From nose to brain: The effect of lemon inhalation observed by whole brain voxel to voxel functional connectivity
Bibliographic record
Abstract
Lemon fragrance is known for its stimulating properties, but its mechanisms of action are not well known yet. This study aimed to examine the effect of lemon essential oil inhalation on healthy participants' alertness level and their neural correlates using magnetic resonance imaging (MRI). Twenty-one healthy men underwent functional MRI scans in different conditions: a resting state condition, a condition where they were exposed to passive lemon smelling (alternating exposure to lemon and breathing fresh air), and a control condition without lemon fragrance diffusion -the order of the last two conditions being randomized. Alertness levels were assessed immediately after each condition using the Karolinska Sleepiness Scale. Voxel-wise whole-brain global functional connectivity and graph theory analyses were computed to investigate brain functional connectivity and network topology alterations. After lemon fragrance inhalation, we observed a higher level of alertness as compared to resting state -but not compared to control condition. During lemon fragrance inhalation, we found increased global functional connectivity in the thalamus, paralleled by decreased global connectivity in several cortical regions such as precuneus, postcentral and precentral gyrus, lateral occipital cortex and paracingulate gyrus. Graph theory analysis revealed increased network integration in cortical regions typically involved in olfaction and emotion processing such as olfactory bulb, hypothalamus and thalamus, while decreased network segregation in several regions of the posterior part of the brain during olfaction as compared to resting state. The present findings suggest that lemon essential oil inhalation could increase the level of alertness.
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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 | 0.000 |
| 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".