Metabolic state modulates neural processing of odors in the human olfactory bulb
Bibliographic record
Abstract
The olfactory and endocrine systems have recently been shown to reciprocally shape the homeostatic processes of energy intake. As demonstrated in animal models, the individual's metabolic state dynamically modulates how the olfactory bulb process odor stimuli using a range of endocrine signals. Here we aimed to determine whether the neural processing of odors in human olfactory bulb is modulated by metabolic state. Participants were exposed to food-associated odors, in separate sessions being hungry and sated, while neural responses from the olfactory bulb was obtained using electrobulbogram. We found significantly higher gamma power activity (51-100 Hz) in the OB's response to odors during the Hunger compared to Sated condition. Specifically, EBG gamma power were elevated while hungry already at 100 ms after odor onset, thereby suggesting intra-bulbar modulation according to metabolic state. These results demonstrate that, akin to other animal models, hunger state affects OB activity in humans. Moreover, we show that the EBG method has the potential to measure internal metabolic states and, as such, could be used to study specificities in olfactory processing of individuals suffering from pathologies such as obesity or anorexia.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".