The orbitofrontal cortex, food intake and obesity
Bibliographic record
Abstract
Obesity is a major health challenge facing many people throughout the world. Increased consumption of palatable, high-caloric foods is one of the major drivers of obesity. Both orexigenic and anorexic states have been thoroughly reviewed elsewhere; here, we focus on the cognitive control of feeding in the context of obesity, and how the orbitofrontal cortex (OFC) is implicated, based on data from preclinical and clinical research. The OFC is important in decision-making and has been heavily researched in neuropsychiatric illnesses such as addiction and obsessive–compulsive disorder. However, activity in the OFC has only recently been described in research into food intake, obesity and eating disorders. The OFC integrates sensory modalities such as taste, smell and vision, and it has dense reciprocal projections into thalamic, midbrain and striatal regions to fine-tune decision-making. Thus, the OFC may be anatomically and functionally situated to play a critical role in the etiology and maintenance of excess feeding behaviour. We propose that the OFC serves as an integrative hub for orchestrating motivated feeding behaviour and suggest how its neurobiology and functional output might be altered in the obese state.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".