Pilot study of food-specific go/no-go training for overweight individuals: brain imaging data suggest inhibition shapes food evaluation
Bibliographic record
Abstract
Food-specific go/no-go training might reduce overeating and facilitate weight loss. In this pilot study, we examined whether a food-specific go/no-go training over five weeks, as compared to a non-food-specific training, could produce changes in behavioral and neural responses to food images and body weight. Here, we used a sample of 51 overweight participants divided into training and control groups whose brain activity and food evaluation were measured before and after the training. Compared with the control group, in the training group we found significant reductions in high-calorie food evaluation. We also found lower activations in inhibitory control- and reward-related brain regions in response to high-calorie food images. Further, activation change of the mid-insula in response to the high-calorie food images was positively associated with change in the evaluation of those images. However, we found no evidence for a significant effect of food-specific go/no-go training on body weight change. Our findings highlight that food-specific go/no-go training in overweight individuals can reduce high-calorie food evaluation, but also neural activations in inhibitory control- and reward- related brain regions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".