Food-cue reactivity in individuals with obesity: Behavioral appeal, reaction times, and neurobiological specificity toward food-cues

Pervasive cues for highly appealing foods are a likely salient contributor towards obesity in an ‘obesogenic’ environment. One way to measure an individual’s response towards these food cues is food-cue reactivity (FCR). An FCR paradigm measures an individual’s reactivity to food cues contrasted against a control (i.e. non-food cues). Behavioral FCR (B-FCR) studies have elucidated some of the relationships between the subjective appeal of a food and ingestive behavior. Most studies have found a positive correlation between subjective palatability of food and food intake1. One limitation in understanding FCR is the degree of which subjective appeal of a cue affects an individual’s measured FCR. One interesting B-FCR outcome is reaction times to food-cues: reaction times are relevant to obesity due to an inverse relationship between reaction times and BMI2. The relationship between the appeal of food-cues and B-FCR reaction time warrants study as it has been proposed as a way to differentiate ‘liking’ and ‘wanting’3. Specifically, reaction time in a forced choice task has been suggested as a quantifiable way to measure ‘wanting’3. Additionally, the concepts are extensively used in trying to understand the brain regions involved in FCR4. Functional magnetic resonance imaging food-cue reactivity (fMRI-FCR) uses functional magnetic resonance imaging (fMRI) to study the brain’s neurophysiological response to food as compared to non-food. Specifically, visual food cues are commonly used because they produce a more robust response than gustatory or olfactory cues5. There is evidence suggesting that individuals with obesity have increased fMRI-FCR in both ‘liking’- and ‘wanting’-related ROIs6. However, it is unclear how the subjective appeal of a cue affects fMRI-FCR. While the fMRI-FCR studies comparing food to non-foods have demonstrated heightened response to food vs. non-foods; most studies have compared somewhat neutral non-food stimuli to highly palatable foods, and it remains unclear whether what is being observed is a generalized hypersensitivity to appeal, vs. a food-specific response. To our knowledge, there have not been any studies that have investigated this phenomenon. Therefore, our general hypothesis is that individuals with obesity have a heightened reactivity that is specific to food-cues as opposed to a generalized sensitivity to high appeal. We aim to examine how the main effects of a) cue type (i.e. food vs. non-foods) b) reward salience as reflected in appeal ratings (RSA; high-RSA vs. low-RSA) and c) their interaction differentially influence 1) behavioral appeal, 2) reaction times, and 3) fMRI-FCR. To accomplish this, a secondary data analysis will be completed on baseline data (study 1) from a prior randomized controlled dietary intervention trial examining FCR. The original data-set contained 32 otherwise healthy adults (age: 19-60 years) with obesity (BMI: 30.0-39.9 kg/m2) in a randomized controlled clinical trial that examined fMRI-FCR. In order to study the possibility of generalized appeal reactivity, fMRI responses to high-RSA vs. low-RSA food and non-food images were compared in a 2x2 factorial design. Behavioral data (i.e. appeal ratings and reaction time) were analyzed using similar ANOVA models in R statistical software. Building upon these results, a new, expanded FCR image bank was developed in study 2. During study 1, several ROIs had clusters that were significantly associated with food > baseline, non-food > baseline, and food > object contrasts. Low-RSA > baseline and high-RSA > baseline also has several significant clusters, but there were no clusters associated with high-RSA > low-RSA contrasts. The right nucleus accumbens was associated with the interaction between cue type and appeal value. Further, cue type was significant in all behavioral models, while the interaction between cue type and RSA was significant in behavioral appeal ratings. The developed image bank showed high reliability during study 2, and a hierarchical model showed mean proportional similarity superiority of matched images of 62.3%