Divergent neural substrates of inhibitory control in binge eating disorder relative to other manifestations of obesity
Bibliographic record
Abstract
OBJECTIVE: An important endeavor involves increasing our understanding of biobehavioral processes underlying different types of obesity. The current study investigated the neural correlates of cognitive control (involving conflict monitoring and response inhibition) in obese individuals with binge eating disorder (BED) as compared to BMI-matched non-BED obese (OB) individuals and lean comparison (LC) participants. Alterations in cognitive control may contribute to differences in behavioral control over eating behaviors in BED and obesity. DESIGN AND METHODS: Participants underwent functional magnetic resonance imaging while completing the Stroop color-word interference task. RESULTS AND CONCLUSIONS: Relative to the OB and LC groups, activity in the BED group was differentiated by relative hypoactivity in brain areas involved in self-regulation and impulse control. Specifically, the BED group showed diminished activity in the ventromedial prefrontal cortex (vmPFC), inferior frontal gyrus (IFG), and insula during Stroop performance. In addition, dietary restraint scores were negatively correlated with right IFG and vmPFC activation in the BED group, but not in the OB or HC groups. Thus, BED individuals' diminished ability to recruit impulse-control-related brain regions appears associated with impaired dietary restraint. The observed differences in neural correlates of inhibitory processing in BED relative to OB and LC groups suggest distinct eurobiological contributions to binge eating as a subgroup of obese individuals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".