Perspective food addiction, caloric restriction, and dopaminergic neurotransmission
Bibliographic record
Abstract
People attempt to change their lifestyle when obesity impairs their quality of life. The attempts often fail when multiple habits must be changed in unison. Here we explore relations among food addiction, the neurobiology of habits, and caloric restriction, when people seek to return to normal eating behaviour, with particular emphasis on the role of dopaminergic neurotransmission. Severely obese individuals have specific neurobiological characteristics in common with drug abusers, including low availability of dopamine receptors in the striatum, impaired neuronal responses to dopamine, and reduced activity in prefrontal regions of the cerebral cortex. The neurobiological characteristics suggest that obese people also have a pathological dependence in common with addicts, in the form of food addiction. Malnutrition and dieting both relate to binge eating, possibly as a compensation for a reduced cognitive reward condition. The combination of caloric restriction and food addiction imparts a high risk of relapse as a result of further reduction of dopaminergic neurotransmission and the subsequent loss of reward. As with drugs of abuse, ingestion of large quantities of sugar in circumstances of uncontrolled eating increases dopamine release in the nucleus accumbens. This and other evidence suggests that abuse of food is a habit learned by means of mechanisms centred in the basal ganglia, with an increased risk of relapse in the presence of associative amplifiers. This risk is predicted by the relationship between dopamine receptor availability in the striatum and sensation-seeking in the form of an inverted U, suggested by recent findings, consistent with two opposite states of hypodopaminergic and hyperdopaminergic neuromodulation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".