foods, and evaluate the relative role of the higher caloric content versus flavor additives/enhancers in activating these regions using a 2 x 2 experimental design.

Aim 2: Test the hypothesis that ultra-processed foods foster stronger learning of cues that predict impending tastes of ultra-processed foods than minimally-processed foods, reflected by greater increases in striatal response over the course of cue exposure and quicker responses to cues for tastes of ultra-processed foods.

Aim 3: Test the hypothesis that participants who show greater activation in reward/attention/memory regions in response to tastes, anticipated tastes, and images of ultra-processed foods will consume more ultra-processed foods ad libitum (Aim 3a) and show greater future body fat gain (Aim 3b). Exploratory analyses will establish neural fingerprints that predict ad lib intake of ultra-processed foods and body fat gain (Aim 3c).

Aim 4: Test the hypothesis that participants who show the most pronounced reward cue learning in response to ultra-processed foods will consume more ultra-processed foods ad libitum (Aim 4a) and show greater future body fat gain (Aim 4b).

Inclusion Criteria:

• female and male adolescents 13-15 years of age
• age- and sex- adjusted zBMI scores between the 25th and 75th percentile
• participant and their guardian must be able to read and speak English to gather valid consent

Exclusion Criteria:

• current eating disorders or other major psychiatric disorders (e.g., depression, bipolar, schizophrenia, substance use disorder)
• fMRI contra-indicators (e.g., metal implants, braces, claustrophobia, pregnancy)
• serious medical problems (e.g., Type 2 diabetes, cancer)
• history of food allergies or restrictive dietary requirements (e.g., lactose intolerance, vegan)
• use of psychoactive drugs more than once weekly
• medications that impact appetite or reward functioning (e.g., metformin, anti-psychotic medication, insulin)