Computerized Response Training Obesity Treatment

This project will test whether a food response training intervention produces lasting body fat loss, use objective brain imaging to examine the mechanism of effect of this treatment and investigate the generalizability of the training to non-training foods, and examine factors that should amplify intervention effects to provide a test of the intervention theory. This novel treatment represents a bottom-up implicit training intervention that does not rely on executive control, prolonged caloric deprivation, and expensive clinicians to deliver, like behavioral weight loss treatments that have not produced lasting weight loss. If this computer-based response training intervention produces sustained body fat loss in overweight individuals, it could be easily implemented very broadly at almost no expense, addressing a leading public health problem.

Obesity causes 300,000 US deaths yearly, but most treatments do not result in lasting weight loss. People who show greater brain reward and attention region response, and less inhibitory region response, to high-calorie food images/cues show elevated future weight gain, consistent with the theory that overeating results from a strong approach response to high-calorie food cues paired with a weak inhibitory response. This implies that an intervention that reduces reward and attention region response to such food and increases inhibitory control region response should reduce overeating that is rooted in exposure to pervasive food cues. Computer-based response-inhibition training with high-calorie foods has decreased attentional bias for and intake of the training food, increased inhibitory control, and produced weight loss in overweight participants in 3 proof-of-concept trials, with effects persisting through 6-mo follow-up. A pilot trial found that overweight/obese adults who completed a multi-faceted 4-hr response-inhibition training with high-calorie food images and response-facilitation training with low-calorie food images showed reduced fMRI-assessed reward and attention region response to high-calorie training foods and greater body fat loss than controls who completed a rigorous 4-hr generic response-inhibition/response-facilitation training with non-food images (d=.95), producing a 7% reduction in excess body fat over the 4-wk period. The investigators propose to evaluate a refined and extended version of this response-training intervention.

Aim 1: Randomize 180 overweight/obese adults to a 4-wk response training obesity treatment or a generic inhibition training control condition that both include bi-monthly Internet-delivered booster training for a year and a smart phone response training app that can be used when tempted by high-calorie foods, assessing outcomes at pre, post, and at 3-, 6-, and 12-month follow-ups (e.g., % body fat, the primary outcome).

Aim 2: Use fMRI to test whether reduced reward and attention region response, and increased inhibitory region response to high-calorie food images used and not used in the response training mediate the effects of the intervention on fat loss. The investigators will also test whether during training participants show acute reductions in reward and attention region response, and increases in inhibitory response to high-calorie training food images to capture the learning process, assess generalizability of the intervention to food images not used in training, and collect behavioral data on mediators.

Aim 3: Test whether intervention effects will be stronger for those who show less inhibitory control in response to high-calorie food images, a genetic propensity for greater dopamine signaling in reward circuitry, and greater pretest reward and attention region response, and weaker inhibitory region response to high-calorie food images, based on the theory that response training is more efficacious for those with a strong pre-potent approach tendency to high-calorie foods.

During the Covid-19 shelter-at-home order, we will not measure in person only outcomes including BodPod assessments, height and weight measurement for BMI calculation, electrocardiogram (ECG) assessments and fMRI scanning for all participants that have assessments due during this order.

Eligibility Criteria:
Inclusion Criteria:

* Body Mass Index Between 25 and 35

Exclusion Criteria: