It takes two: intranasal trigeminal chemosensation and its role in odor processing
Bibliographic record
Abstract
Odor perception is a complex, multimodal experience mainly shaped by the interaction between the olfactory and trigeminal systems. Descriptors such as warm, fresh, or spicy reflect the contribution of chemosensory input from the trigeminal nerve, which adds thermal and tactile dimensions to odor perception. The trigeminal nerve innervates the head, including the nasal cavity; its fibers express several transient receptor potential channels to which odorant molecules can bind. Despite its sensory function and its putative impact on olfactory processing, the chemosensory ability of the trigeminal system has received comparatively little attention. This review examines the molecular and physiological foundations of trigeminal chemosensation, highlighting transient receptor potential channels broad sensitivity, their perceptual roles, and their interactions with the olfactory system. Assessing nasal trigeminal chemosensory function presents several methodological challenges. Here, we explore the tools available for studying the complexity of trigeminal chemosensory encoding ex vivo and in vivo in animal and human models. These techniques have demonstrated that, although the trigeminal and olfactory systems are distinct sensory modalities, they converge at multiple processing stages within the nervous system, including the olfactory epithelium (OE), the olfactory bulb, and other brain regions. In humans, this convergence leads to the activation of overlapping brain regions, resulting in perceptual modulation where information from the trigeminal system enhances or suppresses the response of the olfactory system. As a consequence of this intimate connection, olfactory dysfunction is often accompanied by reduced trigeminal sensitivity. Therefore, we examine the involvement of the trigeminal system in conditions of olfactory dysfunction.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".