FMRI of Dietary Decision-making in Food Addicted Participants Compared to Non-food Addicted Participants

How a Patient's Words Change the Rewarding Value of Food: Mapping the Neurocognitive Shift Generated by Motivational Interviewing During the Therapy of Food Addiction Onto the Brain - MOTIVFOOD

Why in some situations can words soothe our cravings? This research proposal will test the power of self-generated reasons for behavioural change in food addiction, which concerns about three out of ten persons and causes major life hazards such as obesity, diabetes and cancer. While food addiction is becoming more and more frequent in western societies, not much is known about its underlying neurocognitive mechanisms and how to tackle it. This study aims to investigate if and why certain types of affirmation-based therapies such as motivational interviewing (MI) are beneficial for the treatment of food addiction. The working hypothesis proposes that cognitive regulation-based self-control underpins the neurocognitive shift of a patient's willingness to change addictive behaviour, generated by the patient during MI therapy of food addiction. To test this hypothesis this study combines functional magnetic resonance imaging with behavioural testing of dietary decision-making following a participant's change or sustain talk statements. It will compare three groups of participants with and without food addiction and obesity and lean controls. This study will contribute to the improvement of therapies based upon talking oneself in and out of addiction promoting goals. Findings will provide a better understanding of how our everyday life dietary decision-environments prompt good intentions such as improving long-term nutritional quality to actual behaviours such as forgoing immediate desire.

Food addiction is a growing problem that currently concerns 1 out of 5 persons in Western societies. Although food intake is essential to survival and well-being, research in animals and humans has provided convergent evidence that certain types of high palatable, fat- and sugar-rich foods (hp foods) can become as addictive as cocaine or amphetamines. However, in humans, the underlying neurocognitive mechanisms of food addiction are to date unknown, and successful treatment is to be found.

An approach that has been shown to lead to promising results during drug abuse rehabilitation involves Motivational interviewing (MI). MI is a goal-oriented style of communication and focuses on resolving a patient's ambivalence while eliciting his/her own reasons to change addictive behavior, also known as change talk. Functional magnetic resonance imaging (fMRI) studies have shown that patients' individual change talk recordings from prior MI sessions attenuated very, and enhanced dorsolateral prefrontal cortex (dlPFC) responses to addictive drug cues. This finding suggests that a neurocognitive shift in the patients' attitude toward his/her addiction is considered to play a key role in rehabilitation and recovery. However, it is unknown what exactly this neurocognitive shift means on a joint behavioral and neural level. MOTIVFOOD aims to shed light on these dynamics in the context of food addiction.

Hypotheses

• Change compared to sustain talk in obese food addicts alters responses within the brain's valuation and self-control systems, and dietary self-control and food valuation on the behavioral level.
• Food-addicted obese participants will be compared to (a) non-food addicted obese, and (b) to normal weight control participants to explore potential differences in dietary decision-making after the change and after sustain talk on the neural and behavioral level. Expected results are that the MI approach only works when participants are willing and need to engage in therapy. If so, the contrast between change and sustain talk statements should be stronger, when behavior needs indeed to be changed because of (a) obesity, which is a major life hazard, and/or (b) food addiction, for which MI was designed for.

Design Plan

Study type

Observational Study with three groups of participants:

1. food-addicted participants with obesity
2. non-food addicted participants with obesity
3. non-food addicted, normal-weight participants

Food addicted and non-food addicted participants with obesity will be matched on body mass index (BMI), age, gender, and education, whereas the normal-weight controls will be matched to the two groups of participants with obesity on age, gender, and education.

Blinding

No blinding is involved in this study.

Study design

The study design involves a mixed 3x2 factorial design with the factor group (3 levels) crossing the within-subject factor talk condition (2 levels). Before the fMRI session, all participants will attend a motivational interviewing (MI) session with a dietitian, who will guide the participants to elaborate their reasons to change (i.e., change talk: sentences that support a wanting to change addictive behavior) and their reasons to remain in the status quo (i.e., sustain talk: sentences that support the status quo of not changing addictive behavior). The MI session will be recorded, and the relevant statements selected to be included in a dietary decision-making task paradigm performed about one week later during fMRI. A 24h dietary recall will measure everyday life dietary intake to obtain health indexes for each participant. The YFAS will assess food addiction.

