Same Same but Different. Different Trigeminal Chemoreceptors Share the Same Central Pathway
Bibliographic record
Abstract
Intranasal trigeminal sensations are important in everyday life of human beings, as they play a governing role in protecting the airways from harm. Trigeminal sensations arise from the binding of a ligand to various sub-types of transient receptor potential (TRP) channels located on mucosal branches of the trigeminal nerve. Which underlying neural networks are involved in the processing of various trigeminal inputs is still unknown. To target this unresolved question fourteen healthy human subjects were investigated by completing three functional magnetic resonance imaging (fMRI) scanning sessions during which three trigeminal substances, activating varying sub-types of chemoreceptors and evoking different sensations in the nose were presented: CO2, menthol and cinnamaldehyde. We identified similar functional networks responding to all stimuli: an olfactory network, a somatosensory network and an integrative network. The processing pathway of all three stimulants was represented by the same functional networks, although CO2 evokes painful but virtually odorless sensations, and the two other stimulants, menthol and cinnamaldehyde are perceived as mostly non painful with a clear olfactory percept. Therefore, our results suggest a common central processing pathway for trigeminal information regardless of the trigeminal chemoreceptor and sensation type.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".