Olfactory Event-Related Potentials Reflect Individual Differences in Odor Valence Perception
Bibliographic record
Abstract
Investigating the neural substrates of perceived quality in olfaction using different odorants is intrinsically difficult. By utilizing individual differences in perceived quality of the odor of androstenone, we obtained a continuum of individual differences in rated valence of the same stimulus allowing investigations of its manifestation in the olfactory event-related potentials (ERPs). In an initial group consisting of 43 individuals that were screened for their verbal descriptors and sensitivity for the odor of androstenone, 22 normosmic volunteers were chosen forming 2 distinct groups with regard to verbal labels ("body odor" and "nonbody odor") for androstenone while maintaining chemical structure, concentration, and intensity constant. In the main experiment, these participants rated both intensity and pleasantness of androstenone during the recording of olfactory ERPs. There was a significant difference in rated valence between the groups but not in intensity. Participants in the body odor label group had larger amplitudes of the late positive ERP component than those in the nonbody odor label group. A negative correlation between valence and amplitudes of the late positive component for androstenone indicated that these differences were mediated by the difference in odor valence between the 2 groups. This was further supported by a comparison of ERP peaks in response to stimulation with androstenone and the invariably unpleasant hydrogen sulfide that had been used as a control. Altogether, the results suggest that the late positive component reflects the processing of odor valence. Future olfactory studies with the aim of assessing the dimension of pleasantness would benefit from the use of these interindividual differences in the perception of a specific odor.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".