During a second session (about one week after the MI session) all participants will perform the fMRI exam in the fasted state, after at least 2 hours of fasting. During fMRI, they will perform a modified version of a food choice task from decision neuroscience. The task involves viewing food pictures displayed on a trial-by-trial basis on a computer screen. On each trial, the participant decides on how much they would like to eat the food for real at the end of the experiment on a 4-point Likert scale between strong no (1), no (2), yes (3), and strong yes (4). This response corresponds to the variable stimulus value. Importantly, before a series of such yes/no food choices, participants will listen to (1) "their" personal change talk - itself, or (2) "their" personal sustain talk - STself. Participants will also evaluate at the end of the decision-making task each food stimulus on its healthiness and tastiness. These ratings will be used to assess how much taste and health attributes determine food stimulus value, respectively, and how this integration differs as a function of listening to either a change or a sustain talk statement. The depressive mood will be assessed with Beck's depression inventory, weekly physical activity with the IPAQ, and body composition will be assessed by a medically approved, bioelectrical impedance scale (weight, size, BMI, % body fat, % body water).

A month after the MI session, all participants will be reassessed on dietary intake (24h dietary recall) and food addiction (YFAS).

Randomization

The participants will be matched as to BMI, age, gender, and education.

Data collection procedures

Participants will be recruited through (1) a network of healthcare Institutes specialized in eating disorders (the Institute of Cardiometabolism and Nutrition, ICAN) and (2) an electronic public announcement on the RISC website (http://www.risc.cnrs.fr/). Each participant will receive 120€ for participation.

All participants will be aged from 18 to 70 years old, right-handed, able to read, write, understand written information and sign the informed consent. Additionally, the participants should be able to perform the cognitive tasks, without a recent diagnosis of neurological or psychiatric disease, treatment, or history of substance abuse.

The obese patients (BMI ≥ 30 kg/m2) will be divided into two groups according to the score of the French version of the Yale Food Addiction Scale 2.0 (YFAS) score. Those with symptoms ≥ 2 will compose the obesity with food addiction group, whereas those with ≤1 will belong to the obesity without food addition group.

Non-inclusion criteria are contraindications of MRI (eg. Pacemaker, peri-pregnancy period, cochlear implants, brackets, metallic prostheses, and permanent makeup).

As exclusion criteria: Participants with a history of substance abuse, who were unable of performing the experimental tasks, or with bad MRI data quality will be excluded.

Sample size

We will recruit 30 participants in each group (total sample N=90). We further expect a dropout rate of about 10% and therefore foresee recruiting an additional number of maximum of 15 (5 per group) participants.

Measured variables

Variables from seven domains will be collected (1) sociodemographic, (2) anthropometric and dietary data, (3) clinical outcomes, (4) MRI-related, (5) dietary decision-making task-related (6) MI-related, and (7) covariables.

1. Sociodemographic variables :

   gender, age, education.

2. anthropometric variables: weight, height, percentage of body fat, and lean mass.

3. dietary behavior data:

   1. a nutritional anamnesis will focus on weight history, weight loss attempts and methods, use of supplements and maximal weight and approximate dates as well as the date of when it was diagnosed with food addiction,
   2. a 24h dietary recall interview will assess the dietary intake of the previous 24h. This pass involves obtaining a list of all food items eaten on the previous day, the interviewer probes for frequently forgotten foods such as savory snacks, sugar added to beverages, candies. Then, the time and name of the eating occasion (i.e. breakfast or lunch) and a detailed description of the type of food item, cooking method, and other relevant aspects are collected. Once the data is collected, energy and nutrients intake and food group data will be determined by appropriate software (e.g. Nutrilog) to compute the dietary-related variables resorting to a French-specific database.
   3. Food addiction by using the YFAS 2.0. The YFAS 2.0 aims at assessing the addictive-like eating behavior of the consumption of foods high in fat and/or refined carbohydrates (e.g., sugar, white flour) based upon the DSM-5. This questionnaire is composed of 35 items with eight response options that range from "Never" to "Every Day." Each question accounts for one of the 11 diagnosis criteria (e.g tolerance, withdrawal, clinical Significance). The cut-off for food addiction is a total score of at least 2 or more meaning that 2 or more of the 11 diagnosis criteria were met.

4. fMRI-related measures:

   1. we will assess resting-state fMRI
   2. fMRI during a dietary decision-making task
   3. anatomical MRI

5. dietary decision-making task-related measures: The task involves

   1. stimulus value: food wanting to rate each food stimulus on a 4-point Likert scale for strong no (1), no (2), yes (3) to strong yes (4).
   2. healthiness and tastiness ratings to build regulatory success scores that can be operationalized within the dietary decision-making paradigm by the following measures:

   i. The regression coefficient (beta) of the tastiness ratings of food on stimulus value ii. The beta of the healthiness rating of food stimuli on stimulus value iii. The difference between the tastiness and healthiness beta in change vs sustain talk conditions iv. The difference in stimulus value between change versus sustain talk conditions.

   v. The sum of the percentage of healthy, untasty food choices (strong yes and yes food wanting ratings) and unhealthy, tasty food rejections (strong no and no food wanting ratings).

6. MI-related measures will consist in change and sustain talk statement recordings:

   1. sustain and change talk statements will be selected according to their length so every subject is exposed to the same length of stimuli using the Audacity software
   2. sessions will be coded by trained researchers in MI and MISC (Motivational intervening Skill Code). The latter phase will assess both counselor's and subjects' behaviors. The MISC is comprised of behavior counts and global ratings. For behavior count, each counselor's and patient's complete thought or utterance is attributed to an MI technical code (e.g. open question, reflection, affirmation, for counselor; change talk, sustain talk, neutral, for the patient). Global ratings attribute an overall appreciation of relational factors on Likert scales (e.g. overall score of empathy, acceptance).

7. At last, variables are known to influence both functional brain activity and adherence to specific dietary patterns or weight loss will be collected. These include:

   1. psychological comorbidity variables such as depressive mood (BDI)
   2. physical activity: the International Physical Activity Questionnaire (IPAQ-SF).

Statistical models

Within-subjects and between-subjects comparisons will be conducted by using analyses of variance (ANOVA) and linear mixed models. When these analyses yield statistical differences, post-hoc analyses will be conducted through student T-tests to characterize main effects and interactions. The main analysis will focus of the dependant variables: fMRI activity and regulatory success during the dietary decision-making task and dietary behavior as well as food addiction score on the YFAS.

Group: Normal-weight, NON-food addicted control participants

• no food addiction, no eating disorder, no nutrition troubles, no weight management troubles
• BMI: between 18.5 kg/m2 and 25 kg/m2
• age 18 to 70 years
• right-handed
• male / female
• able to understand instructions and perform tasks
• no psychiatric or neurological disorders
• no drug abuse
• written and informed consent

Group: obese, food addicted

• BMI >= 30 kg/m2
• YFAS score > = 2
• no other addictions
• age 18 to 70 years
• right-handed
• male / female
• able to understand instructions and perform tasks
• no recently diagnosed psychiatric or neurological disorders
• no drug abuse
• written and informed consent

Group: obese, NON-food addicted

• age 18 to 70 years
• BMI >= 30 kg/m2
• YFAS score < =1
• no other addictions
• right-handed
• male / female
• able to understand instructions and perform tasks
• no recently diagnosed psychiatric or neurological disorders
• no drug abuse
• written and informed consent

Exclusion Criteria:

• bad MRI quality
• drop out